# Propel Ventures Source: https://www.propelventures.ai/ Propel Ventures is a Melbourne-based AI transformation partner that helps Australian companies rewire how their business operates, ship production AI products, and lift internal AI capability. Founded 2016. ISO 27001 certified. --- # Home Source: https://www.propelventures.ai/ [// your AI consulting partner] # Rewire how you work. Ship what's worth shipping. Propel Ventures is a Melbourne-based AI partner — because real AI transformation isn't a tool roll-out. It's rebuilding how your business runs, to unlock 20x acceleration. Whether you're a tech company shipping AI products or a non-tech business rewiring how it operates, we're the partner that gets it done. [// the propel claim] ## 20x doesn't come from a chatbot. It comes from rewiring how your business runs — decisions, products, processes, ways of working. The companies pulling ahead with AI aren't the ones with the most licences. They're the ones who rebuilt how work gets done. [// services] ## Three ways to work with us Every one is anchored in outcomes, not artefacts: we measure what changed, not what we delivered. ### AI Enablement Get your whole team building with AI from session one. Hands-on workshops, innovation days and embedded build — applied to your real work, with the same tools we use every week. Skip the frameworks and six-month roadmaps; every session leaves something working behind. - Hands-on training — your team builds in the first session - Innovation days that ship working prototypes - Embedded implementation of automations & agents - Coaching for leaders & internal AI champions ### AI Consulting The org-level rebuild that makes the 20x compound. Operating model, AI-native ways of working, capability uplift — so AI changes how decisions get made and work gets done — and how your product & engineering teams build. - Operating model & team design - AI-native PDLC for product & engineering - Capability uplift & training - Change & adoption ### AI Product & Engineering Embedded teams shipping production AI software. New AI-native products, AI features in existing platforms, automations and integrations — all built to the same product-led standard that's defined Propel for a decade. - Discovery, design & delivery planning - End-to-end product development - AI features & automations - Systems integration & data [// our work] ## Just a few of our clients. A decade of work across financial services, energy, retail, health, education, property and the firms that invest in them. [// the propel promise] ## What we mean by an AI partner Most AI initiatives fail for the same two reasons: someone solved the wrong problem, or no-one rewired how the business actually uses it. Our job is to make sure neither happens — across four dimensions. ### Valuable Solves a real problem with a real outcome. We start with discovery, not LLM choice — and we'll tell you when an idea isn't worth pursuing. ### Commercial Works for the business. Cost, risk, ROI and timing — stress-tested before you commit serious capital, and aligned to how you actually operate. ### Responsible Safe, governed, defensible. Privacy, security and IP protection baked in from day one — not bolted on after the model goes live. ### Engineered Actually ships and runs. Production-grade work, not demos. Our teams work alongside yours and lift internal capability as we go. [// frequently asked] ## Common questions about AI consulting. Six questions we hear on every first call — what Propel does, where we're based, how AI transformation differs from implementation, what we actually deliver, how we price, and how long it takes. ### What does Propel Ventures do? Propel Ventures is an AI partner that helps companies rebuild how their business runs so they can unlock 20x acceleration with AI. The work spans two service lines: AI Consulting — operating-model redesign, AI-native ways of working, capability uplift, and governance — and AI Product & Engineering, where embedded teams ship production-grade AI products, features, and integrations. Founded in Melbourne in 2016, Propel has worked with more than 100 teams across financial services, energy, retail, health, education, property, and hospitality, and is ISO 27001 certified and a partner of AWS, Microsoft, Google, and Anthropic. ### Where is Propel Ventures based? Propel Ventures is headquartered in Melbourne, Australia with offices in Sydney, Australia and Ho Chi Minh City Vietnam, and works with ambitious teams across Australia and beyond. The firm was founded in 2016 and operates as an AI partner for Australian companies in financial services, energy, retail, health, education, property, hospitality, and private equity. ### What's the difference between AI transformation and AI implementation? AI implementation is rolling out tools and licences — giving people access to ChatGPT, Copilot, or a new model and hoping behaviour follows. AI transformation is rewiring how the business actually runs: the operating model, decision-making, products, processes, and ways of working. According to Propel Ventures, the companies pulling ahead with AI aren't the ones with the most licences — they're the ones who rebuilt how decisions get made and how work gets done. Implementation is a tool roll-out; transformation is an organisational rewiring that changes the work itself. ### What does an AI partner actually deliver? A Propel Ventures AI consulting engagement produces six concrete artefacts: an AI Strategy on a Page (philosophy, three-horizon goals, prioritised initiatives); a capability uplift plan across technology, data, people, culture, and governance; a prioritised use-case roadmap structured as Now / Next / Later with ROI and dependency mapping; an operating model and governance framework covering how AI work gets funded, measured, and re-prioritised; AI-native ways of working — practical playbooks and embedded coaching for product, design, and engineering teams; and delivered priority initiatives, where Propel ships the first wave of high-value use cases alongside the client's team so capability transfers as work is built. ### How does Propel price engagements? Propel Ventures offers outcome-based pricing for AI Consulting engagements, anchored in measurable outcomes rather than artefacts or time-and-materials. Engagements typically start with one of three options — an Executive AI Sprint, an AI Strategy & Roadmap, or an Embedded Transformation Partner model — each scoped to the client's starting point and risk appetite. Specific commercials are agreed during discovery; Propel commits to coming back within a day with a view on whether they're the right partner and what the first 30 days look like. ### How long does an AI transformation take? Propel Ventures structures AI transformation engagements to match the client's starting point. An Executive AI Sprint — board and C-suite alignment plus a first cut of the AI strategy — runs from one week. An AI Strategy & Roadmap, covering capability assessment, organisation-wide use-case discovery, and a prioritised roadmap, runs from two weeks. An Embedded Transformation Partner engagement, where Propel sits alongside the client end-to-end across strategy, governance, delivery, and capability uplift, starts from one month and runs on a quarterly re-prioritisation rhythm because strategy is treated as a living document, not a one-off deck. [// let's talk] ## Ready to rewire how you work? Tell us where you are — building AI products, transforming how a function operates, or somewhere in between. We'll come back within a day with a view on whether we're the right partner, and if we are, what the first 30 days look like. Call to action: Book a discovery call → /contact --- # About Source: https://www.propelventures.ai/about [// why propel] ## Built to ship. Wired to think. A decade of product-led delivery, now turned on how AI rewires the way work actually gets done. [// who we are] ## Strategists, designers and engineers. We're a firm of strategists, designers and engineers headquartered in Melbourne, with offices in Sydney and Ho Chi Minh City. We started in product. We've spent ten years asking "is this valuable, is this viable, will people use it, can it be built" before writing a line of code — and now we apply that same discipline to AI consulting, for tech companies shipping AI products and non-tech businesses rewiring how they run. [Our ethos] ## The Propel Story Want to learn more about the Propel story and how it all began? We captured our values, approach, services, team makeup and history into our comic book ‘Ethos’. [// Our Values shape how we partner with clients] ## The Propel Way ### Founders Mindset (// Being focused, taking ownership and having a bias for action) At Propel, we balance a healthy respect for process with a delight for breaking rules. We smash through obstacles, always finding new and better ways to achieve our goals. We resolve open questions fast, and favour using data and direct client feedback to make decisions. ### Craftmanship (// Investing the right amount of time to work your magic) The product development process is like a game of snakes and ladders, and we are always on the lookout for ladders to accelerate development. Craftsmanship at Propel embraces the capability to identify parts of the design process where we can disproportionately invest effort vs parts where we can go lean. ### Client obesession (// Building empathy for and understanding of our clients) Client obsession is a potent ingredient in our product recipe. It involves deeply understanding what drives our customers, connecting with both their desires and frustrations. Then using this understanding, to relentlessly evaluate our ideas and actions ensuring we make the best possible outcome a reality. ### Forthright (// Having direct honest conversations focusing on the issue not the individual) We recognise that conflict is the pursuit of truth - conflict always exists, we just expose it through forthright conversations. Forthright conversations are predicated on building a foundation of trust amongst team members. We use the level of constructive conflict in theteam as a barometer for the level of trust. ### Outsized Impact (// We make an outsized impact relative to the time spent) At Propel, we encourage a collaborative approach to working. By mentoring other team members or offering inputs into their work, one person can boost multiple people's productivity levels. This means that we can bring products to the market, faster! --- # AI Product & Engineering Source: https://www.propelventures.ai/ai-product-engineering [// AI Product & Engineering] # Production-grade AI software. Not demos. Embedded squads shipping AI features inside your existing platforms, AI-native products from scratch, and the automations and integrations behind them. Same product-led discipline that has defined Propel for a decade — now with AI engineering as the way we work. ## Most AI initiatives fail in the gap between prototype and production. We're built to close it. Spinning up an LLM demo is a weekend. Shipping an AI feature your customers, regulators, and ops team can rely on is a different sport — one that needs product discovery, real engineering, evals, observability, and ways of working that don't break the moment context changes. That's our craft. [// what we ship] ## Four kinds of work, one bar for quality. We're not picky about the shape — agent, feature, automation, platform — but we are picky about the standard. Every piece of work has to be valuable, commercial, responsible, and engineered. ### AI-native products From discovery through to a launched product. We validate the opportunity, design the experience, build the platform, and ship it — with the team, evals, and operating rhythm to keep it improving once it's live. ### AI features inside existing products Ship AI inside your established product without breaking the install base. We embed alongside your team, work to your engineering standards, and lift internal AI capability while we ship. ### Automations & agentic workflows Internal tools that take cost out and put speed in — pricing agents, document analysis, workflow orchestration, knowledge banks. Built once, audit-able forever, with humans in the loop where they belong. ### Integrations, data & the AI workbench The unglamorous work that makes everything else possible — system integrations, data pipelines, retrieval layers, evals & observability, and the platform plumbing that lets your AI work scale. [// the propel bar] ## Four tests every shipped piece of work has to pass. The same bar that runs across every Propel engagement. Demos are easy. Software your customers, regulators and ops team can rely on is the work. ### Valuable Solves a real problem. We validate before investing in code, and we'll tell you when an idea isn't worth pursuing. ### Commercial Cost, latency, ROI and unit economics tested before scale. The maths has to work — including the inference bill. ### Responsible Privacy, security, IP, evals, guardrails and human-in-the-loop where it matters. Compliance baked in, not bolted on. ### Engineered Production-grade. Observability, deterministic where it needs to be, and the operating rhythm to keep it that way. [// how we work] ## Embedded squads. Forward-deployed. Outcome-focused. Our teams sit inside your team. They're full-stack, T-shaped, and built to thrive in ambiguity. We measure them on what changed for your business — not what we delivered. ### Integrated product + engineering Product managers, designers, engineers and AI architects on one squad. No throw-overs, no phase gates. Discovery and delivery happen in the same room. ### Forward-deployed by default Embedded with your team, on your tools, inside your engineering standards. Knowledge transfers as the work happens — not in a closeout deck. ### AI engineering as the way we work Our people use modern AI tooling to build modern AI software. Evals, observability, retrieval, agent orchestration, and prompt-as-code aren't extras — they're how the work gets done. ### Capability transfer is built-in Every engagement uplifts your internal team. We coach by doing — modelling best practice while actively delivering — so when we leave, your team owns it. ### Discovery before code We validate the opportunity, the experience, and the technical approach before writing the production version. Saves million-dollar mistakes. ### Outcome-based commercials available Rate card by default; shared-risk and outcome-based pricing where it makes sense. We back our work — and price accordingly. [// the stack we know] ## Multi-cloud. Multi-model. Framework-fluent. We're partners with AWS, Microsoft, Google and Anthropic — and we'll pick the stack on the merits, not the relationship. Below: a snapshot of the tools we use most, in production. ### // Cloud & AI platforms - AWS Bedrock, Agent Core - Microsoft Foundry & Agent Framework - Google Vertex AI - Anthropic Claude - Azure OpenAI ### // Models & modalities - Frontier & open-weight LLMs - Voice (Nova Sonic, Realtime) - Vision & multimodal - Embeddings & rerankers ### // Patterns - RAG & context engineering - Agentic & multi-agent (MAF, Strand) - MCP for tool & data access - Human-in-the-loop workflows - Evals, guardrails & observability ### // Engineering - TypeScript / Python / Go - React, Next.js, mobile native - Cloud-native data & APIs - CI/CD, IaC, secure delivery [// proof] ## Recently shipped. A snapshot of production AI work across financial services, hospitality, retail, energy, media and logistics. ### // Cameron Harrison · Wealth: Agentic financial analyst on Microsoft Foundry Specialised agents for qualitative and quantitative analysis. Real-time market events, earnings & annual report processing, surfaced into analysts' email and workflow. Metric: 2× — Analyst productivity · weeks → minutes ### // Doltone House · Hospitality: AI pricing agent inside Microsoft Teams Pulls live CRM data, applies all venue, seasonality and lead-time rules, and surfaces a complete pricing recommendation. Junior staff price like seniors. Human approval, always. Metric: 3-5 min — From enquiry to quote-ready price ### // Moving Hub · Outbound contact centre: Agentic voice agent on Amazon Nova Sonic Real-time natural voice agent built on AWS Agent Core. Verifies identity, detects voicemail, qualifies leads, books appointments — all under human compliance review. Metric: 90% — Cost reduction · 100% qualification accuracy ### // RMS Cloud · Hospitality SaaS: GenAI guest insight card inside RMS Dynamic guest profile built on AWS Agent Core + Strand framework. Embedded directly into the RMS UI; smooth adoption with no workflow disruption for hospitality staff. Metric: +0.4 — CSAT lift · 20% upsell offer rate ### // Aje · Fashion: Brief-aligned creative generation tool Custom prompt-generation app that turns Aje's seasonal creative briefs into Midjourney-ready prompts. Scales the application of AI imagery without breaking design intent. Metric: 47% — Concept-to-sample time reduction ### // Kopa · AdTech: AI video classifier replacing manual sourcing Multi-model PoC validated on cost / accuracy / speed, then productised. Scrapes and tags YouTube videos for ad placement; eliminates the human-in-the-loop bottleneck. Metric: 4× — Campaign coverage · 70% faster setup ### // Redcat · Hospitality tech: Computer-vision PoC for order accuracy Two-week discovery building two PoCs — post-hoc evidence retrieval and live packing monitoring — across 51 structured test scenarios. Honest GO/NO-GO recommendation. Metric: 96% — Removal detection · 0% false positive rate ### // AGL · Energy: EV charge-point management system Discovery, feasibility, and end-to-end build of a charger management platform. Full APIs for the consumer mobile app; foundation for AGL's decarbonisation play. Metric: Live — Foundation for AGL's EV business ### // Netwealth · Wealth platform: Reimagining the AI-native PDLC Rewiring how Netwealth's product and engineering teams ship AI features inside an established financial platform. Operating model + delivery happening in lockstep. Metric: In-flight — PDLC redesign · embedded squad model > Propel have been a key partner in delivering a number of solutions to our customers. They bring deep experience and knowledge in product management that ensures we are delivering the most important features first with a customer-centric mindset. Mixed with their ability to deliver in an agile way, cloud technologies, makes them a strong full-service delivery partner. — DARREN SMITH · CHIEF PRODUCT & TECHNOLOGY OFFICER [// ways to engage] ## Squad shapes that fit the work. Most engagements start with one of these. We'll tell you in the first conversation which is the right shape for the problem. ### Discovery & PoC (// 2–4 weeks) Validate the opportunity, the experience, and the technical approach. Honest GO / NO-GO recommendation with the evidence to back it. - Problem framing & user research - Technical feasibility / model choice - Working PoC in a controlled environment - Unit-economics & risk assessment Ideal when: the upside is real but the path isn't proven yet. ### 0→1 product squad (// 8–16 weeks) Full product + engineering squad to take an AI initiative from validated PoC to first production release. Discovery embedded throughout. - Product manager + designer + engineers + AI architect - End-to-end delivery to production - Evals, observability & guardrails by default - Capability transfer to your internal team Ideal when: you've validated the opportunity and need to ship. ### Embedded engineering partner (// 6–12 months) Ongoing forward-deployed squad inside your product team. Ships AI features alongside your roadmap, lifts capability as it goes, and operates the platform once live. - Persistent squad model (intact teams) - Aligned to your engineering standards - Quarterly priorities & outcomes review - Outcome-based pricing available Ideal when: AI is now core to your product roadmap. [// let's talk] ## Ready to ship something that lasts? Tell us what you're building. We'll come back within a day with a view on whether we're the right squad — and if we are, what the first 30 days look like. Call to action: Book a discovery call → /contact --- # Careers Source: https://www.propelventures.ai/careers [// Careers] # We don't ship pilots. We ship work that lasts. A decade of product-led delivery, now turned on how AI rewires the way work gets done. Embedded squads, real production work, capability uplift built into every engagement — pragmatic, not Big-Four cookie-cutter. We hire ahead of need — if you're the right kind of builder, we want to know you. [// the 60-second pitch] ## Four reasons engineers, PMs and designers pick Propel. No mission statements. No "passionate about innovation". Here's what's actually different about working here. ### Production AI work Agentic analysts running at Cameron Harrison. The AI Dev Toolkit shipping code daily inside Netwealth. Natural-language reporting at the heart of MYOB Advisor. Real software, used every day, with our names on it. ### Embedded — not arms-length Forward-deployed inside the client's team — typically alongside other Propel folks. Same tools, same engineering standards, real ownership of the outcome. Closer to the build than any advisory shop will get you. ### AI engineering as the default Modern AI tooling, evals, observability, and prompt-as-code aren't side projects — they're how we ship. We invest in your toolkit so you stay current. ### You'll grow faster here Capability uplift is built into engagements. You'll coach by doing, lead earlier than you would elsewhere, and work alongside seniors who actually code, design, and ship. [// recently shipped] ## What you'll actually work on. A snapshot of recent client work. The next squad you join is probably building something like one of these. ### Looking after a million family albums Tinybeans is where parents store their kids' first steps, first words, and a thousand other moments they can't afford to lose. Propel runs the product end-to-end — iOS, Android, web and the systems behind them — so families keep loading photos and the Tinybeans team can focus on what's next. ### MYOB Advisor — natural-language reporting Advisory reporting tool built on natural-language generation that turns the numbers in accounting software into client-ready commentary in seconds. Won an AFR Innovation Award and underpinned a material price increase. ### Green Finance launch for solar & battery Worked across nearly six AGL teams to relaunch a competitive green loan for solar & battery bundles. Mapped every flow and edge case, then led delivery end-to-end into market — paving the way for partnerships with Westpac, CBA and others. ### AI Dev Toolkit — enterprise SDLC augmentation Codified Netwealth's architecture into 12 agent modes, 7 custom prompts and 18 instruction files. Five MCP servers wire it into Datadog, Jira, Playwright, Index 7 and Azure DevOps. Deterministic, guided coding inside VS Code, Visual Studio and Rider. ### Computer-vision PoC for order accuracy Two-week discovery building two proofs-of-concept — post-hoc evidence retrieval and live packing monitoring — across 50+ structured restaurant scenarios. Honest GO/NO-GO with a defined path to production. ### ReadyPay employee self-serve mobile app Cross-functional product team running dual-track agile — continuous discovery alongside delivery. Single mobile experience integrating multiple payroll platforms with federated identities. Launched 2023 with a design system that scales mobile and web. [// who thrives here] ## You'll feel at home if… Our values are the table stakes — the actual day-to-day filters for who's a fit. If three or more of these sound like you, we should talk. ### Founders mindset You take ownership without waiting for permission, resolve open questions fast, and move on data and direct feedback rather than committee. ### Craftmanship You know where to disproportionately invest effort and where to be lean. You care about the streaks on the forks. ### Forthright You can have direct, honest conversations about the issue without making it about the individual. Conflict is fine. Avoiding it isn't. ### Client obsession You actually like client-facing work. You enjoy understanding what drives the customer and using that to relentlessly evaluate your own ideas. ### Outsized impact You make others around you better. You care about leverage — multiplying the team's output, not just maxing out your own hours. ### Comfortable with ambiguity You can prioritise and deliver the highest-value work even when context is incomplete. You don't get blocked by it. ### All-in on AI personal productivity You're already using Claude, Cursor, ChatGPT or similar daily — for your own work, side projects, or the thing you're tinkering with this weekend. Not theoretical, not last-quarter. This one's a non-negotiable. ### Curious by default You read the paper, run the experiment, build the thing in your spare time. We'll happily back the side projects — most of our best IP started as one. [// the propel embedded expert] ## A different shape of engineer, PM, designer. We're not hiring people to slot into a feature factory. We're hiring people who can stretch across disciplines, hold context, and lift the team they're embedded with. Column A: Typical feature-team member | Column B: Propel embedded expert - Technical breadth: Specialised; often not full-stack → Full-stack across frontend, backend, cloud and infra - Working style: Task-focused; waits for direction → Outcome-driven; self-directed and proactive - Stretch: Rigid role boundaries → T-shaped — comfortable across engineering, product and coaching - Context awareness: Detached from business or customer context → Deeply embedded; forward-deployed mindset aligned to mission goals - Coaching: Coaching is indirect or external → Uplift by doing — model best practice while actively delivering - AI readiness: Risk-averse; unsure how to engage with AI → Confident guiding safe, practical AI experimentation aligned with the business [// open roles] ## We hire ahead of need. Most of our roles below are pipeline conversations rather than active hires — we like to know good people before we need them. Roles tagged "Active hire" have a defined start date. [// where we work] ## Several offices, one team. Hybrid by default — three days a week in office, more as needed. We're intentional about getting humans together for the high-bandwidth work and giving them the space to do focused work the rest of the time. ### 3 Hill Street Cremorne Strategy, product, design, engineering, AI architecture and the leadership team are based here. The space is where we host clients, run workshops and bring squads together for the high-bandwidth work. ### Level 9, 31 Market Street Small and emerging — planted on purpose. Sydney is Australia's biggest commercial hub, and we want senior consultants on the ground close to the boards and exec teams driving most of our east-coast pipeline. The wider practice is a flight away in Melbourne, or a video call away in HCMC. ### 1st Floor, 89 Ham Nghi, Sai Gon Ward A growing engineering team in HCMC, working as one squad with our Australian crews. Same engagement model, same bar, same access to client work. We back this team for the long term. [// the process] ## A four-step process. No surprises. Most candidates go from first conversation to offer in three to four weeks. We tell you what each step is, who's in the room, and what we're testing for. ### Intro conversation 30 minutes with our Talent Lead. We share what's on at Propel right now and learn what you're optimising for. No CV interrogation — we've already read it. (~30 min · video) ### Craft conversation 60 minutes with a principal in your discipline. Real work, recent decisions, trade-offs you've made. We're testing how you think, not whether you can recite a textbook. (~60 min · video or in person) ### Practical exercise A scoped, paid practical that mirrors real Propel work. You can do it sync or async. We'll tell you exactly how it'll be assessed before you start. (~3–4 hours · paid · async or sync) ### Team & founder time Meet the squad you'd join, plus 30 minutes with one of the founders. We'll make a decision within 48 hours of this conversation. You'll know. (~2 hours · in person where possible) [// diversity, equity & inclusion] ## Different people, sharper team. Our team is made up of people with different values, backgrounds, skills, experiences and needs. That includes gender and identity, marital and family status, ethnicity, language, age, sexual orientation, religious and political beliefs, cultural background, socio-economic status, physical and mental ability, perspective, experience and education. We back this with practice — recruitment, selection, training, remuneration, leave, flexible working, and progression are all designed to reflect it. Our exec is accountable for measurable gender equity outcomes, and the D&I committee owns the rest. Propel acknowledges that we gather, live, work and design on Aboriginal land. We extend that respect to elders past, present and emerging as we walk together on this beautiful land we call home. [// don't see your role?] ## Tell us what you're looking for. We hire ahead of need, and we read every application. Drop a line — what you do, where you'd want to work, and what would have to be true for you to make a move. We'll come back within a week with an honest answer. Call to action: careers@propelventures.com.au → mailto:careers@propelventures.com.au --- # Publications Source: https://www.propelventures.ai/pub [// Thought Leadership] ## Our Publications With a decade of expertise in product-led development and AI delivery, we transform frontline experience into industry-leading insights. Our library features four ebooks on software delivery, two guides on product-led frameworks, and our latest release on the AI software development process. Explore our proven strategies for navigating the next frontier of digital engineering [// From Task-Based AI to Process-Native Delivery] ## AI-Augmented SDLC: The Flywheel of Compounding Delivery While many organizations have "bolted on" AI to speed up individual tasks, the underlying software delivery model often remains unchanged, relying on human-centric handoffs and static documents. Our latest whitepaper introduces the AI-Augmented SDLC, a model built around a central Delivery Knowledge asset that turns every human correction into a compounding signal for improvement. By restructuring the team into a specialized trio—Product, Design, and Engineering—with AI as the orchestration layer, organizations can shift from manual artefact production to high-leverage validation. This framework provides a clear maturity scale for investing in proven AI cores while piloting emerging capabilities, ultimately compressing cycle times and scaling through knowledge rather than headcount. [// Navigating the Shift from Features to Outcomes] ## Product Success Playbook: How to Make the Transition to Become Product-Led Transitioning to a product-led model is a fundamental cultural and operational shift that goes far beyond changing a few job titles. This playbook serves as a strategic roadmap for organizations looking to move away from being "feature factories" and toward becoming outcome-driven powerhouses. We break down the specific steps required to empower product teams, redefine success through the lens of customer value, and align stakeholders around a shared product vision. Learn how to dismantle the silos between "business" and "IT" to create a unified engine for sustainable growth. [// The Foundational Elements of Modern Product Excellence] ## Product Success Playbook: Five Pillars of a Successful Product-Led Organisation What separates the world’s most successful product companies from the rest? It comes down to five critical pillars: Strategy, People, Process, Data, and Culture. This publication provides a deep dive into each of these domains, offering a diagnostic tool for leaders to assess their current maturity. From establishing clear "North Star" metrics to fostering a culture of safe experimentation, we provide the blueprints for building an organization that can adapt to market changes at speed. This guide is essential for any leader tasked with scaling a product organization while maintaining a relentless focus on the user. [// A Framework for Speed, Quality, and Market Fit] ## The Propel Way™ to Successful Product Development Most software projects fail not due to a lack of effort, but due to a misalignment between technical delivery and customer value. The Propel Way™ is our proprietary delivery framework designed to bridge this gap by integrating Product-Led Development with high-velocity engineering. This document outlines how we move from discovery to deployment using a disciplined, phase-based approach that prioritizes "building the right thing" as much as "building the thing right". By focusing on continuous feedback loops and cross-functional transparency, we help organizations reduce waste and deliver software that actually moves the needle for their business --- # Contact Source: https://www.propelventures.ai/contact [// let's talk] ## Ready to rewire how you work? Tell us where you are. We'll come back within a day with a view on whether we're the right partner, and if we are, what the first 30 days look like. [// get in touch] ## Tell us where you're at. We'll come back within a day with a view on whether we're the right partner, and if we are, what the first 30 days look like. --- # People # Abdi Daud — Lead Architect Source: https://www.propelventures.ai/people/abdi-daud Abdi is a seasoned solutions architect and Propel's Lead Architect, bringing deep expertise in modern software architecture, cloud platforms, data-intensive systems, and AI PDLC transformation. He leads architectural design and technical strategy across a portfolio of complex client engagements, shaping scalable, secure, and production-ready platforms that serve real business needs. # Ben Ross — Founder Source: https://www.propelventures.ai/people/ben-ross A product leader and entrepreneur focused on helping businesses apply AI to real commercial problems — from intelligent automation to agent-based systems. An early voice in the field with a 2015 TEDx talk on AI, he now advises executives, product leaders and founders on turning AI ambition into outcomes # Amy Johnson — Chief Product Officer Source: https://www.propelventures.ai/people/amy-johnson A product leader, passionate about empowering teams and fostering inclusion. Multi industry experience, now leading the product team at Propel, where we partner with you to accelerate your product development and achieve product market fit faster. # Paul Greenwell — Founder Source: https://www.propelventures.ai/people/paul-greenwell A product and technology leader with 25+ years building software at the intersection of engineering depth and commercial strategy. A co-founder of Propel Ventures, he helps businesses apply AI through forward-deployed teams that work shoulder-to-shoulder with clients to ship end-to-end solutions with speed, autonomy and ownership. --- # Insights # Claude Partner Program Select Partner Status - What Does it Mean for You Source: https://www.propelventures.ai/blog/claude-partner-program-propel Meta: Ben Ross Anthropic does not hand out partner status. It is measured on certified people, live production deployments and published customer results. Here is what Propel has earned, what it unlocks, and why it should change how you choose an AI delivery partner. # Propel Ventures is a Select partner in the Claude Partner Network. Here is what that actually means. Most “AI partner” claims are a logo on a slide. A firm fills in a form, gets listed somewhere, and from then on the word “partner” appears in every proposal. Nobody checks whether the firm has put anything into production, whether its people can pass an exam, or whether a single customer has agreed to be named. Anthropic built its Claude Partner Network differently, and the difference is worth understanding before you hire anyone to help you deploy Claude. ## Registered is not partnership. Select is. The Claude Partner Network Services Track has an on-ramp and three partner tiers. The on-ramp is called Registered. A Registered firm has been accepted into the program and can access training and certification, but it is not a partner. It cannot use the Claude Partner badge, does not appear in the partner directory, and may not describe itself as a Claude or Anthropic partner. Partner status begins at Select. Above Select sit Preferred and Global Premier, reserved for firms operating at significant scale across multiple regions. Propel Ventures is a Select partner in the Claude Partner Network Services Track. In Anthropic’s words: “The Claude Partner Network is how Anthropic works with the firms that put Claude into production for customers. The Services Track recognizes partners for building a certified delivery team, deploying it with customers, and proving the work through public customer references.” ## How a tier is earned A firm reaches a tier only by meeting every one of three published minimums at the same time. There is no composite score, no averaging, and no application step. Anthropic verifies the data itself at a scheduled review. The three dimensions are: Active certified individuals. People holding a current Claude certification, earned under the firm’s own email domain. The exams are proctored and identity-verified through Pearson VUE, and they are open only to approved partners. Customers cannot sit them. Certifications expire, so a certified bench is a live measure, not a historical one. Deployed joint customers. Unique customers with a live production deployment where the firm is Delivery Partner of Record. Pilots and proofs of concept do not count until they reach production. Each engagement has to be registered with Anthropic and is verified against the customer’s actual Claude usage before it is credited. Public customer stories. Stories that describe the customer’s challenge, the partner’s approach, delivery to production and quantified business impact. A story counts only after Anthropic has reviewed and approved it, and only with the customer’s consent to publish. Notice what this rules out. You cannot buy your way in. You cannot talk your way in. You cannot get in on the strength of a slide deck about “AI transformation”. You get in by having certified people, live deployments a customer is paying to use, and at least one customer prepared to put their name to the result. ## What Propel brings to that measure Propel has been building software and product teams in Melbourne since 2016 and has worked with more than 100 teams across financial services, energy, retail, health, education, property and hospitality. We are ISO 27001 certified and partner with AWS, Microsoft, Google and Anthropic. On the three dimensions that matter to Anthropic: Anthropic has approved more than twenty of our engagements as Services Registrations under the Claude Partner Network, recognising Propel as Delivery Partner of Record. They span wealth management, superannuation, capital markets, energy, media, investigative software, health, property and construction, and the not-for-profit sector. Our Fern Group customer story is published and public: a five-day AI Growth Sprint, governance-first guardrails and a custom Claude plugin took a boutique advisory firm from AI-curious to AI-native in eight weeks. 16 Propel consultants and engineers hold current Claude certifications such as Claude Certified Architect: Foundations. Beyond the tier criteria, there is a number we are prouder of. Propel has now trained more than 3,000 people in how to work with Claude and generative AI safely and productively, from board members and executive teams to analysts, engineers and front-line staff. That is not a marketing statistic. It is 3,000 individual moments where someone sat with a Propel practitioner, worked on their own real task, and left able to do something they could not do that morning. It is also why our deployments stick: the tooling is only half the job, and the half most firms skip is the people. ## What Select means for our clients Partner tiers are easy to dismiss as vendor theatre. This one changes what you get when you engage us. Your risk is lower. Anthropic has independently verified that we put Claude into production for real customers and that those customers are actually using it. You are not the firm we learn on. Our people are examined, not self-described. Every Claude certification on a Propel CV was earned in a proctored, identity-verified exam that is not open to the general market. When we say someone is a certified Claude architect, a third party has tested that claim. We hear about product changes before you need to react to them. Select partners join Anthropic’s product update calls and receive partner briefings on new models, safety features and enterprise capabilities as they land. When Anthropic ships a change that affects your governance posture, your cost profile or your roadmap, we have usually already read the material and formed a view. We can prototype at no cost to you. Select partners have access to Anthropic sandbox credits, which means we can test an approach on your problem before you commit budget to it. We have a direct line to Anthropic. When something is unclear about a model’s behaviour, an enterprise control, or a licensing question, we ask Anthropic’s partner operations team rather than guess. That is faster and safer than either of us reading forum posts. We are not a reseller. Propel earns nothing from your Claude subscription or API spend. Our advice on when Claude is the right tool, and when it is not, is the same advice we would give if Anthropic did not exist. ## What it means for the people who work here Being a Select partner obliges us to keep certifying, keep deploying and keep publishing. For our people that means: Access to the Claude certification program, which is partner-only, with the exam discount that comes with our tier. Every consultant and engineer at Propel is expected to hold a current credential relevant to their role. Anthropic Partner Academy courses on the Claude API, the Model Context Protocol, Agent Skills and Claude Code, taken under a Propel email so the completion counts toward the firm. Partner-only briefings, model documentation and sales enablement material as it is released. Sandbox credits to build and break things without asking a client to fund the experiment. If you want to work somewhere that treats AI capability as an examined professional standard rather than a line in a LinkedIn headline, this is the point. ## Where this goes next Select is where partner status begins, not where it ends. The tiers above it are earned the same way, on the same three dimensions, and we intend to earn them the same way we earned this one: by putting Claude into production for customers who are willing to say so publicly. If you are weighing up a Claude deployment and want a partner whose credentials Anthropic has checked, talk to Ben at  ben.ross@propelventures.ai Propel Ventures is a Select partner in the Claude Partner Network Services Track. The Claude Partner Network is how Anthropic works with the firms that put Claude into production for customers. Learn more at  claude.com/partners . # How Bayley Stuart Got Its Whole Team Building in a Week Source: https://www.propelventures.ai/blog/bayley-stuart-claude-customer-story-copy Meta: Ben Ross A keynote, five days of side-by-side coaching and one working automation per person took Bayley Stuart from installing Claude to running its own workflows inside a single week. # How Bayley Stuart Got Its Whole Team Building in a Week A keynote, five days of one-to-one coaching and one working automation per person took Bayley Stuart from installing Claude to running its own workflows inside a week. Bayley Stuart · Commercial property investment management · Melbourne · One week ## The challenge Bayley Stuart is a ~ten-person Melbourne commercial property investment manager holding an AFSL, running almost entirely on email and documents with no in-house engineering function. The work that consumed them was the work that repeats - monthly and quarterly cycles across funds, asset management and office operations. Leasing hand-offs often took days; a lease summary cost external legal fees; one question relating to the fund model could remain open for days as the analysis was crunched. In a team of ten, nobody can disappear into a week of training and nobody is spare to maintain something afterwards. Whatever got built had to be built by the people who would use it, and it had to be working by Friday. ## Governance first Bayley Stuart holds an AFSL, so the regulatory floor - ASIC, APRA, AUSTRAC, privacy, cyber resilience - is not optional. Before kick-off the COO was already drafting an AI Framework and Policy with external compliance advisers, built on seven principles including mandatory human oversight, privacy and data protection, and proportionality. We worked to that document: data residency, connector permissions and acceptable-use boundaries were settled with the firm's IT provider in the same week the team was learning to prompt. ## The approach: one keynote, then five days side by side Monday  - the whole company in one room. A two-hour kick-off with live demonstrations built on Bayley Stuart's own leases and fund model, not sample data. The afternoon went on licences and connectors. Tuesday to Friday  - desk-side, one person at a time, building a skill against work they genuinely did that week. Two method choices did the work: nobody left their 1:1 without shipping their own first skill, and every question was put to Claude together rather than answered for them - teaching the mindset, not just the answer. It moved fast because the firm arrived with its operations already in order - disciplined folders, categorised email, genuinely documented processes. Most of the cost of automating knowledge work is archaeology; Bayley Stuart had done that work already, so automations could point at real folders and a real documented sequence from day one. ## What was deployed and built Claude installed for every member of staff on site, with the Microsoft 365 connector admin-consented at tenant level (governed SharePoint and mail access), plus Cowork, the Office add-ins and a Plaud meeting-recorder integration A Heads of Agreement skill  - leasing minutes in; updated minutes, a drafted HoA and covering email out, in one pass A Lease Review skill  - any lease in, a one-page analysis out, flagging early termination rights, incentive clawbacks and pro-rata repayments A batch-payment skill  turning an Excel schedule into signed PDFs, plus monthly PDF/spreadsheet reconciliation, a newsletter builder and a scheduled email-to-PDF filing pipeline A client-owned skill library on SharePoint, filed by business line and indexed in a self-updating, version-controlled reference list, plus a written FAQ and best-practice handbook - both built to outlast the week ## The results 100% of staff on site built and deployed their own first working automation, start to finish 4.75 / 5 overall, NPS +50, no detractors, nothing scored below four 5.00 / 5 that the week left people confident using Claude on their own work unaided, and 5.00 / 5 that they'll keep using what was built in their 1:1 Automations live across funds, asset management and office operations Adoption spread with no internal mandate - the team member the firm expected to resist is now leading it internally Scores from the post-engagement participant survey, four responses. "It's not to reduce our team. It's to maintain our team - not grow exponentially - keep a good team of people and get a lot more efficient." Andrew MacGillivray, Managing Director, Bayley Stuart ## What happened next Once we had gone, the firm independently turned the same approach on leasing - loading its own executed leases as reference material and surfacing commercially significant provisions for a decision, with every draft approved by a person. Participants have named further automations unprompted: condition reports, board reporting, and rental reconciliation against a live model. The 1:1 build-your-own-automation method is now Propel's standard delivery model for Claude enablement. "We're a small team with no IT function, so the risk is that it gets built for you and then sits there. That didn't happen. Everyone built their own thing, which means we can keep going without needing someone from Propel to come back." Piers Jalland, Head of Funds and Transactions, Bayley Stuart ## The pattern that works Governance before enthusiasm, so nobody has to slow down to ask if they're allowed. Every person builds, because doing it yourself teaches you what to ask for next. Then make that skill or asset part of the firm's IP, not the individual's - the best version promoted into a shared library is what turns a good week into institutional capability. It is repeatable for any document-heavy firm without an engineering team, and it travels at the speed of the operational discipline it lands on. If that's the journey you're on, talk to us at  propelventures.ai/contact . Propel Ventures is a partner in Anthropic's Claude Partner Network. # How Fern Group Made Claude the Way the Whole Firm Works Source: https://www.propelventures.ai/blog/fern-group-claude-customer-story Meta: Ben Ross A five-day AI Growth Sprint, governance-first guardrails and a custom Claude Plugin took Fern Group from AI-curious to AI-native in eight weeks. Most small firms are experimenting with AI. Very few have turned it into institutional capability — tools every person uses the same way, with guardrails built in. That's what Fern Group set out to do, and it took eight weeks. ## Where Fern started Fern Group, a boutique Australian advisory firm, was already using AI — but adoption lived with individuals. Each person had their own prompts and habits, results were inconsistent, and the firm's capability walked out the door whenever attention shifted. More critically, there were no guardrails: no data classification policy, ad-hoc decisions about what client information went into AI tools, and SharePoint permissions that couldn't stop sensitive data flowing into AI via the Microsoft 365 Connector. ## A sprint, then a roadmap — governance first We began with a five-day AI Growth Sprint : an AI maturity assessment, target operating model, technology recommendation and phased roadmap. The assessment found Claude was the team’s strongest tool — outperforming Copilot across every use case Fern tested — and set three imperatives: make Claude the firm’s primary intelligence layer, fix the governance foundations before building further, and sequence builds by time-recovery value. We then executed the roadmap in three phases: 1. Data Guardrails. A three-tier classification framework (AI-Unrestricted / AI-Restricted / AI-Prohibited) with every client classified, firm-wide PII rules — passports, police checks and bank details never enter any AI tool — SharePoint permission hardening with Fern’s IT provider, and a Claude Enterprise evaluation. 2. The Fern Plugin. One installable Claude Plugin bundling Fern’s tone and style guide, a shared prompt library, branded presentation and Word document creators, and a proposal-generation workflow — with the data guardrails built in. Install it, and every team member has identical, production-grade tools from day one. 3. AI Philosophy. A leadership workshop defining what Fern will use AI for, and the capabilities to invest in. ## The results Client proposals that used to absorb around 10 hours of drafting now take about 20 minutes — on-brand, in Fern’s tone, built by the plugin’s proposal workflow. Across the team, that and the document tools free up around five hours per person per week . Beyond the numbers: 100% of Fern’s clients are now covered by the classification framework, the full team works from one production-grade plugin, and AI capability now belongs to the firm rather than to individuals. The strongest signal came unprompted — on the strength of the work, Fern referred us to another firm, which became a new engagement. Propel didn’t just show us what AI could do — they made it how our firm works. Every one of us now produces client-ready documents with the same tools and the same guardrails, and we trust what goes into AI because the governance was built first. — Daniel Khong, Co-founder, Fern Group ## The pattern that works Fern’s journey — sprint, guardrails, then institutional tooling — is repeatable for any professional-services firm that wants AI to be how the firm works, not just what a few keen people do. If that’s the journey you’re on, talk to us at propelventures.ai/contact. Propel Ventures is a partner in Anthropic’s Claude Partner Network. # Your AI Transformation Is Invisible (Until You Measure It Like This) Source: https://www.propelventures.ai/blog/your-ai-transformation-is-invisible-until-you-measure-it-like-this Meta: Abdi Daud Most enterprise AI transformations can't show what changed. Here's how to measure the shift with existing telemetry, not a new metrics regime. Here's the uncomfortable pattern in enterprise AI adoption. An organisation invests real money in AI-assisted engineering (tools, training, new ways of working) and six months later, nobody can say what changed. Some developers transformed how they work. Others quietly didn't. And nobody can tell which is which. The executives sponsoring the change are funding something they cannot observe. Every claim of uplift is a story, not evidence. Continued funding rides on those stories. We've been working on how to fix this, and the answers cut against most of the measurement advice on the market. ## Raw output metrics answer the wrong question The obvious move is to buy developer analytics: lines of AI-generated code, PR counts, suggestion acceptance rates. These measure raw output. What actually matters is something else: how far a team has shifted toward agentic software development, and what that shift means for the business. That distinction is everything. The gap in the market is not a data gap. Telemetry is nearly free now; modern AI coding tools ship with OpenTelemetry support and hook systems out of the box. The gap is a framing and reporting gap: connecting that exhaust to a transformation narrative an executive can steer by. ## Don't impose a metrics regime. Arrive where the client is. The standard playbook says: establish DORA metrics first, then measure improvement against them. We've watched that fail in practice, and we now believe leading with it is the wrong move for many organisations. Plenty of successful enterprises run two-month lead times and monthly releases, with no appetite to change that cadence. Others release quarterly. Push a faster-delivery measurement model onto them and you're fighting the client instead of helping them. At best your metrics work "virtually" while reality carries on unchanged. At Propel, we still push for DORA metrics, and faster delivery can remain a gradual long-term goal. It just can't be the entry fee for AI enablement. The better move is to report against the delivery cadence and metrics the organisation already runs. Every business tracks its own productivity somewhere: a single DORA metric, epics completed per quarter, cycle time in their PM tooling. Which leads to the most useful trick we know: Retrofit the baseline.  Because the organisation's own metrics have history, you can go back in time and build the before/after picture from data that already exists, rather than freezing delivery while you stand up a fresh measurement regime. The "baseline first" instinct is right. The "build new instrumentation first" reflex usually isn't. ## Expect a compounding curve, and measure it forward One more thing trips up impact reporting: AI-assisted delivery is not fastest on day one. Adoption follows a compounding curve. Efficiency gains scale non-linearly as organisational skills, context, and trust build. Evaluate at week four against a promise of instant transformation, and you'll kill programs that were about to pay off. We're not against uplifting metrics, but measurement shouldn't block the work of starting a transformation. Instead, run two tracks. Retrofit the organisation's existing metrics for the historical before/after, and start an AI-adoption-specific metric that trends forward from day one of the change. Together they tell the story honestly, without requiring anyone to bet on a heavy upfront measurement build. ## Extend what's running; don't build a collector Existing IDEs and agentic developer tools already expose built-in hooks. Enterprises, meanwhile, operate mature observability stacks and maintain the infrastructure to deploy extensions to every developer machine. So the strategy is straightforward: push custom events from those existing hooks directly into the client's current observability platform, then focus on the reporting layer above it. That's where the differentiating value lives. Aligning an organisation with entirely new metrics tools is never a drop-in process. It's fundamentally a data-governance challenge: deploying a new data-collection product inside a client's ecosystem introduces heavy security, privacy, and compliance obligations. None of this is an argument against advanced tools. It's an argument for implementing them correctly. Measurement should serve the transition, not hinder it, and tracking should never become the bottleneck that delays the actual rollout. Three practices make this concrete: Metrics as code.  No AI capability ships without its metrics. A code review agent, a code-generation agent, a skill: each emits its own usefulness signals from day one, versioned alongside the thing it measures. Instrument the conversation layer.  Default dashboards tell you that developers used an AI tool. Custom metrics and hooks tell you how: which skills, which capabilities, which workflows. That's where adoption actually shows up. We run this in production today. Roll AI effectiveness up to one score.  As outlined in AI-Augmented SDLC: The Flywheel of Compounding Delivery , a custom AI-effectiveness score computed from existing telemetry gives executives a trendline to steer by. Two core questions define it: Of what the AI wrote, what survived? And of the final output, what came from the AI? ## The takeaway If you can't show the baseline, the shift, and the trend, your AI transformation is a leap of faith wearing a business case. Measure the shift toward new ways of working, not out-of-the-box metrics. Measure it against the metrics your organisation already trusts, not an imposed regime. Do it through telemetry you already have, not a new product. And give the compounding curve time to compound. # Coding Is Getting Cheaper. Thinking Never Will Source: https://www.propelventures.ai/blog/coding-is-getting-cheaper-thinking-never-will Meta: 2026-04-06 · Paul Greenwell AI is the biggest leap in software productivity in 30 years. But cheaper code without product thinking just creates bloated, generic products nobody wanted. # Coding Is Getting Cheaper. Thinking Never Will. After 30 years in product and engineering, AI-assisted development is the most significant leap in software productivity I've seen. We're using these tools every day at Propel, and the acceleration is real. Features that used to take days take hours. Prototyping cycles that took weeks now happen in an afternoon. The cost of turning an idea into working software has dropped dramatically, and that's exciting. ## The bottleneck was never writing code However, everyone talks like the biggest constraint in software was the ability to produce code. But was it? For over a decade, platforms like .NET, Spring Boot and the broader cloud-native ecosystem have abstracted away massive amounts of complexity. Enterprise teams could stand up services, integrate systems, and ship working software faster than ever. Low-code and no-code tools have existed for years. If removing code was the magic bullet, developer demand should have collapsed long ago. It didn't. Because the real constraint was never syntax. It was thinking. Problem framing. System boundaries. Data flow. Failure modes. Designing systems that survive contact with real users. These are the hard parts, and they remain stubbornly human. AI is making the mechanical side of coding dramatically faster — and that's a welcome change. The question is whether teams keep investing in the thinking now that the building feels effortless. ## Constraints were a feature, not a bug When implementation was expensive, teams were forced to think carefully. You debated trade-offs. You questioned whether a feature was worth maintaining. You killed mediocre ideas early because they carried real cost. That pressure created discipline. The best products didn't win because they generated code faster. They won because they picked a narrow problem, executed well, and said no to a thousand tempting features. AI doesn't remove the need for that discipline — but it does remove the forcing function. When the cost of shipping a feature drops close to zero, it's tempting to try five variations instead of picking the right one. The result, if you're not careful, is products bloated with half-baked ideas that become maintenance nightmares. This is the risk I'd call "AI Slop" — bloated, generic features and experiences that technically work but nobody actually wanted. Not because AI is bad at writing code, but because nobody applied the product thinking to decide whether the code should exist in the first place. ## More software, not less There's an economic principle called the Jevons Paradox: when a resource becomes more efficient to produce, we don't use less of it. We use more. Lower the cost of generating software, and you don't shrink the industry. You expand it. More internal tools. More experiments. More dashboards. More automation. More surface area. And that's largely a good thing — entire industries that once relied on spreadsheets and manual processes now have access to purpose-built software that would have been cost-prohibitive five years ago. We see this at Propel every day, organisations coming to us because they've outgrown their spreadsheets and need real software to operate at scale. The opportunity is enormous. But more software also means more complexity, more maintenance, and a greater need for clear-headed decisions about what to build and what to leave alone. ## The teams that win will be the ones that were already winning The 2025 DORA Report captured something I keep seeing in practice: AI doesn't fix a team; it amplifies what's already there. Strong teams use AI to become even better. Struggling teams find that AI only highlights and intensifies their existing problems. This makes intuitive sense. Give a well-structured product team AI tools and they'll move faster, prototype smarter, and validate ideas with less waste. They'll use the speed to iterate toward better outcomes, not just more output. Give a team with no clear product strategy the same tools and they'll ship more features nobody asked for — just quicker. AI is a force multiplier. But a multiplier is only as good as what it's multiplying. ## The real bottlenecks haven't changed Even with code generation running 10x faster, you're still constrained by distribution, user attention, discovery, trust, and — let's be honest — bureaucracy. The app stores are full of millions of unused apps. Generating another thousand lines of code doesn't solve that. Speed of delivery was never the thing holding most products back. ## So what actually matters now? There will be more software. That much is certain. AI has permanently lowered the cost of building, and the Jevons Paradox guarantees we'll fill every gap we can find. That's exciting — it means more problems get solved, more workflows get automated, more organisations get the tools they need. But more software doesn't mean better products. Good product management — the discipline of understanding what to build and, critically, what not to build — matters more than ever. Good design, the craft of shaping experiences people actually want, matters more than ever. Good engineering, the practice of building systems that are maintainable, secure, and fit for purpose, matters more than ever. It's why at Propel, our roots in product management have become our sharpest edge. The ability to build is table stakes now. The ability to decide what's worth building — to hold the line on quality, to shape software around real user problems rather than letting AI fill every gap it can find — that's the differentiator. We've always believed the best software starts with the best product thinking, and AI has only made that conviction stronger. The teams that thrive won't be the ones that generate the most code. They'll be the ones with the discipline to wield AI as a force multiplier while maintaining the product thinking that separates signal from slop. Coding might be getting cheaper. Thinking never will. # Sense-Making v Speed in an AI'ified SDLC World Source: https://www.propelventures.ai/blog/sense-making-v-speed-in-the-ai-sdlc-world Meta: 2026-03-19 · Amy Johnson Balancing speed and sense-making in product development is crucial. Learn why AI enhances execution but human judgment is essential for context and strategic decisions. # Speed vs. Sense-Making As a product operating model consultant, one way to go fast is to standardise how we approach our engagements. Less building the plane while flying it. It would be easier, and we'd move quicker, but every time we consider this at Propel, we just can't bring ourselves to do it. We find that anything close to a "cookie-cutter" approach just misses too much context. There is nuance everywhere we look and while we are expert pattern-matchers, there are always enough quirks in every organisation that even if we aren't building the plane from scratch, we're making some pretty serious modifications. While I'm talking about operating model and strategy consulting here, I'm starting to feel the same about the AI-assisted SDLC work we're doing for our clients. If we standardise everything for everyone, how do we make sure the sense-making muscle is still working? ## The Execution Layer Is Getting Automated. Fast An AI-ified SLDC is exceptional at the execution layer: Writing tickets and acceptance criteria from rough inputs Generating code and scaffolding Test automation and regression coverage Documentation of existing systems and decisions Solution design for well-understood problem classes Tools like GitHub Copilot, Linear AI, and Cursor are genuinely compressing the cost of building. This is a real unlock, but it creates a dangerous illusion: that going faster means you're going better. ## What AI Can't Do: The Context Layer The same tools that accelerate execution still struggle with the layer that determines whether any of that execution was worth doing. The context layer looks like this: Why does this problem actually matter to this customer, right now? Which customer segment is worth prioritising — and which is a distraction? Is this solution genuinely valuable, or does it just satisfy the brief? What are the organisational constraints and politics that will make or break adoption? I once heard (thanks Imperfects Podcast and Hugh van Cuylenburg) that the answer to many of life's challenges is exercise. Good advice I often come back to. For product, I'd say the answer to almost everything is customer insight, as in, actually talking to them. You can't answer those questions with a prompt, they require sitting with a customer in conversation, interpreting cues and signals, and holding competing priorities together in your mind. AI can help you move through the solution space faster. But I don't think it can help you find the right problem...yet. While AI can provide the scale, in the Propel model, humans still provide the judgment. ## But, Standardisation Is Helpful (There's always a but)... good standardisation can help turn this context into reusable patterns. Templates, playbooks, and repeatable processes are valuable when: The problem is already well understood and stable Customer needs are clear and unlikely to shift dramatically The cost of inconsistency is high — regulated industries, enterprise contracts, multi-product coherence Standardisation becomes dangerous when: You're still exploring the problem space and don't yet know what good looks like Customer needs are ambiguous or evolving faster than your delivery cycle Decisions are hard to reverse — architectural choices, pricing models, go-to-market positioning Applying execution-layer thinking to a discovery-stage problem is one of the most common (and most expensive) mistakes we see product organisations make. ## Speed Without Sense-Making AI does amplifly the risk of focusing too much on outputs rather than outcomes (customer and business value). If your team didn't have strong discovery habits before, giving them AI execution tools doesn't solve that, it just lets them build the wrong thing faster. Genuinely understanding your customer is an ongoing discipline. In practice, it looks like: Regular, structured customer conversations — not just support tickets and NPS scores Interpreting cues and signals — what customers say vs. what they do vs. what they actually need Judgement calls under uncertainty — making a call without waiting for perfect data Organisational navigation — knowing whose buy-in you need, and why, before the wrong person kills a good initiative This all gets more valuable as execution gets cheaper. ## The Implication for Product Leaders We should absolutely be using AI and automation, that's not in question. The point is that it creates more time for the work that actually matters: understanding users, framing problems, making strategic bets, and navigating the organisation. The how is being automated. That frees us to double down on the why. That's where competitive advantage lives and I know I'm not alone when I say that AI is not going to commoditise it time soon. You can download our latest e-book on the AI-SDLC at this link: https://www.propelventures.com.au/ebooks # Where Every Step Matters: Designing AI for High-Consequence Work Source: https://www.propelventures.ai/blog/ai-trust Meta: 2026-03-03 · Amy Johnson Building trust in AI-powered tools is crucial for adoption in high-stakes professions. Learn how to design systems that ensure reliability, traceability, and user confidence from the start. In the middle of a product validation cycle, a user of the product we were testing framed their evaluation criteria in a single line: “If it hallucinates when I try it on something I know well, we’re done.” They were describing how they would test the system: take it into their own area of deep expertise and see how it behaved under scrutiny. One confident but incorrect result in a domain they understood intimately would be enough to end the experiment. That moment captured something many AI teams underestimate: in high-stakes environments, adoption depends less on the breadth of capability and more on perceived reliability under pressure. If trust in the product breaks, the conversation rarely continues. I was working with an organisation developing an AI-powered assistant designed to support complex professional workflows. Think a legal practice, an engineering firm, scientific research or a financial advisory team. The ambition was to create an intelligent workspace that helps experts move from question to analysis to interpretation while preserving traceability and professional rigour. Early users could see the potential to reduce time spent wading through dense material and repetitive analysis. However, that single comment revealed the real constraint shaping adoption. When a product is powered by AI, trust cannot be treated as an enhancement to be layered on after the core functionality is complete. It influences architectural decisions, data flows, governance models, and user experience. If it is not designed deliberately from the outset, driving adoption may well be an insurmountable challenge. ## How risk conscious professionals evaluate products Like many AI teams, we initially focused on the obvious value proposition. Professionals are overwhelmed by information, and an intelligent assistant can summarise, synthesise, and highlight what matters most. Time is saved, cognitive load is reduced, and productivity improves. Many users described meaningful time savings and relief from information overload. Yet what we observed repeatedly was that risk conscious experts (scientists, lawyers, financial advisers) do not adopt AI tools in the same way that some of us adopt a new tool to create slide decks or synthesize interviews. They approach them as they would any critical instrument in their practice. They begin in their area of greatest expertise. They test edge cases. They probe for weaknesses. They look for evidence of fabrication or overconfidence. If your product surfaces an obvious error in an area they know intimately, the impact is disproportionate. From a product team’s perspective, it may be a defect among many. From the expert’s perspective, it calls into question the reliability of the entire system. Professionals whose reputation depends on accuracy will not persist with a tool that compromises it. This leads to a critical design question. What does your architecture do when the model is wrong? Because it will be wrong. We all know by now that Gen AI, regardless of sophistication, can produce confident inaccuracies. Research across domains, from scientific literature review to legal drafting consistently shows that hallucinations require structural mitigation. ## The deeper concern: “What happens to what I put in?” Accuracy is only the most visible trust issue however in many professional contexts, the more destabilising concern relates to inputs rather than outputs. When experts consider using an AI assistant, they inevitably ask what happens to the information they provide. In a research environment, this may include unpublished hypotheses or experimental designs. In a legal firm, it could involve confidential client strategies. In finance, it may encompass sensitive deal information. Across domains, these inputs represent competitive advantage, fiduciary responsibility, and professional liability. “If I put my ideas into this system, will they be used by someone else?” Sophisticated professionals may not know the nuances of each vendor’s policy, but they understand risk. In the absence of clear, enforceable boundaries, they assume exposure. When these concerns are taken seriously, “trust as architecture” becomes a set of concrete enabling constraints. ## The architectural decisions trust forces you to make Instead of identifying a list of trust features, the focus shifts to defining trust properties that must hold true across the system. ### 1. Define and enforce the trust boundary If users are unsure whether their inputs might be used to train models or shared beyond their intended context, reassurance in onboarding flows is insufficient. The credible response requires alignment between policy, contracts, and system behaviour. This involves deliberate choices about data retention, model training practices, access controls, permissioning, audit trails, and default configurations. Defaults are particularly important because they shape behaviour and expectations. Where possible, trust boundaries should be made explicit and configurable. If a project or workspace can be designated as private, restricted, or shareable, that designation must govern data handling in practice. ### 2. Prioritise traceability over abstract explainability In high-stakes professions, users are less concerned with theoretical discussions about model interpretability and more concerned with practical traceability. They want to know which sources were used, which steps were taken, which tools were executed, and where uncertainty enters the process. They need to reproduce results, inspect intermediate outputs, and apply human judgment at critical points. Designing for traceability often means integrating AI into existing workflows rather than attempting to replace them wholesale. When an AI system orchestrates or augments established processes that professionals already trust, it inherits some of that credibility. ### 3. Make quality visible and continuously managed A common pattern in AI teams is to treat model quality as an internal optimisation problem and user trust as an external perception issue. In practice, they are tightly coupled. In domains where mistakes carry reputational, financial, or legal consequences, a single high-profile error can have lasting effects on adoption. Addressing this requires more than disclaimers. It demands mechanisms for monitoring output quality, capturing structured feedback, reviewing edge cases, and iterating deliberately. When users can see that quality is measured and improved over time, trust becomes a shared endeavour rather than a blind leap of faith. ### 4. Recognise that trust decays without maintenance Trust evolves alongside models, regulations, vendor policies, and user expectations. Changes in data retention rules, legal requirements, or third-party dependencies can alter the effective trust boundary without a single line of product code changing. Sustaining trust requires ongoing governance, risk assessment, and transparent communication. It resembles operating critical infrastructure more than releasing periodic feature updates. ## Trust as infrastructure Rather than thinking of it as a clever assistant layered on top of professional practice, we began treating it as professional software that incorporated AI components. This reframing influenced prioritisation, investment, and internal language. We focused less on persuading users to trust the system and more on engineering behaviours that deserved trust. We treated integration with established tools and processes as part of the trust equation, reducing risky workarounds. We also became more precise about appropriate use cases. In any professional setting, there are tasks where AI assistance is valuable and others where reliance may be premature. A well-architected system helps users calibrate their expectations, signalling where it is robust and where caution is warranted. ## A question for product leaders If your most valuable user entered their most sensitive client matter, hypothesis, strategy, or deal into your product today, could you clearly and accurately explain where that information goes, who can access it, how long it is retained, and whether it influences any future model training? The answer needs to be visible in the architecture, enforced by defaults, and observable in how your products behave. # When AI Becomes Confetti Source: https://www.propelventures.ai/blog/when-ai-becomes-confetti Meta: 2026-02-23 · Amy Johnson Discover why a validated problem should precede any AI initiative and learn effective strategies for successful AI implementation in your organization. Every leadership session eventually circles back to it. More and more we are hearing this from clients. “We need an AI strategy.” “What are our AI use cases?” “How are we showing progress on AI?” The pressure is understandable. The market is loud, competitors are announcing things and boards are asking questions. But the reality is that most AI initiatives start without a clearly validated problem. It's technology solutions looking for use cases. Sprinkling AI like 🎊 confetti 🎊 over isolated use cases rarely creates value. Solving real, material problems does. If you cannot clearly describe the problem, the evidence behind it, and the economic impact of solving it, you are not ready to discuss AI. ## Always Start with the Problem Strong product teams begin with evidence. What customer behaviour indicates friction? What data shows this is a high-frequency or high-value problem? What is the quantified cost of leaving it unsolved? Too often, AI ideation sessions skip this step. In enterprises, I’ve seen full roadmaps built around AI features where none of the underlying problems were validated. A list of “AI-enabled” initiatives looks impressive in a strategy deck. Underneath it, no one can clearly articulate the customer pain or the commercial upside. In scale-ups, I’ve seen leadership teams attempt to “AI the whole product” when the real issue was inefficient workflows and manual back-office processes that could have been improved with straightforward automation. In large organisations, I’ve watched millions spent building internal AI platforms without speaking to customers to understand whether the proposed capabilities were even desirable. That is AI confetti. It looks exciting when scattered across a roadmap but it rarely creates sustained value. Clayton Christensen’s Jobs to Be Done framework remains a useful lens. Customers hire products to make progress. If you cannot clearly articulate the job and where progress is breaking down, you are guessing.  And, guessing is expensive when the solution involves probabilistic systems, new infrastructure, and governance complexity. If anything, AI raises the bar. The margin for sloppy thinking is smaller because the cost of implementation can end up higher. ## Think of AI as a Capability When teams start with “Where can we apply AI?”, they default to surface level enhancements. Ethan Mollick (https://www.oneusefulthing.org/p/working-with-ai) has written about how generative AI performs impressively in controlled settings but becomes unpredictable in complex environments. The gap between prototype and production is where many organisations lose discipline. You need someone (often a Product Manager) to continually ask what measurable outcome are we improving, and by how much? If the initiative does not clearly tie to revenue, retention, margin, or risk reduction, it is unlikely to justify the complexity. ## Then, is AI the Right Capability for this Problem? AI works well for: Pattern recognition across large datasets Prediction under uncertainty Language generation and classification at scale It works poorly when: The process itself is broken Data is inconsistent or sparse Deterministic rules would achieve similar outcomes Error tolerance is low and explainability is critical Ben Evans (https://www.ben-evans.com/benedictevans/2023/ai-and-the-next-platform) has described AI as a shift in computing capability, not a replacement for structured thinking and system design. It expands options and it does not eliminate trade-offs. If a simpler intervention solves the validated problem, choose it. ## Raise the Bar on Validation Eric Ries’ principle of validated learning (https://hbr.org/2013/05/lean-startup-methodology) is even more relevant in an AI context. Form a hypothesis, define leading indicators, run controlled tests and measure impact. Validate that the problem is worth solving Validate that users will trust and adopt an AI-driven solution Validate that the economics justify infrastructure and oversight Validate that you can operate and monitor the system safely This is not about being conservative, it is about being disciplined. AI introduces probabilistic outputs into systems that may previously have been deterministic. That increases complexity, governance requirements, and risk exposure. The evidence threshold should rise accordingly. AI is powerful but it is also costly, complex, and often misapplied. Organisations of every size are vulnerable to chasing AI as a signal of progress. The ones that create advantage will do something less fashionable: identify real problems, gather evidence, quantify impact, and only then decide whether AI is the right tool. Identify the problem first, prove it matters and then choose the solution. # Do we even need Product Managers anymore? Part 2: The Tech Perspective Source: https://www.propelventures.ai/blog/do-we-even-need-product-managers-anymore-part-2 Meta: 2026-02-16 · Paul Greenwell Exploring how AI reshapes product management, highlighting the evolving roles of engineers and PMs in a fast-paced, AI-driven environment. In the last post, Amy Johnson asked the question of what happens when AI accelerates delivery, and but discipline of product thinking starts to erode. Here's a perspective from a Tech Leader. Amy shared how we tested out having our forward-deployed engineers embedded with our clients without the partnership of a product manager. The challenges shared were that without someone accountable for strategy and outcomes, the team drifted into a steady stream of enhancements and edge cases. While the work remained technically strong, focus weakened, prioritisation suffered, and burnout risk increased. # Tech Perspective: The Title Might Not Survive, But the Thinking Must Clearly, teams are converging. Forward-deployed engineers working directly with clients already shorten the loop — adding a PM layer can feel like adding a translation gap, another point where requirements lose fidelity on their way to implementation. But the answer isn’t to eliminate product thinking, it’s to recognise it needs to live wherever ambiguity lives. As PMs get more technical to leverage AI, engineers also need to lean into product — learning established frameworks for discovery, validation, and prioritisation. As building gets faster, more time opens up for these deeper conversations about value. Engineers who can ask the right questions, validate problems, and think beyond implementation will be the ones who thrive. The PM title might not survive this convergence. But the discipline of being value-oriented rather than output-oriented must persist, regardless of who carries it. If you’re technical and working closer to the client or end user , invest in product skills now — the frameworks exist, and the time AI frees up is your opportunity to use them. # Tech Perspective: If PMs Stay, They Must Adapt With the Technology I agree that there is value in breaking work down and putting some structure around delivery planning. However, if your team does keep a dedicated product manager in a fast-moving AI-powered environment, the old ways of working won’t cut it. Slide decks, Miro boards, and verbal handoffs are invisible to AI-assisted development. If the AI can’t see your research, your prioritisation logic, or your domain context, it builds without it. The PM who thrives here is one who captures and maintains AI-friendly artefacts — structured research findings, documented decision rationale, acceptance criteria that AI can parse — and makes them accessible where AI can reach them. That might mean product artefacts living alongside the code in the repository, or surfaced through integrations like MCP (Model Context Protocol), so they inform every phase of delivery automatically. This upskilling is the difference between a PM who adds value at the speed the team now operates, and one who becomes the bottleneck they were brought in to prevent. The artefacts you produce need to be as connected and machine-readable as the code your engineers write. Tech Perspective: Disovery that Compounds As Amy mentioned, it remains important to keep checking that we are solving the right problems. The risk here is that even when discovery is happening, the insights don’t persist in a way the system can use. An interview finding that lives in a research report but never reaches the AI context is invisible to every subsequent implementation decision. AI is perfectly placed to continually re-evaluate new findings from the market against the product, and vice versa — surfacing contradictions, validating assumptions, and identifying where new evidence changes priorities. But it can only do this if it has access to the full picture. The key is incorporating discovery outputs —research findings, competitive analysis, user feedback, market signals — in a centralised way that AI can leverage holistically. When that happens, discovery doesn’t just inform the next decision. It compounds across every sprint, and AI becomes a continuous sense-check against the market reality your product lives in. Overall Tech Perspective: Product Thinking MUST Remain In this new world, the risk is that teams just build the wrong thing faster. Whether the responsibility sits with a dedicated PM, a tech lead, or the whole team, someone must keep anchoring decisions in customer value, prioritisation, and learning. The teams that win won’t be the ones with the most output, they’ll be the ones who combine strong engineering with strong product judgement, and use AI to amplify insight, not replace it. # Do we even need Product Managers anymore? Part 1 Source: https://www.propelventures.ai/blog/do-we-even-need-product-managers-anymore Meta: 2026-02-11 · Paul Greenwell Discover how AI acceleration impacts product management and the critical role of PMs in maintaining focus, prioritization, and continuous discovery in an AI-driven world. It’s the question doing the rounds right now: with AI collapsing development timelines from months to days, a good engineer with the right tools can go from napkin sketch to working prototype before lunch. So why would you slow that down with customer interviews, workshops, story mapping, and all the usual product stuff? We asked ourselves the same question, and for a moment, we thought we’d found a better way. Spoiler alert – we hadn’t. # What We Tried Our bet was on forward-deployed engineers: senior, full-stack engineers embedded directly with clients, armed with AI-accelerated dev tools, building mind-blowing AI-powered products. (At Propel, we partner with our clients — but if you’re in a product company or enterprise, insert “stakeholder” for "client".) We embedded our engineers close to the problem, with the autonomy and tooling to build at pace. No handoffs or no waiting for specs, just talented engineers solving problems fast with AI driven solutions. The theory was they could absorb the product thinking alongside the delivery.  Who needs a product manager when your engineer is this good? # What Actually Happened Clients (Stakeholders) Will Always Want More Here's something that shouldn't surprise anyone: when you embed with a client and start delivering visible value at speed, they want more. Of course they do. "Can we just add..." becomes a steady stream of enhancements, edge cases, and shiny new ideas. But without someone (a product manager) whose job it is to hold the line on strategy and measure whether the outcome has been achieved, there's nobody consistently asking: "is this actually the most important thing we should be building?" Building something cool and watching a client's eyes light up is a lot of fun but doing everything because you can, fast, is no substitute for focus and prioritisation. We found our teams doing genuinely impressive engineering work, that was, at times not focused on the core problem they'd been brought in to solve. Engineer burnout is also a real risk when working this way. We lost the discipline of breaking work down Breaking down work from vision to goals, goals to epics, and epics to stories isn't process for process’s sake. It’s how you turn an idea into a sequence of thin, valuable slices that can be shipped, tested, and improved. We didn’t do a great job of this, as it’s hard to do this without collaboration, and utlimately was deprioritised to allow more time on the tools, building. We lost the estimation discipline that gives stakeholders (and ourselves) the ability to deliver predictability. And we lost the shared understanding that comes from a team aligning on what “done” actually means at each step. Continuous discovery largely stopped We also had a miss on the discipline of systematically checking whether the problems being solved were the right problems. Nobody was testing assumptions before working on solutions. The ongoing rhythm of discover, validate, ideate, validate again just wasn't happening. The output was fast and seriously impressive. But if we were honest, we weren’t spending enough time on answering: Are we getting the most valuable pieces into users' hands first, or are we just... building? # What Should Product Management Actually Look Like Here? Our view is that in a world of AI products (I'm talking about Gen AI), the fundamentals haven't actually changed. Discovery, slicing, collaboration, prioritisation, all matter even more when AI acclerates what you can do. But the shape of the product manager role does need to shift. With AI outputs being probabilistic, behaviour can drift over time, and quality is something you need to manage continuously. It's not a once off QA exercise. The product manager’s job expands from deciding what to build to also understanding: what’s possible with today’s models what’s safe and trustworthy for users what needs guardrails, evals, and human oversight and what should never have been an AI feature in the first place Knowing where AI actually adds value The judgement muscle for product managers needs to be extended to know where AI genuinely helps and where it doesn't. That means building a working understanding of what AI is good at today, what's on the horizon, and what's still mostly hype. It means recognising patterns, the common use cases where AI reliably delivers but also knowing the limits. Not everything needs AI, and knowing the difference saves you from the "AI hammer looking for nails" trap. Product managers need to understand the different ways to engage with AI, assess AI-specific risks (around reliability, bias, trust), and have a framework for evaluating opportunities that goes beyond "could we use AI here?" to "should we, and what's the realistic upside?" Designing AI features that work as expected As a Product Manager working with AI features, you need enough fluency to weigh up different models and approaches, when prompt engineering is enough, when you need retrieval-augmented generation (RAG), when you need structured workflows, when fine-tuning is worth the investment. Answering these questions directly will shape the user experience, the cost structure, and how reliable the thing is in production. You need to design for when it goes wrong. Traditional software either works or it breaks whereas AI features exist on a spectrum: sometimes the output is brilliant, sometimes less so... How the product handles that grey zone matters enormously. Confidence indicators “citations”, human-in-the-loop checkpoints are the difference between a feature people trust and one they abandon after a bad experience. Shipping AI with quality Quality means something new when AI is involved. The data going in matters as much as the code, your AI output is only as good as what you feed it. You need success metrics that go beyond usage to capture accuracy, reliability, and whether users actually trust the thing. Evaluations (evals) are the feedback loop that drives continuous improvement. Without them, you're flying blind on whether your AI features are getting better or degrading. And bias, fairness, safety need to be baked into the product from day one, not bolted on before launch when someone remembers to check. # What We Took Away From All This AI hasn't made product management obsolete. If anything, it's made the consequences of not doing product properly far more visible and far more immediate. The speed AI gives you is real and it's genuinely exciting. Forward-deployed engineers with AI superpowers can build remarkable things, but without someone anchoring that capability to the right problems, keeping discovery alive, breaking work into valuable slices, you end up with a lot of impressive output and not nearly enough meaningful outcomes. The product managers who'll thrive in this world are the ones who pair their existing product skills of discovery, strategy, prioritisation, collaboration with genuine fluency in what AI can and can't do. The role is a bigger one than it's ever been, so we have added an AI bootcamp for PMs to all our PM learning plans at Propel. We will be launching this for our clients in the coming weeks so if you are interested in getting access – email me at amy.johnson@propelventures.ai. # Opportunistic Sales - The Silent Killer of B2B SaaS Growth Source: https://www.propelventures.ai/blog/opportunistic-sales-the-silent-killer-of-b2b-saas-growth Meta: 2026-02-09 · Paul Greenwell Learn how opportunistic sales can derail your product strategy and discover actionable steps to protect your Ideal Customer Profile for sustainable growth. You’re sitting between $2M–$20M ARR. Your growth targets are adding pressure, but the runway feels finite. Then a “whale” shows up in the pipeline with a contract value that would make your quarter. So... you bend. A bespoke workflow here, a custom integration there, a pricing exception “just this once”. It feels like you'r being commercial, however, it’s an anti-pattern. Opportunistic sales is what happens when revenue pressure starts setting product direction. Slowly at first, then all at once. You’ll recognise it by the trail it leaves: Churn is highest among your biggest accounts (because they were never a natural fit, just a big cheque). Product strategy constantly shifts to accommodate edge cases and executive escalations. Marketing and sales are forced to speak to too many buyer types, with too many narratives, so nothing lands cleanly. This is the path to a product that’s hard to sell, hard to build, and hard to love. # Why it hurts April Dunford nails the root of it: your best-fit target customers are the ones who “really care a lot about your unique value.” Opportunistic sales pulls you away from that unique value and into a mess of conflicting customer goals: The enterprise buyer wants governance, risk controls, and procurement-friendly packaging. The mid-market buyer wants speed, templates, and clear ROI. The SMB buyer wants a simple setup and a low-friction trial. Trying to satisfy all of them at once doesn’t create a bigger market, it blurs your market. The business impact is obvious: CAC rises because messaging gets generic and conversion drops. Sales cycles lengthen because every deal becomes a bespoke conversation. NRR becomes fragile because expansions depend on exceptions and favours, not repeatable value. Roadmap focus collapses because your backlog becomes a list of promises. You end up shipping more and learning less. In reality, that whales make it worse. Big accounts don’t just request features. They pull your company toward their org chart, compliance requirements, integrations, and internal politics. Jason Lemkin of SaaStr has a simple warning: selling “90% out-of-the-box is great, butthat 10% custom work can quickly spiral out of control.” The spiral usually looks like this: One-off commitments become “must-haves” Engineering time shifts from compounding work to account servicing Your core customers stop seeing progress Your next 10 customers don’t want those custom features anyway (or they want different ones) Christoph Janz literally calls out the temptation in his “SaaS animals” framework: “Hail the whale!” https://christophjanz.blogspot.com/2019/04/five-years-later-five-ways-to-build-100.html Whales can be a viable strategy if you choose it deliberately. Opportunistic sales is when whales choose you. # What the best products do differently The companies that scale win by being crystal clear about who they’re for, then expanding without breaking that clarity. Atlassian built Jira for software teams shipping work. Enterprise came later as packaging (admin, security, controls), not a rewrite of the core workflow. Stripe stayed developer-first. They expanded into billing, fraud, tax, and enterprise needs, but the primitives stayed consistent: predictable APIs, great docs, clean abstractions. HubSpot wedged into inbound for SMB/mid-market, then broadened into a CRM platform while keeping one coherent story: help growing businesses acquire and serve customers. They didn’t “take every deal", they protected the product’s centre of gravity. # How to avoid 1) Have a specific Ideal Customer Profile (ICP) “Mid-market” isn’t an ICP, neither is “anyone with budget.” Write it down in a way that a new account executive can use on day one, then treat it as a constraint for product and GTM decisions. Cover the basics: Firmographics: industry, company size, geography, regulatory needs Technographics: stack requirements, integration patterns, data maturity Use case + urgency: the job-to-be-done, the trigger event, why now Buying dynamics: economic buyer, budget owner, typical sales motion Disqualifiers: who you don’t sell to (even if they ask nicely) April Dunford’s positioning advice fits here: you win by being clear about who gets disproportionate value from your product. If you can’t say that in one sentence, your ICP is too fuzzy. 2) Track ICP fit metrics Most teams measure adoption instead of fit. Fit predicts retention, support load, and expansion. Track it like you track activation. Start simple: Retention and churn by ICP vs non-ICP NRR by segment (expansion looks very different when the customer is a natural match) Sales cycle length and win rate by segment Support hours per account by segment Time-to-value by segment Add a light-weight fit score in your CRM. Don’t make it academic, make it usable: 1–2 points for each core ICP attribute matched -3 points for a clear disqualifier (heavy customisation demand, atypical buyer, incompatible stack) Flag “out-of-ICP” deals in pipeline reviews the same way you flag discounting If your non-ICP accounts churn the fastest, you don’t have a “CS problem.” You have a fit problem. 3) Give your sales team permission to say no Opportunistic sales thrives when account executives feel they’ll be punished for disqualifying deals. In the end, it's always about incenties. Make “no” a respected outcome when it protects the business. Concrete ways to do it: Reward good “no’s.” Call them out in weekly reviews. Celebrate the deals you didn’t take that would have pulled you off-course. Do not allow conditional sales, where feature build is required to get ink on paper. They are not the ICP. Coach disqualification language: clear, calm, and commercial “We’re not the best fit for that requirement.” “We can support it through services, but it won’t be in the core product.” “If that’s critical, we should step back.” Jason Lemkin’s warning is the clearest summary: the last 10% of custom demands can spiral and consume your roadmap. Your sales team needs cover to avoid promising that 10% just to land the logo. # Sustainable growth comes from being choosy Opportunistic sales feels like momentum. It’s often just motion. Choose your Ideal Customer Profile. Protect it with deal rules, pricing boundaries, and a roadmap that’s anchored in repeatable value. If whales are part of the strategy, make that a strategy, not a panic response. # Self-Organising Teams - Don’t Scale on Hope Source: https://www.propelventures.ai/blog/self-organising-teams Meta: 2026-02-03 · Paul Greenwell Scaling self-organizing teams requires clear standards and governance to ensure alignment, trust, and effective decision-making, rather than relying solely on autonomy. “The best architectures, requirements, and designs emerge from self-organizing teams.” Agile Manifesto This line gets quoted a lot, usually as shorthand for autonomy and empowerment. It comes from a simple but powerful insight: when teams are trusted to organise their own work, they adapt faster, make better decisions, and produce higher-quality outcomes. Anyone else feeling the vibes of unicorns and rainbows... But I'm not sure self-organisation was intended to mean no structure or no standards. It requires that strong capability and the right fundamentals are already in place. Without those, self-organisation can lead to chaos. I’ve seen inconsistency become the enemy of speed. Teams interpret “agile”, “ready”, and “done” differently. Delivery is unpredictable as rework creeps in which erodes trust, at leadership and stakeholder levels, but with clients too. Getting back to basics means clearly defining the minimum standard for how product and delivery teams work together. I don't mean command and control by any stretch, but rather to create alignment and trust through a shared understanding of how things get done. If you’re looking to scale, or you’re an enterprise struggling with outcomes, delivery confidence, or trust, here are a few principles that we see as foundational and are worth testing yourself against. ### 1. Measure success by outcomes (not just delivery) Delivery metrics tell teams how efficiently they’re working. Outcome metrics tell them whether their work actually matters. Remember, shipping the thing is output, delivering measurable value is the outcome. You need both, but teams must be crystal clear on the difference. When teams regularly review customer and business outcomes, they’re better equipped to adjust direction, refine solutions, and stop work that isn’t delivering value. That feedback loop strengthens product strategy and helps ensure growth doesn’t come at the expense of customer impact. ### 2. Be explicit about the basics In early-stage teams, ways of working are often implicit. People sit close together so decisions happen quickly and gaps get filled through conversation. As teams scale and distribute, that implicit understanding disappears. Rather than forcing a one-size-fits-all process, I prefer thinking in terms of hygiene, a baseline that creates alignment while still leaving room for teams to adapt. For example, Definition of Ready and Definition of Done help to ensure quality standards are met. Do you have clear "minimums" for your teams? That baseline should make it easier to collaborate across teams, onboard new people, and coordinate work at an organisational level. At a minimum, teams should be aligned on how they: Capture opportunities Prioritise discovery and delivery Plan and prepare work Deliver Test and release Launch, measure, and iterate But of course, this isn't a linear process: ### 3. Anchor work in opportunities, not commitments One of the earliest signs of scaling strain is when teams are overloaded with commitments before they’ve had a chance to understand the problem they’re solving. Work gets framed as solutions instead of opportunities. A more sustainable approach starts with clearly articulated opportunities. These describe the customer problem, the strategic context, and the outcome the organisation is trying to achieve. They also create a consistent entry point for ideas, whether they come from customer feedback, sales conversations, operational pain points, or leadership strategy. By anchoring work in opportunities, teams retain the ability to explore options, test assumptions, and make informed decisions before delivery begins. That flexibility becomes critical as stakeholders multiply and priorities compete. ### 4. Do discovery (goldilocks style...) Just right-sized discovery helps teams understand the problem, validate the best solution approach, and clarify what success looks like. It doesn’t need to be a three-month exercise. When done well, teams enter delivery with a shared understanding of the outcome they’re aiming for and the risks they’re managing. As organisations scale, discovery also helps avoid a familiar and costly pattern: committing too early, then uncovering complexity halfway through delivery. Yes, building software is getting faster and cheaper. But waste is still waste. If you can validate assumptions or test a proof of concept before making a big investment, you should. ### 5. Have a clear strategy and prioritise to deliver it At scale, prioritisation becomes a series of trade-offs between strategic bets, customer commitments, operational needs, and technical health. There are plenty of frameworks you can use. RICE is a good one, but strategy comes first, scoring ideas second. Transparency about what has been prioritised, and what hasn’t, reduces noise, builds trust, and is a key enabler of real empowerment. ### 6. Governance that helps, not hinders As organisations scale, governance is unavoidable but isn't necessarily a bad thing. The real question is whether it enables progress or gets in the way. Effective governance is lightweight and principle-led. It clarifies decision rights, creates transparency around progress and risk, and helps teams resolve dependencies. It avoids unnecessary approvals and keeps accountability close to the work. When governance forums are well designed, they reinforce alignment without slowing teams down and give leaders confidence so they'll leave you alone. Example: ### Finally Self-organising teams fail when organisations mistake autonomy for the absence of clarity. At scale, empowerment comes from clear intent, shared standards, and fast feedback.  The goal is creating the conditions where teams can make good decisions, repeatedly, and with confidence. This means being explicit about what's expected and getting the basics right. # The AI trust gap: Why 66% use it but only 46% trust it Source: https://www.propelventures.ai/blog/the-ai-trust-gap-why-66-use-it-but-only-46-trust-it Meta: 2025-11-25 · Paul Greenwell AI is transforming product teams by merging roles, enabling smaller, versatile groups to innovate faster and more efficiently. Discover how adaptability drives success in the AI era. Your team uses AI daily. They draft emails with ChatGPT, summarise reports, generate analysis. But ask them if they trust the output—really trust it—and watch the hesitation. This tension isn't unique to your organisation. A 2025 KPMG/University of Melbourne study across 48,000 people in 47 countries revealed the gap: 66% use AI regularly, but only 46% trust it. That 20-point gap is costing you adoption, velocity, and value. ## Trust doesn't come from reassurance Most organisations try to close the trust gap with policies, governance frameworks, and compliance checkboxes. These matter but they don't build trust. Trust comes from understanding. When people know how AI works, what can go wrong, and how to verify outputs, they trust it more because they know when to trust it and when not to. They don't need permission to use it, they have the judgement to use it well. We've seen this pattern across 100+ regulated organisations in finance, government, energy, and healthcare. The teams that get 3-5x more value from AI aren't the ones with the biggest budgets. They're the ones where literacy is distributed, not centralised. Legal teams spot biased outputs before they cause harm. Finance verifies AI-generated forecasts instead of accepting them blindly. Product teams know when not to trust the model. The result? They use AI more, not less. Awareness builds confidence. Confidence builds adoption. ## The bottleneck isn't technology Walk into any Australian boardroom and you'll hear the same story: strong enthusiasm for AI, ambitious pilots, but uncertainty about what happens next. One team experiments with AI for customer insights while another debates blocking ChatGPT entirely. Executives call for an "AI strategy" without clarity on who owns it or how success will be measured. The pattern is consistent: the gap isn't technical. It's literacy. Not coding bootcamps. Not another tool rollout. But a shared understanding across the organisation of what AI can do, what it can't, who's accountable, and how to use it safely at scale. ## Different roles need different literacy AI doesn't succeed when everyone learns the same thing. It succeeds when every function develops the literacy their role demands. Board members don't need to write prompts. But they absolutely need strategic foresight and critical intelligence to govern AI risk effectively. Product managers need all five literacy domains—responsible use, applied fluency, critical intelligence, technical foundations, and strategic foresight—to balance innovation with ethical design. Operations leads need responsible use, applied fluency, and critical intelligence to deploy AI tools safely and verify outputs before acting on them. When literacy aligns with responsibility, AI stops being a project. It becomes part of how work happens. ## The framework: Five domains that scale In our new whitepaper, we outline the Five AI Literacy Domains Framework, developed through Propel's work helping organisations build AI capability across industries. The framework addresses: Responsible Use: Ethics, governance, and accountability in daily practice Applied Fluency: Everyday confidence using AI tools to improve thinking and execution Critical Intelligence: The discipline to verify, question, and contextualise AI outputs Technical Foundations: Understanding AI mechanics without needing to be an engineer Strategic Foresight: Connecting AI literacy to long-term competitive advantage The whitepaper includes field lessons from 100+ regulated organisations, practical implementation guidance for every organisational level (individual, team, department, executive), and role-specific literacy maps showing which domains matter most for boards, product teams, operations, legal, and more. Download the full whitepaper: "Why Do Some Organisations Achieve 10x More Value from AI Than Others?" The organisations pulling ahead aren't waiting for perfect tools or complete clarity. They're building literacy now. Distributed, practical, and tied to real decisions. The question isn't if your people will work with AI. It's how ready they'll be when they do. # From Guesswork to Greatness: What Leaders Can Learn from AI-Driven Pricing Source: https://www.propelventures.ai/blog/from-guesswork-to-greatness-what-leaders-can-learn-from-ai-driven-pricing Meta: 2025-10-13 · Ben Ross Discover how AI-driven pricing can transform supply chain management, from boosting decision-making confidence to envisioning future organizational structures. Learn key takeaways from a recent leadership forum. # Generative AI: From Guesswork to Greatness Last month I had the privilege of presenting at Enable’s Supply Chain Leadership Forum on how AI is transforming pricing and rebate management. The conversation in the room confirmed what we’re seeing across clients at Propel with a shift from manual reaction to confident, AI-driven decision-making. Below are some key highlights and quotes from the session, along with a link to the full recording. ### 1. Agentic AI: From Tools to Teammates I demonstrated GenSpark Super Agent analysing semiconductor supply-chain risk in real time. It selected its own data sources, built a visualisation, and even drafted an email to a CPO summarising the results. This is Agentic AI in action. These systems that understand your intent, make trade-offs, and surface insights you hadn’t thought to ask for. ### 2. Focus Beats Frenzy We’ve all seen it: sprawling AI initiatives that start strong and end in confusion.  The organisations that win start small and strategic. They pick one workflow (pricing, contract analysis, or rebate optimisation) and master it. That single win builds confidence, capability, and internal momentum. ### 3. Envisioning the Firm of the Future Imagine a flatter organisation where AI agents handle the repetitive grind - market-monitoring, margin calculations, and supplier analytics - while humans focus on strategy, relationships, and creativity. We’re already seeing this play out. One client now runs AI agents 24/7 to track markets, giving their analysts richer insights each morning. The number of people hasn’t changed, but the quality of thinking has skyrocketed. ### 4. The 90-Day Challenge Start simple. Build, learn, repeat: Day 30: One working AI assistant solving a real problem Day 60: Share it with your team and refine it Day 90: Scale or start the next use case And from an organisational perspective, Propel's 90 day value flywheel: Day 30: Establish your LLM infrastructure and enable the team Day 60: Run pilots and optimise Day 90: Drive network effects and ecosystems ### 5. Final Thought AI isn’t here to replace expertise - it’s here to amplify it. The leaders who get hands-on now will shape how AI works in their organisations. Those who wait will be reacting to others who moved faster. ### Watch the Full Presentation # MCP: The AI-Native Enabler Source: https://www.propelventures.ai/blog/mcps-the-ai-native-enabler Meta: 2025-09-22 · Paul Greenwell AI is transforming product teams by merging roles, enabling smaller, versatile groups to innovate faster and more efficiently. Discover how adaptability drives success in the AI era. # Model Context Protocol: From Plumbing to Strategic Rails When people first hear about Model Context Protocol (MCP), they think of it as a simple technical gateway for an AI model to talk to an API. That’s true, but it’s the smallest part of the story. At Propel, we see MCPs as organisational infrastructure. They’re becoming the rails that AI systems run on. And if you only treat them as backend plumbing, you’ll miss some of the biggest opportunities: revenue, productivity, and customer experience. ## Beyond Developer Experience Most teams design MCPs with developers in mind. But once you add natural language interfaces, something changes: non-technical users step in. We’ve watched analysts, paralegals, and operations staff use MCP-powered workflows to pull data, update records, or draft documents—without touching an API. Suddenly, it’s not just about developer experience. It’s about how your whole organisation interacts with AI. ## The Risks of Overlooking MCPs When MCPs are treated as small side projects, we see the same traps: Lost revenue: SaaS companies that don’t connect MCPs to their monetisation strategy miss chances to differentiate, upsell, or advertise capabilities. Becoming relics: MCPs built for one integration drift into irrelevance. Without ownership, metrics, and evolution, they’re technically correct but strategically disconnected. Forgetting the user’s user: In one client project, we refactored complex workflows into natural language. The big win wasn’t just better staff UX—it transformed the experience of their customers’ customers. ## Rethinking Maturity AI maturity isn’t about whether you “have an MCP.” It’s about how embedded MCPs are across your business. Ask yourself: Are they tied to critical workflows? Do they evolve alongside your product strategy? Can non-technical staff use them easily? Do you measure ROI and usage like you would any other product surface? ## A Second Brain for the Organisation Well-designed MCPs act like a second brain. They connect systems, cut across silos, and surface context where it’s needed. AI agents handle the repetitive pulling and reconciling so people can focus on higher-value work. We’ve seen teams save hours every week by collapsing multi-step processes into one natural language request. This isn’t theory - it’s happening now. ## The Strategic Imperative The real opportunity is to treat MCPs as part of your business model: Monetisation: How you capture and signal value. Product roadmaps: How you build capabilities that users discover and adopt. Org design: How non-technical staff interact with AI day to day. If you want AI to stick, MCPs need to be more than connectors. They should shape pricing, new roles, and customer experiences. That’s how you move from technical plumbing to building the rails of an AI-native future. # Value Streams and the Power of Shared Accountability Source: https://www.propelventures.ai/blog/value-streams-and-the-power-of-shared-accountability Meta: 2025-09-08 · Amy Johnson Unlock team accountability and deliver true customer value. Propel's Value Stream training with Ken Sandy emphasizes outcomes over outputs and the power of shared responsibility. Last week, Propel and Ken Sandy teamed up to run Value Stream training with product managers, engineers, business analysts, and QAs. It was a whole lot of fun infused with plenty of learning. One of the big ideas that weaved through, was how value streams (those cross-functional teams) unlock accountability for outcomes, not just outputs. If only product managers own the customer problem, or only engineers own delivery, we get stuck in silos. The best results come when the whole cross-functional team feels responsible for solving customer problems and delivering business value. That means everyone: product managers, engineers, BAs, QAs, needs to understand: Who the customer is What problem we’re solving for them What success looks like in outcomes, not just activity When every role has that clarity, it changes how people show up to work. Prioritisation decisions become easier, trade-offs make more sense, and most importantly, we stop celebrating “done” and start focusing on whether what we delivered actually made a difference. ## Why Launch Isn’t the Finish Line One of the most powerful lightbulb moments came when we talked about apples and oranges. Too often, teams treat “launch day” like the end of the marathon, when really it’s just the starting line in the race toward product success. The activities under the orange look fine in isolation until you level up, shifting to the outcome and customer-centric mindset of the apple. ## Vanity Metrics: Guilty as Charged There were a few nervous laughs when Ken shared the “vanity metrics” slide — oops, we use those a lot! Registered users, downloads, social followers… they feel good in the moment, but they rarely tell us if we’re creating value. The challenge is moving past vanity metrics and agreeing on the measures that matter: customer adoption, sustained engagement, reduced churn, and business impact. When we measure what matters, we stop patting ourselves on the back for activity and start holding ourselves accountable for (that word again) outcomes. ## Personas: Bringing Customers Into the Room Another highlight was the exercise on personas. Day to day, if you're just picking up Jira tickets without any connection to the human being you are solving a problem for, you won't have any real sense if you are focused on the right tasks. Having everyone build out personas and customer journeys introduced empathy and meaning for everyone in the team. Even the hardcore mainframe engineers valued being able to trace the connection between their work and the customer. Who are we solving this for? What will success look like for them? Suddenly, it’s not “my story” or “your feature”, it’s our customer problem to solve. ## Why This Matters Shared accountability across the whole team isn’t just theory. It’s how the best product teams leverage the best of each other, challenging the what AND the how. When engineers, BAs, QAs, and product managers all feel responsible for the outcome, not just their part of the process we stop chasing “done” and start chasing impact. That’s the product mindset in action: Start with the customer problem Define success as outcomes, not outputs Measure what really matters Bring everyone closer to the customer When teams work this way, the chances of delivering what customers actually want is a lot higher which is ultimately what being in business is about. You can find check out Ken's book, The Influential Product Manager: here and if you think your team would benefit from a session like this, reach out. # Smaller Teams, Stretchier People Source: https://www.propelventures.ai/blog/smaller-teams-stretchier-people Meta: 2025-08-11 · Amy Johnson AI is transforming product teams by merging roles, enabling smaller, versatile groups to innovate faster and more efficiently. Discover how adaptability drives success in the AI era. The killer question of today's panel talk at AWS' Unicorn Day was ... if you’re scaling in a world where AI means everyone can do everything, do you get an engineer to do product management, a product manager to do design, or a designer who can vibe code? This is no longer a hypothetical, it’s the decision many founders and leaders are making right now. AI has shifted the balance of skills in product development, collapsing the walls between roles that used to be distinct. The question isn’t if these roles blur, but how far we let them merge. In the old model, the “three-legged stool” (one of my favourite metaphors!) of product, design, and engineering was about balance. Each discipline had a distinct craft, and collaboration was the magic. In today’s AI-augmented teams, those boundaries are dissolving. With tools like Notebook LLM for customer interview synthesis, Lovable, Cursor, Replit for vibe coding, we can bring concepts to life in hours or less, meaning the core skills of each role are more accessible than ever. Designers can spin up working prototypes. PMs can vibe code a flow to validate an idea with users before a single sprint kicks off. Engineers can translate customer interviews into prioritised backlogs. The result? Smaller, tighter teams where people “stretch” and move fluidly between discovery and delivery without the overhead of bigger teams. Co-location becomes more valuable then too. ## Why Vibe Coding Changes the Game For PMs and designers: It bridges the gap between “what we imagine” and “what we can actually build,” helping teams make tangible decisions earlier. For engineers: It’s a chance to validate whether an idea has legs before coding. This shared prototyping fluency means cross-functional conversations are grounded in something visual, not a PRD. The faster you can loop from idea → prototype → feedback, the less you waste on polishing the wrong thing. ## The AI Advantage: From Weeks to Hours AI is already cutting cycle times dramatically: Customer insight: AI-powered interview synthesis means we can understand patterns across dozens of conversations in minutes instead of days. Prototyping: Vibe coding tools make it possible to generate usable visual flows instantly. And for those using Miro, check out the AI prototyping functionality - incredible! Workflow acceleration: Engineers can auto-generate scaffolds for features, freeing more time for tricky edge cases. That speed makes experimentation cheap, but in my opinion, it's still worth validating the problem space as even though you can do many experiments, waste is still waste. AI can help scale ideas, but it’s human insight that makes them worth scaling. ## Where Humans Still Lead For all its acceleration, AI has sharp edges: Ethics and security: Malicious use of AI features, risky recommendations, or data leaks require human oversight. Quality assurance: AI-generated outputs still need manual validation to avoid costly mistakes. Context and empathy: AI can synthesise what was said, but it can’t watch a user’s facial expression mid-interview and spot the unspoken frustration. Teams that combine AI’s speed with human judgment will outpace those chasing automation for its own sake. ## So… Engineer in Product or PM Who Codes? The answer might be: both. Engineers stepping into product bring deep feasibility instincts and can move straight from concept to code. PMs or designers who can code bring user empathy and the ability to translate that directly into something tangible. In AI-era scaling, the most effective teams will be built around versatile product thinkers, whether they come from design, engineering, or product management, who can speak each other's language and use AI to collapse the gap between them. If AI makes it possible for everyone to do a little bit of everything, the winning move isn’t to defend old boundaries. It’s to hire for curiosity, flexibility, and the ability to prototype ideas into reality and then let those smaller, stretchier teams run. Because in the end, AI won’t replace the product team, it will just make it easier for the right kind of product team to win. # OOOps & Happy Accidents Source: https://www.propelventures.ai/blog/the-ooops-of-happy-accidents Meta: 2025-07-25 · Paul Greenwell Discover how "Unbundling the Enterprise" can revolutionize your business with the OOOps Model, fostering flexibility, opportunity, and optimization for thriving in a dynamic market. I often use the principles of Team Topology when working with large enterprises, so was excited to see Matthew Skelton on stage at the recent Agile Australia conference. He recommended Unbundling the Enterprise by Stephen Fishman and Matt McLarty as a follow up, and I'm so glad he did. It couldn’t be more relevant to the work we’re doing to help companies shift to value-aligned ways of working. The book explores how organisations can be designed to harness flexibility, modularity, and responsiveness so they’re not just built for efficiency, but built to catch that elusive opportunity, that lightning in a bottle. They call this the OOOps Model: Optionality, Opportunity, Optimise. They use a great example of Google’s Maps API, originally a tightly controlled internal system, which became transformative once opened up to developers. It reminded me of the Post-it Note story: a failed experiment that turned into an iconic product. These “happy accidents” aren’t really accidental when your organisation is designed to respond to the unexpected. Here’s a quick breakdown of the OOOps model: ### Optionality – Be Ready for Anything Optionality is about designing for flexibility: Understand your business capabilities. Create modular, API-enabled digital assets. Fund exploration, not just delivery. The goal is to enable fast movement, not just efficient execution of fixed plans. Optionality is what lets you capture that serendipity. ### Opportunity – Know How Value Flows To seize opportunities, you need to know how value flows. Value mapping is a cool technique shared in the book. At Propel, we talk about "organising around value" as one of the five pillars of a strong product company. What this book adds is a way to visualise those dynamics and design for them, making it easier to spot and act on an opportunity as it arises. ### Optimise – Sense and Respond You need feedback loops to keep improving and adjusting. That means building systems where data flows both ways and where product teams can learn fast and adapt. APIs are often the enabler here. This is what separates product-led organisations from project-led ones. Optimisation isn’t about squeezing more out of a plan, it’s about building learning into how you work. ### Cross-Functional Collaboration is the (not so) Secret to Success One of the most powerful reminders in the book is that product model transformation isn’t about IT catching up to business; it’s about the two becoming indistinguishable. It's creating a culture where there is shared ownership of outcomes, with the individuals in cross-functional teams having aligned incentives. In many large enterprises, the "business" still sees "IT" as a delivery unit which results in a breakdown of accountability. And let’s not forget the golden rule: you build it, you run it. Digital-native companies generally already operate this way. But for legacy enterprises, this isn’t just an opportunity to leapfrog the competition, it will become a ticket to play, if it isn't already. ### Now that AI is ReShaping what's Possible, Decision Speed is the New Advantage As AI reshapes what’s possible, the real constraint is no longer how fast you can build, it’s how fast you can decide. That means: Understanding how value flows for you customers and your business Being flexible in how you deliver And having the tech architecture to respond fast In other words, being set up to capitalise on happy accidents. If your org isn’t ready for that, I recommend reading Unbundling the Enterprise as a great place to start! # The Multiplier Effect of Connecting Strategy to Reality Source: https://www.propelventures.ai/blog/the-multiplier-effect-of-connecting-strategy-to-reality Meta: 2025-07-14 · Amy Johnson Connecting strategy to daily work boosts team focus and impact. Learn how aligning tasks with company goals fosters engagement and drives results. One of the things I’ve seen time and again: strategy often lives with the executive, teams heads down in the day to day, with no clear link from their work to the bigger picture. But when that connection is made, when teams get the why, not just the what, something shifts. It creates a kind of multiplier effect. Teams have more focus, more energy, and are able to deliver more impact. Marty Cagan says: “When teams understand the company’s objectives and strategy, they can align their work accordingly. They are no longer just implementing features—they are solving real problems.” And that’s the magic. When the work feels connected to something that matters, people are more engaged, they are more likely to share ideas, they care more. Some of the simple things that help: Ensure each feature or story visibly links to a strategic goal in your tool of choice Talking regularly about the why behind the work Showing how team priorities connect to real outcomes - share the measures Making room to challenge things that don’t line up - I love using Radhika Dutt's vision rubric to visualise whether the work being done aligns with the vision, or is building vision debt Using OKRs, Outcomes or North Star metrics as guides One of the most famous examples of someone understanding the bigger picture comes from NASA in the early 1960s. The story goes that when President John F. Kennedy was touring the NASA space centre in 1962, he stopped to chat with a janitor who was sweeping the floor. JFK asked him what he was doing. The janitor looked up and said: “I’m helping put a man on the moon.” It’s a simple line, but it says everything. He understood that his work mattered. He saw how his part, however small it might have seemed, fit into the larger mission. Knowing how your work contributes to something bigger unlocks commitment, care, and passion at every level of an organisation. # Decision Reps: Building Intuition One Choice at a Time Source: https://www.propelventures.ai/blog/decision-reps Meta: 2025-06-30 · Paul Greenwell Build decision-making intuition faster with Decision Reps. Learn to reflect on past choices, leverage others' experiences, and analyze business outcomes to enhance strategic thinking. Everyone preaches the 70-20-10 rule: 70% experience, 20% coaching, 10% formal learning. It's gospel in corporate training rooms everywhere. However, it's just too slow for accelerated growth ! The 70-20-10 rule assumes you'll slowly grind through decades of "experience" before you develop decent intuition. Organizations can't wait for you to build better muscle for intuition—traditional experience-based learning is inefficient when markets move fast and the competition never stops. And if you want to climb towards a leadership role, that's a luxury you can't afford either. Senior decisions aren't black and white—they're greay, they’re messy, and require leaps of faith. What you need is Decision Reps. Think of them as mental muscle-building exercises. Just like you don't go to the gym once a year and expect to bench press 100 kg, you can't make a handful of consequential decisions over five years and expect world-class intuition. You need to regularly get the reps in. ## The 3 Types of Reps that Build Mental Muscle ## 1. Core Reps: Most product managers make decisions and immediately move on to the next problem. They're missing the most valuable part: the reflection. Core Reps are your personal decision retros. They're systematic reflections on your own past decisions to extract lessons and build pattern recognition. Think of them as doing a retrospective after every project - only this time, it’s your decision-making, outcomes and achievement’s being reviewed. Every decision you make contains data about your thinking patterns, biases, and blind spots. Most professionals miss this opportunity by never looking back systematically. Effective product managers approach this differently—they mine their decision history religiously because they understand something crucial: pattern recognition is what separates competent execution from strategic leadership. When you reach senior levels, decisions become greay and messy. You need intuition built on thousands of micro-lessons, not just a handful of major experiences spread across years. ## 2. Shared Reps: While everyone else is networking for the sake of collecting LinkedIn connections, you should be analysing decision patterns from every conversation. Shared Reps are learning from other people's experiences through strategic listening. Every war story, podcast interview, and casual coffee chat contains compressed wisdom from someone else's real-world decisions. The trick is extracting the lessons learnt systematically instead of just nodding along politely. Think about it: every successful product leader has made thousands of decisions you haven't faced yet, and every failure story contains a lesson you can apply before making the same mistake. Why reinvent the wheel when you can learn from their experience? Most people listen to stories for entertainment, but effective product managers listen for patterns. When someone tells you about their biggest product launch disaster, they're handing you a valuable case study—if you know how to extract the lessons learnt. The math is simple: one hour listening to someone's 10-year career journey gives you decision patterns that would take you years to discover on your own. You're not just accelerating your learning—you're learning from mistakes you'll never have to make. ## 3. Synthetic Reps: The best workout is one you can do anywhere, anytime, with nothing but your brain and a good framework. Synthetic Reps are analyzing other people's decisions as if you were in the driver's seat. You take any business outcome you see—successful or failed—and reverse-engineer the decision-making behind it. Then you ask the critical question: "What would I have done differently?" This is your mental gym. No waiting for the right experience to land on your desk. No hoping your company faces interesting strategic challenges. You can build decision-making muscle by dissecting every business move happening around you, from Ninja's product line expansion from single-use blenders to complete kitchen ecosystems (who needs a Ninja creamy) to why your local café's has introduced weekend surcharges. Every company pivot, product launch, or strategic failure becomes your personal case study. You're not just consuming business news—you're using it to train your strategic thinking. The beauty of Synthetic Reps is volume. You can analyze dozens of decisions every week without waiting years for your company to face similar challenges. It's like having access to every company's boardroom discussions without the politics or ## No Rest Days Once you start building this habit, you can't turn it off. I've caught my mind drifting, breaking down Logan Roy's power moves or empathiszing with both the frustrated employees and the managers making impossible calls while eavesdropping on café workplace gossip at the table next to me. This isn't about becoming a decision-making robot—it's about building the intuitive foundation that lets you navigate ambiguity with confidence. Most people wait for experience to find them. Decision Reps let you actively train your intuition, pump up your pattern recognition, and build the mental strength that separates good product managers from great leaders. Over the next week, keep a note of every decision rep you do. A real one, a story someone shared, or a hypothetical you worked through. Then look back. What did you learn? What would you do differently next time? Before you know it, you'll be building decision-making muscle that would have taken years to develop through traditional experience alone. Your future self will thank you later. # There's no point going fast if you're going the wrong way Source: https://www.propelventures.ai/blog/theres-no-point-going-fast-if-youre-going-the-wrong-way Meta: 2025-06-25 · Paul Greenwell Discover how Agile and AI can accelerate your product development, and why a Product Operating Model is essential to ensure you're building what truly matters. Agile helped us to move faster. AI is now supercharging that speed. But here’s the uncomfortable truth: Velocity without direction just amplifies waste. We’ve all seen it. The big launch that was on time and on budget, but flopped. The team worked hard. The features were built. But the business or customer impact? Negligible.. The value never materialised. Often we celebrate hitting deadlines, but stop to ask: Why did we build this in the first place? To avoid “mistaking making stuff for making progress” (as Josh Seiden put it), and start building what actually matters. ## Why You Need a Product Compass Agile and AI provide the speed, but without a compass, you risk heading in the wrong direction faster than ever before. A Product Operating Model is you that compass. It helps teams move quickly and with confidence.  The compass means having these 4 points: Vision A clear direction that shows the change you will bring about 3-5 years out, for what user, with what technology Strategy Focused choices and trade-offs that align resources to achieve your vision and create competitive advantage Discovery Evidence-based ways to uncover customer needs and validate solutions, rather than working on hunches Focus on Outcomes Focus on value-based measurements rather than simply tracking outputs and activities. ## Vision: Your North Star A strong product vision sets a clear direction. It paints a picture of the change you’ll bring about in 3–5 years, for what user, using what technology. A good vision helps your teams make decisions today that you’ll be thankful for tomorrow. It stops you from building “solutions looking for a problem.” And with AI, that temptation is real. It’s fun. It’s clever. But you need to stop an ask, is it actually useful? ## Strategy: Making Focused Choices “The essence of strategy is choosing what not to do.” – Michael Porter Strategy is often misunderstood as a long document or a laundry list of initiatives. But at its core, it’s about focus and trade-offs. The best strategies: Make trade-offs clear Create a unique position Align the whole organisation Enable fast, aligned decisions You don’t need McKinsey. You need clarity. Understand your customer, know your market, and make focused, coherent choices. If your team can’t connect what they’re working on to your top 3–5 strategic goals, you’ve got a strategy-to-execution gap. That’s how flops happen. ## Discovery: Get the Evidence to Reduce Risk “Everyone does discovery. The difference is when.” Too often, we build first and ask questions later. Real discovery means: Talking to users Testing assumptions Using data to verify hypotheses Bringing engineers in early Tools like the Opportunity Canvas and Assumption Mapping make your thinking visible. Discovery helps reduce risk and align teams. It’s not just a nice-to-have. ## Outcomes: Measuring What Matters “Outputs track production. Outcomes track impact.” We all say we care about outcomes. But we often celebrate outputs: “We launched!” “We shipped everything in scope!” “We hit completed all the story points!” Despite this, you could still have a flop on your hands. Outcomes are about: Customer success Business impact Solving real problems Your roadmaps should talk to outcomes, not features. Tie initiatives to leading metrics, strategic goals and outcomes. Get clear on the results you’re aiming for and measure them. ## Shared Accountability Changes Everything A real product model unites cross-functional teams around a common goal. It’s not “the business” handing over a backlog to IT. It’s shared ownership of the outcome. When engineers understand the customer problem and have a say in solving it, they're not just delivering code. They’re delivering results. This shift, from delivery to accountability unlocks creativity, collaboration, and impact. I’ve got a few sailors on my team, one has done the Sydney to Hobart race a few times, and one is gearing up for the Sydney to Auckland race in October (Impressive!) That’s a journey of about 2100km. But here’s the thing, if her compass is just 5 degrees off, she won’t land in Auckland. She’ll miss New Zealand completely... and end up in Chile 12,000 km away. Now sure, Chile’s great. Amazing wine. Beautiful mountains. But if your customer’s in Auckland, landing in Chile is… well, a navigational flop." Because in the end, speed doesn’t matter if you’re heading to the wrong continent. # Why Tiered Subscription Pricing is the Best Monetisation Strategy for B2B SaaS Source: https://www.propelventures.ai/blog/why-tiered-subscription-pricing-is-the-best-monetisation-strategy-for-b2b-saas Meta: 2025-06-20 · Paul Greenwell Discover why tiered subscription pricing is the optimal monetisation strategy for B2B SaaS, promoting revenue stability, customer value, and innovative product development. In today’s competitive SaaS landscape, monetisation models don’t just drive revenue they shape product strategy, customer experience, and team effectiveness. Among the various options, tiered subscription pricing is considered the best practise approach for B2B SaaS companies. Here's why: Revenue Stability Without the Risk Unlike “pay-per-feature” models that tie income directly to the adoption and performance of each feature, tiered subscriptions decouple revenue from individual product components. This means that even if certain features underperform or fail to gain traction, the company’s financial foundation remains intact. This revenue resilience allows product teams to take bold bets - experimenting with innovative features or ideas - without the fear that a single misstep will derail revenue. Over time, this creates space for bigger breakthroughs and commercial growth. Greater Customer Value and Adoption Tiered models encourage users to explore a broader set of features, often unlocking functionality they may not have paid for individually. This results in: The “got it for free” effect, where customers feel they’re getting more than they paid for. Higher adoption rates across the product, leading to better engagement and satisfaction. Stronger retention, as users become more embedded in the platform and perceive greater value. In contrast, pay-per-feature models often cause hesitation, as users resist paying upfront for tools they haven’t tested, leading to slower adoption and fragmented feedback. Empowered Product Teams When revenue is tightly coupled to individual feature success, product teams face high validation burdens, constant sales pressure, and delayed release cycles. This leads to a fear-driven culture where only safe bets are pursued, stifling innovation. Tiered pricing eliminates this pressure. Teams are free to focus on continuous value delivery, iterate quickly, and innovate boldly without being shackled by immediate financial justification. Avoiding the Roadmap Trap The slides also highlight a common anti-pattern: tying the product roadmap too closely to short-term revenue targets. This leads to a cycle of revenue pressure, risk aversion, and missed opportunities. Tiered subscriptions support outcome-based roadmaps, where teams target broader business metrics like reduced churn, higher CLV, and increased NPS, rather than being forced to monetise every new feature individually. For B2B SaaS companies aiming to scale sustainably, the tiered subscription model delivers on every front—predictable revenue, higher customer satisfaction, and more empowered, innovative product teams. It’s not just a pricing strategy; it’s a growth enabler. # Deciding to change is the easy part Source: https://www.propelventures.ai/blog/change-is-hard Meta: 2025-04-18 · Paul Greenwell Learn why deciding to change is easy but making real transformation happen within organisations requires deep, structural shifts and unwavering commitment. It's one thing to paint a transformative vision of the future. It may only take a single meeting to light a fire under executive teams, challenge the status quo, and inspire organisations to rethink how they work. The message is clear: if you want to deliver real value, empower your teams with problems to solve and focus on outcomes. It’s compelling. And it’s right. But here’s the thing most leaders underestimate: Deciding to change is the easy part. In many organisations, the decision gets made. There’s alignment at the top. A vision is set. Leadership announces: “We’re going to work this new way. Empowered teams. Customer-centricity. Experimentation. Outcome focus. Let’s go.” If only it were that simple... ### The Illusion of a Simple Shift In theory, it sounds like flipping a switch. But in practice? You’re trying to reinvent how value flows through a company that was built for something else. In one large business we worked with, teams were excited to adopt a new way of working. But the starting point was this: teams were assigned projects, quality issues clogged every release, and customer insight barely made it to the delivery backlog. In another case, leaders declared a shift to outcome focus, but funding still flowed through project gates. Teams were temporary. Discovery wasn’t supported. Strategy sat in PowerPoint decks, disconnected from roadmaps. Product owners were buried in Jira tickets and release planning, with little time or capability to talk to customers. Elsewhere, a business facing industry headwinds knew it needed to simplify and scale. But decades of tech debt, a trunk-and-branch code base, and bespoke client delivery made agility impossible. They didn’t just lack cross-functional teams, they lacked shared goals, shared governance, and a shared understanding of what needed to change. These aren’t edge cases. This is the pattern. ### The Hard Part: Making Change Real If you want to shift from project-based, output-driven delivery to a model that delivers sustainable value, here’s what you really need to change: ### 1. Connect Strategy to Teams Declaring a vision isn’t enough. Teams need to see how their work links to company goals. They need outcome roadmaps that prioritise problems to solve, not lists of features to ship. Articulate a compelling strategy. Build outcome-focused roadmaps. Connect the dots all the way to team backlogs. ### 2. Fix the Funding Model If funding is tied to fixed scope and time-bound projects, teams are not empowered, no matter what you tell them. Value doesn’t flow in quarterly bursts; it’s continuous. So your funding must be too. Shift to persistent funding of cross-functional teams aligned to value streams. ### 3. Reorganise Around Outcomes Most orgs are still structured around tech stacks, internal capabilities, or business functions. That creates handoffs, delays, and a lack of ownership. Real change means designing teams that own outcomes end-to-end. Map your value streams. Redesign team topology to reduce dependencies and align with outcomes. ### 4. Build Real Empowerment You can’t just tell teams they’re empowered and walk away. Empowerment comes from clear roles, access to data and customers, psychological safety, and the right support systems. Coach teams in discovery. Embed design and research. Give space for teams to explore and learn. ### 5. Invest in Technical Foundations Teams can’t ship quickly or safely if they’re battling broken environments, brittle tests, or manual releases. In several organizations we worked with, CI/CD was a concept — but not a reality. That’s a major blocker. Prioritise engineering enablement. Build in automated testing, modern pipelines, and environments that support continuous delivery. ### 6. Uplift Capability Across the Board In one company, there were no true product managers — just people called product managers. The result? No discovery. No strategic thinking. Just delivery. Capability uplift isn’t just about training; it’s about reshaping roles and expectations. Define what good looks like. Invest in role clarity, mentoring, and structured capability uplift across product, design, and engineering. ### Final Thought Many organisations talk about becoming more adaptive, customer-focused, and outcome-driven. They make the decision. They share the vision. But the vision won’t deliver itself. Changing how you choose problems, how you fund work, how you organise teams, how you measure success, how you release, and how you learn, that’s the real work. That’s the transformation. And it doesn’t happen overnight. It happens one team, one value stream, one system at a time and takes courage, consistency, and commitment. # Stakeholder Buy-In: A Secret Sauce for Product Operating Model Success? Source: https://www.propelventures.ai/blog/stakeholder-engagement Meta: 2025-03-10 · Paul Greenwell Effective stakeholder engagement is vital for successful product operating model transitions, addressing fears, aligning strategies and collaborating to drive business outcomes. # Stakeholder Buy-In: A Secret Sauce for Product Operating Model Success? Transitioning to a Product Operating Model requires a fundamental shift in how an organisation delivers value. But the biggest challenge may not be just changing ways of working, it can also be addressing underlying fears. Fear of failure, loss of control, wasted resources, or reputational risk can silently create resistance, stalling progress before it even begins. Unlike the traditional project-based approach, where teams form around specific initiatives and disband after delivery, the product model revolves around long-term ownership of customer and business value. To make this transition successful, you must surface and address stakeholder concerns early. Without understanding the context and rationale for concerns, embedding lasting change becomes significantly more difficult. ## What Happens If Stakeholder Engagement Is Poorly Managed? ### 1. Lack of Strategic Alignment Without consistent stakeholder engagement, teams operate in silos, each following their own agenda, ultimately slowing down progress and reducing impact. The strategy may be well understood at a high level but if it fails to translate into day-to-day execution, teams will lack clarity on how their work aligns with overarching business goals. This leads to scattered efforts and competing priorities. ### 2. Resistance to Change When shifting to a product model, teams accustomed to the project mindset can resist the new ways of working. Business stakeholders often struggle to see the benefits of product thinking and instead continue to push for feature delivery over outcome-driven work. It's vital that the product teams have the tools to ask questions, such as "what is the problem you are trying to solve?" and consistently bring the conversation back to outcomes. ### 3. Inefficient Ways of Working and Decision-Making Bottlenecks Traditional project approaches can lead to heavy governance processes, rigid funding cycles, and inefficient work allocation. Decisions made too far upstream without input from those closest to the work often result in misaligned priorities and wasted effort. Product teams without autonomy to make strategic decisions may rely on top-down prioritisation, which stifles innovation and slows time-to-value. ## How to Engage Stakeholders Effectively ### 1. Uncover Stakeholder Fears When engaging stakeholders, one of the most valuable things you can uncover is what they are afraid of.  If you don’t take the time to understand their fears, you risk blind spots that can derail alignment, stall progress or create hidden resistance. Stakeholders rarely state their fears outright. Instead, they might push back on an idea, add hurdles to a process, or slow down decision-making. These behaviours often signal underlying concerns rather than purely rational objections. To navigate this, you need to listen carefully, ask the right questions and sometimes read between the lines. Once you understand their fears, you can address them directly. This might mean offering a low-risk way to test a new idea, providing data to counteract uncertainty, or framing your proposal in a way that makes sense for their context or priorities. ### 2. Use Stakeholder Mapping Before engaging stakeholders, start by identifying who they are, have a perspective on their level of influence and likely concerns. Stakeholder mapping helps teams: Identify key stakeholders across the organisation who influence or are impacted by the transformation. Segment stakeholders by level of influence and interest, ensuring tailored engagement strategies. Understand what they fear most about the transformation—whether it’s loss of control, increased accountability, or uncertainty. Develop a communication plan that keeps stakeholders informed and aligned throughout the transformation journey. Mitigate risks early by proactively addressing concerns from high-influence stakeholders. By visualising the stakeholder landscape and acknowledging their fears, teams can prioritise engagement efforts and foster stronger collaboration. ### 3. Communicate the Vision and Strategy Without a compelling vision, stakeholders will default to their existing perspectives and experience. Clearly articulate the product vision and strategy. Strategy communication needs to go beyond leadership to all levels of the organisation. Tie business goals to product outcomes. Move away from feature-driven roadmaps and towards outcome-based roadmaps that directly support business objectives. Use real-world examples to show what success looks like. ### 4. Infuse Cross-Functional Ways of Working Rather than treating stakeholders as external approvers, embed them directly into discovery and prioritisation. You don't need to change the structure to work cross-functionally, start by inviting your key stakeholders to a workshop, planning meeting or discovery playback: Use tools like an Opportunity Canvas or a 1-pager that suits your context to ensure there is a clear goal and work aligns with strategic objectives. Actively engage with business stakeholders to share knowledge, communicate strategy, and align on priorities. Bring them into the tent! Listen for hidden resistance. When stakeholders hesitate, ask probing questions to uncover whether fear of failure or uncertainty is driving their concerns. Experiment safely. Use pilots, prototypes, or controlled rollouts to reduce perceived risk and build trust. ### 5. Shift to Outcome-Based Measurement One of the biggest challenges in a product transformation is moving from output-based success measures (e.g. features delivered) to outcome-based metrics (e.g. impact on business goals). Measure the effectiveness of work based on value delivered, not just completion. Focusing only on predictability can lead to teams working towards delivery targets rather than real customer impact. Use data to build trust. Regularly share insights with stakeholders on how changes are improving outcomes, whether through reduced support tickets, increased customer satisfaction, or revenue growth. ### 4. Break Down Those Siloes ### If IT is seen as an execution function rather than a partner in solving customer problems, then you won't succeed. A whole pile of value will be left on the table, unrealised. Encourage cross-functional collaboration. Bring together product, technology, and business leaders to align on priorities. This doesn't mean decision by committee, but you need to walk out of the room with a shared understanding on the priority problems to solve and the desired outcome. Provide training and coaching. Help peopl understand product thinking, and equip product teams with the right skills. Co-design solutions. Rather than IT “delivering” what the business wants, engage stakeholders in product discovery to jointly define solutions. ## Don't let Engagement be an Afterthought The success of a product operating model requires change across the whole business, it is not just a technology or IT team thing. This requires building a shared understanding of strategy, collaboration, and alignment around what you are trying to achieve. Without intentional and proactive stakeholder engagement, teams will struggle with misalignment, resistance and the change simply won't stick. Want to ensure your product transformation succeeds? Don't forget stakeholder engagement. # Why AI is Exposing Weaknesses in Agile – and How a Strong Product Operating Model Can Fix It Source: https://www.propelventures.ai/blog/why-ai-is-exposing-weaknesses-in-agile Meta: 2025-02-27 · Paul Greenwell This blog post discusses the shift towards the product operating model that many engineering and product leaders are recognising as essential for delivering value faster. Ben Ross, CEO of Propel, highlights Propel’s unique position as both a product operating model coach and engineering partner. The post explains why Propel’s real-world experience in product delivery sets it apart from traditional consultancies and emphasises the importance of integrated coaching and engineering to drive successful transformations. For over eight years, Propel Ventures has been at the forefront of product thinking in Australia—helping businesses not only build great products but also embed a strong product mindset across their organisations. A true product-led business isn’t just about having product managers—it’s about ensuring that everyone understands the broader business context, is connected to customer needs, and continuously iterates to refine product-market fit. ## Why AI is Exposing Gaps in Agile As industries across food, logistics, and retail reposition themselves as tech-enabled businesses, many are realising that Agile alone is not enough. Agile has helped optimise engineering delivery, but it doesn’t inherently ensure that companies are building the right things. With AI unlocking new opportunities, businesses need a clear way to prioritise investments and align technology with strategic goals. This is where a Product Operating Model (POM) becomes critical. A well-defined Product Operating Model helps businesses move beyond feature-driven roadmaps and focus on outcome-based product development. However, many organisations lack mature product management capabilities. Instead, we often see BAs or project managers rebranded as product owners or product managers, without the necessary upskilling in product discovery and strategic thinking. The result? Backlog-driven development that delivers outputs rather than real business and customer value. For businesses serious about scaling AI adoption, these weaknesses in product management and Agile delivery are now being exposed. ## The AI Shift: From Cost Cutting to Revenue Growth AI adoption has followed a familiar trajectory. Early investments focused on cost-cutting and efficiency gains—what we call the "corporate Ozempic" approach. These quick wins were attractive because they provided measurable savings with low risk. However, once costs are optimised, the benefits plateau. The next evolution of AI is revenue enablement—using AI to create new products, services, and business models. The potential upside here is far greater and uncapped, but realising this value requires a mature Product Operating Model. Companies that lack clear product leadership and structured decision-making frameworks are struggling to apply AI effectively. They have no systematic way to evaluate opportunities, prioritise investments, or ensure AI initiatives are delivering measurable business value. The absence of a strong POM leads to AI being deployed in fragmented, tactical ways—rather than being embedded strategically into core business offerings. ## What This Means for Leadership Just as Agile transformations required leaders to adapt their mindset, the shift to AI-enabled businesses will demand an even greater change. Executives can no longer rely on top-down decision-making—they must trust and empower their teams, providing the right structures and guardrails rather than micromanaging execution. For AI to be a competitive advantage, organisations must integrate it within a strong Product Operating Model. This ensures that AI investments are: ✔ Prioritised based on business and customer value ✔ Governed effectively to manage risks like IP security and compliance ✔ Integrated into broader product strategy, rather than remaining isolated experiments ## The Bottom Line The companies that succeed in AI-driven growth will be those that have already done the work to build a strong product mindset, refine their Product Operating Model, and evolve their leadership approach. Those that haven’t will struggle—not because AI isn’t valuable, but because they lack the organisational structures needed to unlock its full potential # How to get the most out of your communities of practice Source: https://www.propelventures.ai/blog/communities-of-practice Meta: 2025-02-27 · Paul Greenwell Discover effective strategies for building and maintaining Communities of Practice, with insights on what works best and how to keep your team engaged in knowledge sharing. # Communities of Practice - are they working for your people? At Propel, our teams work on different opportunities for different clients, so finding a way to connect our product managers, engineers and designers with their peers to build knowledge and share insights requires us to be more intentional than is probably the case for teams who are all working together on the same product. We have tried a bunch of approaches to Communities of Practice (COP) with different approaches working for different teams at different times. Here are 4 of the approaches we have tested with some key take outs: ### 1. Formalised Learning Sessions Structured sessions where team members present on relevant topics, often with a set agenda and Q&A. Pros: High-quality knowledge sharing from experts Clear objectives and takeaways Useful for upskilling on technical or complex topics Cons: Requires significant preparation Can be difficult to maintain momentum Scheduling challenges Hot take: It's really hard to keep this going! Test and learn score: 2/5 ### 2. Collaborative Working Sessions Smaller groups tackling shared problems, meeting regularly to collaborate and co-create. Pros: Practical, hands-on learning Builds strong cross-functional relationships Participants feel ownership of the outcomes Cons: Requires ongoing commitment from participants Can be difficult to maintain momentum Risk of becoming another ‘meeting’ without clear value Hot take: This works for us ad hoc, with product managers or engineers supporting each other through feedback and fresh perspectives. Test and learn score: 3/5 ### 3. Asynchronous Knowledge Sharing Knowledge is shared via Slack (or your message tool of choice) allowing everyone to engage at their convenience. Pros: No time constraints; flexible participation Creates an ongoing knowledge repository Reduces meeting fatigue Cons: Hard to gauge engagement Lacks the real-time connection of discussions Contributions can taper off without regular prompts Hot take: Easy, interesting and in the moment. Test and learn score: 4/5 ### 4. Casual, Time-Boxed Knowledge Shares Short, informal sessions where anyone can share insights, experiences, or learnings with minimal prep. Having a roster helps keep it going. Pros: Easy to maintain with low commitment Encourages diverse contributions Builds a sense of community without becoming a burden Cons: Can lack structure or depth May require facilitation to keep conversations valuable Participation can fluctuate Hot take: This is a winner! We time ours at the end of the week to combine quick learning with fun connection and "almost the weekend" vibes. Test and learn score: 5/5 By keeping it simple and structured around shared learning, our casual, time boxed check ins have become a routine people actually want to participate in. We've removed the barriers of traditional Communities of Practice while still creating connection and knowledge exchange. # Is your operating model holding you back? Source: https://www.propelventures.ai/blog/operating-system Meta: 2025-02-19 · Paul Greenwell Discover how shifting from project-based to product-based thinking can unlock true agility, enhance customer value, and drive sustainable growth. Fund Teams not Projects, Outcomes not Features There’s no shortage of evidence out there about the value of the product model, yet surprisingly (to me anyway), there are many companies still spinning up project funded teams to deliver digital products and solutions. They are locked into annual budgets and fixed scope commitments, optimising for predictable outputs rather than any meaningful outcomes. They may have big ambitions of growth, and talk the talk of customer-centricity, but their ways of working simply don’t support these ambitions. Often they have gone through an "Agile Transformation" but there is nothing agile about their reality. Instead, they’re stuck in an old-school project mindset, prioritsing deadlines over outcomes, handoffs over collaboration, and short-term wins over long-term value. When projects fail to deliver on a promise made months or years ago, distrust grows and leadership responds with more governance, more command, more control. I'm not being overdramatic when I say that it's heartbreaking. Here is what happens when organisations work this way: Fragmentation – Business and IT operate in silos with IT as a service provider, not partner. Lack of End-to-End Ownership – Work is handed off from function to function, with no shared accountability for outcomes. Project-Based Thinking – Teams are formed to deliver fixed-scope initiatives, then disbanded, rather than owning long-term value creation. Governance Overload – Heavy approval layers slow decision-making and kill agility. The Wrong Success Metrics – Shipping features gets celebrated, but actual customer impact? That’s an afterthought. Teams continue delivering, but the system itself is working against them, making real value realisation impossible. Shifting away from this old school approach is largely cultural and without exec sponsorship, certainly not easy. It means breaking down silos, realigning incentives, and empowering teams with clear ownership and autonomy. The Playbook for Change This isn’t just an IT problem. It’s an organisation problem that requires leaders to step up and lead the change. 1. Organise Around End-to-End Value Project-centric organisations are built around internal structures, not customer value. The fix? Cross-functional teams that own a domain from strategy to execution. Instead of forming teams for a project, fund them persistently so they can iterate and improve continuously. Give them clear accountability for business outcomes, not just task completion. Shift direction from “here’s a list of features to build” to “here’s a problem to solve” and let the teams figure out how. Traditional funding models kill momentum. They force teams to fight for budget every cycle, instead of focusing on long-term value creation. Instead, companies should: Allocate budgets to value streams or product areas instead of individual projects. Measure success by customer and business impact rather than delivery deadlines. Give teams the financial autonomy to prioritise what moves the needle Too many teams build first and ask questions later. We need to flip that. Validate customer problems before committing resources. Test assumptions early to reduce waste and increase confidence in solutions. Treat iteration as the default, not an afterthought. If success is measured by features shipped, teams will optimize for shipping features. The shift? Track what actually moves the business. Instead of measuring “velocity,” track customer adoption and satisfaction. Instead of celebrating project completion, track actual impact on business goals. Instead of just tracking how fast teams work, track how fast value reaches customers. Making the shift to product thinking isn’t just about strategy, it’s about execution. To build trust, deliver value faster, and create a scalable model, get the basics right. Having guardrails and measuring delivery performance is not a blocker to agility, they are enablers. Ensure teams understand their capacity and plan for discovery, BAU as well as strategic initiatives. Estimate effort by using relative sizing, historical data and ongoing refinement. Break down the effort and slice work into smaller, valuable increments to enable fast feedback loops and learning. Teams want to succeed. But they can’t do that if they’re trapped in a system that rewards the wrong things. Genuine agility and cross functional accountability are the keys to outpacing the competition, consistently creating real, tangible value. So the next time you’re caught in the system, ask: Is there a better way? # The Case for "Bad AI" Source: https://www.propelventures.ai/blog/bad-ai Meta: 2024-11-19 · Paul Greenwell Discover why imperfect AI can enhance human decision-making by encouraging critical thinking and deeper engagement, leading to smarter, more thoughtful outcomes. Why a Little Imperfection is Just What We Need ### AI Outputs Are Just Half the Story AI’s output alone isn’t what really matters; it’s how we humans choose to use it. AI can churn out answers, recommendations, and solutions, but the real value is how we interact with those outputs. In Tim Harford’s example, researchers conducted an experiment where recruiters used AI to help screen resumes. Some recruiters had a “good AI” tool, highly accurate, spot-on recommendations. Others had a “bad AI” tool, a less accurate, imperfect version. Surprisingly, those with “bad AI” made better hiring decisions because they engaged more deeply with each resume, actively weighing the AI’s input against their own judgment. Those with “good AI”? They essentially went on autopilot, blindly trusting the tool without thinking critically. ### Humans Are...Well, Quirky AI is often designed with the ideal, rational user in mind, but real life isn’t so straightforward. When we get too comfortable, we start rubber-stamping AI’s decisions instead of using our own judgment. That’s exactly what happened with the recruiters. When the AI seemed highly accurate, they stopped questioning it, trusting its recommendations instead of staying engaged. But the ones using “bad AI” knew it was unreliable, so they remained more alert, catching mistakes and making better decisions. ### Design Thinking: AI Needs to Be Built for Real People This is why design thinking—a people-centered approach to creating products—is vital in AI development. Rather than creating an AI that works in perfect conditions for ideal users, design thinking emphasizes building AI that aligns with real human behavior. AI should be designed to solve specific problems for specific users. And sometimes, that means introducing just enough imperfection to keep us involved in the process. As we saw with the resume-screening study, imperfect AI encouraged critical thinking, which is exactly what you want when making decisions as important as hiring. ### Why Imperfect AI Keeps Us Sharp Sometimes, we need AI to be a little less perfect so we stay actively involved. Perfect AI can lull us into a “tick and flick” mentality, where we mindlessly approve whatever the algorithm spits out. Imperfect AI keeps us on our toes, prompting us to evaluate suggestions and apply our own judgment. In the case of the recruiters, “bad AI” actually led to better decisions, precisely because it kept people from going into autopilot mode. ### Embracing Imperfect AI for a Better Future In a world of fast-evolving AI, let’s appreciate the benefits of a little imperfection. Building AI that doesn’t just give perfect answers but also nudges us to think critically and stay engaged can help us avoid the traps of over-reliance. “Bad AI” might be exactly what we need to keep our minds sharp, our decisions thoughtful, and our reliance on technology balanced. # A Pragmatic Approach to Product Operating Models Source: https://www.propelventures.ai/blog/pragmatic-product-operating-model-0-0 Meta: 2024-10-23 · Paul Greenwell Discover how adjusting work environments and fostering open communication can help neurodiverse employees thrive and unlock their full potential in the workplace. Sharks, Cakes and Kebabs We welcomed John Cutler, self-proclaimed optimistic pragmatic sceptic today, to share his perspective on product operating models, team topology, governance and how to focus efforts for success. With participants tuning in from both Melbourne and Sydney, John shared a wealth of insights, drawn from his experience working with companies of all sizes. His anecdotes and practical advice are invaluable for anyone embarking on or deepening their product-led journey. The tension between the ideal and the reality John started by noting the importance of acknowledging the reality of your organisation when considering how you move to a product operating model. The principles we read in books about "the best" manifest differently depending on the context. Many of those companies that we put on a pedestal, were actually “born” as product-led organisations, while others — think banks and insurance companies with high levels of regulation — have deeply ingrained centralised IT functions and historical ways of working. Transformation isn’t about copying what works at top-tier tech companies; it’s about adapting those principles and lessons to the specific context of your business. "It's like a teenager growing up by the beach and being able to surf. It is very different than when I arrived in Santa Barbara never having surfed. I'm supposed to just go in the water? It's not going to go so well for me. I'm scared of sharks" Team topologies A service blueprint of customer journey is a good place to start, combined with understanding the capabilities needed as the customer moves through various touchpoints. "What are our stable parts of our business? What do we need to be extensible? What doesn't need to be extensible. How are customers navigating our product surface area differently now than they did 5 years ago?" Try to take into account collaboration needs and leave room to flex. "It's better to have a somewhat fungible org chart initially." Companies sometimes pile on architecture or processes without considering how well they integrate, much like stacking kebabs on layers of cake. The shift to becoming a platform team takes time, as teams migrate services and refine the architecture. "I joke with enterprise architects. They all have that one slide that looks like the kebab on top of the cake." Labelling a team a "platform team" doesn't make it true. Platform capabilities should emerge organically as the company scales and recognises the need for shared services. Different work, different governance Not all work is the same, and it helps to recognise different shapes of work. Whether it’s highly incremental tasks, heavy governance efforts, or innovative greenfield projects, each type of work demands a tailored approach. As John put it, “you need to name it to tame it.” In practice, this means not applying a one-size-fits-all framework across every project. Some efforts may require close oversight, heavy dependencies, and legal involvement, while others can be left to run autonomously. Outcomes v outputs When shifting to a product operating model, one of the first concepts companies encounter is the shift from outputs to outcomes. However, be careful about becoming too “religious” about outcomes over outputs. In the real world, outputs (what you ship) still matter. After all, you can’t create value if you aren’t delivering anything. "you can only make the shots that you take" Overall, there were lots of great reminders about where to start in your Product model journey, how to think pragmatically about outcomes over output, the art and science of defining the optimum team topology and thinking about the right model for your company. Be cautious about taking lessons from FAANG companies as they all have their OWN version of a product operating model and each are vastly different to each other. # Embracing Neurodiversity in the Workplace Source: https://www.propelventures.ai/blog/embracing-neurodiversity Meta: 2024-10-16 · Paul Greenwell Discover how adjusting work environments and fostering open communication can help neurodiverse employees thrive and unlock their full potential in the workplace. Embracing Neurodiversity in the Workplace: Why Managers Must Adapt to Help Employees Thrive In tech, we are surrounded by neurodiverse people, whether we know about it or not. Some of us are out and proud, others chose not to disclose, some of us may not even be diagnosed. We might come across as socially awkward, we may miss social cues, some of us are so good at hiding in plain sight you’d never even notice. Other times you might notice our performance seems to drastically fluctuate with no understandable rhyme or reason. All of that said, we can be pretty amazing employees - even if we sometimes we are so anxious about picking up a phone we will email about a fire. According to estimates, up to 17% of people have been diagnosed with neurodivergent conditions, with some research suggesting the true figure could range from 30% to 40%. That means statistically (at least) one in every five people you interact with is likely to have some form of neurodiversity. And while we don’t always disclose at work – you can be pretty sure we are there, hiding among you. So, neurodivergence being so widespread, it’s essential for workplaces to understand how to manage these underutilised, misunderstood, oft neglected employees and to recognize that doing so is not just a choice, but a responsibility. And an economic imperative. Rethinking Performance: Adjusting the Environment, Not the Individual “Too often the neurodivergent are noted as under-performing. Feedback is often focused on what the individual needs to do in order to improve, instead of looking at environmental factors which could be limiting their ability to be successful.” as Helen Needham, founder of Me.Decoded, aptly puts it. This is a crucial shift in thinking. Rather than focusing on what the individual should change, managers should explore how the environment, workload or workstyle might be adjusted to better suit the person’s needs. Suddenly a conversation can happen. “I notice that you’re struggling with X, Y, Z. What’s going on? How can we adjust things to enable you to meet this goal?” I can talk to this personally. My neurodiversity regularly impacts my ability to be on time. It impacts my capacity to concentrate in noisy open plan offices. It means I think better when talking through things out aloud or drawing them out on a whiteboard. I can’t seem to ‘think’ at a computer, then I get uncertain and start second guessing myself and undermine my own productivity. So my employers who are open having walking meetings, or are open to chat through an approach standing at a whiteboard get much more out of me! I have my approach and thoughts on that whiteboard, and now I don’t need to ‘think’ when I am sitting at my computer – I can just do. A simple change in approach to the task, supported by my manager, and there are drastically different outcomes. But it is more than just being ‘open’ to these different work styles. It’s about recognizing that neurodivergent employees may experience work differently, and that adjusting the way tasks are structured, deadlines are set, or communication happens  that can lead to much better outcomes. Peter Drucker, the famed management consultant, sums this up well: “The best managers find ways to maximize their team members’ strengths and make their weaknesses irrelevant.” By shifting focus from the individual to the system they operate in, managers can create an environment that empowers neurodiverse employees to excel. The Power of Asking: “How Can I Help You Thrive?” A key element of supporting neurodiverse employees is fostering open, honest conversations. Managers should actively ask their team members, “How can I help you thrive?” Regularly. This simple yet powerful question opens the door to understanding each individual’s unique needs and preferences. When I was first asked this question by Amy Johnson, our Chief Product Officer, I was floored. I started sweating. I didn’t know what to say. Despite years of being an advocate for Neurodiverse people, years of asking my team members what needs to be adjusted so you can do your best – I had never been asked. And it scared me. I didn’t know how to answer in a way that didn’t show case my ‘weaknesses’. But Amy lead by example. Not being scared to talk through her experiences. What she thrives doing, and what drains her. Without this emotional vulnerability from both parties, a successful conversation wouldn’t have been possible. Leaders must lead by example, showing that it’s okay to express needs and request changes to the environment, workload or workstyle (sometimes referred to as accommodations or adjustments). Moreover, these discussions need to happen regularly. As people grow and learn more about themselves, their needs and preferences may evolve. It may take time for neurodivergent employees to develop the confidence to advocate for what they need, but consistent communication helps build this trust. I know my answer to Amy’s question has already changed dramatically. I have thought about my answer more. I have reflected on what is working well for me at the moment, what isn’t, developed a few ideas that we can trial together to see what works best for us. These regular check-ins ensure that managers stay attuned to their team’s evolving needs and insights, and can adjust their approach accordingly. Moving Beyond Obligations: A Path to Higher Performance Providing accommodations for neurodiverse employees is not just about meeting legal or ethical obligations; it’s about unlocking potential. By tailoring the work environment to suit the strengths of neurodivergent individuals, managers can help these employees achieve their full potential. The right adjustments — whether it’s more flexible deadlines, clearer communication, or quieter workspaces — can make a world of difference in performance and job satisfaction. Ultimately, neurodiverse employees bring a wealth of creativity, innovation, and unique problem-solving skills to the table. To truly leverage these strengths, managers must actively engage with their team members and create environments that support, rather than stifle, their growth. As Marty Cagan attributed to Bill Campbell in his book Empowered, “Leadership is about recognising that there is a greatness in everyone, and your job is to create an environment where that greatness can emerge.” With regular conversations, a little vulnerability, and thoughtfully asking right questions managers can make considered adjustments, and enable their neurodivergent employees to thrive. # An integrated approach to Product Operating Model transformation Source: https://www.propelventures.ai/blog/integrated-product-operating-model Meta: 2024-10-14 · Paul Greenwell This blog post discusses the shift towards the product operating model that many engineering and product leaders are recognising as essential for delivering value faster. Ben Ross, CEO of Propel, highlights Propel’s unique position as both a product operating model coach and engineering partner. The post explains why Propel’s real-world experience in product delivery sets it apart from traditional consultancies and emphasises the importance of integrated coaching and engineering to drive successful transformations. 🚀 What We Are Seeing in the Market: The Product Model Shift 🚀 I’ve been quiet on LinkedIn for a few weeks because, at Propel, we’ve been busy engaging with executives responsible for engineering team delivery. They’ve echoed a similar message, one that’s worth sharing. The engineering and product leaders I’ve been speaking with have already been through the agile journey, but they’re now recognising the importance of shifting towards a product model—where teams deliver value to customers faster and more effectively. The good news for us is that this is something Propel has lived and breathed throughout our history, delivering the right product faster (hence “Propel”). We’ve been building successful products for clients, and we’ve developed both a coaching capability and an engineering delivery capability to help clients deliver the right product faster and transform to the Product Operating Model. Although some clients seek coaching or engineering assistance separately, we’re seeing a rise in demand for integrated product model coaching and product model engineering to maximise the chances of a successful transformation. This shift impacts not just the engineering function but all functions, including those outside the engineering teams. 👥 What Sets Propel Apart? We’re not just talking the talk; we’re walking the walk. Propel has been building successful products using the product operating model for almost a decade. It’s this real-world product experience that sets us apart. We’ve observed the challenges that arise when transformation is promised by those who take a single-threaded approach: • Coaches: While adept at discussing product models, they often lack the real-life experience or a proven track record of delivering successful products themselves, which undermines their credibility. • Agile Engineering Consultants: These consultants typically focus on agile delivery, not product model engineering. Although familiar with the latest books on product models, their experience lies in agile engineering, whereas the product model requires significant changes both inside and outside of your engineering team. • Coaching and Engineering from Large Consultancies: Firms like Deloitte and PwC have impressive partners who have read the latest books and podcasts on the product operating model, but the delivery of their service to your organisation is typically executed by junior associates and they are usually following a cookie-cutter playbook. This approach can lead to an ill-fitting model for your organisation—something we’ve been asked to come in and fix on multiple occasions. At Propel, we: • Coach your teams to adopt a product model; • Engineer and deliver products that showcase how the model works in practice; and • Guide executives and team members to shift their mindset, aligning people, processes, and technology, both inside and far outside of the engineering teams Clients turn to us because they understand that to truly transform, they need a partner who can deliver the right product faster—not just coach them through a process, but show them how it’s done by doing it. # Conclusion 💡 If you are considering a Product Operating Model Transformation, watch out for the following: • Real-world expertise and proven results: Does your partner have experience delivering products where they have taken on the product market fit risk themselves? Is their experience practical or academic? What products have they delivered using the product operating model? • Coaching and engineering assistance: Does your partner have the capability to define the right Product Operating Model for your organisation. Do they have the credibility to offer coaching and engineering delivery in an integrated fashion? If your engineering function is ready to move beyond agile and become a true product-driven engine, Propel is here to partner with you to coach and execute, delivering the right thing faster. # To restructure or not to restructure? Source: https://www.propelventures.ai/blog/organise-around-value Meta: 2024-09-27 · Paul Greenwell Learn how to reorganize your teams for optimal value delivery, enhancing creativity, autonomy, and efficiency through a value-focused, cross-functional approach. ...that is the question Organising Teams Around Value: A Blueprint for Success When you bring those solving the problems close to the customers they are solving the problems for, you will come up with more creative and innovative results. Sound obvious? It is surprising how distant most engineers and even product owners are from customers. In many organisations, there are multiple hand-offs from stakeholders and "the business" to the teams charged with delivering the solution. On the flip side, when teams have line of sight and ownership of end-to-end value, delivery speeds up and the likelihood of the solution meeting the mark is much higher. But what does it mean to "organise around value," and how can you implement this effectively? To clarify that when we talk about “organising,” we’re not referring to formal organisational charts or hierarchical structures. Instead, we're focused on how people collaborate and communicate within their teams and across other teams. ### Guiding Principles for Organising Around Value There isn’t a one-size-fits-all solution when it comes to operating models. However, there are several guiding principles that can help ensure teams are optimised for value delivery: Value Focused Teams Aligned to Measurable Customer or Business Goals The first step is ensuring that teams are organised around specific outcomes that are tied to customer or business value. When teams are aligned with these goals, they can better focus on what they are there to do rather than just completing tasks or features. It's also much more rewarding to move the dial on an outcome rather than just deliver outputs. Autonomy to Make Decisions and Take Ownership of Outcomes Teams need the autonomy to make decisions regarding how they deliver on their goals. So how can you set up the teams to enable this?  Ownership leads to a culture of accountability. Platform and Enabling Teams to Handle Complex or Shared Concerns Platform and enabling teams can take on complex or shared responsibilities, such as infrastructure or core systems, allowing stream-aligned teams to focus solely on delivering customer and business outcomes. Limit Dependencies and Handoffs to Enable Fast Delivery Cycles and Feedback Loops One of the major obstacles to fast and efficient delivery is the number of dependencies between teams. Minimising these dependencies and handoffs allows teams to iterate quickly, integrate feedback, and continuously improve. Cross-Functional Expertise with the Necessary Mix of Skills to Deliver Value Independently Teams should have a mix of expertise to deliver value without relying too much on external teams. Cross-functional capabilities allow teams to solve problems and deploy solutions independently, which accelerates the pace of delivery. If you were to audit your operating today, how many of these principles are you adhering to? ### The Role of Team Topologies As companies evolve, they tend to organise in three primary ways: around technical components, features, or value streams. Regardless of maturity, Matthew Skelton and Manuel Pais in Team Topologies outline four essential patterns for teams that enable value-driven delivery: Stream-Aligned Teams: These teams are directly aligned with a value stream and are responsible for delivering customer or business outcomes within that stream. Enabling Teams: These teams help streamline the processes of stream-aligned teams, offering expertise and support to reduce friction. Complex Sub-System Teams: Focused on handling parts of the system that require deep specialisation. These teams do not always endure, forming and dispanding to solve a complex problem for a period of time. Platform Teams: These teams manage infrastructure and shared platforms to support other teams, enabling them to move faster by reducing cognitive load. Ideally the stream-aligned teams can self-serve platform capability. Your architecture should enable this. Skelton and Pais argue that these four types of teams should act as "magnets" that draw in all team types as organisations grow and scale. ### Evolving with Purpose The goal is to design teams intentionally rather than applying a one-size-fits-all template. As organisations grow, the way they operate must evolve too. What worked when a company was smaller might create unnecessary dependencies and roadblocks as it scales. In many cases, what started as a rational grouping of teams becomes a bottleneck, slowing down progress and preventing teams from being truly empowered. “In many cases, what started off as a rational grouping is not creating unnecessary dependencies or complications that work against team empowerment” Marty Cagan in Empowered By consciously designing teams around value delivery, companies can remove the barriers that prevent rapid innovation and create an environment where teams are not just efficient but also empowered to make decisions and own their outcomes. The journey to organising around value isn’t always easy, but the rewards are clear: faster delivery, higher customer satisfaction, and a culture of accountability and innovation. By following these guiding principles and adopting the team topologies approach, organisations can build teams that are resilient, adaptable, and aligned with delivering measurable value. Ultimately, it’s about moving beyond traditional ways of thinking and embracing a model that prioritises collaboration, autonomy, and continuous improvement. When teams are aligned with delivering value, everyone wins! # The power of mission driven innovation Source: https://www.propelventures.ai/blog/mission-driven-innovation Meta: 2024-08-30 · Paul Greenwell Unlock the power of a mission-driven thread to inspire teams, drive innovation, and achieve long-term success. Learn how to align vision, strategy, and goals for impactful outcomes. The Power of a Mission For teams to truly excel, they need more than just tasks to complete—they need to see how their work ties into the bigger picture. By aligning the mission with a clear product vision, strategic goals, and a well-crafted roadmap, companies can transform daily work into meaningful contributions toward long-term success. "Teams that are healthy, happy, have a sense of pride and ownership, and have the right mix of challenge and skill, are the path to happy customers." John Cutler, The Beautiful Mess When teams understand the "why" behind their efforts, they are more likely to be highly  engaged, innovative, and focused on creating real value. It’s not just about getting things done; it’s about moving in the right direction together. It's also not just about articulating the mission, there needs to be a the thread from this purpose to what the teams are actually doing. What steps can you take to bridge the gap from mission to task? Define a Clear and Compelling Mission: Start with a well-defined mission that resonates with everyone. This mission should be more than just a statement; it should be a guiding principle that informs all levels of decision-making. Craft a Vision that Inspires: Develop a product vision that translates the mission into a specific, tangible goal for the product. This vision should be provide direction and help make day-to-day trade-offs. Develop a Cohesive Strategy: Create a product strategy that outlines the path to achieving the vision. This strategy should include key initiatives and priorities that will guide the roadmap and ensure alignment with the mission. Set Aligned Goals: Translate the strategy into specific, measurable goals. These goals should be clear and actionable, giving teams a roadmap for success. Align the Roadmap: Ensure the roadmap is directly informed by the product strategy and aligned goals. Communicate and Reinforce: Regularly communicate the mission, vision, strategy, and aligned goals to teams. Empower Teams to Make Aligned Decisions: Give teams the autonomy to make decisions aligned to the vision. A sense of ownership leads to accountability. # The Benefits of Creating a Mission Driven Thread When teams are connected to a clear mission, vision, strategy, and aligned goals, the magic happens: Increased Engagement: Teams that understand the purpose behind their work are more engaged and motivated, leading to higher levels of productivity and job satisfaction. Better Strategic Alignment: A well-defined vision, strategy, and aligned goals ensure that all activities are in line with the organization's broader goals, reducing waste and increasing efficiency. Enhanced Innovation: Teams are more likely to innovate in ways that drive the business forward when their efforts are aligned with the long-term vision and goals. Improved Customer Outcomes: A clear connection between mission, vision, strategy, and goals ensures that the product evolves in a way that meets customer needs, leading to better business results. Resilience and Adaptability: A strong alignment with mission, vision, strategy, and goals provides direction and motivation, helping teams navigate challenges and stay focused on what matters. First, make sure you have the pieces of the pyramid articulated, communicate often and set your systems of work up so there is a direct link from that jira ticket all the way up to your mission. # Tech and Product - Friends or Foes? Source: https://www.propelventures.ai/blog/friends-foes Meta: 2024-07-19 · Paul Greenwell Explore the dynamic relationship between tech and product teams in achieving better outcomes and a healthy culture. Discover key strategies for fostering collaboration and success. Tech and Product: Friends or Foes? On a cold and clear July night in Sydney, Propel partnered with the Sydney Tech Leaders community to explore whether product and tech were indeed friends or foes. It was a wide-ranging discussion that was at times a little tense, reflecting the reality of what happens in most of the organizations we work in. I came away with the sense that while we are all trying to reach a point of healthy and productive tension, the unhealthy type is still prevalent. Naturally, product and tech leaders have different perspectives, and how to prioritize scarce resources is contentious. Here are some ideas shared about how to keep the tension healthy: ### Symmetry at All Levels Mirror the model of the design, tech, and product triad throughout the organization. Power imbalances at any level lead to issues with information sharing and can result in suboptimal decision-making. Think about who is providing updates at the Quarterly Business Review (QBR); if it’s your product manager in isolation, chances are there will be bias in the message. ### One Backlog to Rule Them All Create one backlog that includes all product and tech initiatives. Make it visible and ensure that the initiatives are linked to outcomes. Prioritization should be objectively and collectively aligned with strategy and goals. ### Shared Measures of Success Align on those goals – call them Key Performance Indicators (KPIs), Objectives and Key Results (OKRs), or your north star, but keep them consistent across tech and product to ensure everyone is moving in the same direction. ### Connection Goes Both Ways We product people love to tell engineers to spend time with customers to create a connection to the problems we are solving for users. This is indeed true, but I loved the counterpoint from the tech leaders that product folks should also spend time with engineers to build knowledge of the tech stack, creating a better understanding of the rationale for tech initiatives. Empathy is a two-way street. ### Communication Breakdowns Communication breakdowns can derail even the most well-intentioned teams. Ask questions for clarity. Be explicit in asking, "What do you need from me?" Raise risks early and often. Share context. Share the why. Who knows, you may end up with a better outcome when all voices are heard. Language matters, so try to speak the same one to prevent misunderstandings. When in doubt, ask questions and be upfront about what you don't know. Vulnerability and openness build a culture of continuous learning and improvement. ### Measure Early and Often Placing bets on initiatives but measuring them early is the way to go. Metrics should be tracked at every sprint review, focusing on leading indicators that can provide early signs of success or areas needing adjustment. People often default to time-based metrics because they're easy to track, but they won’t help when it comes to knowing if you will make the impact you are targeting. ### What Do You Get When Tech and Product Are “Friends”? Better Outcomes By friends, I don’t mean rainbows and kittens at every turn. I mean some conflict, the healthy kind that results in decisions that are better than they would have been without the robust debate. Think of the Steve Jobs story about rocks in a machine that start rough but come out smooth and shiny. A Happy Culture Personally, working with people who have empathy and where there is mutual respect and trust is a place I want to be. A Healthy Tech Stack Keeping tech debt under control and ensuring scalability and reliability is a great place to be. If it helps, you can call an ongoing allocation to tech health your “Mandalorian” capacity, like Melissa Klemke shared that they do at Prezzee. # How long does it take to do product strategy? Source: https://www.propelventures.ai/blog/product-strategy Meta: 2024-07-10 · Paul Greenwell Crafting a product strategy in a week is possible! Learn how to efficiently develop a winning strategy by focusing on customer insights, market trends, competitor analysis, and revenue opportunities. Product Strategy – Can You Do It in a Week? Short answer: yes. When starting a role as a product leader in a new company, the sensible advice seems to be to take your time: talk to lots of customers, meet the team, and build those important relationships before making changes. But when it comes to product strategy, I have a different perspective. Crafting a strategy doesn’t need to be a long and laborious process. It's should be about progress over perfection. In fact, a fresh perspective not tainted by agendas or knowing too much can block out the noise and help you focus on what matters most: insight from customers. Keep it as a set of hypotheses and be clear on what is informed by insight and where there are open questions that need exploration and validation. Here is how I would outline the thinking in Miro (or your tool of choice) to get started: Market Landscape Trends that Impact This Market: What are the current trends that could influence your market? What are you reading about in the papers or on social media? Regulatory changes, digital adoption, cost of living, scams, and privacy concerns are some of the current trends. Do these impact your product? Customer Segments Who Are They and What Are Their Needs: What are your customer segments? Please segment. Warning: if you speak to people in your organisation and they tell you that your product is for everyone, while that may be true, being able to focus on a target segment, understanding their specific needs will give you the best chance of achieving product-market fit and sustained product success. Competitors Who Are They and Where Are They Winning: Analyse your competitors to understand their strengths and weaknesses. Identify the areas where they are succeeding and the gaps they might be leaving open. This competitive analysis helps in positioning your product uniquely and capitalizing on untapped opportunities. How will you solve a problem or meet a need in a better or different way than is being done today? Product Experience Mapping Out Key Journeys: If you or your team are familiar users of the product, map out key customer journeys. Take some screenshots that show how you complete a workflow and ask if this is a good experience. Identify pain points and areas for improvement to enhance user satisfaction and engagement. Customer Sentiment Utilizing Transcripts and AI Tools: Gather transcripts from existing customer interviews to gain insights into customer sentiment. Upload these into a large language model (LLM) for analysis but tread with caution. You should get a steer in the right direction, but speaking to customers yourself or reading the transcript in full will give you a better picture than any Chat GPT interaction will do. If you are using an LLM, make sure you ask it for verbatim feedback to understand genuine customer issues and reduce hallucinations. This helps in identifying barriers to adoption and areas needing improvement. Path to Adoption: Evaluate whether your product works seamlessly with other tools or if it aims to be an all-in-one solution. Understand the path to adoption, as change is hard, especially when there are integrations. Commercials Revenue Opportunities and Market Landscape: Identify where the revenue opportunities lie and assess the difficulty in unlocking these opportunities. Where are those fast-flowing streams (refer back to the market landscape) that offer high potential for revenue growth? Hypothesis-Driven Strategy Formulating Hypotheses: Based on the gathered insights, formulate hypotheses about what the actions you could take are and the outcomes they will deliver. Identify what is validated and where there are open questions. Outline how you will find the answers to these questions through further research, testing, and customer feedback. Strategy doesn't have to be a lengthy and arduous process. You don't need to have all the answers to get started. You do need to understand customer needs and it sure helps to have a thought partner to challenge ideas and synthesize the insights. # The Uncomfortable Truth About Technical Debt Source: https://www.propelventures.ai/blog/truth-about-tech-debt Meta: 2024-06-24 · Paul Greenwell The uncomfortable truth about technical debt, tech leaders are the problem Over my 30-year career, I’ve encountered the issue of technical debt in every organisation I’ve worked with. Teams frequently complain about their inability to address technical debt, often blaming business stakeholders. However, a significant part of the issue lies with technical leaders who struggle to articulate the impact of technical debt and the benefits of addressing it. What is Technical Debt? Intentional Technical Debt is akin to taking a strategic financial loan. Development teams might knowingly incur it to speed up the release of a product, planning to address the debt later. This can be a smart move when time-to-market is critical, as it allows for early revenue and customer feedback. However, like financial debt, it requires a clear plan for repayment to prevent it from becoming a long-term burden. Unintentional Technical Debt resembles unexpected financial debt resulting from unforeseen expenses. It often stems from poor design, rapidly changing requirements, or insufficient knowledge. This type of debt is usually more problematic because it catches teams off guard and can be more challenging to manage and repay. How Technical Debt Comes About Technical debt typically accumulates due to a variety of reasons. Rushed development is a common cause, where speed is prioritised over quality to meet tight deadlines. This often leads to shortcuts that need to be addressed later. Changing requirements can also contribute to technical debt. As project needs evolve, quick changes are made to keep up, often at the expense of code quality. Poor code quality, often due to a lack of adherence to coding standards and best practices, is another significant factor. Inadequate testing leads to fragile codebases that are prone to bugs and difficult to maintain. Additionally, a lack of comprehensive documentation can hinder future development efforts, making it harder for teams to understand and work with the code. When Is Technical Debt Positive? As mentioned above, technical debt isn’t inherently bad. Like leveraging financial debt for investment, intentional technical debt can be beneficial. It enables faster market entry, early revenue, and quicker customer feedback, which can be crucial for a product’s success. It can even save you from over investing if the feature you are building does not have product market fit and you need to change direction. The key though is to have a clear plan for addressing this debt. By recognising the debt upfront and planning for its repayment, teams can balance short-term gains with long-term stability. The Downside of Technical Debt As is more often the case, unchecked technical debt can be crippling, and much like high-interest financial debt, it can slow down development, introduce bugs, and inflate costs. Over time, the codebase becomes increasingly difficult to work with, leading to developer frustration and higher turnover. In the worst cases, it can lead to project failure as the cost and effort required to address the accumulated debt become overwhelming. Strategies for Addressing Technical Debt Addressing technical debt requires a strategic approach. Regularly prioritising refactoring and code improvement is essential. This involves setting aside dedicated time to clean up and enhance the codebase. Implementing automated testing helps ensure ongoing code quality and catch issues early. A strategic approach to addressing technical debt requires the buyin and alignment of business stakeholders. Bridging the Communication Gap with Business Stakeholders Technical leaders often blame business stakeholders for hindering their efforts to address technical debt. However, the real issue frequently lies in the inability of technical leaders to effectively communicate the impact and cost of not acting. Here’s how to bridge that gap: Quantify the Impact: Use clear metrics to show how technical debt affects performance, costs, and timelines. Numbers speak louder than vague concerns. Align with Business Goals: Explain how reducing technical debt leads to faster, more reliable product delivery. Link technical debt reduction to business outcomes like improved market competitiveness and revenue growth. Highlight Risks: Clearly outline the risks of ignoring technical debt, such as potential project failures, increased costs, and delayed time-to-market. Paint a vivid picture of the consequences to make the urgency palpable. Propose a Clear Plan: Present a well-structured, actionable plan for addressing technical debt. This should include specific timelines, required resources, and expected benefits. Make it easy for stakeholders to understand the steps and their positive impact on the business. Use Analogies: Draw parallels with financial debt. Explain how, like financial debt, technical debt can be a strategic tool but becomes problematic if not managed properly. Emphasise the importance of a repayment plan to prevent long-term crippling effects. Foster Ongoing Dialogue: Regularly update stakeholders on progress and changes in technical debt. Keep the conversation continuous to maintain alignment and support. By improving how you communicate the realities and implications of technical debt, you can secure the necessary buy-in from business stakeholders to address it effectively. This approach not only highlights the immediate benefits but also ensures the long-term health and success of your software projects. Technical debt is an inevitable aspect of software development, but it doesn’t have to be detrimental. By understanding its nature, strategically managing it, and effectively communicating with stakeholders, technical leaders can leverage technical debt to their advantage while mitigating risks. Balancing short-term gains with long-term stability is key to ensuring sustainable success. # Reflections on 13 hours with Marty Source: https://www.propelventures.ai/blog/13hours-with-marty Meta: 2024-06-12 · Paul Greenwell Discover key reflections and insights from a "Transformed" product leadership workshop with Marty Cagan. I had the privilege of spending the day at Marty Cagan’s Transformed leadership workshop yesterday, followed by dinner with a dozen product coaches from Australia and New Zealand. I've summarized my takeaways into areas where my thinking and the Propel approach converge and diverge with what I heard yesterday. ## We Converge ## We Diverge Counterview: Managing and embedding change is a process. It helps to co-design an operating rhythm (aka process), communication methods and cadence. Counterview: The double diamond approach to identifying and narrowing problems and solution spaces is a valuable way to embed design thinking and customer centricity. Frameworks and tools are useful for teaching techniques. Counterview: Solving the wrong problem is a waste. User interviews to deeply understand the problem are as important as discovering the solution. Counterview: Governance needs to be right-sized. In heavily regulated and high-risk environments, checks and balances matter. They reduce risk and build trust. ## Where I'm Still On the Fence Counterview: Prototyping doesn’t always require working software. Tools like Figma can validate value and viability before further investment. For existing products, estimating based on experience and previous developments can be effective for high-integrity commitments. Counterview: The above scope is true but can be unrealistic for a single person to cover in heavily regulated products. Overall, it was a fantastic day. Lots to think about and truly inspiring to hear of the examples where the product operating model has delivered remarkable results. # Balancing AI Investment: How to Stay Ahead Without Overcommitting Source: https://www.propelventures.ai/blog/generative-ai-balance-investment Meta: 2024-05-30 · Paul Greenwell This blog post explores the complexities of investing in AI for software product businesses. It highlights the necessity of being proactive with AI investments to stay competitive while acknowledging the rapid evolution of AI technology. The article uses Intuit's GenOS platform and Propel Ventures' brand voice agent as case studies to illustrate the importance of flexible, incremental development and strategic planning to future-proof AI investments In the fast-paced world of software product development, the decision on how much to invest in AI can be challenging. For software businesses, being "all in" on AI is essential to offer users the maximum benefits available today and staying competitive. If you don't make the investment to go all in, your competitors certainly will. However, this isn't a straightforward decision, as today's leading AI technologies can quickly become outdated with each new announcement from OpenAI, AWS, and Google, which often provide new functionalities for free. # The Intuit Case Study Take Intuit, for example. They made a significant investment in developing their own GenOS platform, a proprietary system for integrating generative AI across their product teams. At the time, AWS didn't offer similar tooling as part of their platform. Intuit went ahead and built custom LLMs, tooling, instrumentation, test frameworks, and observability infrastructure. Shortly after, similar capabilities became available for free from major AI providers like OpenAI, Google, and AWS. Without this investment, Intuit risked falling behind competitors like Xero, who were also heavily investing in AI. This underscores the importance of being proactive with AI investments, even when the technology is rapidly evolving. # The Propel Ventures Approach At Propel Ventures, we faced a similar challenge. Our clients requested a brand voice agent to help their staff write all communications in the appropriate brand voice. We knew that whatever we built now might seem outdated within months. To address this, we ensured the architecture of our solution was flexible and adaptable. We built the agent to allow for easy upgrades as LLMs improved, for example, enabling us to switch from GPT-4 to Gemini as new models surpassed each other in capabilities. This approach of building lightly and quickly ensures that we remain up-to-date with the rapid pace of model improvements by swapping out the fastest-changing pieces of functionality. # Key Considerations for AI Investment Future-Proofing: Invest in a flexible architecture that can adapt to new advancements. This means designing systems that can easily integrate new models and functionalities as they become available. Strategic Planning: Be aware of the AI landscape and anticipate upcoming releases from major providers. This helps in planning your investments wisely without overcommitting to technologies that might soon be outdated. Incremental Development: Build and deploy AI solutions incrementally. This allows for continuous improvement and adaptation without the risk of massive overhauls. Competitive Edge: Recognise that timely investment in AI can provide a competitive edge. Even if the technology evolves, being an early adopter can help you stay ahead of competitors who might lag in implementation. # Conclusion Investing in AI is essential for staying competitive in the software product market. While the rapid pace of AI advancements can make investment decisions challenging, adopting a flexible, incremental approach can help mitigate risks. By planning strategically and future-proofing your architecture, you can ensure that your AI investments continue to provide value, even as the technology landscape evolves. # Empowering Software Engineers with Generative AI: The Rise of Internal Developer Platforms Source: https://www.propelventures.ai/blog/generative-ai-platform Meta: 2024-05-30 · Paul Greenwell This blog post explores how leading companies, such as Intuit, are using generative AI to power internal developer platforms, enhancing the efficiency and effectiveness of their software engineers and data workers. It highlights Intuit's GenOS, a proprietary operating system, and discusses key components and challenges, emphasising the importance of a streamlined approach to AI integration. Propel Ventures' expertise in developing and implementing these AI systems is also showcased. In today’s fast-paced tech world, generative AI is revolutionising how companies develop and deploy software. Many of our larger clients, including leading listed companies, are using generative AI to power internal developer platforms. These platforms are making their software engineers and data workers much more efficient and effective. I started off my product management career at Intuit, so have kept a close eye on their product progress and have taken a close interest in Intuit's GenOS internal product, a proprietary operating system designed to integrate generative AI across their product teams. GenOS addresses a big challenge: making generative AI widely accessible while ensuring it’s safely and responsibly integrated into applications on the Intuit platform. Many of our larger clients, including leading listed companies, are trying to use generative AI and looking into creation of internal developer platforms. These platforms are making their software engineers and data workers much more efficient and effective. # What is Intuit's GenOS? GenOS is essentially an operating system because it brings together the essential components for developing and deploying generative AI experiences at scale like having a set of pre-built lego blocks so developers can re-use pieces of AI infrastructure. Here are some of its key features: Monitoring and Governance: Built-in tools for monitoring, governance, and cost management, so teams don’t have to build these themselves. Source: https://medium.com/intuit-engineering/how-to-accelerate-development-velocity-in-the-genai-era-build-a-genos-e71ac2e17b82 # The Need for GenOS GenOS was created to provide a single, streamlined path for developing generative AI applications. This approach makes development smoother, institutionalises organisational knowledge, and offers valuable shortcuts, so teams don’t have to reinvent the wheel each time. # Tackling Key Challenges with GenOS Speeding Up Product Development: GenOS accelerates product development and scales it across the company, ensuring rapid and consistent AI implementation. Incorporating Domain Knowledge: Off-the-shelf large language models (LLMs) are great, but they lack Intuit’s domain knowledge. GenOS tackles this by incorporating techniques like retrieval-augmented generation and grounding prompts with domain-specific capabilities. This means teams can simply plug in their domain knowledge into GenOS and get to work. Ensuring Responsible AI and Data Governance: Intuit's principles for responsible AI and data governance are built into GenOS. This ensures all teams follow these standards without having to manage them separately, providing consistency and peace of mind. # Propel Ventures' Expertise At Propel Ventures, we have deep experience in developing strategies for these generative AI operating systems and their components. Here’s how we help: Strategic Planning: We work with clients to develop comprehensive strategies for integrating generative AI into their platforms. Component Development: Our team builds the critical components that make up these AI systems, ensuring they are robust and scalable. Governance and Compliance: We set up solid governance frameworks to ensure safe and responsible AI use. Custom Solutions: We tailor our solutions to meet the specific needs of our clients, helping them leverage AI to its fullest potential. Investing in generative AI operating systems like GenOS is a smart move. It empowers software engineers and data workers, fosters innovation, and speeds up AI initiatives across the organisation. # Conclusion Generative AI is changing the software development game, and internal developer platforms like GenOS are leading this charge. By providing a solid and scalable framework, these platforms help companies integrate AI into their applications safely and efficiently. At Propel Ventures, we’re excited to support our clients on this journey, helping them make the most of generative AI. # When it comes to AI Product Design, Make Sure We Allow People to Add the Egg Source: https://www.propelventures.ai/blog/generative-ai-product-management Meta: 2024-05-30 · Paul Greenwell This blog post discusses the importance of balancing automation with user agency in AI product design. Using the historical example of General Mills's Betty Crocker instant cake mix, it highlights how allowing users to participate meaningfully in the process can lead to greater engagement and satisfaction. The article provides key considerations for product designers to ensure users feel involved and valued in AI-enhanced products. Incorporating AI into software products presents a unique challenge for product designers: finding the balance between automation and user agency. This balance is crucial for creating products that are not only efficient but also engaging and satisfying for users. To illustrate this, let's look at a story from the 1950s involving General Mills's Betty Crocker instant cake mix. Back in the 50s, General Mills introduced a ready-to-use cake mix called Betty Crocker. All you had to do was pour in water, mix it up, and bake it. An hour later, you'd have a delicious cake. Despite the convenience and quality of the product, it didn't sell well. The reason? It was too convenient. People felt guilty serving something that required so little effort. They wanted to feel involved in the process. General Mills responded by removing the powdered egg from the mix and instructing users to add a fresh egg themselves. This simple change made users feel like they were truly baking, not just following a simple step. Sales skyrocketed as a result. This story highlights an essential lesson for AI product design: while automation can greatly enhance efficiency, users still need to feel like they are contributing to the process. Here are some key considerations for product designers when incorporating AI into their software products: # 1. Identify Critical Decision Points Determine which parts of the workflow benefit most from human input. For example, in a content generation tool, AI can suggest options, but the user should make the final selection. This keeps the user engaged and ensures the output aligns with their preferences. # 2. Maintain Transparency Users should understand how AI makes decisions and have the ability to override or adjust those decisions. Transparency builds trust and allows users to feel more in control. # 3. Provide Customisation Options Allow users to customise AI behaviour to suit their needs. This could mean adjusting the level of automation or personalising the AI's responses based on their style and preferences. # 4. Encourage User Interaction Design the product to encourage regular user interaction. This could involve periodic prompts for user input or opportunities for users to refine AI-generated suggestions. # 5. Balance Efficiency and Engagement Ensure that while AI handles repetitive or complex tasks, users still engage with meaningful parts of the process. This maintains a sense of ownership and satisfaction in the final outcome. In conclusion, the story of Betty Crocker's cake mix teaches us that even in highly automated systems, there's value in allowing users to "add the egg." By thoughtfully integrating user input into AI workflows, product designers can create more engaging and satisfying products that users feel connected to. # The Surprise & Delight of Learning Source: https://www.propelventures.ai/blog/the-surprise-of-learning Meta: 2024-05-28 · Paul Greenwell Explore the joy of continuous learning in product management with insights on embracing feedback, adaptability, community engagement, and promoting a learning culture. Reflecting on what I find most enjoyable in product management roles, I surprised myself somewhat when I realised it was the learning. Of course, achieving outcomes and delivering customer value is great, but the greatest satisfaction comes from what I learn along the way. Counterintuitively, being wrong is inspiring, there is delight in having assumptions disproved. Having a  customer conversation change the course of what you were going to do is incredibly valuable and personally I find, a joy. There's a lot of fun in learning new domains, spotting patterns, and applying a product mindset to solve problems in different domains and industries. It’s a good workout for the brain. Learning about product management through others has also been eye opening. The product management community here in Australia and globally is open, giving and willing to share knowledge. There is plenty of robust (and for the most part), healthy debate that challenges our thinking and help us each sharpen our tools. I also love learning frameworks and gobble up new ideas about how to approach new challenges. What I have learned most about frameworks and tools that you need to understand what they are intended for; just filling in the boxes is pointless. ### Here are some of my learnings from learning: Intentional & Continuous Learning: Embracing a mindset of continuous learning for better decision-making. Seek out learning opportunities and be open to being wrong. Value of Feedback: Listening to customer feedback and being willing to pivot based on that feedback. Adaptability and Flexibility: Being adaptable and open to learning new domains can enhance problem-solving skills. Explore different industries and apply your skills in diverse contexts to broaden your perspective and expertise. Community Engagement: Engaging with the product management community can lead to valuable insights and support. Participate in discussions, attend events, and network with peers to learn from their experiences and share your own. Effective Use of Frameworks: Understand the purpose behind frameworks and use them as tools rather than rigid rules. This ensures you apply the right approach for the right situation, leading to more effective solutions. Promoting a Learning Culture: Foster a learning culture within your team and organisation. Create an environment where team members feel safe to experiment, fail, and learn from their experiences. Encourage knowledge sharing and continuous improvement. In short, product management is perfect for the curious and those who love to learn. You get to explore new areas, chat with customers, and adjust your plans based on what you discover. It's a job where being open to surprises and challenges keeps things exciting and helps you grow both personally and professionally. # Moving to the Product Operating Model - a Cultural Shift Source: https://www.propelventures.ai/blog/product-operating-model-culture Meta: 2024-05-14 · Paul Greenwell Discover the key to successful product transformation through empowered teams, cultural shifts, and lasting change in organizations. Learn how to navigate the challenges and embrace the principles for a successful product operating model. Marty Cagan's latest book, Transformed, along with its accompanying 'spicy' podcast tour, has stirred quite a reaction. While some honed in on the critique of feature team product managers, product ops as a function, and agile coaches (and got a little defensive), I found myself in vehement agreement with what Marty and his colleagues explained so simply. Moving to the Product Operating Model unlocks enormous value and is the light on the hill that we should head toward. I'm also a pragmatist. It's a lot easier said than done. Organisational context is everything. The leaders that we need to influence want to be confident that they are not unleashing chaos. They all come to the party with different experiences, mindsets and agendas. As a result, we need to be super transparent, over communicate and put in place right-sized governance along the way. So indeed, some process helps with managing the change. Thinking about process with principles in mind can actually help deliver the cultural change, which is what is really needed to ensure that the transformation succeeds in the long term. What do we see in organisations working in the feature team model? Let's take it back a step and talk about why we are even writing about this. The reasons for embarking on a transformation are compelling. These organisations are quite often working to create and enhance products using the feature team or delivery team model. This is what we see in organisations who haven't transformed. Combine clarity and alignment with a cultural shift Because analogies are fun, one way to think about transformations is as an iceberg. The visible 20% above the water includes your vision, strategy, roadmap, and success measures — super important for creating clarity and alignment. However, the enduring change comes from the 80% below the surface. This is where cultural changes, practices, and principles need to be deeply embedded. Key principles (with a dash of process) for enabling the cultural change Capability Matters The reality is, the role of a feature team product manager takes different skills to an empowered product manager. Marty covers this extensively in Transformed. Calling out a few areas that are often lacking. Make it Stick I love the suggestion in Transformed about conducting Culture Retrospectives. These sessions help you check progress, celebrate successes, and identify areas for improvement. They ensure that the cultural shift remains an ongoing process, not a one-time event. # Melbourne Software Engineering and Product Management Meetup Event: Double your productivity with AI Source: https://www.propelventures.ai/blog/artificial-intelligence-double-productivity-produc-management Meta: 2024-05-10 · Paul Greenwell Explore the key insights from Propel Ventures' latest Tech Talk series, where our experts discuss the transformative impact of artificial intelligence in enhancing productivity, revolutionising software development, and refining product and API strategies. This blog post delves into practical AI applications, ethical considerations, and the power of AI-driven innovation in the tech industry. Discover how Propel is leading the charge in integrating AI to solve real-world business challenges effectively. What a great night! A whole lot of fun with a wide variety of AI presentations from Propel team members at the Propel Base Station. You can watch a recording of the whole evening at this link, or have a read below for some of the highlights: # Copilots as a productivity multiplier The Propel team members explored how AI technologies like Microsoft Copilot are revolutionising productivity in the workplace. By automating mundane tasks such as meeting summaries and email management, employees can focus on more strategic activities. The integration of AI in daily operations not only simplifies tasks but also enhances decision-making processes through comprehensive data analysis and action item tracking. # Innovative Applications of AI in Software Development Our development team shared insights into how AI is being leveraged to double productivity within software projects. Using advanced AI tools, the team has successfully streamlined various stages of the software development lifecycle, from initial design to deployment. This includes automating code generation from designs and enhancing project management with AI-driven insights and predictions. # AI-Driven Product and API Strategy The Tech Talk also highlighted the innovative use of AI in creating detailed architecture diagrams. This segment demonstrated how AI tools can rapidly translate complex system requirements into clear and structured architectural representations, enhancing understanding and communication among development teams. By automating the generation of these diagrams, AI enables architects and engineers to focus on optimising design and strategy, significantly speeding up the initial stages of project planning and ensuring a more streamlined execution # Interactive AI Tool Demonstrations The Propel team members also provided live demonstrations of AI tools in action, showcasing their capability to transform ideas into prototypes swiftly. These demos provided practical examples of AI's potential to facilitate rapid development cycles and innovation. # Networking As always with events, it is fantastic to bring the community together, see the regulars and some new faces too. The volume was LOUD in the room as people got to know each other, shared stories and set up time to keep the connection going. Really good fun. # Leading the Charge in Product Operating Models: Propel Ventures' Unique Approach Source: https://www.propelventures.ai/blog/product-operating-model Meta: 2024-05-06 · Paul Greenwell Discover how Propel Ventures is revolutionizing the product operating model in Australia. Learn from global experts like Marty Cagan and Radhika Dutt through our live events and see our own strategies in action in our unique comic books. Dive into our blog to see how we apply these principles to deliver software that's on time, within budget, and market-fit. At Propel Ventures, we're not just advocates of the product operating model; we are pioneers in implementing and teaching it across Australia. Our commitment to advancing this approach is demonstrated through our series of live events on the topic of Product Operating Models, featuring global thought leaders like Marty Cagan, Radhika Dutt, Sean Ellis, Josh Seiden, John Cutler, Janna Bastow, and Ant Murphy. These events have established Propel as a beacon of knowledge and innovation in the realm of product management. You can see the event details below and can find summaries of each presentation in the blogs on our website. We are so deep on Product Operating Models, we wrote a book about it ... well it's a comic book.... and there are four of them..... so that still counts right! Beyond hosting seminars and discussions, Propel Ventures has also creatively expressed our expertise through three original comic books. These publications illustrate our proven strategies in software development, ensuring projects are not only completed on time and within budget but also perfectly aligned with market needs. This unique blend of educational tools underscores our deep understanding of the product operating model and our ability to translate theory into actionable success. Propel doesn't just coach clients on how to transform to be a product business, we are a business which delivers software ourselves - so we know where the theory meets the practice At Propel, we practice what we preach. We don’t just teach companies how to operate like a product business; we ourselves develop software using the very principles of the product operating model. This approach, often referred to as 'eating our own dog food,' allows us to continuously refine and perfect our methods, ensuring that we deliver the most effective and efficient solutions to our clients. Our dual role as educators and practitioners in the product operating model not only enriches our understanding but also enhances our delivery, making us a trusted partner in the software development industry. At Propel Ventures, we are committed to leading the way in bringing the best thought leadership on product operating models to the Australian audience, helping companies transform theoretical knowledge into practical excellence. If you are keen to learn more about the Product Operating Model, please get in touch and we can share best practice with you to help you develop better products, cheaper and faster .... and increase the engagement of your team members at the same time. # Tech Talk Recap - Leading Through Change Source: https://www.propelventures.ai/blog/leading-through-change Meta: 2024-04-11 · Paul Greenwell Tech Talk Recap on leadership and transformational change with insights from industry leaders. Learn about being a multiplier, tech leadership, imposter syndrome, and building a strong product vision. What a great night! A whole lot of fun with insightful and entertaining talks from Benjamin Wirtz and Herry Wiputra on leadership and transformational change. You can watch a recording of the whole discussion at this link, or have a read below for some of the highlights: # Be a multiplier Think like the sun. Start the day by bringing light (clarity) for your teams, bring them energy so they feel safe and inspired and empower (solar power) them ensuring they have what they need to succeed. # The double load Tech and product leadership is a bit different. Not only do you need to lead your teams and be focused on building the skills to do that, you also need to work on your craft. We operate in a very fast (and getting faster) domain and we need to keep up! # You are not alone All leaders (except for maybe the toxic sociopaths) experience some sense of imposter syndrome at times. Even Mike Cannon-Brookes - check out his Ted talk on the topic. Find a mentor, build your community and seek help so you can be your awesome best. # The hipages journey Herry took us on a captivating tour of his transformative leadership at hipages, sharing with us "how it started" with rigid functional silos and top-down mandates to "how it's going" with empowered cross-functional teams and a culture of experimentation and accountability. It was Marty Cagan's Transformed IRL! One of the approaches Herry took was to have SLT members outside the product and tech organisation sponsor product teams. This was a great way to build 2-way empathy. Have you ever heard a Head of Sales suggesting prioritising 5 things down to 2? # Leadership learnings So how do you know if you're doing a good job? What does success as a leader look like? We loved hearing Herry re-thinking the approach of asking the team for feedback, shifting to the view that, "they'd tell me if there was something wrong". (and i don't give a .... anyway) Liberating! # Networking As always with events, it is fantastic to bring the community together, see the regulars and some new faces too. The volume was LOUD in the room as people got to know each other, shared stories and set up time to keep the connection going. Really joyous. # Title: Navigating the Shift in Search: Monetisation, AI Costs, and Business Visibility in the Age of ChatGPT Source: https://www.propelventures.ai/blog/artificial-intelligence-money-and-energy Meta: 2024-04-10 · Paul Greenwell Explore the evolving landscape of online search as it moves from traditional models like Google to AI-driven platforms such as ChatGPT. Delve into the challenges and opportunities around monetisation strategies, the costs of AI technologies, and how businesses can maintain visibility in a changing digital environment. In the digital age, the search landscape is undergoing a seismic shift. As AI-driven platforms like ChatGPT emerge as formidable contenders to traditional search engines such as Google, questions about sustainability and monetisation strategies come to the fore. How will Chat GPT make money? Google's success has been underpinned by its robust advertising model, generating revenue while facilitating user access to information. However, with the advent of ChatGPT, the paradigm appears to be shifting away from advertising towards subscription models. The question then arises: Is subscription a more sustainable avenue for monetisation compared to advertising? AI search is really expensive compared to conventional search The operational costs associated with AI-driven search are significant. Recent discussions, including considerations by Google to introduce charges for AI-powered searches, highlight the financial implications of the technology's energy consumption. This idea of charging for AI search was raised in this recent FT article. According to the International Energy Agency, an AI search consumes tenfold the electricity of a standard search, underlining the necessity of effective monetisation. This recent AFR article captured the issue well. The interesting angle here is that Bing might have a competitive advantage vs google because it's AI powered search is not costing it as much as google's AI powered search because it still only has such a small proportion of global search volume. I suspect that someone at Bing and google is watching their COGS and getting nervous!! The financial backbone of Google has enabled substantial investments in technology and engineering, fostering advancements with widespread benefits. This underscores the critical nature of monetisation not just for operational sustainability, but also for continued innovation and being able to offer a great service. What I am saying here is that I think it is very important for these players to make sustainable profits from search so we have a sustainable great search service offering. Could NVIDIA's advancements make search cheap again? As we ponder the future of AI in search, the conversation extends to the cost dynamics and potential for new business models. Could advancements in technology, such as NVIDIA's chip improvements, usher in cost-effective AI search capabilities that negate the need for subscription or advertising models? How can I get found in AI search as a business owner? Moreover, the question of visibility for businesses within AI-driven search platforms remains paramount. Traditional search engines have developed models for paid inclusion, offering companies a pathway to be found online. With ChatGPT, the absence of such a model presents a challenge for businesses seeking to maintain visibility in AI-powered search results. This presents an opportunity for innovative approaches to emerge, potentially moving beyond the conventional advertising model. As the search landscape evolves, the path forward for monetisation, operational sustainability, and business visibility in the age of AI-driven platforms remains a subject of intense speculation and opportunity. The industry stands at the cusp of transformative changes, promising new models for search that could redefine online engagement and accessibility. I can't wait to see what model innovation will come next to support this transformative shift in AI. # Growing Pains? Maybe you need to think about your first product hire Source: https://www.propelventures.ai/blog/growing-pains Meta: 2024-03-15 · Paul Greenwell Discover how Propel Ventures CPO, Amy Johnson emphasises the importance of capability assessments in scaling your business effectively. Learn how to avoid common pitfalls and focus on your customers for sustainable growth. You've found product-market fit and are ready to scale. As a founder, where do you begin? You know your company inside out, but sometimes you're too close to the magnifying glass to see the bigger picture. That's where Propel can help, providing an external perspective of where you're at and what's needed to scale effectively. As a founder, this might mean scaling yourself by hiring your first product manager or investing in your existing teams capability. # Start with a Pulse Check To successfully scale, it's essential to know where you are at now. That's where a comprehensive Propel capability assessment comes into play. This includes understanding if you have the product operating model foundations in place, the maturity of your delivery practices, and the competencies of product managers within the organisation (if you have them). Think of it as a health check-up for your company's product development lifecycle. # Go Deeper by Talking to Your Teams We talk with your team and really dig into how things are done to get a clear picture of what's happening inside your business.  From what we learn, we provide you with a list of actionable recommendations that make sense for your specific situation, designed to help your business grow and improve in the right way. We then work with you and your leadership team to prioritise the actions and ensure the change you are making, sticks. # Common Pitfalls we Find Any of this sound familiar? - Vision or strategy is locked away in the founder's head - A lack of product discovery meaning money spent on features that don't get used - Changing priorities confusing the team - Inconsistent voice of customer and missing feedback loops - Go-to-market planning is last minute and incomplete, confusing the team and customers # The Straight Talk on Discovery One big thing we harp on about is listening to your customers, empathising with their pain and how you can solve genuine and valuable problems for them. It’s not about throwing features at the wall and seeing what sticks. It’s about knowing what the right thing to build is before you start building it. That means less waste, less frustration, and products and features that people actually want to use. # One Source of Truth Forget the loudest voice in the room. We help you set up systems where decisions are made on real data, real feedback, and real results. Everyone’s on the same page, driving towards the same goal. # Closing the Loop Feedback isn’t just about collecting it; it’s about acting on it. We show you how to close that loop, so nothing valuable falls through the cracks. # Bottom Line Growing your business is about making sure your vision comes to life in the best way possible. Your company is unique, and so is the plan we'll create with you. It's not about giving you a cookie-cutter solution—it's about crafting a way forward that fits your business and carefully considers how to effectively manage the change so your people are on board. # Harnessing Generative AI for Software Development: Our Experiments with automated testing Source: https://www.propelventures.ai/blog/generative-ai-for-enhanced-software-development-03 Meta: 2024-02-15 · Paul Greenwell Successfully using Generative Ai for automation testing Welcome back to our series on how Propel Ventures is pioneering the use of Generative AI into software development to boost productivity and enhance quality. In our previous blogs, we discussed the foundational steps and early successes in adopting Generative AI for requirements development and generating code for UI components. Today, we delve deeper into our journey, sharing insights from our recent experiments with GitHub CoPilot and the transformative impact they've had on our development process. # The Evolution of AI in Development at Propel At Propel, our commitment to innovation has led us to explore the vast potential of off-the-shelf AI products in software development. Our experiences have been a mix of challenges and triumphs. Initially, while these AI tools showed promise in improving outcomes, their rigidity and the significant effort required for customization presented hurdles. Despite these obstacles, our pursuit of efficiency and quality has borne fruit, particularly with the use of GitHub CoPilot. # GitHub CoPilot: Living up to the hype A natural choice to begin our code generation journey was GitHub CoPilot, and we were delighted to discover two of its extensions to be incredibly valuable. 1. The IntelliSense-like Extension: This early tool offered a glimpse into the future, providing code suggestions based on comments or the project's context. It proved invaluable for autocomplete functionalities, streamlining the coding process. 2. The Copilot Chatting Extension: The true breakthrough came with this second extension. It transformed our interaction with AI, allowing us to communicate more effectively with the copilot. This extension has been instrumental in generating high-quality unit tests for API controllers, business logic, and other complex components of our software, enhancing both efficiency and quality. # Test Driven Development with AI One of the most exciting aspects of our AI journey has been challenging traditional software development methodologies. One area where CoPilot proves its value is by transforming the conventional approach of writing code before tests and transitioning to Test Driven Development. Although Test Driven Development is not a new concept, it is rarely implemented in practice. However, with the aid of Generative AI, Test Driven Development becomes more natural and intuitive. By establishing unit tests or contracts as a priority and then utilizing AI to generate code that meets these specifications, we envision a software development process that is both more efficient and higher quality. # Propel's AI-Powered Code Generation Extension Inspired by the success of these GitHub extensions, we embarked on creating our own VS Code extension for code generation. By focusing on usability features like context menu integration and AI-generated file outputs, we've lowered the barrier to adoption for our team, facilitating a smoother transition from prototypes to production. # Looking Forward As we continue to explore the capabilities of Generative AI, our goal is to redefine the norms of software development. By flipping traditional methodologies on their head and embracing AI's potential, we believe we can unlock increasing levels of productivity and quality in our projects. Stay tuned for more updates as we further our journey into the future of software development with Generative AI. Propel Ventures remains at the forefront, pushing the boundaries of what's possible and sharing our learnings with the wider community. Thank you for following our series. Your engagement and feedback inspire us to keep innovating and sharing our experiences. Together, let's shape the future of software development. --- *This blog is part of a series exploring Propel Ventures' use of Generative AI in software development. Be sure to read the first two entries (Our Experiments with User Story Generation and Our Experiments with UI Code Generation) for more background and insights into our journey.* # Doubling Our Productivity: The Propel Ventures AI Revolution Source: https://www.propelventures.ai/blog/artificial-intelligence Meta: 2024-02-09 · Paul Greenwell At Propel Ventures, we're dedicated to pushing the boundaries of what's possible with technology. Recently, we've embarked on an ambitious journey to double our productivity by leveraging the power of internally developed AI tools. This goal, however, isn't just about speed—it's about enhancing the quality and efficiency of our work across the board. At Propel Ventures, we're dedicated to pushing the boundaries of what's possible with technology. Recently, we've embarked on an ambitious journey to double our productivity by leveraging the power of internally developed AI tools. This goal, however, isn't just about speed—it's about enhancing the quality and efficiency of our work across the board. The Challenge of Efficiency: The quest for heightened productivity led us to a pivotal question: How can we be twice as effective in our tasks? This question set the stage for an exploration into the integration of AI across our software engineering processes, transcending traditional tools to cover the entire development lifecycle—from requirements gathering and user story creation to development and testing. Our Approach: Our approach goes beyond conventional AI integration. We're not just using AI; we're innovating with it. By developing bespoke AI tools, we aim to not only expedite our processes but also to elevate the quality of our work and minimise the mundane aspects of software engineering. This holistic application ensures that every phase of project development benefits from AI-driven enhancements. Overcoming Resistance: Adoption of new technologies often meets resistance, and our journey was no different. Many of our seasoned experts were initially sceptical, doubting the necessity of AI tools given their own high levels of productivity and efficiency. However, the transformative power of AI became undeniable once they experienced firsthand the consistency and quality it brought to their work—particularly in tasks like user story creation, where fatigue can lead to decreased quality. Real-World Impact: The use of AI has proven to be a game-changer. In user story creation, for example, we've seen a 50% reduction in time spent, alongside noticeable improvements in quality. This is a testament to AI's ability to maintain high standards from start to finish, regardless of human factors like fatigue. Beyond the Headline: While the concept of being "2x faster" is compelling, it's crucial to consider the specifics of time spent on tasks and their frequency. Not every task's acceleration will have the same impact on our overall productivity. Consequently, we're also focusing on optimising meetings—often the biggest productivity drain—through AI for better note-taking, action item clarity, and agenda setting. Conclusion: At Propel Ventures, our mission to double productivity with AI is about more than just speed. It's about quality, efficiency, and transforming the way we work. By embracing AI, we're not just keeping up with technological advancements; we're setting new standards for what's possible in software development. To learn more about how Propel is helping engineering teams transition beyond Agile to a product-led approach and create market-resonant, business-driving products, feel free to contact us. We're eager to share more stories of how we've helped steer the course towards commercial success. # Can I Build it Myself? (with the help of tools & AI) Source: https://www.propelventures.ai/blog/ai-for-productmanagers Meta: 2024-02-06 · Paul Greenwell Can product managers build their own apps using low-code solutions and AI? The Chief Product Officer at Propel shares her experience and progress so far. I’ve been tinkering with an idea: Is it possible for product managers, or really anyone without much coding know-how, to create an app using low-code solutions or Gen AI? I decided to have a go. The idea is to create a tool product managers can use to self-assess their skills and competencies, and then provide them with a tailored development plan. ## Tools I'm Using ChatGPT: For Q&A along the way - and the Development Plan generator. Typeform: For the questions that product managers answer about themselves. Zapier: This ties the survey to ChatGPT without any coding. Outlook & Slack: To send out the finished plan. ## How'd it go? I started by building the survey in typeform, using the Propel Product Manager Capability Matrix as the base and asking the user to identify their level for each capability: - no experience - some experience - proficient - leading strength The matrix covers end to end PM capabilities from vision and strategy, to delivery to adaptive skills. It was then pretty easy to set up to zaps. I initially went off on a tangent when I asked Chat GPT how to “code” an integration.  It wrote a bunch of python and told me I needed to provide the API end points. Prompt fail... no code needed, I was able to create the ChatGPT prompt inside Zapier. First try results using GPT3.5 model and a fairly generic prompt: “review the survey and create a development plan with 3 focus areas and no more than 3 actions for each”. Output v1: "Based on the survey results, the two highest priority areas to develop in are Product Discovery and User Story Mapping & Requirements. Here are three actions to improve product manager capability in these areas: 1. Education:    - Enroll in a Product Discovery training course to learn about different research techniques, customer interviews, and how to identify user needs and pain points.    - Attend a User Story Mapping & Requirements workshop to understand how to effectively capture user stories, prioritize features, and define product requirements. 2. Experience:    - Assign product managers to cross-functional product discovery teams where they have the opportunity to practice and gain experience in conducting user research, validating assumptions, and exploring new ideas.    - Encourage product managers to actively participate in user story mapping and requirement gathering sessions, working directly with development teams and stakeholders to understand their needs and translate them into actionable stories.3. Exposure:    - Provide opportunities for product managers to attend industry conferences, workshops, or webinars focused on product discovery and user story mapping. This exposure will help them stay up-to-date with the latest trends, best practices, and tools in these areas.    - Facilitate knowledge transfer and collaboration among product managers by organizing internal knowledge sharing sessions or creating a platform for them to share their learnings and experiences in product discovery and user story mapping.By focusing on these areas and implementing these actions, product managers will be better equipped to drive successful product discovery efforts, effectively gather and prioritize requirements, and ultimately deliver valuable products that meet user needs." ## Round 2 Two small changes made a big difference. I switched to the GPT-4-1106-preview model and tweaked the prompt. Now, the tool talks directly to the product manager using "you" to make it feel more personal. I also made sure it could use advice from top industry experts (I named a few) and real, solid information from trusted sources. Output v2: "Thanks for completing the Product Manager Capability Assessment. Based on your survey results, it's clear that you've developed a strong proficiency in many key areas such as Product Roadmap, Product Discovery, User Experience, Agile Delivery Practices, and more. This is a great foundation! Now, let's build on that foundation and prioritize areas for growth. After reviewing the results, it looks like we should focus on Product Strategy, Product Vision, and Fluency with Data & Measurement to enhance your capabilities further. Here's a 3-point development plan tailored for you: **1. Product Strategy Development**:    - *Read and Learn:* Delve into "Inspired: How to Create Products Customers Love" by Marty Cagan, which can lay the groundwork for building effective product strategies.    - *Training Course:* Consider enrolling in a Product Strategy course at Reforge or similar platforms to get formal training and frameworks that you can apply directly to your work.    - *Mentorship:* Seek out a mentor or colleague who has extensive experience in creating Product Strategies to gain insights and practical advice. **2. Refining Product Vision**:    - *Workshop Participation:* Join more vision crafting workshops and take on a more active role. This hands-on experience will deepen your understanding and ability to craft compelling product visions.    - *Expert Insights:* Follow thought leaders like Teresa Torres and observe how they articulate and share their product visions. Engaging with their content can provide a clear model for effective product vision communication.    - *Collaborate and Practice:* Partner with a teammate who excels in product vision to collaboratively develop new product concepts, which can refine your thinking and articulation skills. **3. Enhancing Fluency with Data & Measurement**:    - *Certification Course:* Investing time in a data analytics certification course, perhaps through platforms like Coursera or edX, could greatly boost your data proficiency.    - *Project-Based Learning:* Take on a project where data analysis is key. This could mean leading a user research initiative that requires validating qualitative insights with quantitative data.    - *Cross-functional Partnering:* Work closely with your data science or analytics team to understand the metrics they use. Learning by doing alongside experts can be incredibly valuable. Remember, this journey is all about incremental improvement and continuous learning. Start with these development steps and adjust as you grow. Feel free to reply here or drop an email if you have any questions or need further guidance. Keep pushing the boundaries, Amy. Your progress as a Product Manager is only going to accelerate from here!" ## What I'll Try Next Use Hubspot to create the email with the goal of improving the poor formatting result I'm getting in Outlook. Add in the the option for users to specify desired areas of focus, then customise the development plan to plan to bridge the gap from current capability to their goal. # Propel & Iterate's Technology strategy meetup - "From Launch to Lift Off" Source: https://www.propelventures.ai/blog/technology-strategy Meta: 2024-02-01 · Paul Greenwell The event delved into three core areas: Understanding Tech Strategy: We will explore the concept of tech strategy, demystifying what it really means in today's fast-paced tech environment. Creating a Tech Strategy: This session aims to provide actionable advice on formulating a strategy that aligns with both business goals and technological capabilities. Implementing Tech Strategy: This part of the meetup will be particularly beneficial for engineering managers, offering insights into how to work effectively within the framework of a tech strategy. Last night's meetup event was a rare opportunity to learn from some of Melbourne's most experienced leaders in the field of software engineering and product management. Organised by Propel and Iterate, the session brought together industry experts Simon Raik-Allen, Tomas Varsavsky, and Dee Kulkarni to share their insights and experiences. Simon introduced the evening in his inimitable way and Tom kicked off his presentation by diving into the essence of what constitutes a robust tech strategy. He emphasised the importance of selecting an appropriate timeframe—neither too long nor too short—to avoid the allure of "sexy futurism" and instead concentrate on addressing the immediate, tangible challenges that businesses face. His discussion extended beyond mere technology or architecture, covering the crucial aspects of people and processes as well. Tom outlined a strategic approach to prioritising actions and sequencing them effectively, detailing who should do what and when. He also shared a compelling scale-up example from REA, illustrating how companies can 'launch' innovative strategies effectively within their operations. Dee, hailing from Sidekicker with significant experience at Redbubble, provided a concrete case study that brought theoretical concepts to life. She detailed her journey through a specific project, from the initial approach to the final outcomes, offering attendees a vivid glimpse into the real-world application of these strategies. Simon provided a neat contrarian view about a leading book on Technology Strategy and highlighted the shortcomings of the text, with clear guidance on how to fill the gaps where the textbook falls short...... and then there was lots of pizza and beer and drinks for everyone to have fun until the late evening. The evening was not just about sharing knowledge but also about fostering a community of like-minded professionals who are eager to learn, share, and apply new ideas to propel their companies forward. The insights shared by Tom, Simon and Dee highlighted the multifaceted nature of technology strategy, encompassing not only the technological components but also the human and procedural elements vital to any company's success. This meetup event was a testament to the value of community and the sharing of real-life experiences and strategies in the ever-evolving landscape of software engineering and product management. For those of us looking to enhance our understanding and application of tech strategies, the learnings from last night are a step forward in navigating the complexities of the digital world. We are looking forward to many more! You can see Tom's slides at this link You can see Dee's slides at this link You can see Simon's slides at this link A little bit of video is also available here and here Propel is Melbourne's premier product and software engineering consultancy, renowned for our expertise in software engineering services and also for its deep commitment to helping companies identify and build the RIGHT solutions to enter new markets and expand their existing market reach. To learn more about how Propel is helping engineering teams transition beyond Agile to a product-led approach and create market-resonant, business-driving products, feel free to contact us. We're eager to share more stories of how we've helped steer the course towards commercial success. # Have your Product Managers been relegated to mere order-takers? Source: https://www.propelventures.ai/blog/product-manager-role Meta: 2024-01-25 · Paul Greenwell Learn why Product Managers being reduced to mere order-takers is a common problem and the essential components of a successful Product Manager role. Discover how investing in these capabilities can transform organizations into hubs of innovation, empowerment, and strategic growth. I had lunch last week with some product folk I've worked with previously, and one of my friends shared her frustration that Product Managers in her company are simply order-takers. On reflection, this is a pretty common anti-pattern, where the Product Managers are effectively corporate waitstaff — merely ferrying directives from executives or business stakeholders to the engineering teams, without autonomy or empowerment. I have a few thoughts as to why this happens: Misunderstanding of the Role: There's often a lack of clarity about what product management entails, leading to reduced expectations and a narrowed scope of work. Capability of the Product Manager: Sometimes, the skillset of the product manager may not align with what is expected of the role, leading to a reliance on orders from above. Voice of the Customer: Product Managers may not be perceived as representing the customer's voice within the organization, diminishing their influence on product decisions. Internal Perspectives "We know best": A common assumption that internal voices always know best so you should just do what they say, especially in companies with a history of success. Authoritarian Leadership: Executives who favour a top-down approach tend to centralize decision-making and limit the creative input of their teams. This mindset leads to several negative outcomes, including: Disempowered Teams: When creativity is stifled, teams can become demotivated and disengaged. Wasted Potential: Highly skilled professionals are underutilised, spending their time on administrative tasks rather than strategic thinking. (Might also mean you are wasting $$$ on high PM salaries). Lack of Customer Centricity: With an internal and often short term focus,  making decisions without understanding the customer need can lead to waste and rework. So what do we see as essential components of a Product Manager role? Product Vision and Strategy Vision: They craft a customer-centric vision that motivates and guides the product's direction. Market Acumen: They maintain a keen understanding of market dynamics, competition, and opportunities for innovation. Strategy and Roadmapping: They formulate and communicate a strategic path to realize their vision, detailing short-term and long-term goals through effective roadmaps. Fluency with Data & Insight Product Discovery: They excel at identifying problems and collaborating to design solutions that meet customer needs and align with business objectives. Data Utilisation: They leverage data to inform decisions and track progress towards desired outcomes. User Experience: They have a basic knowledge of end-to-end product design, from user research to prototyping and testing. Technological Awareness: They stay informed about emerging technologies to harness trends that benefit product development. Product Delivery Agile Practices: They are comfortable with agile methodologies that emphasize customer feedback and iterative development. User Stories and Requirements: They can decompose complex processes into user stories, ensuring clarity and focus in development. Go-to-Market Value Proposition: They clearly communicate the unique benefits of their product. Market Execution: They are capable of planning and executing product launches, including marketing, pricing, and sales. Operational Readiness: They ensure that the infrastructure for support and training is in place before product launch. People Skills - The "Soft" Stuff Leadership & Influence: The ability to motivate and inspire the team toward achieving the shared goal. Gaining buy-in and driving initiatives forward. Communication: Crafting a story. Including verbal and written communication to foster collaboration and understanding. Adaptability: Capability to adjust quickly to change or new information. Comfortable in navigating uncertainty. Decision Making: Confidence in making informed, effective and timely decisions. The benefits of having such capabilities are profound: Inspirational Leadership: Product managers with a clear vision inspire their teams and guide the product with strategic decisions that resonate with long-term objectives. Innovation and Creativity: An environment that encourages experimentation and risk-taking ensures that the product stays relevant and competitive. User-Centric Focus: Continuous engagement with user feedback and market trends guarantees that the product evolves to meet genuine user needs. Team Morale and Collaboration: When product managers are visionaries, they create a collaborative atmosphere where every team member's contribution is acknowledged and valued. By investing in these capabilities, organisations can shift from a hierarchical, order-taking culture to one of innovation, empowerment, and strategic growth — essential ingredients for success. Or maybe I should just quote John Cutler whom when asked "What is the Product Manager's job?" in a linked in post a second ago simply replied "A successul product". Fair enough! # Harnessing Generative AI for Software Development: Our Experiments with UI code generation Source: https://www.propelventures.ai/blog/generative-ai-for-enhanced-software-development-02 Meta: 2024-01-22 · Paul Greenwell Successfully using Generative Ai for UI code generation In our previous article, Harnessing Generative AI for Software Development: Our Experiments with User Story Generation,  we explored the innovative ways Propel Ventures leverages Generative AI to generateuser stories. Today, we delve into the next phase of our AI journey: the automation of UI code generation, a leap towards translating high-fidelity designs into functional code seamlessly. # Experiment One: Off the shelf Tools Our first foray into AI-assisted code generation involved off the shelf tools such as CodeJet, Lofofy, and Builder.io. These platforms promise to convert Figma designs into usable code, ideally streamlining the development process. We embarked on this experiment with the hope of reducing the manual coding required to bring our UI designs to life. The reality, however, was a mixed bag. While these tools could indeed translate a design into code, the "one and done" output frequently missed the mark. The generated code often needed significant reworking to meet our coding standards, and the rigidity of the output offered little room for easy adjustments. Moreover, the integration with our existing frameworks and libraries was far from seamless, requiring a manual, time-consuming process to ensure compatibility. # Back to the drawing board Determined to find a more efficient solution, we reflected on our requirements. We needed a tool that minimised upfront work and better understood our design intent, allowing for integration with our chosen frameworks and libraries. With these criteria in mind, we decided to look at a more flexible and general AI solution, leading us to our second experiment. # Experiment Two: GPT-4 Vision Preview Our second experiment shifted towards the cutting edge of AI technology: the GPT-4 Vision Preview. This AI model promised to understand and interpret high-fidelity images exported from Figma, offering a more intuitive approach to code generation. We started with a simple Python script to feed our Figma exports into the AI. The results were astonishing. With carefully crafted prompts, we instructed the AI to generate TypeScript code using React.js and the Material-UI component library, focusing on producing well-structured, maintainable components. The AI’s output was impressively accurate, requiring far less tweaking than the code from traditional tools. By refining our prompts, we could direct the AI to include extension points for custom logic and to adhere to specific library versions, ensuring the code worked right out of the gate. Our success with GPT-4 Vision was so impressive that we created our own Visual Studio Code extension. This allowed our team to generate TypeScript code directly from JPG exports, significantly accelerating our development process. Figma on the left, generated code on the right # The Future of UI Code Generation at Propel This breakthrough with GPT-4 Vision has paved the way for a more integrated and efficient code generation process at Propel. It represents not just a step, but a leap forward in our continuous quest to refine and enhance our development workflows. Our experiments have led us to an important realisation: while off-the-shelf products offer convenience, they currently lack the maturity to fully understand and convert our UI designs into code effectively. However, the capabilities of advanced AI models like GPT-4 Vision have not just met but exceeded our expectations, demonstrating that with good prompting describing your technical environment, GPT 4 has an impressive understanding of design and code generation. As we continue to explore the frontiers of AI in software development, we invite you to join us on this exciting journey. The future is bright, and at Propel Ventures, we’re just getting started. Stay tuned for more insights as we propel forward into the next generation of software development. # Harnessing Generative AI for Software Development: OUR Experiments with User Story Generation Source: https://www.propelventures.ai/blog/generative-ai-for-enhanced-software-development-01 Meta: 2024-01-17 · Paul Greenwell Discover the power of a product-led engineering as the next lever of transformation of your engineering team. We at Propel Ventures are fully embracing the power of Generative AI to revolutionize our work processes. With great success in our marketing and Product Strategy teams, we are now embarking on an exciting journey to integrate Generative AI into our software development lifecycle. This comprehensive blog series aims to share our one-of-a-kind experiences, highlighting how these advanced tools can significantly enhance productivity and quality across all stages of development. To begin our exploration, we carefully identified the key stages of development – discovery, planning, design, development, testing, deployment, and support – and pinpointed where AI could bring about transformative changes. This first blog focuses on our experiments with user story generation. # Experiment 1: The Quest for AI-Generated User Stories We launched our first experiment with a focus on user story generation. The goal was to automate the creation of detailed, actionable user stories that could guide our development teams more efficiently. Approach: Using ChatGPT, we initiated a dialogue about our project, generating a series of questions. Through this interactive process we crafted a comprehensive one-pager that encapsulated the essence and scope of the project. This document became the foundation for breaking down project milestones and deriving specific tasks. Our ultimate ambition was to transform these derived tasks into meaningful, actionable user stories that could guide our development teams more efficiently. Challenges and Lessons Learned: This process was not that successful. We observed that the quality of outputs varied as the interaction with the AI became longer. This necessitated frequent redirection to keep the AI on track. The process itself was quite labor-intensive, requiring constant tweaking of the conversation to achieve desirable results. In comparison to the traditional method of hand-writing user stories, this approach did not yield a satisfactory return on effort. Additionally, the single conversation was highly focused on a specific purpose and could not be reused to gain other insights about the project. Nevertheless, the experiment provided us with valuable insights and hints as to the next experiment. Experiment 2: Customisation for Greater Precision Building on our initial learnings, we ventured into our second experiment with a more tailored approach. Approach: We developed a customised GPT specifically designed for our project using OpenAI's ChatGPT Builder. This model was preloaded with detailed project information, including a one-pager, milestones, and a user story template. The aim was to streamline the AI's understanding and enhance the relevance of its outputs. Outcomes: The outcomes were remarkably improved. The customized GPT model efficiently produced user stories that were not only precise but also contextually relevant. The setup process required much less effort and yielded measurable gains in productivity. This approach not only accelerated the process and improved the quality but also unlocked new possibilities, such as creating summaries that are valuable in client communications. # Reflecting on the Experiments Our journey with these two experiments highlighted the importance of experimentation and customisation in leveraging Generative AI tools. The Road Ahead Our experiments with Generative AI in software development have been enlightening. While challenges remain, the potential benefits are clear. As we continue to integrate these tools into our workflows, we aim to further refine their application, ensuring they contribute meaningfully to each stage of the software development lifecycle. Next in the Series Stay tuned as we delve deeper into other stages of development, sharing our experiences and learnings in using Generative AI for development, testing, and beyond. # Product-Led Engineering - Better Results Than Agile Alone Source: https://www.propelventures.ai/blog/product-led-engineering-agile Meta: 2024-01-12 · Paul Greenwell Discover the power of a product-led engineering as the next lever of transformation of your engineering team. In the past two decades, Agile methodologies, notably promoted by Thoughtworks, have been the standard for enhancing software engineering's productivity and reliability. However, as a product and business manager, I've observed significant shortcomings in companies' Agile implementations. You can read my previous comments here. Often, theory overshadows practice. For example, team members frequently demand empowerment and autonomy but fail to assume the necessary responsibility for delivering tangible customer and business outcomes, resulting in a disconnect between 'doing' Agile and 'being' Agile. Paul discussed this in detail in this blog post last year. Large consulting firms have contributed to this issue, imposing a rigid, theoretical Agile framework that hinders rather than helps, leading to what I term 'agile wokeness.' This approach has proven detrimental to many companies, and Propel Ventures is often called upon to remedy these 'agile gone wrong' situations after large consulting firms have done their damage. Propel Ventures collaborates with leading Australian software development companies, such as Papercut, Netwealth, ReadyTech, Nuix, and MYOB. Our goal is to guide them beyond Agile, towards a more optimized phase of their engineering teams towards product-led engineering. This post-Agile approach, rooted in Propel's five pillars of product-led engineering, ensures that engineering efforts are not only efficient in software development but also effectively aligned with market needs and business values. This strategy integrates Agile principles with a focused, product-centric mindset, driving companies towards greater operational excellence and innovation. McKinsey's recent article, "The Bottom-Line Benefit of the Product Operating Model", aligns with and re-iterates Propel’s product-led engineering theory. The article stresses the significance of a mature product and platform operating model in enhancing business performance. The key insights from the article include the importance of a mature product operating model for performance. At Propel, we're actively embedding our five pillars of product-led engineering success into our client's processes, specifically: To learn more about how Propel is helping engineering teams transition beyond Agile to a product-led approach and create market-resonant, business-driving products, feel free to contact us. We're eager to share more stories of how we've helped steer the course towards commercial success. # Product-Led Engineering, the way to go. Need Proof? Source: https://www.propelventures.ai/blog/product-led-engineering Meta: 2024-01-10 · Paul Greenwell Discover the power of a product-centric culture in driving business success. There's something exciting about seeing numbers that confirm what you've been seeing in the field. At Propel, we've noticed a trend that's now backed by hard data from a McKinsey Report. Simply put, companies that really have their act together when it comes to product-led engineering are not just a little ahead—they're leaps and bounds beyond their competition. We're talking about a whopping 60% higher returns to shareholders and a 16% bigger slice of operating margins compared to those trailing behind. The report zeroes in on a product-led mindset as the secret for achieving exceptional business outcomes and the most engaged customers. And while it seems obvious that culture and talent management is strongly correlated to innovation, I was surprised to see that tooling was even more so. This isn't just about the platforms that help capture ideas or manage the flow of work; it extends to embracing Generative AI, to accelerate generating code, translating it, creating documentation, and testing it with an efficiency that would have been unimaginable just a few years ago. Where to Begin? The research points to a handful of starting blocks: Define how your product team works together with clear roles and responsibilities. Make sure what they're working on aligns with the big-picture business goals. Fund projects based on progress toward outcomes. Manage technical debt — make decisions today that you will be thankful for tomorrow. Choose tools that nurture a product culture — customer centred, link to vision and strategy, encourage experimentation and learning. While these are all important, I think there's a bit too much focus on the process and not enough on the destination. At Propel, we see these 5 foundational pillars in place at the most successful product organisations: A vision that paints a picture of the change you want to bring into the world. A strategy that maps out the journey to that vision. A team organization that's all about delivering value. Roadmaps tied to outcomes you're aiming for. Success metrics that everyone can rally behind. Begin with a vision that reflects the change your product aims to make in the world over the next 3-5 years and chart a course to realise it. Structure teams around delivering value and construct roadmaps that are outcome-oriented. It's not just about having a process; that's the easy bit. It's about where you are heading. And remember, if you want people to follow a process, you need to engage them in defining and implementing it. # Cutting Quality Corners Can Allow You to Go Faster, Until It Doesn't Source: https://www.propelventures.ai/blog/cutting-quality-corners-can-allow-you-to-go-faster-until-it-doesnt Meta: 2023-12-01 · Paul Greenwell Quality, Speed, Software Engineering, Product Success This last six months I have had several Technical Due Diligence and Consulting engagements where I have encountered a common problem being experienced by the product companies, the race to market trumping the pursuit of quality. It's a common scenario: deadlines loom, and the pressure mounts, leading teams to sideline quality practices for the sake of speed. But this approach, while seemingly advantageous in the short term, often leads to significant setbacks in the long run. # The Sacrifice of Quality for Speed in Software Engineering The question arises: why are software engineering quality practices frequently sacrificed for speed? It's not uncommon to witness even the most fundamental aspects of quality practices, like automated unit and component testing or static code analysis tools, being overlooked in many organisations. The temptation to skip these steps is understandable. In the early stages of product development, with a small team and a manageable codebase, manual testing seems sufficient, and development is primarily focused on delivering the next feature. This approach can indeed be faster in the short term, as cutting corners allows for rapid advancement. However, as highlighted in an insightful piece on Better Programming, the lack of quality practices is a temporary fix that soon reveals its flaws. # The Tipping Point of Quality Neglect The pendulum swings quickly. Organisations, especially those in the scale-up phase, soon encounter the drawbacks of neglected quality practices. As teams expand and the codebase grows, new members lack historical knowledge of the project. Additionally, there's an increased need to revisit and refine existing features based on customer feedback and requirements of new customer cohorts. This scenario marks a tipping point. Firstly, there's an uptick in defects, leading to a surge in unplanned work. This not only diverts resources from new development but also imposes a 'context-switching tax' on teams, further decelerating progress. This situation is well-described in an article by Blackmill, highlighting the paradox where the pressure to maintain pace inadvertently fuels further corner-cutting. Secondly, developers become wary of working in certain code areas. Project estimates balloon, timelines extend, and the cost of features escalates due to the increased need for manual testing. This cycle of cautious development and extensive testing ensures that the initial gains made by skipping quality checks are lost. # Technical Debt: The Accumulated Cost of Cutting Corners One cannot discuss quality in software engineering without addressing technical debt. As elucidated in both the Better Programming and Blackmill articles, technical debt accumulates when quality is sacrificed for speed. This debt, often invisible in the early stages, compounds over time, eventually manifesting as a significant hindrance to development velocity. # The Role of Modern Tools and Early Implementation of Quality Practices In this landscape, new tools like GitHub Copilot offer a beacon of hope. They can expedite the creation of robust automated testing, which, if implemented early in a project, can stave off the inevitable slowdown. Incorporating such tools from the outset not only maintains development pace but also ensures a sustainable and scalable codebase. # Conclusion: A Balanced Approach for Long-Term Success In conclusion, while the allure of speed by cutting quality corners is tempting, it's a strategy fraught with risks. The initial gains are quickly overshadowed by the long-term consequences of increased defects, technical debt, and slowed development. A balanced approach, one that integrates quality practices from the onset and leverages modern tools, is essential for sustainable and successful software development. As we embrace this balanced path, we can ensure that our pursuit of speed does not become a race to the bottom, but rather a journey towards lasting efficiency and excellence. # DORA Metrics: Necessary but Not Sufficient for PRODUCT Success Source: https://www.propelventures.ai/blog/dora-metrics-necessary-but-not-sufficient-for-product-success Meta: 2023-11-21 · Paul Greenwell DORA, Software Engineering, Product Success As a proponent of DevOps Research and Assessment (DORA) metrics, I've long appreciated their ability to enhance engineering practices within development teams. These metrics – including Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service – offer significant benefits in fostering a culture of efficiency and continuous improvement. They play a crucial role in streamlining development processes and improving operational performance. However, recent experiences with various clients have highlighted a critical oversight in relying solely on DORA metrics. While development teams often take pride in their performance as measured by these metrics, their achievements may not resonate with the broader business. The reason? DORA metrics excel in promoting sound engineering practices but fall short in assessing the actual value delivered to the business and its customers. Take, for instance, a case with one of my clients. The engineering team made commendable strides in reducing delivery frequency from over three months to a consistent two-week cycle. Yet, this achievement was met with lukewarm reception from the business. Why? Because, despite the faster release cycle, the business didn’t perceive any significant value in these regular updates, especially considering the product was a desktop application where updating carries more overhead than a SaaS product. After three months of bi-weekly releases, there was still no substantial value delivered that justified the update effort. This scenario underscores a crucial point: while DORA metrics are excellent for enhancing engineering practices, they are not comprehensive enough to drive a team towards overall business success. They need to be complemented by metrics that focus on delivering customer and business value. It’s about striking a balance between technical efficiency and delivering tangible, valuable outcomes to customers. In conclusion, while DORA metrics are an indispensable part of modern software development, they should not be the sole focus. Aligning them with metrics that measure customer satisfaction and business value is crucial. This balanced approach ensures that while engineering practices are refined, the end goal always remains the delivery of real value to the business and its customers. # Propel's Generative AI Artistry Source: https://www.propelventures.ai/blog/aiartistry Meta: 2023-11-21 · Paul Greenwell Cutting-edge AI image generation model that transforms imagination into digital reality. We at Propel Ventures are thrilled to announce our latest endeavour in the realm of artificial intelligence: a cutting-edge AI image generation model that transforms imagination into digital reality. ### Our Journey with 'Draw Things' Our journey began with "Draw Things", a remarkable program available for free on the Apple App Store. This tool laid the foundation for training our bespoke model. ### Training Process We embarked on an exciting process, feeding our model a plethora of spaceman images. This wasn't just about data input; it was about teaching the AI the nuances of cosmic aesthetics and the versatility of space-themed imagery. Adjusting the parameters with precision, we initiated the training phase. ### The Magic of Waiting Patience played a key role in our journey. Surprisingly the model took five days for our machines to diligently work, learning and evolving to create something exceptional. ### The Results And the results? They're out of this world! Imagine a spaceman – the quintessential Propel Spaceman – in scenarios you'd never expect: Riding a motorbike with the cosmos as his backdrop. Galloping on a horse, melding the past with the future. Strolling through the romantic streets of Paris. Catching waves, surfing under a starlit sky. Each image is a testament to the capabilities of our AI model, reflecting our commitment to innovation and creativity. What This Means for You This advancement isn't just about us. It's about how we at Propel Ventures can help you envision and realise your digital dreams. Our model signifies a leap towards a future where imagination knows no bounds. Stay tuned for more updates and explorations in AI-driven artistry. # Let's Chat About That Sneaky Feeling of Doubt: Imposter Syndrome in Product leaders Source: https://www.propelventures.ai/blog/product-leaders Meta: 2023-11-03 · Paul Greenwell Explore the common signs, learn practical strategies to overcome self-doubt, and follow tips to build confidence in your role. Embrace your instincts and make a lasting impact in your organization. Let's start with a story about Alex... Alex's first day as Head of Product was tinged with the fresh excitement of new beginnings. Walking into her first team meeting, she was greeted by eager faces, each ready to embark on a journey led by Alex. Yet, as she laid out their vision for a product-led transformation, a whisper of doubt crept in. "Should I really shake things up from the get-go?" Alex wondered, confidence wavering. Deciding to proceed with caution, Alex gently nudged the team towards a product-centric approach, but stopped short of the bold overhaul she had initially believed in. Time ticked by, and the team made steady progress. However, a certain something was missing. It was during a casual team feedback session that the truth surfaced. The team craved the very transformation Alex had hesitated to implement. Mixed emotions flooded Alex; there was an undeniable sense of validation, yet it was laced with a hint of regret. "If only I'd trusted my instincts," she thought. This moment, though, was far from a defeat. It was a pivot, a catalyst for change. Emboldened, Alex championed the product operating model with renewed vigour, fostering an environment where a product mindset was not just encouraged but celebrated. Overcoming the initial imposter syndrome wasn't easy, but it was a journey that bore fruit. By pushing past her comfort zone and advocating customer centric ways of working Alex not only propelled the startup to new heights but also solidified her confidence as a leader. Where once hesitation lingered, now stood a beacon of conviction and results. Alex's ideas and leadership didn't just whisper—they resonated with the unmistakable clarity of success. Ever feel like you're just winging it in your leadership role or as a product manager? At any moment, someone's going to tap you on the shoulder and say, "We're onto you!"? If you're nodding along, you've got company. That's imposter syndrome trying to crash the party, and it's more common than you think, especially among folks steering the ship in product development and management. So, What’s This Imposter Syndrome Thing Really Like? Imagine you're at the helm, making decisions, leading teams, and somehow, there's this nagging voice in your head. It whispers, "Do you really know what you're doing?" or "You just got lucky this time." Imposter syndrome is like that uninvited guest who doubts your skills, downplays your achievements, and loves to remind you of that one time things didn't go as planned. How Does It Show Up in Your Day-to-Day? Working Overtime for No Reason: You might catch yourself burning the midnight oil, trying to prove you're not just making it up as you go. Playing It Too Safe: Scared of slipping up? You might avoid taking bold steps or trying out fresh ideas, just to stay in the safe zone. Brushing Off Compliments: When someone says, "Great job!" do you think, "They're just being nice"? That's imposter syndrome talking. Biting Your Tongue: Got an idea? A hunch? But you clam up because, "What if I'm wrong?" Yep, that's another classic sign. Chasing Perfection: Setting the bar sky-high for yourself? That's imposter syndrome making you think anything less is not good enough. Alright, So What Can You Do About It? Give It a Nod: First off, recognize that feeling like an imposter sometimes is perfectly normal. You're definitely not alone in this. Flip the Script: Instead of letting those doubts run wild, try talking back to them with some positive vibes. Replace "I'm not cut out for this" with "I'm here because I earned it." Keep a Brag Book: Stash away all the nice things people say, the wins, the milestones. On a rainy day, flip through it to remind yourself of your rockstar moments. Get Real With Expectations: Perfection is a myth. Embrace the mess-ups; they're just stepping stones to getting better. Spill the Beans: Talk it out with your peers or find a mentor. Chances are, they've been in your shoes and have some wisdom to share. Toast to the Tiny Triumphs: Got through a tough meeting? Nailed a presentation? Celebrate those! It's the little victories that build up your confidence. Wrapping It Up: Dealing with imposter syndrome is like learning a funky dance. It might feel awkward at first, but once you get the hang of it, you'll be grooving along just fine. Remember, your journey as a leader or product manager is uniquely yours, and it's lined with way more wins and smart moves than those pesky doubts would have you believe. Keep your chin up, and don't let that imposter syndrome tune out your own success soundtrack! 🎶 # A Product Vision is the key to engaged teams Source: https://www.propelventures.ai/blog/productvision Meta: 2023-10-25 · Paul Greenwell Discover how a strong product vision can transform your team's engagement and drive innovation. This blog explains the pivotal role a clear and impactful product vision plays in fostering team motivation, customer-centric alignment, and meaningful work, all while keeping pace with industry trends. Learn why it's not just a goal, but a guiding North Star that catalyzes collaboration and propels your product towards success. A strong product vision doesn't just outline a future goal; it establishes the direction for the team, fueling motivation, collaboration, and alignment. But how exactly does a well-articulated vision foster team engagement? ### It's Not About You. It's About the Change At the heart of a compelling product vision is the understanding that it's not about the individual or even the company – it's about the change you want to bring to the world. It's the impact, the difference you'll make that becomes the North Star. When a team understands that they are working towards a cause they believe in, passion and commitment is ignited. ### The Customer at the Forefront A product vision ensures everyone's efforts align with the end user's needs. As a North Star, it guides decision toward a common goal – serving the customer in a way that works for the business. This alignment fosters a sense of purpose. When a team knows that their work directly impacts their customer's life, they're more likely to be invested in their roles and take pride in their contributions. ### Making Work Meaningful When a product vision is articulated and shared effectively, it can clearly showcase the 'why' behind the 'what.' It's not just about building a feature or launching an update; it's about knowing that what you deliver contributes to a larger purpose, making it more meaningful. ### Staying Ahead with Industry Trends A future-focused vision means that the team is always on its toes, researching and leveraging relevant industry trends and technologies. This proactive approach ensures the product remains innovative and relevant, fostering a culture of continuous learning and growth. ### Providing Clarity to Engineering and Beyond From the engineers to the marketers, when there's clarity about the direction, it paves the way for proactive planning. For instance, the engineering team can anticipate needs and design an architecture that's robust and scalable, ensuring that the product remains resilient as it evolves. ### So What? A well-thought-out and articulated product vision is more than just a statement. It drives the roadmap, it inspires, and forges cross team alignment. As Marty Cagan rightly pointed out, "An inspiring and compelling product vision serves so many critical purposes that it is hard to think of a more important or higher-leverage product artifact." When teams understand and buy into this vision, engagement lifts with vested interests taking a back seat, replaced by a collective focus on achieving a shared goal. # Why is no-one doing Product Discovery? Source: https://www.propelventures.ai/blog/product-discovery Meta: 2023-10-25 · Paul Greenwell Explore the importance of product discovery in the development process and why it's often overlooked. This blog delves into common misconceptions and pressures that lead companies to bypass this critical phase, highlighting the potential pitfalls and advocating for a discovery-first approach to ensure success and user satisfaction in a competitive market Product discovery is an invaluable phase in the product development process. It's all about uncovering what users truly want and ensuring that development resources are directed towards solutions that genuinely address these needs. Yet, it's baffling to observe that many companies skip or underutilize this step. Here are my thoughts about why this might be the case. ## 1. Mistaking Assumptions for Facts Many teams believe they already know what the user wants. Maybe they've been in the industry for decades or have anecdotal evidence from a few customers. The problem? These assumptions can be misleading and don't reflect the broader market. ## 2. Pressure to Move Fast There's often pressure to get products to market as quickly as possible. Product discovery can be seen as a time-consuming detour, even if it ensures a more successful product launch in the long run. The problem? Without validation, you are likely to need to do rework or a complete overhaul. ## 3. Lack of Awareness or Understanding Some teams might be unaware of the product discovery process or may not understand its value fully. They might confuse it with market research or see it as just another brainstorming session. The problem? Decision making down the line may be slower without stakeholder alignment. ## 4. Resource Constraints Product discovery requires time, effort, and sometimes even money. Companies running on tight budgets or schedules might decide to bypass it, often to their detriment. The problem? When you're not sure about what needs to be built, it's hard to allocate resources effectively. ## 5. Fear of Negative Feedback Engaging in genuine product discovery can expose flaws in a product idea or indicate that there's no real market for it. Some teams might avoid discovery out of fear of such revelations, opting for blissful ignorance instead. The problem? You may miss out on uncovering even better ideas. ## The Path Forward Avoiding product discovery is a perilous approach. While it might seem like a time-saving decision initially, it can lead to wasted resources and failed product launches in the long run. Embracing a discovery-first mentality not only ensures better products but also fosters a deeper connection with the user base. As the world becomes more competitive, understanding and meeting genuine user needs is a crucial differentiator. Shake off the myths and reservations about product discovery and place it at the heart of how you create and enhance products. # Remote Product Managers Are Losing Vital Skills Source: https://www.propelventures.ai/blog/remote-productmanagers Meta: 2023-10-23 · Paul Greenwell Are remote product managers sacrificing essential learning and skill development? Our latest blog post delves into the limitations of remote work in the context of product management, exploring what's lost when mentorship and hands-on experience are sidelined The mass shift to remote work has been a double-edged sword for many, including product managers. While the flexibility is unparalleled, we are definitely sacrificing essential learning and skill development. ## The Lost Art of Apprenticeship In trades like plumbing and carpentry, apprenticeship is non-negotiable. Newcomers work alongside seasoned experts to learn the ropes, benefiting from years, if not decades, of accumulated knowledge. It's hands-on, it's gritty, and it’s real-world education. This kind of apprenticeship is what product managers are missing when working remotely. ## Why Flight Hours Matter In aviation, pilots often discuss their total flight hours, a metric that goes beyond mere experience. It’s a testament to their practical skills, situational awareness, and the nuanced understandings that can only be acquired through active practice and mentorship. Likewise, the day-to-day grind alongside experienced product managers equips newcomers with a range of soft and hard skills that Zoom calls can never replicate. ## The Limits of Virtual Training Sure, you can attend webinars, virtual workshops, and online courses. But can these replace the experience of troubleshooting a live issue with a veteran product manager by your side? The answer is a resounding no. When I think about the biggest increases in my own product management capability, the first thing that comes to mind is a list of names of the people I watched a learned from. They had the flying hours and I was able to accelerate my learning by seeing them in action with their experience under their belt. ## The Cost of Convenience The convenience of remote work comes at the expense of intellectual growth and skill enhancement. You might be ticking off tasks, but are you really advancing in your craft? ## Conclusion The move to remote work poses serious questions about the future of skill development in product management. As comfortable as your home office may be, it's worth asking: what invaluable lessons are you missing out on? Stop dialling it in and ask yourself - who should I be working alongside and watching and learning from their every action and reaction and decision? # The Role Clarity Myth: Is It Stifling Your Team's Potential? Source: https://www.propelventures.ai/blog/roleclarity Meta: 2023-10-23 · Paul Greenwell Is role clarity stifling innovation and collaboration in your team? Our latest blog post challenges the conventional wisdom surrounding role clarity, exploring its impact on trust, capability, and high-performing teams. I meet with people working in large companies on a daily basis and too often hear complaints about 'role clarity' - I always come away confused about the remark. The concept of role clarity has been lauded as a cornerstone of effective teamwork, particularly in large organisations. But is it always beneficial, or could it be a double-edged sword? I think it is usually a big red signal of something more sinister at play. ## Role Clarity in Large Organisations I am just going to lay it out there - in big companies, role clarity often becomes a mechanism for delineating work, sidestepping responsibility, and even laying blame. It’s a safe haven in environments where trust is low and teamwork is more about fulfilling one's predefined role than truly collaborating. ## The High-Functioning Team Paradox In high-performing teams, the boundaries between roles aren't just blurred—they're actively crossed. This isn't a byproduct of disorganisation; it’s a feature of a healthy, collaborative environment. Members of these teams are T-shaped, meaning they have depth in their own domain but sufficient knowledge across other disciplines to constructively challenge and collaborate. ## The "Stepping on Toes" Complaint When you hear someone complain about team members stepping on their toes, it's worth investigating the underlying issue. Is it truly about role encroachment, or could it be a symptom of deeper issues like lack of trust or capability? ## The Value of Multidisciplinary Skills Look at figures like Elon Musk, who constantly crosses boundaries between engineering, product, design, and marketing. The ability to understand, question, and even challenge decisions across different fields can be an invaluable asset. ## Rethinking Role Clarity Next time you hear complaints about lack of role clarity or people stepping on each other’s toes, dig deeper. Examine whether trust or capability issues might be the real culprits stifling collaboration and productivity. Encourage team members to be flexible, multidisciplinary, and, in the best sense of the word, "dangerous." ## Conclusion Role clarity has its place, especially in large, low-trust environments. But in a truly collaborative setting, rigidity around roles can be more of a hindrance than a help. In high-functioning teams, responsibilities bleed healthily across roles, and that's not just okay—it's essential for achieving the best outcomes. # The Next-Generation Skills of a Product Manager in the AI Era Source: https://www.propelventures.ai/blog/nextgenerationproductmanager Meta: 2023-10-23 · Paul Greenwell Learn how the role of a product manager is evolving in the age of AI. Discover the next-generation skills that are becoming indispensable in modern product management. In a world increasingly dominated by Artificial Intelligence (AI), I am commonly asked how product management is changing. The essence is that product managers are no exception to the wave of change and in fact there are a bunch of things that now seperate the next generation of product managers from those who were good per the old ways of working, and need to switch up their game. Essentially, the advances in AI are not just changing the product landscape; they're also altering the skill set needed to excel in product management. Let's dive into what sets next-generation product managers apart from their traditional counterparts. ## 1. Using AI to Expedite Concept-to-Prototype Traditional product management often hinges on lengthy discussions with UX and engineering teams to transform a concept into a viable prototype. The next-gen product manager leverages AI tools to accelerate this phase. These tools can perform tasks like market research, design suggestions, and even code generation, enabling a faster transition from idea to prototype. ## 2. Streamlining Requirements with AI Defining clear, actionable requirements has always been crucial in product management. The next-generation product manager uses AI to automate this process, ensuring a much more efficient use of time and resources. Advanced algorithms can help sift through large amounts of data, drawing insights that can refine product requirements more effectively than ever before. ## 3. Lifelong Learning and Teaching In a rapidly evolving tech landscape, continual learning is indispensable. Next-generation product managers don't just learn; they actively teach others, sharing insights about new technologies and methodologies. This not only keeps the team updated but also fosters a culture of continuous improvement. ## 4. Mastering Stakeholder Management Excellent communication skills are a cornerstone of effective product management. The next-generation product manager takes every opportunity to refine these skills, whether it's through brown bag lunches, workshops, or presentations. They constantly engage with senior leaders, making an effort to not just convey their ideas but also to ask, "How can I help?" ## 5. Proactivity in Special Projects Seizing opportunities for special projects shows initiative and can lead to significant career growth. Next-generation product managers are always on the lookout for these projects, and they’re proactive about offering their skills. Rather than waiting for opportunities to come to them, they go to senior leaders and ask, "How can I help?" ## Conclusion As the capabilities of AI continue to grow, so too must the competencies of product managers. By adapting to these next-generation skills, product managers will not only stay relevant but also become indispensable assets in the new AI-driven landscape. What are you doing to keep up with the game? # Resolving Ethical AI and questions about Traceability Source: https://www.propelventures.ai/blog/ethical-ai Meta: 2023-10-13 · Paul Greenwell Explore insights from Product and Technology leaders on ethical and trustworthy AI. Uncover challenges, best practices, and new plugins for enhanced traceability. Last month, we convened dinners in both Melbourne and Sydney, uniting leaders in Product and Technology. The focus? The immense potential and ethical implications of generative AI. The enthusiasm was palpable, but it was matched by serious discussions on the ethical dimensions of AI. For instance, consider the potential of Chat GPT in streamlining internal investigations. Upload all the documentation, synthesise and generate a recommendation. Sounds productive in theory, but would it be fair, would context be factored in and could you trace back to evidence? While the efficiency gains are impressive, questions around fairness, context, and traceability remain unresolved and critical. Towards Trustworthy AI In 2018, the High-Level Expert Group on AI in Europe established a set of guidelines aimed at ethical and lawful AI deployment. Updated in 2021, these guidelines have crystallised into seven core requirements for "Trustworthy AI": Innovations in Traceability The complexity of this subject is not easily distilled into a single post. However, emerging tools like the Web Search AI Plugin and PortfolioPilot Plugin offer mechanisms for enhanced traceability and real-time data access. In conclusion, the key lies in achieving a balanced approach: leveraging AI's transformative capabilities while maintaining a steadfast commitment to ethical, transparent, and secure practices. The journey is as crucial as the destination in shaping a responsible AI landscape. #AI #EthicalAI #TrustworthyAI #GenerativeAI #Innovation # The Balancing Act of Product Operations Source: https://www.propelventures.ai/blog/productoperations Meta: 2023-10-13 · Paul Greenwell Delve into the intricacies of scaling product management functions effectively, balancing process and innovation, and fostering a culture-first approach. Learn about the 5 pillars of product architecture and the frameworks that guide successful product development. Plus, get expert insights on planning and prioritization strategies that align with organizational goals. Whether you're a startup scaling rapidly or an established company seeking to refine your product operations, this blog provides valuable principles and practical tips for success. There's lots being written about Product Operations these days, but what does it all mean? In the words of Melissa Perri "Product Operations is the discipline of helping your Product Management function scale well. Surrounding the team with all of the essential inputs to set strategy, prioritize, and streamline ways of working." I think the use of the word "scale" is key here. We work with a lot of clients who have scaled quickly and either not added enough process which has resulted in products mutating and becoming unmaintainable, or have overdone it and stifled innovation. The reality is, Product Operations is a balancing act and needs to work for your organisational context. As always, culture first, process second. Understand the problem you are looking to solve, engage people in the solution and communicate, communicate, communicate. We don't advocate (at all!) for slamming in frameworks like SAFe or cookie cutting what worked for one organisation into another. Focus on principles while also ensuring there is the right level of transparency to give confidence up, down and beyond the organisation. PRODUCT ARCHITECTURE Have you got the 5 pillars in place? 1. A Product Vision that defines the aspirational future state of the product organisation and Product Prinicples that inform the nature of the product you are creating. 2. A Product Strategy that charts the course to realises the vision. 3. Shared success measures that help you understand if your strategy is on track. 4. A roadmap that focuses on outcomes with time horizons like now, next, later. 5. Your teams are organised around value, have a clear sense of purpose and are empowered to solve problems. PRODUCT FRAMEWORK Are you clear on how you "do things around here?" Is there a shared understanding of how ideas are captured, explored and prioritised? 1. Idea - consistent way to articulate an opportunity and the evidence you need to validate it. Pick a canvas or create your own but ensure you cover the problem statement and hypothesis about how it will help you deliver on your strategic intent. 2. Discovery - fit for purpose approach to validate your assumptions and reduce feasibility, viability and desirability risk. What data do you have or need to get? 3. Experiment - prototype and test with users to validate your concepts, get a sense of the effort to deliver the first slice. 4. Delivery - follow your delivery practices and get working software in the hands of users, capturing their feedback and measuring success against your goals. 5. Iterate toward the outcome! PLANNING & PRIORITISATION 1. Quarterly Planning - bring the teams together to prioritise the problems to solve. Communicate progress to goals and ensure the strategy still makes sense given customer and market insight. 2. Inform the Exec - playback the priorities and listen to their feedback. Do they have broader context to share that is not yet understood by the teams and will have an impact? 3. Delivery Planning - how will you solve the problems that you have prioritised? Estimate and plan features and non functional requirements, leaving capacity for discovery, iteration and quick wins. Make high integrity commitments where needed. Your product operations is part of your product, success is dependent on adoption, feedback and continuous improvement. # Making a generative AI copilot of your very own! Source: https://www.propelventures.ai/blog/copilot Meta: 2023-09-27 · Paul Greenwell Making a generative AI copilot of your very own! The image above is hectic, but it is a neat break down to show the component parts that we can customise to create a copilot for your app or business. Clients have been asking me a lot about the most accessible impact of AI and I think that Microsoft's copilot platform will be a major boost for the productivity for all the people using Office 365 in large enterprises AND for your own app or product. Early next year we will see copilot integrate seamlessly with common Microsoft tools such as Office 365, Word, Excel, and more. However, for the builders out there, you should know that copilot can also serve as a platform-as-a-service, enabling you to design a bespoke copilot for your own app or business. A copilot is a system that's more than just a bot - think of it as a highly advanced assistant powered by GPT-4, tailored uniquely to your context, furnished with your data. The copilot stack is neatly customisable (see image above) and we now have the tools to determine the information it processes, the persona it adopts, and more. Here at Propel, the demand to develop such 'co-pilots' for our clients has surged. As we ride this wave of technological innovation, the possibilities are both exciting and endless # Transitioning your App Development: From Agency to Software Development Partner Source: https://www.propelventures.ai/blog/from-agency-to-development-partner Meta: 2023-09-27 · Paul Greenwell Transitioning your App Development: From Agency to Software Development Partner In Australia, talking about the ups and downs (mostly ups) of the property market is a national pastime. At Propel, we have been working with the team at Auction Snitch who have built a fun and intuitive app that crowdsources “hot off the press” property insights and prices that are often not readily available or are often delayed in their public release. To validate the idea, Auction Snitch worked first with a mobile app agency to create a simple mobile application to test market demand. While this was a necessary first step to ensure the concept was viable and there was genuine interest among users before making a larger investment, the difficulty is that often, agencies make apps that are not scalable and have a short initial life. They barely survive first contact with real users and are difficult to extend as the feedback comes flooding in. We have seen this several times where clients have come to us to ask for our help to scale up an app and ensure that there is comprehensive documentation to explain the code, automation testing to prevent regressions in quality, a build pipeline to reliably and safely deploy updates as well as a separation of testing and production environments to ensure releases are well tested and compatible. At Propel, we ensure the highest standards of engineering when it's time to scale. We work with clients like Auction Snitch to implement robust development and build processes including modern infrastructure practices to allow you to scale your solution quickly. “Auction Snitch is a bit of a passion project for us as we firmly believe that transparency is the cornerstone of a healthy real estate ecosystem, and this app will empower both buyers and sellers alike to make informed decisions with confidence. We were thrilled with the initial reaction of users to our App indicating a high level of interest and we wanted to be able rapidly respond to feedback and provide App updates without interruption” said Tamsin Lapointe, Co-Founder, “We approached Propel with the challenge of taking our App to the next level and we are so glad that we did!” Getting to market to test your idea at low cost may make sense to start, but once you gain traction with your users, a more structured and robust infrastructure is crucial for handling your app's growing success and ensuring a sustainable expansion. We are delighted to have helped Auction Snitch improve the reliability and scalability of the app, positioning it well for future growth. Have a look for yourself and get Snitching! https://auctionsnitch.com.au/ # You don't have a prioritisation problem, you have a strategy one! Source: https://www.propelventures.ai/blog/product-strategy-masterclass Meta: 2023-09-27 · Paul Greenwell Product strategy Anyone else had times in their product career where an excel list of features was the source of prioritisation truth? I have. We’d list out all our ideas, give them scores based on what we thought was important and then spend hours debating why one feature ranked higher than another. It seemed structured way to handle things and make sure all the voices were heard. Do you know what? Those endless debates on why one feature scored a point higher than another were draining and honestly, a bit pointless. Ant Murphy alongside our panel of product leaders including Emily Chen and Frank Feustel brought this to life brilliantly last night at our Product Strategy Masterclass sharing their approach to strategy and prioritisation. Here are some of the highlights: Product strategy is all about making choices: What opportunities should be pursued and just as importantly, what not to do. "It's simply choices to do something, to be something to target a certain person or customer or market segment or do something in a certain sequence. Every single time you make a choice, you're also making a choice to not do something." "Strategy shouldn't be easy. If the choices you're trying to make are easy, then you're probably not making the right choices." Think in layers: Prioritisation happens in layers, starting at the top with vision and strategy and then working down to opportunities and finally solutions. Spend most of the time in the problem space: Think about developing strategy in the way Einstein thought about problem solving, "If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions.” Rethink value: While value is undoubtedly crucial, solely relying on it can sometimes lead to misguided decisions. A task perceived as high-value might not always translate to a desirable outcome, especially if there's a lack of clarity or confidence regarding the execution. "Prioritise based on value. Yeah logical. Although it turns out that that's pretty bad advice because what do we mean by value? Is it customer value, business value? Is it revenue? Is it reducing costs?" Consider confidence: Confidence entails having a clear understanding and assurance about a particular task's feasibility and impact. When you have a higher degree of confidence in a task, the likelihood of its success and achieving the outcome increases significantly. Intersection of confidence and value: Prioritisation becomes more effective when there’s a balanced consideration of both value and confidence. It’s about assessing the potential value of a task alongside the level of confidence you have in being able to successfully complete it and achieve the desired outcome. "what we're looking for is the intersect between the strategic choice we've made, the goal that we've set and all of the customer problems that we can solve". Align to business goals: A good product strategy helps ensure that the features or opportunities you're considering actually match up with what you want to achieve as a business. This way, you’re more likely to work on things that contribute to your business’s success. Be evidence informed: There is more to data than metrics. Product discovery comes in many forms and is key to developing the right strategy. Think hard about the questions you need answered and the assumptions you have made and get the data to validate - talk to customers. Communicate your strategy: Bridge the gap so that what the teams are actually working on is connected to the strategic intent. If they are not, find out why. It what you are asking unrealistic? Have they not bought into it? Product Strategy is often the missing piece in the puzzle for organisations that are stuggling with prioritisation and achieving sustained product success. It connects the Vision to the Roadmap and without it, there is often misalignment and waste with confused internal teams and products that don't resonate with customers. # From Project-Centric to Product-Centric: A Paradigm Shift Source: https://www.propelventures.ai/blog/from-project-centric-to-product-centric-a-paradigm-shift Meta: 2023-08-22 · Paul Greenwell Explore the shift from project-centric to product-centric models, emphasising lasting value, innovation, and a focus on impactful business outcomes. In traditional business models, the emphasis has often been on executing projects by predetermined deadlines. This approach, while rooted in the demands of IT departments to deliver features and projects swiftly, and with a level of certainty around timing and cost, unfortunately overlooks the evolving and creative nature of technology-driven products. Historically, projects have been seen as large, time-consuming, and costly endeavours aimed at achieving a particular outcome by a set date. This involves estimating team sizes, predicting timelines, securing funding, and then, more often than not, realising that the scope was underestimated. The rush to meet deadlines often overshadows the quest for genuine value. Once a project is completed, instead of refining it, teams are quickly shuffled to their next assignments. This methodology is fraught with challenges: Iterative Development: True value often emerges after several iterations. However, the project-based approach seldom budgets for more than the initial launch. Ownership and Sustainability: When teams are transient, hopping from one project to another, there's a diminished sense of ownership in the end outcome. This lack of permanence often results in products that aren’t built for longevity or maintainability - but do meet the stated requirements in the initial or agreed spec. Innovation Stifling: The focus remains on delivering what stakeholders demand, sidelining engineers from exploring the realm of the newly possible. Consequently, innovation becomes a lower class citizen. Tech Debt Accumulation: With the primary goal being project completion, there's less foresight into the long-term implications of the work. This shortsightedness leads to a growing level of technical debt. Enter the product-centric model, which contrasts with the project model, in a product-centric model, we emphasise products and their outcomes. In a product-centric model, product teams are aligned with business objectives, be it reducing customer attrition, enhancing growth, or any other pertinent KPIs. Their every move is geared towards influencing these metrics positively. It's not just about adding features; it's about ensuring those features translate to desired outcomes. This approach fosters an environment where teams are deeply invested in the results. This shift isn't merely structural; it's cultural. It's about transitioning from temporary project teams to enduring product teams that are accountable for tangible outcomes which are measurable, not just feature delivery. While the project model celebrates time-to-market, the product model champions a more consequential metric: time-to-value. In this new era, it's not just about launching; it's about launching with purpose and continuous improvement. # Insights from Jon Smart Source: https://www.propelventures.ai/blog/product-delivery Meta: 2023-07-27 · Paul Greenwell Learn how to transition your organisation into a product-led approach with these 5 essential pillars. Explore each pillar in-depth and take the first step towards a successful transition. We had a fantastic time last night at the Base Station, welcoming Jon Smart to share his experience in how to transform agility in organisations. Many relatable moments as he talked to the mistakes he's made along the way and the valuable learnings as a result. The human element Jon brings is unique. Sadly, it's not often that the social and environmental factors are considered in organisational transformations. The Better Sooner Safer Happier movement cares about this "improving ways of working is not at the expense of society or the planet". Improving ways of working is key, "If we don't get better at the how, we won't get better at the what". 1. "Be" agile, don't "Do" agile: Agile isn’t merely about checking boxes and performing motions in robotic manoeuvres. It's about delivering genuine value in the context of your unique organisation. Being overly process-driven can overshadow the true essence of Agile. Move from productivity to "valuetivity" - don't ignore the weakest link in flow to value, focus on it first. 2. Achieve big through small: Envision your organisation as a fleet of nimble speedboats instead of a colossal oil tanker. Smaller teams and smaller slices of work. Celebrate intelligent failure, creating a psychologically safe environment. 3. Invite over inflict. Not one size fits all: Leverage the enthusiasm of early adopters to drive the change. It's about your culture, play to it. 4. Leadership behaviour will make it or break it: Leaders play a critical role in enabling business agility. Jon highlighted the importance of supportive leadership that trusts and empowers teams to make decisions. Leaders should act as enablers, providing the necessary resources and removing obstacles to help teams deliver value effectively. 5. Whole organisation agility: In today's fast-paced world, change and uncertainty are constant. Jon discussed how Agile and Lean principles enable organizations to adapt quickly to changing market conditions and customer needs. By embracing uncertainty and leveraging feedback loops, businesses can stay ahead of the curve. 6. Build the right thing. Focus on outcomes over output: Producing more doesn't inherently mean achieving more. The spotlight should remain on crafting things that matter, those which offer real value, rather than just increasing output. 7. Go slower to go faster: Improving daily work is as important as daily work. Encourage experimentation, learn from failures, and constantly seek ways to improve. Iterate for faster learning and innovation. Jon also talked to the anti-patterns the he sees, things like "all the names" but no agility. Calling yourself a "squad, tribe, mission" doesn't mean you will be better at delivering value in the shortest time with the least effort at quality. # Product-Led Maturity - The Results Are In Source: https://www.propelventures.ai/blog/productledmaturityassessment Meta: 2023-07-24 · Paul Greenwell Learn how to transition your organisation into a product-led approach with these 5 essential pillars. Explore each pillar in-depth and take the first step towards a successful transition. Being Product-Led means your organisation has a relentless focus on delivering genuine customer value through the products you create.  It means having a clear view of the change you want your products to bring about in the world and a path to get there. It means leveraging the power of your teams by giving them problems to solve and holding them accountable for the outcome. As you embark on a product-led transformation start with getting the foundations right. From our experience, the best product companies have these 5 pillars in place: Our recent survey showed that many organisations have gaps when it comes to these foundational pillars. Product Vision 43% of respondents have a product vision that articulates the problems their product is trying to solve and the change they want to make in the world. However, only a quarter of those organisations have a product strategy that maps the course to achieving that vision. A further 32% do have a high level vision, but what the teams are working on rarely aligns with achieving it. If your organisation doesn’t have a clear vision, it will be very difficult to align the business around where you are going. Different departments will head off in different directions based on their own ideas, with resource not concentrated on the most critical priorities. "An inspiring and compelling product vision serves so many critical purposes that it is hard to think of a more important or higher-leverage product artifact" Marty Cagan When creating your vision, here are some questions to answer: What problem are you looking to solve? Who is your customer? What change do you want to bring about? Product Strategy Only 17% of those surveyed said they had a product strategy that provides teams with clarity on “how” they will reach their vision. 38% are focused on churning out features, all for a reason but with no clear strategy. Without a well-defined strategy, it’s difficult to make informed choices and prioritise initiatives that align with the vision (assuming you have one). The default ends up being decisions based on the loudest voice (customer or stakeholder) or an overly metricated / scored feature backlog. An understanding of the problem to solve gets lost and there is little room for innovation and creativity. Questions to answer: What are your business goals? What challenges are standing in the way of reaching your product vision? What problems can you address to tackle the challenges? What are the options? What data and insight do you have to inform the choices? How Teams are Organised There was a fairly even split across how teams are organised. 26% given problems to solve and organised around customer value 22% cross functional teams organised around product features 26% organised by function 26% reorganised based on current priorities If the whole team have a deep understanding of customer needs and pain points there is a higher chance you’ll come up with innovative solutions to solve problems and deliver value. An easy first step for a team to take is to map out the customer journey and consider: What is the problem your are solving? What are the pain points and opportunities for your customers? What are your hypotheses and what experiments can you run to test them? Measuring Success The vast majority (close to 90%) track outcomes as the measure of success for their product. 41% do this based on financial KPIs and 45% define and measure success based on targeted metrics (financial and non-financial) for an initiative or feature. Only 11% measure success based on delivery output, story points and whether features were shipped to meet deadlines. When deciding what to measure, consider: What is happening in your product when you picture your successful customer? What are the metrics that tells you your strategy is on track? "An imperfect measurement for the right idea is better than a perfect measurement for the wrong idea” John Cutler Outcome Based Roadmaps 22% of respondents indicated that they have a theme driven roadmap that focuses on outcomes. Wherever possible we advocate for roadmaps categorised in this way, defining the benefits and outcomes over time horizons such as now, next, later. You should be able to articulate the goals or outcomes of your strategy and know what you are working on now that focuses on those goals. There will be times when you need to hit a date – call this out. It should be the exception for compliance or other time sensitive drivers rather than the norm. 36% have quarterly roadmaps that communicate delivery milestones based on objectives. 30% maintain project plans and 12% have roadmaps based on commitments to customers with set dates. Ultimately, a product roadmap is a communication tool, helping to align the organisation. It should be iterative, evolving until the desired outcomes are achieved. “Think outcomes, not output. Your roadmap should be tracked to company-level objectives, not a pile of features for features' sake.” Janna Bastow As you build your roadmap, can you answer? What are the outcomes of your strategy that you are working toward? What are you discovering and deliviering now with those goals in mind? What questions do you need to answer next? What high level "how might me" questions will you consider later? By focusing on delivering value and exceptional user experiences, product-led companies  achieve sustainable growth and a customer-centric culture which result in a more resilient and successful business in the long run. Where do you stand? Take our assessment here to find out. # Microsoft's Latest AI Product Announcements Source: https://www.propelventures.ai/blog/microsoft-latest-product-announcements Meta: 2023-07-19 · Paul Greenwell Propel Ventures, an official Microsoft Solutions Partner attended Microsoft Inspire event - latest AI Chat GPT and Open AI product announemcents. ## Update from Microsoft Inspire event today in Washington - tons of AI innovation As a Microsoft Solutions Partner for Digital & App Innovation (Azure) I was keen to take the opportunity to watch the Microsoft inspire event today live from San Francisco where I was holidaying with some friends. There were lots of big announcements from the event. The biggest things I think that you should think about are below: ## Bing Chat Enterprise Earlier this year, we saw Bing do search, plus add complete answers to questions for internet searches. ie. like Chat GPT embedded into bing search.  Now you can use that same search and chat to query all of your own documents in your own enterprise (not just the internet). You can search across Office 365 in a secure Internal Enterprise ChatGPT which Enables safe access to ChatGPT on internal and external data. ## Copilot Our developers have been using copilot to help them develop software, now if you are a microsoft office user ie. excel, word, ppt etc.. Using microsoft copilot inside O365, will be embedded and built in at $30 per user pm. Next step is to be able to create your own copilot… not just use microsoft out of the box copilot solution. More info about that is at this link. ## Plugins For people and companies with their own app, or you are someone who works in a product company, then there is a big opportunity to add a version of your app as a plugin into Bing Enterprise chat and Plugins into O365 so users can access your functionality in the context of a search or their own workflow. ## Process automation How do you go about finding parts of your business to improve? This usually starts with a process mapping exercise. If you are looking for ways to put AI into your everyday tasks to make them faster and easier, we have been helping clients to map processes and use generative Ai to improve their day to day - now there is an even more powerful MSFT tool to do that Power Automate - process mining. Check that out here. ## Certifications and recognition With all of this new stuff about AI, how do you know you are working with someone who knows what they are talking about? Microsoft have created a bunch of new specialisations and designations (certifications) around modernising and building AI apps - ie. you do the test and they certify you as being an expert in that area. Propel already have three developers who have now completed their AI Engineering MSFT Certification. If you want to know more about how you can use Ai in your business, ping me. Looking forward to chatting further about this stuff on my return. ## Propel's Generative AI research App .... and if you do a lot if interviews and are looking to query the transcripts to understand the insights and identify direct quotes to support those insights, sign up for the waitlist of Propel’s Customer Discovery Generative AI Research Assistant - you can do that here. ## We can help you with your AI journey If you have a brilliant new product idea that could benefit from the powerful, flexible Azure toolset, let’s chat today. We look forward to showing you what we can do on Azure, helping you to accelerate towards success. # The Tragedy of Large-Scale Agile Transformations: Losing Sight of Outcomes over Output Source: https://www.propelventures.ai/blog/the-tragedy-of-large-scale-agile-transformations Meta: 2023-07-18 · Paul Greenwell The Tragedy of Large-Scale Agile Transformations: Losing sights if Outcomes over Output Agile methodologies like Scrum, Kanban, and the Scaled Agile Framework (SAFe) have been adopted worldwide and permeated not only software development but various facets of business, helping teams to deliver high-quality products faster, iterate on feedback, and adapt to change. Yet, as more companies initiate large-scale agile transformations, many are failing to realize the promised benefits. The culprit often isn't the agile methodologies themselves, but a misunderstanding and misapplication of their principles. As Christian Idiodi says at the 12 minute mark in the below video, "It fails because we fail to empower people - it fails because it becomes an exercise in exercise. They think that all the ceremonies equals agile." ## The Essence of Agile The Agile Manifesto, penned in 2001, proposed a revolutionary way of thinking about software development. It emphasized individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a plan. At its core, Agile is about accelerating the rate of learning by breaking down large problems into smaller, manageable parts. Scrum, for instance, employs a series of short iterations or "sprints" aimed at continuous improvement and adapting to change. Similarly, the Scaled Agile Framework (SAFe) focuses on applying agile principles at an enterprise scale, emphasizing alignment, collaboration, and delivery across multiple agile teams. The idea is to increase cadence, foster collaboration, get products into customers' hands early, and relentlessly focus on business and customer outcomes. The focus is on customer value, team empowerment, and continuous improvement rather than rigid planning and control. ## Misguided Intentions The problem arises when executives misunderstand or distort these principles. Often, agile transformations are initiated with the expectation of "doing more with less" - increasing productivity and speed at a reduced cost. This mindset betrays a profound misunderstanding of agile, effectively reducing it to a mere productivity tool. Agile is not merely a magic wand that makes teams work faster and more efficiently. It is, fundamentally, a shift in how teams approach their work, emphasizing learning, adaptation, and customer-centricity. ## The Process Over Outcomes Paradox The focus on productivity often leads to an overemphasis on the mechanics of agile methods, such as sprints, backlogs, and process tools like burn down charts and velocity. The actual business and customer outcomes recede into the background. Teams become so engrossed in sticking to the process that they lose sight of the bigger picture - delivering value to the customer. This narrow focus on processes can result in the tragic irony of agile transformations: Teams may be working at an incredible pace, but without generating any meaningful impact. ## The Empowerment Fallacy Another misstep in many agile transformations is treating teams as "order takers," merely executing directives from above. This approach flies in the face of the agile principle of empowering teams to self-organize and make decisions. Instead of merely adopting agile rituals, organizations need to imbibe the spirit of agile: empowering teams to solve problems creatively. Without this empowerment, agile transformations can become a hollow exercise, and teams can become disillusioned, leading to failed transformations. ## Final Thoughts Large-scale agile transformations fail not because agile methodologies are flawed, but often due to the misinterpretation and misapplication of agile principles. Agile is not a panacea for all organizational woes; it is not merely about going faster or squeezing more from less. Instead, agile transformation should be viewed as a paradigm shift, a new way of thinking and working that prioritizes customer value, collaboration, adaptation, and team empowerment. Executives should approach agile transformation with these principles in mind, focusing not just on the velocity but on delivering value to the customer, fostering a culture of learning, and empowering their teams to become problem solvers, not just order takers. # Trust beyond the team: Our ask of Execs Source: https://www.propelventures.ai/blog/trustbeyondtheteam Meta: 2023-07-14 · Paul Greenwell Learn how to transition your organisation into a product-led approach with these 5 essential pillars. Explore each pillar in-depth and take the first step towards a successful transition. Inspired by the training we did at Propel last month diving into Lencioni's 5 dysfunctions of a team, I wrote a blog about what we see at Propel when there is a high trust environment within the team. While “trust within the team” is a good place to start, an environment where there is real “trust beyond the team” will ensure decisions are made at the right level, fostering team accountability and engagement which in turn accelerates innovation. Rather than thinking about what product teams need to do to earn the trust of stakeholders and executives, let’s instead flip it - and have a look at what we need from our leaders.  What are the actions and behaviours that we need from executives to build a culture of trust? OUR ASK OF EXECS: DO THIS Provide the strategic context:  In order to make the right decisions and trade offs day to day, the team needs to understand where they are heading.  What’s the “big picture” for the company, what are the goals and long term objectives? Transparency should be a two way street and as much as possible the exec should provide it. This builds trust and a greater sense of connection to the broader business goals. As Marty Cagan says in his recent article, it also means better decisions.. “But teams can only make good decisions when they are provided the necessary strategic context.  So, it’s critical for executives to share the broader context – the business strategy, financial parameters, regulatory developments, industry trends, and strategic partnerships.” Communicate commitments: So you’ve told the market something, made a promise to a key client? The team needs to know this! Even better, involve the team before the promise is made and explain the “why”. There is almost always a way to deliver value within constraints, but coming up with how to do this is dependent on understanding what the actual problem to solve is, and what has been communicated. Turn up to discovery playbacks and showcases: Exec diaries are generally pretty full, but taking the time to provide feedback early and be present in product demos is really powerful. Demonstrating genuine interest and appreciation for your teams' work sends a strong message that says, "We value you, and we're invested in your success." This visibility and engagement are trust-building gold. OUR ASK OF EXECS: BE THIS Open to challenge: An environment of trust is one where everyone feels comfortable challenging ideas and offering different perspectives. Embracing diverse viewpoints promotes critical thinking, innovation and fosters trust. Executives should actively seek out and listen to these alternative ideas, showing that they value forthright honesty and are open to changing their mind. Listen to the bad news: Sometimes things go wrong. Sometimes a whole heap of effort, money and resources are invested but the outcome won’t be achieved. Sharing the bad news takes bravery, so don’t shoot the messenger. In fact don’t shoot anyone, start by believing what you are being told. Many of the execs I’ve worked with are optimists and I’ve experienced a response that immediately moves to reframing the message more positively or assuming that the team is being pessimistic. Don’t do that, believe, understand then ask what the team needs. Focused and consistent: Consistency when it comes to how decisions are made is the name of the game when it comes to building trust. The team need to see that executives are focused on the vision, objectives and company values in all the decisions that are made - or when that is not possible, it's explained.  A business strategy that changes too often or is not focused on a clear outcome is impossible to deliver and asking the teams to do everything all at once breeds uncertainty and erodes trust. Finally, a personal reflection on what has worked for me in terms of fostering trusted relationships with my team, peers and leaders - do what you say you will do and remember David Maister's trust equation. Trustworthiness = credibility + reliability + intimacy / self orientation. # Masterclass Takeaways - Product Thinking in Agile Delivery Source: https://www.propelventures.ai/blog/product-masterclass-takeaways-christian-idioi-product-thinking-in-agile-delivery Meta: 2023-06-28 · Paul Greenwell Christian Idiodi product thinking in agile delivery takeaways. It was truly energising to hear from a product expert and all round good human, Christian Idiodi today about bringing a product mindset into agile delivery. Christian took us back to the agile manifesto where that famed group of engineers "went to a ski resort and didn't ski" and spoke to the current trend of "doing Agile" rather than "being agile" and that "agile alone is not enough".  He reiterated that Agile is a powerful methodology to help build things faster, but doesn't guarantee that you are building the right thing - unless you build discovery into the delivery process and do discovery well to validate what you put into the delivery cycle. Here are some of the key takeaways: Understand the 'Why' The first step to embedding a product mindset into Agile delivery is understanding the 'why'. Achieving product success is more than just the 'what' and the 'how'. Start by falling in love with the problem that needs to be solved, understand the problem space deeply and iterate on the solutions with customers who face that problem and want a solution to the problem.  A clear product vision steers the agile team in the right direction and ensures alignment with the product's mission and goals. Talk to your Customers You can’t be product-led if the product team doesn’t know the customer deeply. The most influential person in a company is the person who understands the customer problem the most deeply. True product value comes from using technology to solve real pain points. Teams need to build empathy with their customers to ensure the best decisions are made. Continuous Learning & Iteration Prototype, test and learn - do this 10 or 20 times in a week.  "We need to fake it, discovery,  then we need to make it, delivery". All successful products have a graveyard of failed experiments - ideally these failures happen fast and cheaply. Discover and validate before building, and have the engineers involved so you build it with technology that is available and viable. The Importance of Cross-Functional Teams "It is a waste when we just tell the engineers what to do". Cross functional collaboration is crucial and a diverse team with a variety of skills can lead to more innovative and holistic solutions. By promoting an environment where everyone feels their expertise is valued and their voice is heard, teams can leverage their collective skills to enhance product value. Ultimately, value is the most important thing - we exist to solve problems on behalf of humans and solving those problems is a team sport.  Innovation is everyone's role. # What are 5 signs of a high trust team environment? Source: https://www.propelventures.ai/blog/5signs-high-trust-teams Meta: 2023-06-23 · Paul Greenwell Learn how to transition your organisation into a product-led approach with these 5 essential pillars. Explore each pillar in-depth and take the first step towards a successful transition. Moving from feature teams to empowered product teams who are given problems to solve and held accountable for the outcomes requires, more than anything, trust. Trust within the team and trust beyond the team. Starting with "Trust within the team", the power of a high trust environment is undeniable. Fostering trust unlocks the full potential of the team, driving innovation, faster product delivery and stronger team engagement. Taking the time to build and nurture trust is an investment in the long term success of the team and the products they create. What are the 5 signs you are working in a high trust environment? Diverse Opinions and Ideas Team members feel comfortable expressing their ideas, sharing concerns and taking risks without fear of judgement or reprisal. They know their opinions are valued and that their voices will be heard. Open and honest communication leads to increased collaboration, innovation and collective problem-solving. What you'll see: The whole team sharing diverse opinions openly. Authentic Collaboration Team members share knowledge, insights and resources freely, recognising that building each other's capability leads to better outcomes. There is a sense of unity and a collective drive to achieve shared goals. Ideas are exchanged, refined and built upon, harnessing the diverse expertise and perspectives within the team. What you'll see: There won't be a sense of mystery around anyone's knowledge. Constructive Conflict Team members feel safe to question assumptions, propose alternatives and engage in healthy debates. Different viewpoints are welcomed, as they contribute to a more comprehensive exploration of possibilities. By challenging ideas the team can refine and strengthen their solutions, leading to better decision-making and innovative outcomes. What you'll see: There will be more options and better answers to the problems you are solving and there will be strong commitment to decisions. Culture of Acccountability Each team member holds themselves and others accountable for their commitments and contributions. There is a shared understanding that everyone's efforts impact the team's success. Team members take ownership of their responsibilities, follow through on commitments and support one another in achieving collective goals. This accountability fosters a sense of reliability, dependability, and a commitment to excellence. What you'll see: Team members go outside what they are responsible for, to achieve team, not individual outcomes. Change is Embraced In a high trust environment, teams are more adaptable, resilient and open to new ideas and approaches. Instead of resisting change, they proactively seek it, understanding that it is essential for innovation and staying ahead in a dynamic market. Trust allows team members to navigate uncertainties and experiment with new methodologies, enabling the team to evolve and thrive in a rapidly changing landscape. What you'll see: Continous improvement comes often and easily. Conclusion A high-trust empowered product team cultivates psychological safety which is foundational in all high performing teams. "I hope you are working in an environment where this is true for your product teams.  If not, I would argue that your company’s future depends on the productivity and continuous innovation that comes from this model of work." Marty Cagan # Sam Altman's Melbourne Visit Source: https://www.propelventures.ai/blog/sam-altman-melbourne Meta: 2023-06-19 · Paul Greenwell Sam Altman's visit to Melbourne 🚀 Last week, I had the incredible opportunity to attend an enlightening speaking event featuring Sam Altman, renowned entrepreneur and visionary. Altman shared invaluable insights about the impact of Chat GPT, and I couldn't resist capturing some of his most profound quotes to share with you all.🌏 ## My top 13 insights from Sam about AI # The Risk of Confusing Agile with Product-Led Source: https://www.propelventures.ai/blog/warning-signs-not-product-led-0 Meta: 2023-06-05 · Paul Greenwell Exploring the risks of agile leaders without product experience guiding product-led transformation: Misguided strategies, role confusion & more. Over the past year it's been fascinating to observe the rise of agile software delivery project management leaders shifting their focus from advocating agile software development to pushing for product-led transformation. Welcome! It's a significant and positive change, but, as someone with decades of experience in product management, this shift is potentially fraught with peril because agile thought leaders are project managers, not product managers.  Agile thought leaders may have have experienced success delivering products, but only with responsibility for delivery, not product leadership. - yet they are now purporting to speak knowledgeably about product management. In this blog post, I aim to shed light on the potential pitfalls inherent in agile thought leaders crossing the bridge to become 'product leaders'. ## Project Management vs. Product Management: A Key Distinction Before delving into the risks, it is crucial to highlight the fundamental differences between project management and product management. Project management typically deals with a finite set of activities with a predetermined end goal. It is all about planning, organising, and managing resources to deliver a specific, one-off project. On the other hand, product management is an ongoing process. It entails steering the development and success of a product or product line over its entire life cycle. The product manager's goal is not just to 'deliver' but to ensure that the product solves a market problem, fits the business strategy, and meets customers' needs. What does it mean to be product led? “Product led companies optimise for business outcomes, and align their product strategy to these goals. To become product led-you need to take a look at the roles, the strategy, the process and the organisation itself” – Melissa Perri, The Build Trap ## The Perils of Misguided Leadership Now, let's dive into the risks. The first is the potential for misdirected strategies. Product-led transformation isn't just about delivering products faster or more efficiently. It's about instilling a culture that places the product and customer at the centre of every business decision. Agile methodologies can certainly be a part of this, but they're not the whole picture. An agile thought leader without a solid background in product management might focus too much on processes and not enough on the bigger strategic picture, leading to misaligned priorities. Secondly, there is the risk of misunderstanding the role of a product manager. The PM is not just a project manager who ensures that a product gets delivered on time. A PM must also be a strategist, a marketer, a customer advocate, and a team leader. Without experience in these areas, agile leaders are susceptible to undervalue the broader responsibilities or miscommunicate their importance, leading to a diluted or misconstrued perception of the role. Finally, there's a risk of fostering a project-based mindset in a role that should be product-oriented. As we've discussed, project management is about delivering a specific project, while product management is about owning a product over its entire lifecycle. If agile leaders approach product management with a project mindset, they are at risk of focusing too much on the short term and neglect the long term strategic growth of the product. ## Conclusion The shift towards a product-led approach is a positive one. It places the customer and the product at the centre of the business. However, organisations need to be wary of thought leaders who purport to be knowledgeable about product management without having the requisite experience. Agile methodologies are an essential part of modern product development, but they don't replace the need for deep product management expertise. The success of a product-led transformation hinges on the experience, expertise, and vision of genuine product leaders. Ask your advisor how many products they have personally led from inception through to product market fit - or did they just help lead the agile rituals on the way through. At Propel, we believe that it’s time to start the journey to become product-led. But what does that really mean? To become truly product-led, companies need empowered product teams, who are focused on and measured by outcomes rather than outputs. Propel is a strategic product development partner with the skills and capabilities to add empowered product teams to your company. These teams have the product, design and technical leadership required to ensure the right product is delivered, even if that ends up being a little different to what you initially expected or asked for. Our team members will work collaboratively with you at every level, from creating a compelling product vision and developing a strong foundational strategy, to bringing this vision to life through product design, development and implementation. Want to know more? Let’s talk. # Propel Pulse Survey: Structuring Development Teams for Product Success Source: https://www.propelventures.ai/blog/survey-structuring-development-teams-for-product-success Meta: 2023-04-20 · Paul Greenwell Discover how companies are organising their development teams and using offshoring to maximise productivity and efficiency based on our recent survey. Are you struggling to organise your development team and wondering how other companies are doing it? Have you considered offshoring but are unsure about the best practices? Our recent survey, conducted in partnership with Davidson, gathered valuable information on how companies are organising their development teams and using offshoring to maximise productivity and efficiency. ### Common team structures and offshore locations Based on responses from 20 product companies and enterprises across multiple industries, we found that most organisations structure their teams based on products or platforms, with offshore teams commonly located in Asia, particularly in India, Vietnam, and the Philippines. When it comes to which roles are kept onshore versus offshore, technical and product managers tend to stay onshore, while developers and quality analysts are more commonly offshore. However, the biggest challenge with offshore teams is efficient collaboration between offshore and onshore teams due to time zone differences. This often puts extra work on onshore team members, such as product managers, business analysts, and technical leads, who have to be more prescriptive when supporting offshore team members. ### How teams approach development In terms of development methodologies, more than 70% of respondents follow Scrum methodology, with over 50% complementing Scrum with Kanban. Most teams measure performance using OKRs or outcomes, with larger organisations also incorporating DORA metrics. Looking ahead, the biggest concerns for software development leaders are costs, productivity, and capacity, with 70-90% of respondents ranking these as their highest concerns. This is not surprising given the steep rise in salaries and scarcity of onshore resources. ### Conclusion: maximising productivity and efficiency in your development team Our survey provides valuable insights into how companies are organising their development teams and using offshoring to maximise productivity and efficiency. While offshore teams can be beneficial, it's important to be aware of the challenges and ensure efficient collaboration between offshore and onshore teams. By following proven development methodologies and measuring performance effectively, companies can stay ahead of the curve and address concerns around costs, productivity, and capacity. {{cta('dd0cc700-910e-4b59-a6e4-533e562584f9')}} # How to approach your transition to product led Source: https://www.propelventures.ai/blog/transition-to-product-led Meta: 2023-04-06 · Paul Greenwell Want to adopt practices of successful product companies? Learn how to become product-led with Propel Ventures. You’re convinced of the value of being product led (and the very real risks of not being product led) and have decided to adopt the practices of the best product companies. Brilliant. So, what now? In theory, becoming product-led is simple. In reality, very few organisations make the transition successfully. Those that do, like Amazon, Netflix and Adobe, continue to disrupt, innovate and achieve product success. They thrive in the face of challenges and grasp new market opportunities with gusto. Before you begin, it’s important to realise that becoming product led means you are changing how you solve problems for customers. Marty Cagan, founder of Silicon Valley Product Group, says this means “moving from stakeholder-driven roadmaps and feature teams, to empowered product teams given problems to solve, and then using product discovery to come up with solutions that are valuable, usable, feasible and viable.” This means the first and most important thing you need to become truly product-led is empowered product teams. We talked in our last article about what makes empowered product teams better than feature or delivery teams. Here’s a quick recap: If your teams are given a detailed set of requirements or a feature backlog and it’s your executives who are responsible for business and customer value, it’s likely your teams are set up as delivery or feature teams. On the other hand, if your teams start with a problem to solve, are focused on managing risk, and are accountable for the success of the product, there’s a good chance you have empowered product teams. ## Laying the foundations There are certain pillars you need in place to become product-led – such as a compelling vision, focused product strategy and the right team topology – which we’ll focus on in the next article. But becoming product-led runs deeper than that. It’s about cultivating a mindset and cultural change that think about the product first. For that, you need to make sure you have the right people with the right mindset: The transition to product-led often demands fundamental change across every part of the company. The leadership team is team number one. Your CEO and leadership need to be aligned and committed to drive that scale of sustained change. “Grass roots only will soon hit a glass ceiling” -- Jonathan Smart, Sooner Safer Happier Identify who your product leaders and evangelists are and ensure they are connected and aligned with the CEO. The CEO and leadership team need to open up the decision-making process to a wider, larger and more diverse group of stakeholders. The goal is to shift the product team from a subservient relationship, where they were order takers for the business, to a collaborative relationship where they discover a solution that customers love, yet also deliver value for the business. 2. Product leaders A successful transition can only happen with strong product leaders – that is, the people who lead product management, product design, and engineering. The importance of this can’t be stressed enough. The State of DevOps Report 2017, which collated research from more than 3200 people, found that low performing teams had leaders with the lowest transformation leader scores. Product leaders need to be stepping up and willing to model the right leadership behaviours, because they are the people responsible and accountable for everything that follows. In a feature team organisation, these people have a much easier job than in an organisation with empowered product teams. In a feature team organisation, teams are just there to serve the business. That's not the case in empowered product teams, where the team needs a product vision, product strategy, and a well-thought-out product roadmap – all of which the product leaders are there to provide. 3. Product managers Do you have true product managers? Without strong, competent product managers you cannot have empowered product teams. In organisations that are not product-led, often the product manager is not customer-facing enough to understand the problem they are solving, which means they act as an order taker, rather than driving the strategic direction of the product and the roadmap. Product managers should have deep knowledge about customers. But it’s not only customers; they should understand all the dimensions of the company – sales, marketing, services, security, privacy, funding, and beyond. ## Everyone needs to think like a product person Becoming product-led means thinking like a product person. That means focusing on customer outcomes (not outputs) whilst considering the major risks. In his book INSPIRED, Marty Cagan outlined Four Big Risks with everything we pursue in product: The last one (business viability) is critical, because as Cagan says, “It’s not enough to create a product your customers love; the product must also work for your business.” Think of the Four Big Risks as a framework to help you consider what could go wrong, before moving ahead to develop a feature. In an empowered product team, everyone has a job to think about these risks. The product manager is responsible and accountable for addressing value and viability risk, the designer covers usability, and the tech lead covers feasibility. ## Start small Empowered product teams require a high trust culture and that takes time – which means, you should start small. A small pilot will build confidence and, with confidence, trust and empowerment can follow. In most organisations, you will be able to get support to pilot a new way of working with a single team or domain. Be transparent about what’s working and what’s not. Share your measures of success and how you are tracking toward them. ## No silver bullets If you truly want to transform your company to become product-led, and move to empowered product teams, it’s going to take some hard work. There are no silver bullets or shortcuts. But the good news is there are partners who can help, and Propel is one of them. We are a strategic development partner with proven experience helping clients move from sales-led, tech-led or visionary-led companies to product-led companies primed for product success. # To build powerful products you first need to build empowered teams. Here’s why. Source: https://www.propelventures.ai/blog/powerful-products-empowered-teams Meta: 2023-04-06 · Paul Greenwell Learn about the three types of product teams: Delivery Teams, Feature Teams & Empowered Product Teams, and understand their differences in managing risks. Not all teams are created equal. When a company is building tech products, there are three types of product teams it might have: At a superficial level, they might seem the same. After all, they all deliver products, right? But there are distinct differences in the way the teams are set up and empowered to make decisions that will ultimately determine whether the product succeeds or fails. To explain how important they are, let’s first take a closer look at the types of team: Delivery Teams: The most common teams are not really product teams at all, they are delivery teams, aka “dev teams”, “scrum teams” or “engineering teams”. A delivery team comprises a backlog administrator (product owner) and developers who are focused on delivering output. Requirements which are often well-defined upfront are handed over to the team and the focus is on delivering those requirements on time and on budget. There’s no real drive to push true, consistent innovation for customers. Feature Teams: Feature teams are all about output. They are instructed which deliverables (typically features) are expected, and will generally do minimum product discovery work. Deliverables are usually provided to the team by executives across the business in the form of a prioritised list, aka “roadmap”. This means feature teams have a low sense of ownership over the outcome, and can’t be adequately held responsible for the results. If your team is really just managing a backlog of requests, it’s probably a feature team. Empowered Product Teams: Product teams are focused on and measured by outcomes, rather than output. Rather than being given exact deliverables, the team is asked to solve problems and has strategic context. This means they are empowered to figure out the best way to solve the problems, and are accountable for the results. Empowered product teams include a product manager who provides the much-needed context for team members. That context forms the basis for thousands of micro-decisions made by a diverse mix of team members as they work to deliver product-market fit. ## The most important difference between product, feature and delivery teams Building products that achieve product-market fit is tough. If the team building the product is not set up to solve problems, innovate and address the risks, the product is more likely to fail. One of the differences between the three types of teams comes down to how they manage risks. What do we mean when we talk about risks? Consider the four key elements that make a successful product: In any team, different people have responsibility for ensuring each of these factors does not become a risk. In a feature team, it is the designer’s role to ensure usability, while engineers are responsible for ensuring feasibility. The person called a product manager is typically just herding the cats and providing a backlog. Importantly, in a feature team there is nobody in the team explicitly taking responsibility for value and business viability. That comes down to the executive who requested the feature on the roadmap. If the executive says they need the team to build a feature, it’s because they believe that feature will deliver value and is viable for the business. However, this can cause problems down the track if they do not take responsibility when the feature hits the market and doesn’t deliver product-market fit. In a product team, value and viability are the responsibility of the product manager. That’s how empowered product teams reduce your risk of failure. An empowered team will make hundreds of decisions each day as they build the product and every single decision is reducing the risks of failure – they are not blindly following instructions and delivering what was asked in letter, but not in spirit. By contrast, delivery teams rarely have control over any of the risks. Often, the design and key technical decisions lie with external design and architecture teams. Their goal is to focus on delivery in the allocated time. ## Example: Empowered Product Team vs Feature Team One of Propel’s early projects was to develop an employee payroll app to allow employees to add their hours to a timesheet. The executive gave the team instructions to “create this pre-designed specific workflow which lets me, as an employee, punch in and record my hours” So that’s exactly what the team did. They designed and developed the workflow to achieve what the executive asked, and the executive considered it to be a job done. However there were a bunch of use cases which were not considered in the request from the executive which unnecessarily narrowed the audience for the feature. How would an empowered product team do things differently? An empowered product team would have been given broader context which would enable them to include a broader range of important requirements that an executive is likely to miss. For example, they could ensure the design worked well for a broader range of employee use cases, such as where only part days were worked or where people worked past midnight and the dates when the employee started and stopped work are different, and when the user is visually impaired. If the team is able to take the initiative to identify and incorporate these considerations early, they can build them into the design to cater for the needs of the variety of users, sometimes without any additional cost and avoiding rework. ## Recap: Why you really need empowered product teams Empowered product teams are given problems to solve. Engineers and designers are asked to step up and not just design and code, but actually come up with the right solution. A team that is entrusted with the product is highly motivated to achieve both business and customer outcomes and will provide a better solution and enjoy their experience at work more. ### How to accelerate your development and innovation with Propel product teams When accelerating with a development partner, are you asking your partner to operate as a feature team or a product team? Remember, one of the major differences between a feature team and an empowered product team is whether they are tasked with the delivery of specific features or being tasked with the context of a problem to solve. Often when businesses decide to accelerate development, they tend to augment their existing teams with feature teams or development teams. These teams build what they are asked, focusing on outputs without context or agency to drive the outcomes that are needed to achieve product success. Whilst the feature may be delivered as requested, this often leads to suboptimal outcomes or, worse, product failure. A better way is to find a strategic product development partner like Propel that has the skills and capabilities to add empowered product teams. These teams have the product, design and technical leadership required to ensure the right product is delivered – even if that ends up being a little different to what you initially expected or asked for. # Warning signs that your company is not product led Source: https://www.propelventures.ai/blog/warning-signs-not-product-led Meta: 2023-04-06 · Paul Greenwell Propel explores the warning signs that show your company is not product-led and risks falling into the build trap. There’s a striking difference between how the best companies do product versus the rest. Take Apple, Amazon, BBC, Google, Microsoft and Netflix. These are companies that innovate and excel in being able to solve real problems for customers and create profitable businesses. So what is it that makes the best different from the rest? Whether you look at their processes, people, structure or culture, they all have something in common: They are all product-led. What does it mean to be product led? “Product led companies optimise for business outcomes, and align their product strategy to these goals. To become product led-you need to take a look at the roles, the strategy, the process and the organisation itself” – Melissa Perri, The Build Trap The capabilities and results of those companies, especially their ability to respond to market disruptions and exploit new opportunities, should be enough reason to take a hard look at how you create your products and consider making the transition to become product led. But for those company leaders who need concrete evidence that it’s the right move, or for those product people who need to convince the company leaders, we’re going to outline a compelling case for change and some warning signs that you need to shift your product thinking before it’s too late. ## Signs that your organisation is not product-led ### You chase customer delight, not sustainable business value Anyone who works in product has most likely learned that the key to building successful products is to iterate quickly and see what delights customers. Unfortunately, as Radhika Dutt explains in her book Radical Product Thinking, it turns out that chasing customer delight alone doesn’t guarantee a successful product. You need to ensure your teams are making the trade-offs necessary between long-term thinking and short-term customer satisfaction. This is especially the case for sales-led companies, which are always building for the next or loudest customer. In these companies, decisions rarely align to the overall strategy, because you are always responding to the squeaky wheel. ### You focus on outputs, not outcomes A common anti-pattern we observe here at Propel is companies with a deterministic mindset towards product. In other words, the company funds, staffs and pushes large-scale projects and initiatives based on predetermined launch milestones, often at great expense. Then the company moves on – even if they haven’t achieved any tangible or measurable value. Product success relies on continually iterating towards the vision. But projects are all about outputs and hitting delivery milestones, rather than achieving business and customer value. With a project mindset, teams are accountable for the output only, and don’t own the outcomes. As legendary VC, John Doerr says, we need “we need teams of missionaries, not teams of mercenaries.” Mercenaries build whatever they are told to build and feel no empowerment or accountability, no passion for the problem to be solved, and little real connection with the actual users and customers – in other words, none of the things you need for real collaboration and problem solving. Missionaries, on the other hand, are true believers in the vision, are engaged and motivated to solve problems for their customers, have a deep understanding of the business context, and real empathy for the customer. ### Your product lacks a clear value proposition In a tech-led company (see previous article), you are driven by the latest and most up-to-date technology to drive the product strategy, without looking at the customer needs. It’s a “build it and they will come” approach, rather than one focused on creating value. The product strategy and vision require the identification of a strong value proposition for customers. A value proposition is a product, service, or experience that creates desired gains or relieves existing pains for customers. As Melissa Perri says in Escaping the Build Trap, “solving big problems for customers creates big value for businesses”. ### Don’t be like Kodak Kodak is a classic example of a company that didn’t make the shift to become product-led. As Melissa Perri explains in her book, once one of the most powerful companies in the world, Kodak responded to the challenge of digital photography by doubling down on the way it had always done things. Its sales and technology-led approach dominated its roadmap. It continued to measure its success in terms of outputs, not outcomes, and kept launching products without producing any real value for its users. Kodak invested billions to develop a range of digital cameras, but they were never the right products. Then, the inevitable happened: they lost market share and by January 2012, there was no coming back. Kodak went bankrupt. # Signs that your organisation is falling into ‘the build trap’ There are some warning signs to look out for. While not a definitive list, we’ve outlined here some of the most common symptoms we’ve seen in our years working with companies: Everything is always top priority Every ticket logged is placed in the highest priority section. This results in a huge list that always needs to be done immediately and inevitably outpaces resources. This also comes back to the misunderstanding of value we talked about above, which drives an emphasis on full backlogs and speed of delivery, without taking into account whether the right thing is being delivered. The last customer request is top priority Without considering current loads and schedules, senior management or product managers often add requests from customers they’ve recently spoken to with the hope that, if the features are delivered, the customers will want to buy the product more. Founder ideas are the best ideas You have an autocratic decision-making structure where the founders’ ideas are fast tracked and jump the queue. It’s also known as HiPPO-ism, where the Highest Paid Person's Opinion is the most important, or as then-CEO of Netscape Jim Barksdale said: “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” Features over bugs There’s a tendency for product managers to neglect bugs and technical debt in favour of adding more features. As Melissa Perri explains in her book, when product teams are focused on feature delivery, they become a “feature factory” and are not focused on their customers. Whereas in a product-led company, it is the product manager’s role to ensure the product provides value and viability. Recognise any of these symptoms in your company? If the answer is yes, it’s time to start the journey to become product-led. But what does that really mean? To become truly product-led, companies need empowered product teams, who are focused on and measured by outcomes rather than outputs. Propel is a strategic product development partner with the skills and capabilities to add empowered product teams to your company. These teams have the product, design and technical leadership required to ensure the right product is delivered, even if that ends up being a little different to what you initially expected or asked for. Our team members will work collaboratively with you at every level, from creating a compelling product vision and developing a strong foundational strategy, to bringing this vision to life through product design, development and implementation. Want to know more? Let’s talk. # Are you ready for a product-led transformation? Source: https://www.propelventures.ai/blog/product-led-transformation Meta: 2023-04-06 · Paul Greenwell Discover why being product-led is the path to success. If your approach to business has been sales, tech or visionary led, it's time to reconsider. Think about your company for a moment. Is your product roadmap constantly disrupted by sales requests? Do you constantly prioritise customer requests for features? Do you measure success by the number of features you build, not the outcomes they deliver? Or does the product take shape entirely based on the vision of the founder? If any of these sound familiar, you fall in the same box as lots of companies – your company is sales, tech or visionary led. ### So what’s the problem? Your approach has brought you this far, and it will keep things moving… for a while. But it’s not sustainable and will soon become a roadblock which will slow your growth. When the time comes to scale and grow (and chances are you’re reading this because that’s where you are at now), being sales, tech or visionary led just won’t cut it - your functional teams will start to focus their precious energy on the wrong things. Features will be delivered, but they won’t hit the mark. Productivity will drop. Delivery teams will miss the market opportunities and, critically, business value will not be realised. And all this because you’re not led by the one thing that really matters – Product! ## What does it mean to be product-led? Being product-led means your company uses the product to provide real value to the customer through constant customer- and technology-led innovation. It means being guided by the potential of products and product teams. You create a vision that provides a common goal – a North Star for your product teams that delivers on the business goal. The product strategy then provides the plan to get there. It guides the tough choices and tradeoffs for what you will focus on to develop products or features that sustainably drive growth. “The key to product is what you don't do…so that you can focus in and really do a good job on what you need to do.” Marty Cagan (source) Becoming product-led has become an aspiration of many tech companies today. And if it isn’t your aspiration, it should be. The reason is simple: ### Being product-led is the path to success. You only need to look to many multi-billion dollar public and private enterprises that have been built on the foundations of a product-led approach, such as Shopify and Canva. In fact, the cumulative market capitalisation of product-led-growth companies has increased more than 100 times over the past seven years. ## How exactly does being product-led drive success? Customer-centred: You have truly customer-centric thinking – the product roadmap and innovation process is driven by solving problems for the customer, not features and roadmaps defined by sales teams to get the next sale, or the business leaders’ preferences. Focused: Decisions and trade offs are aligned to the vision and business strategy so you build the right thing and don’t waste time and resources. Outcome-driven: The focus on outcomes, rather than features and outputs, drives sustainable growth. Market value: You scale for a target market, with a focus on delivering long term value, rather than building for specific customer requests for short term results. All of this works together to drive the all-important product-market fit – when you’ve made a product people want, and that drives a profit for the business. In other words, it delivers customer value and business value. Only when you have reached product-market fit can you truly think about growth and scaling your organisation. ## Where are you now? Most companies that are not product-led fall into three groups: sales led, tech led or visionary led. Which one are you? See if any of these sound familiar: Sales led: You prioritise customer requests without aligning to the overall strategy. Many companies start off this way and focus on a single customer. But as the customer base grows, it becomes increasingly difficult to build bespoke solutions for each customer and for your product teams to explore new ways to achieve product success. Visionary led: You rely on a single ‘visionary’ to do all of the work of developing a powerful product strategy. Operating in this way is not sustainable. Equipping entire teams and organisations to solve problems together is much more powerful and sustainable for long-term product success. Tech led: You are driven by the latest and most up-to-date technology to drive the product strategy. This is a risky approach, as you wind up developing products that have no clear value proposition, resulting in no customers. ## What it looks like to be product-led You have a clear vision that describes the future, focuses on the customer and provides a North Star for the organisation. Your product strategy describes the path to achieving that vision, is insight-driven and focused with a clear action plan. The teams are organised with clearly articulated customer-centric value streams. The product roadmap supports the vision and strategic intent with a focus on delivering value. Initiatives talk to the outcomes which are goal and benefit oriented. Cross functional teams are given problems to solve and held accountable for outcomes, rather than being given features to build and being measured on output. In other words, you fund teams, not projects. ## Example: How we helped iSelect move from Sales-led to Product-led When we met iSelect, they were sales-led. Teams focused on short-term feature delivery rather than long-term customer value. Internal departments had differing stances on areas of accountability, ownership and decision rights, and there was no aspirational vision to support a move towards a digital and customer centric future. At the heart of their transition was the product vision. Propel delivered a transformative and meaningful product vision along with supporting principles, refreshed team topology, product roles and responsibilities, and measurable success metrics that have paved a clear way forward for iSelect to achieve uplift in product success. We’ll delve deeper into this process in the next article, so you can understand what it takes to become product-led and see how Propel can help accelerate your journey. # Why you shouldn’t hire your MSP to build an app Source: https://www.propelventures.ai/blog/why-you-shouldnt-hire-your-msp-to-build-an-app Meta: 2022-07-12 · Paul Greenwell There are lots of benefits to partnering with a managed service provider, but building an app is not one of them. Learn how to choose the right partner to achieve success. Choosing the right partner to build your application is critical to its success. As Tony Fadell, the product leader behind the iPod and iPhone, said in his book Build: “In the end, there are two things that matter: products and people. What you build, and who you build it with.” It’s tempting to simply look to existing partners, like your managed service provider, for the solution. After all, you already have a relationship – they look after all your maintenance activities, hosting applications, upgrading software, managing support, helping with hardware… the full gamut. But that doesn’t mean they are the best choice for building your app. Here’s why: Let’s say you have a handyman you always call on for house maintenance. He makes sure the taps don’t leak, fixes the dodgy window, and does other odd jobs. Now imagine you want to invest in an extension to your house. You wouldn’t ask that same handyman to build it because building an extension requires a different set of capabilities and services. Sure, your handyman might look like he has the technical skills to do the extension – just like a managed service provider might look like they have the technical skills to build an app – but he doesn’t. What you need is a building team with the right skills and experience who will take a product-led approach. A product-led approach means they’ll ask the key questions like: Who’s going to use the extension? What’s the room for? What’s the purpose of the extension? How is it going to fit within the rest of the house that already exists? This ensures you have a fit-for-purpose extension, and a valuable addition to your property. Now think again about the app you want to build. You need to understand what problem you’re trying to solve, who for, and how it’s going to fit within your existing system. This means you need to choose a partner who will approach it from a product lens. This is the difference between focusing on a problem to solve versus having a list of features to build. ## A partner with product management leadership will help you achieve this Here at Propel, we have both product leadership and development leadership. In other words, you have access to the thinking to make sure you’re building the right thing and the execution to make sure that as you’re building the right thing, it’s still the right thing all the way through to launch. Because just like with renovations, it’s expensive to make mistakes! With product management leadership, our teams are given the broader context which empowers them to identify and include any important requirements that will solve the problem. A managed service provider, on the other hand, might have the technical skills to build the product, but they do not bring a broader view that ensures they know the exact problem you are trying to solve, and for who. As such, they are more likely to fall into traps, just like a handyman would when trying to build your dream extension. The product is more likely to fail, or you need to invest extra time and budget for rework. The bottom line? ## Don’t use a handyman to build your extension There are lots of benefits to partnering with an MSP, but building an app is not one of them. They might have the technical skills for the build, but chances are they will build something that does not solve the problem. At Propel, our product management leadership is combined with an intact development team who can not only “build that extension”, but will make sure it’s the right product. # Are you capturing the delivery turbo-boost from Product Teams, or plodding with Feature or Delivery teams? Source: https://www.propelventures.ai/blog/product-teams-feature-or-delivery-teams Meta: 2022-07-04 · Paul Greenwell Are your teams just ticking boxes or are they turbocharging product delivery? This is the difference between a feature team and an empowered product team. Not all product teams are created equal. The reality is, when a company is building tech products, there are three types of product teams it might have: product teams, feature teams and delivery teams. At a superficial level, they might seem the same. After all, they all deliver products, right? But there are distinct differences in the way the teams are set up and empowered to make decisions that will ultimately determine whether the product succeeds or fails. We recently hosted a Q&A Breakfast with Marty Cagan, author of “EMPOWERED: Ordinary People, Extraordinary Products”, a partner at the Silicon Valley Product Group and a former product leader at eBay, Netscape and HP. He explained the thinking behind one very simple truth: ### To build powerful products you first need to build empowered teams. To explain how important they are, let’s first take a look at the different types of team you can have: ## Delivery Teams The most common teams are not really product teams at all, they are delivery teams, aka “dev teams” or “scrum teams” or “engineering teams”. A delivery team comprises a backlog administrator (product owner) and developers who are focused on delivering output. There’s no real drive to push true, consistent innovation for customers. ## Feature teams Feature teams are all about output. They are told which deliverables (typically features) are expected, and will generally do minimum product discovery work. The deliverables are usually provided to the team by executives across the business in the form of a prioritised list, aka “roadmap”. This means feature teams have a low sense of ownership over the outputs, and can’t be adequately held responsible for the results. If your team is really just managing a backlog of requests, it’s probably a feature team. ## Empowered Product Teams Product teams are focused on and measured by outcomes, rather than output. Rather than being given exact deliverables, the team is asked to solve problems and has strategic context. This means they are empowered to figure out the best way to solve the problems, and should be held accountable for the results. Importantly, empowered product teams include a product manager who provides the much-needed context for team members. That context forms the basis for thousands of micro-decisions made by a diverse mix of team members as they work to deliver product-market fit. ## The most important difference between product, feature and delivery teams Building products that achieve product-market fit is tough. If the team building the product is not set up to solve problems, innovate and address the risks, the product is more likely to fail. The biggest difference between the three types of teams comes down to how they manage risks. A successful product is valuable, usable and feasible. Will people buy it or choose to use it? Will people be able to work out how to use it? And can the product be built with the time, skills and technology you have? There’s also a fourth key risk: business viability. Will the solution work for the business? In any team, different people have responsibility for ensuring each of these factors does not become a risk. In a feature team, it is the designer’s role to ensure usability while engineers are responsible for ensuring feasibility. However, there is nobody in the team explicitly looking after value and business viability. That comes down to the executive who requested the feature on the roadmap. If the executive says they need the team to build a feature, it’s because they believe that feature will deliver value and is viable for the business. However, this can cause problems down the track if they do not take responsibility when the feature hits the market and doesn’t deliver product-market fit. In a product team, value and viability are the responsibility of the product manager. That’s how empowered product teams reduce your risk of failure. An empowered team will make hundreds of decisions each day as they build the product and every single decision is reducing the risks of failure – they are not blindly following instructions and delivering what was asked in letter, but not in spirit. By contrast, delivery teams rarely have control over any of the risks. Often, the design and key technical decisions lie with external design and architecture teams. Their goal is to focus on delivery in the allocated time. ## Empowered Product Team vs Feature Team example One of Propel’s early projects was to develop an employee payroll app to allow employees to add their hours to a timesheet. The executive gave the team instructions to “create this pre-designed specific workflow which lets me, as an employee, punch in and record my hours” So that’s exactly what the team did. They designed and developed the workflow to achieve what the executive asked, and they considered it to be a job done. ### So, how would an empowered product team do things differently? An empowered product team would have been given broader context which would enable them to include a broader range of important requirements that an executive is likely to miss. For example, they could ensure the design worked well for a range of employee use cases, such as where only part days were worked or where people worked past midnight and the dates when the employee started and stopped work are different, and when the user is visually impaired. If the team is able to take the initiative to identify and incorporate these considerations early, they can build them into the design to cater for the needs of the variety of users, sometimes without any additional cost and avoiding rework. ## How to accelerate your development and innovation with Propel product teams When accelerating with a development partner, are you asking the partner to operate as a feature team or a product team? Remember, one of the major differences between a feature team and an empowered product team is whether they are tasked with deliverables to output or problems to solve. Often when businesses decide to accelerate development, they tend to augment their existing teams with development teams. These teams build what they are asked, focusing on outputs without the context or agency to drive the outcomes that constitute product success. This often leads to suboptimal outcomes or, worse, product failure. A better way is to find a strategic product development partner like Propel that has the skills and capabilities to add empowered product teams. These teams have the product, design and technical leadership required to ensure the right product is delivered – even if that ends up being a little different to what you initially expected or asked for. # The goldilocks solution to BAU: how to get it just right Source: https://www.propelventures.ai/blog/the-goldilocks-solution-to-bau Meta: 2022-06-14 · Paul Greenwell How do you harness market opportunities and move your business forward when you’re drowning in BAU? We’ve got some tips to help accelerate your business. So, you’ve built a successful product, launched and are ready to develop new features to capture new business opportunities. How do you meet the need for more Business as Usual (BAU) work, while also satisfying the demand for more features to grow adoption? You have all the momentum to scale and grow the business, but your team is stuck continually juggling the BAU work of responding to user feedback, making improvements, and maintaining tech security. Many companies underestimate the amount of BAU required and do too little, while others recognise the need for more BAU but get bogged down, missing the opportunities for growth. And if you’re ever going to capture emerging business opportunities and grow adoption, you really need to deliver new features. The value of spending time on new work is proven: According to Accelerate by Nicole Forsgren et al, high performers spend 49% of their time on new work versus 38% for low performers. Check out this diagram from Accelerate below. The question is how do you find the Goldilocks solution – not too little BAU, not too much – and get it just right? ## Use internal talent to help with BAU The biggest mistake you can make is to outsource your BAU. It might not be the sexy stuff but it’s the core platform and foundation of the system, and it needs to be kept in good health. In the early stages of a product’s life, you receive a high level of customer feedback, and it’s the team who built the product that’s best equipped to respond to this feedback. Using an internal team also means you aren’t putting your intellectual property at risk. ## Make BAU more visible Just to stand still you need to invest more. With your development team spending  time on BAU work, their capacity for new feature work will be limited to 50% at best. But this can be difficult for business stakeholders to get their heads around, especially when their focus is on growth. So, how do you communicate this to business stakeholders? Communicate upwards to ensure stakeholders understand how BAU is worth the investment now to avoid bigger issues in future. Explain what BAU is without using the phrase “business as usual”. For example, explain how you’re updating frameworks to limit exposure to viruses, or monitoring and improving stability of the system. Set expectations with how you frame the work and the language you use. The most important thing is to surface the risk, and implication of that risk to the business. The better you can frame it using customer and business outcomes, the easier it is to win buy-in. Ensuring you have good managers is key. Good project and product managers will be focused on what’s best for the business and can measure where efforts are going, which makes it easier to prove the value of BAU work. ## Scale the leaders and doers While the original team is focusing on BAU and has a limited capacity for new feature work, now is the time to hire product leaders and doers to work on new features. The ideal solution is to bring in a ready-made team that can operate relatively autonomously while moving forward with direction. Working with a strategic partner, like Propel Ventures, means you have an intact product team, including leadership, who have experience working together and the ability to act fast on new market opportunities as they arise. The advantage of bringing in a strategic partner is that you can keep momentum even while onboarding the team. When you hire externally, your internal teams need to dedicate time to upskill new hires, so there is often a hit to productivity while this happens. By bringing in a strategic partner, there is still a small hit to productivity, but it is minimised. You simply focus on onboarding Propel’s leaders, who will then onboard the rest. By scaling the onboarding, you can become productive as quickly as possible and accelerate towards growth. ## The bottom line Driving the momentum for growth demands a dedicated approach and an expanded team. With your product team focused on BAU and a strategic partner to work on new features, you can accelerate towards success and take your place as a long-term challenger in your market. # Need to move fast to seize the market? Here’s why you need to scale the whole team Source: https://www.propelventures.ai/blog/why-you-need-to-scale-the-whole-team Meta: 2022-05-03 · Paul Greenwell Scaling your business to chase a particular market opportunity is not as simple as just adding to your headcount and loading up your leaders. It takes a thoughtful approach to increase your performance as you scale up. To capture market opportunities, you need to move fast. And to move fast, you need to scale your team. That much is clear. Logic tells you to focus on scaling your delivery team. After all, it’s easy to scale up your technical brains-trust by throwing more talented people at the countless micro-tasks that arise to support and scale a product. But in practice, scaling only your delivery team will prove counterproductive, and hold your business back over the long-term. Instead, here are three pieces of advice on how to scale strategically. ### Scale your product team and engineering team in parallel It’s tempting to just bring in more engineers when you want to scale, but the challenge is making sure they are focused on the right things. If not, they will wind up just spinning the wheels and being inefficient due to lack of clarity. At the same time, bringing in more engineers will only put pressure on your product people if you don’t scale the product team as well. ### Build the management scaffolding to provide clear navigation Where you need standardised, modular, and repetitive technical effort for your product, it’s true that many hands make light work. But only up to a point. The reality is that scaling effectively isn’t determined by resources, but by how well you can continue to manage all the increasingly complex moving parts as they multiply. It doesn’t matter whether you have scaled your product and engineering teams – if they don’t have a clear vision there is no guarantee they are going to build the right thing. Rather, you will spend more money achieving less because the team is not going in the right direction or even if they are going in the right direction, they are not completely productive. Not only will you pay a financial cost, but you’ll lose time and pay an opportunity cost too. The solution is to build management scaffolding around bigger cross-functional teams and navigate them towards a cohesive product vision. This means bringing in more product and design leaders, who can ensure the team is led well. Most importantly, these leaders need to be aligned on what you want to achieve and be able to communicate the vision effectively. This will ensure many micro-decisions that product teams make every day are cumulatively moving the product in the right direction (read more on how to make a million correct decisions). ### Scale without losing control and overloading leaders A product and development leader is a leveraged role. If a product leader is stretched across more capacity than they can handle, it is potentially the work of five or more developers that is impacted, and the cost multiplies. It becomes more challenging for them to maintain context and alignment across teams, which leads to unintentional and unhelpful micro-decisions – all of which cumulatively add hidden costs to the product development. That’s why, if you’re looking to scale rapidly, it makes good business sense to engage a strategic development partner who can take up some responsibility. Ideally, it should be a partner with experience in leading businesses and products for success at scale. With a partner like Propel Ventures, you benefit from a combination of an internal and external approach to outsourcing. Our team is autonomous but works within the company’s infrastructure, meaning the company is part of the whole journey and you maintain control and quality even as you outpace your original expectations. Critically, this also means you don’t have to worry about the risk of handing over your IP and product knowledge to an external consultant. Instead, we always work within the company’s infrastructure and give you full visibility and ownership. Successful product scaling is not just about technical scaling – it comes down to optimising business processes and working towards a clear vision. That’s why the single most important aspect is to manage at scale. Without building the management structure and up-skilling managers to navigate a growing team of valuable talent, the company and product will lose its way. # myadvisor.ai - the codification of accounting knowledge Source: https://www.propelventures.ai/blog/myadvisor-ai-the-codification-of-accounting-knowledge Meta: 2022-05-02 · Paul Greenwell Propel developed a market leading advisory reporting solution which utilises artificial intelligence (natural language generation) to convert the numbers in accounting software into words. myadvisor.ai automatically generates management reports in minutes, which would otherwise take hours. Artificial intelligence continues to transform the way people work in every industry, and the finance sector is no exception. AI technologies have automated almost all manual accounting tasks including audits, payroll, tax and banking. Despite there being many attempts throughout the industry, for over 20 years, accountants still struggled to find the tools they needed to utilise the volume of data now at their fingertips. The options available to them were simply too complex or cost prohibitive. Seeing this gap in the market, Propel Ventures set out to give an unfair advantage to those accountants who were ready to explore the role of AI and automation in helping them reshape their roles and offer advisory services to their clients. The aim of this tool, later named myadvisor.ai, would be to allow accountants to generate a report filled with tailored information and insights in less than ten minutes. ### Challenge # Accountants and AI joining forces Accountants play an important role in supporting businesses with financial analysis and providing them strategic insights. However, the manual analysis of a company’s accounting data takes a great deal of time, and accountants had been forced to choose which of their customers were going to receive a high quality advisory experience or a low quality one. The baseline level of advisory service from accountants is a vulnerable point in the retention strategies of most practices. Accountants need to be able to prepare for an in-depth advisory discussion without hours of pre-work to study the trends in the numbers — if they are going to raise their standard of services across their entire customer base. With an innovative and creative vision of an AI advisory assistant in mind, Propel Ventures set out with a plan of intensive user testing, development and research that aimed to see this new advisory solution released to market in six months. ### Solution # AI-powered advisory reports Propel Ventures identified the power of placing the accountant who plays the roles of data custodian and advisor into the AI loop, to great effect. The AI solution designed by Propel Ventures scrutinises accounting data, identifies insights and crafts those insights into sophisticated natural language reports – accountants are then able to overlay their own commentary onto those reports and focus their time on having insightful conversations with their customers. The combination of natural language generation, with generally accepted accounting principles and AI algorithms are complementary and capable of producing valuable business insights and forecasts. ### AWS services used to deliver this application EC2, DynamoDB, S3, Route53, Cloudfront, Cloudwatch, ECR AWS Instances were provisioned in EUR, USA and AU to serve different markets and manage privacy and GDPR concerns. ### Outcomes # myadvisor.ai Propel developed a market leading advisory reporting solution which utilises artificial intelligence (natural language generation) to convert the numbers in accounting software into words. myadvisor.ai automatically generates management reports in minutes, which would otherwise take hours. myadvisor.ai was awarded an AFR innovation award and subsequently expanded from the Australian market to the US, Canada, Finland and Sweden (in Finnish and Swedish). “I have to say, it feels like cheating! Stuff that I have poured over and analysed over my career in accounting now at the click of a button! Incredible! I am very impressed.” “myadvisor.ai has been such an effective tool for our firm. It not only saves us time when creating reports but provides our clients with an insight to their financials that is easy to read and truly does help them make better financial decisions. The reports are top notch and a must if you want to provide the best service to your clients. You’ll definitely stand out with these reports.” # How do you make a million correct decisions? Source: https://www.propelventures.ai/blog/how-do-you-make-a-million-correct-decisions Meta: 2022-02-21 · Paul Greenwell This article shares how product managers can drive a million correct decisions over the life of a project and what happens if product management falls short. Every day, each member of a product team makes hundreds of micro-decisions that influence the product design and build. That’s thousands or even millions of micro-decisions over the life of the project. In the usual course of business, there is no way and no desire for leaders and managers to oversee or control every single micro-decision. If even a small proportion of those daily micro-decisions are incorrect, it adds weeks and thousands of dollars to the development and go-to market expense, not to mention the effectiveness of the product. So, how do you make sure that the cumulative impact of these micro-decisions results in product-market fit? The answer is ‘Product Management done well’. We have found that not enough executives understand what a product manager is there to do, and how their role is critical to building a successful business. Even product managers have their own divergent understanding of what a PM does, depending on the different companies they’ve worked for. That’s why Propel has chosen to support the Association of Product Professionals - we think that the APP plays an important role to communicate the purpose and practices of product management to ensure leaders within organisations understand the value of product management. Below I have shared some thoughts about the importance and the centrality of product management done well and have tried to paint a picture of the significant implications of it falling short. ## Picture a starling murmuration A murmuration is where hundreds or even thousands of starlings fly together in swooping, intricately coordinated patterns - like the one in this video. A murmuration is a dazzling display but it doesn't happen by accident; it happens because the birds are influenced by the movement of the group of birds around them. Think of it as large-scale coordination done well. The challenge with software development is that, without a central figure acting like the conductor, the product development and go to market flock will fly in all directions and will not achieve their equivalent of a beautiful murmuration - product-market fit. This coordination role is uniquely the job of the product manager. Many product managers don’t think about it, but a core part of their job is to facilitate decision making - in other words, ensuring the right micro-decisions are being made at every stage. Some are obvious decisions, such as what functionality to include in the first iteration. But when you go down another layer, almost every aspect of a feature requires a multitude of micro-decisions to be made - from scope to tech to design to copy. The product manager’s challenge is not to make every single decision but to facilitate these micro-decisions effectively. ## How can product managers drive a million correct decisions? The product manager has a secret weapon: context. Product managers provide the much-needed context for team members right across an organisation. That context forms the basis for thousands of discretionary micro-decisions made by a diverse mix of team members, from day-to-day coding undertaken by engineers to marketers as they draft copy for the target audience. Providing context can be something some product managers do naturally without realising. Often product managers might feel frustrated because they have spent a day ‘talking’ with people across the business - it might seem like they haven’t delivered something for the day. But what they have done is provide context to the team members - and that’s critical. Without that context is where things start to fall apart. You start to see misjudged micro-decisions. Let’s say product and development leaders are stretched across more development capacity. It becomes more challenging for them to maintain context and alignment across offshore or augmented teams, leading to unintentional and unhelpful micro-decisions which cumulatively add hidden costs to the product development. Another way to think about the impact of poor micro-decisions is to think about your golf swing. A small imperfection in your golf swing has an impact on your overall golf score. A small slice can result in the ball being further away from the pin, adding an extra stroke or two to each hole. At the end of each round, the extra strokes add up. Instead of going around the course in 100 strokes, it could be more like 120. ## Why you need the right culture There’s another important element that helps product managers drive effective decision making in their team, and that’s the right culture. It is reasonable to assume that all team members act with good intention, but without the context and coaching provided by product managers, the product development process is littered with unintentional and unhelpful incorrect micro-decisions. With the right culture, product managers will be empowered to provide the context and leadership to help their team make a million correct decisions and create the best product-market fit. In the future, we would hope that the work of the APP can assist executives to understand what a product manager is there to do, and how their role is critical to building a successful business. We think that it is so critical that we have built a business to showcase the impact of great product management. # 4 Ways To Kick-Start Your Journey into Product Management Source: https://www.propelventures.ai/blog/start-your-journey-into-product-management Meta: 2022-02-21 · Paul Greenwell Thinking of starting a career as a product manager? We reveal the top resources to kickstart your product management journey in our latest article. From the outside, the role of a product manager isn’t always clear-cut. It involves customer research, product development, user experience, engineering, design, and even marketing. That’s a lot of skills and knowledge to build. One attribute you definitely need to succeed in product management is a desire to learn. That’s why the best place to kickstart your PM journey is by gathering as much intel as possible, then distilling it to work out where you need to focus on building your skills and knowledge. In this article, we’ve gathered the best resources to kickstart your product management journey. Let’s dive in: ## Learn from the pros Start by gathering knowledge and advice from product management pros. This Quora page is run by Ian McAllister, former director at Amazon and one of the best product managers around, so it’s a great place to begin. You’ll find answers to questions like: What distinguishes the top 1% of product managers from the top 10%? Spoiler: You need to think big, communicate, simplify, and prioritise. Want to fill your Twitter feed with product insights? Follow these product management folk for bite-sized PM wisdom and vibes: Ian McAllister – Product leader, operator, advisor and former Amazon leader who created @AmazonSmile. Josh Elman – Product leader and investor in Silicon Valley known for leading the growth and engagement teams at Twitter and LinkedIn and launching big platforms (Facebook Connect/Login). Keith Rabois - American technology executive, investor and currently a general partner at Founders Fund. Known for his early-stage start-up investments and his executive roles at PayPal, LinkedIn, Slide, and Square. ## Top up your skills Product management requires some very specific skills. That’s why here at Propel, we encourage our product managers to complete one of the Brainmates courses – like “Essentials of Product Management” and “Financial Fundamentals for Product Managers”. If you’re not sure where to focus, head over to the Association of Product Professionals. This new association, which Propel is supporting, is on a mission to advance the profession of product management. Complete a skills assessment to find out which skills you should focus on, and most importantly, how to fill those gaps. The framework identifies five distinct levels of career mastery and defines the 26 skills in the product management domain: ## Read a book If you only read one book on your product management journey, make it this: Inspired: How to Create Tech Products Customers Love by Silicon Valley Product Group. It delves into how today's most successful tech companies (think Amazon, Google, Facebook, Netflix, and Tesla) design, develop, and deploy the products that have earned the love of billions of people globally. Want to extend your reading list? Here are some suggestions based on your area of focus: ## Dive into expert content If you love receiving nuggets of wisdom in your inbox, sign up to the short blogs from Mind The Product. You’ll find insightful articles on a wide range of PM topics, from What exactly is a product manager? to How I got my job in product and Driving customer adoption and retention as a product manager. If you prefer to listen to your content, the Association of Product Professionals has compiled a handy list of the top product podcasts to follow. ## Connect with local PM groups There’s nothing like meeting up with like-minded product gurus and nerding out over the latest product management framework. Check out your local product management communities for face-to-face talks, meetups and conferences. For example, in Melbourne, there’s Product Anonymous and Product Tank. To find your local groups, head to Meetup. Now, it’s over to you.. # How to move fast and get rapid results for your investors Source: https://www.propelventures.ai/blog/get-rapid-results-for-your-investors Meta: 2022-01-25 · Paul Greenwell So you've won venture capital investment? Congrats! Now you're faced with a big question: how do you move fast and get rapid results for your investors? So, you’ve found backing from a venture capital firm for your product - congratulations! Now, the real work begins. The thing about investors is that their big cheque comes with a few big strings attached. VC investors expect you to deliver rapid results to capture market share and win the land grab. The reason for this is simple: they need large exits to clear their hurdle rate and make up for investments that don’t work out. The bottom line? You need to move fast. How do you do this? ## Option 1: Bring in more product developers You might think that the best and easiest option is simply to bring in more product developers. After all, you just want to get the product out there in the market fast, so throwing more resources at it is the best way to achieve this, right? The answer is yes…and no. You do need more development firepower, but the question you should be asking is how best to achieve that. The big drawback of outsourcing your product development team or augmenting your team with more developers: you and the VC wind up with more people to onboard and manage, which means a bigger drain on their investment and your time. Then you need to wait while the new people actually become productive. So what’s the alternative? ## Option 2: Bring in a strategy development partner You don’t need to permanently scale your product leadership to temporarily accelerate your roadmap and hit the milestones your investors expect. Working with a strategic development partner, like Propel, gives you access to the appropriate product and technology leaders and delivery team with the capability to deliver without putting extra management burden on you and your current leadership team. Why is this approach to increasing development velocity better than a body shop or staff augmentation model? Here are three advantages: ### 1. It takes a product and user led approach to maximise product-fit. At Propel, we spearhead our teams with a combination of Product Management and UX to ensure that user, workflow and business needs are understood and always central to the product development approach. ### 2. The team is productive as quickly as possible. We’re not adding a developer here and there. Instead our teams are intact product teams who have experience working together and have already formed, stormed, normed and are performing. ### 3. We minimise the management requirement on you (but you retain control). Our experienced leaders manage Propel team members and work autonomously within your business, giving you full visibility and control without taking up valuable managerial bandwidth. This is important because, in rapidly growing businesses, there is already significant overhead on internal product and delivery leaders. Propel’s product and delivery leaders still report into your structure - that means Propel product managers report into your product leader, and so on. Most importantly, we do more than develop products. We will guide you and your business through the development cycle, focusing on building the right product to capture market opportunities quickly - just as your investors expect. Because our team is there through every stage, unlike an outsourced team of product developers, we can stay close to customer feedback so there’s never a risk of missing the market fit with unnecessary features. So, you can maximise every dollar of your investment and get your product to market faster. This is especially important as you start thinking about the next round of investment. Series B investors will be looking at the momentum you’ve already gained and how you are planning to scale and grow. The right strategic development partner will help you do that. ### Are you a start-up or portfolio company looking to create product-market fit, faster? Contact our founders Ben or Paul at Propel Ventures to find out how we can work together. # The value-add venture capital firms need to accelerate market success Source: https://www.propelventures.ai/blog/value-add-venture-capital-firms Meta: 2021-12-16 · Paul Greenwell If you’re a venture investor in today’s market, a big cheque alone won’t win the best deals. Value-add services have become the true differentiator. The venture capital ecosystem is more competitive than ever before. Smaller local investors are increasingly competing against big money from Silicon Valley, New York and Singapore, along with a growing number of hedge funds, angel investors, and other power players. The bottom line? If you’re a VC operating in today’s market, a big cheque alone won’t win you the best deals. Reputation and a great track record helps, but it’s the additional services and capabilities offered by venture investors that have become the true differentiator. After all, the odds are stacked against founders. Industry statistics show that somewhere between 65% to 75% of VC-backed startups fail, proving that funding alone doesn’t guarantee success. That’s why value add has become more than a ‘nice to have’ - it’s table stakes. But not all value-add services are created equal. In research by UK firm Forward Partners, almost half (49%) of founders reported that value-add had no impact on their business at all. So, if VCs are going to truly make an impact, value-add should be results-driven, and focused on driving clear outcomes. ### You need to help founders achieve product-market fit faster. We’ve seen first hand at Propel that a key area VCs can add value to their company portfolio is through accelerating to achieve product-market fit, faster. But how do you offer this when you don’t have your own army of developers and product managers on hand to deploy to the startup? That’s where a product strategy development partner offers a key advantage. Let’s be clear - we’re not talking about a team of product developers. While product developers will build the product to spec, that’s where their services usually end. They won’t continue to test and utilise customer insights and feedback throughout the development process, which means the product won’t necessarily be the right fit for the users or market. Nor will they work shoulder-to-shoulder with you to seek out process and cost efficiencies to get the product to market faster, meaning you might miss out on the market opportunity altogether. Another big drawback of outsourcing your product development team or augmenting your team with more developers is that you wind up with more people to manage, which means a bigger drain on investment and time. If you double the delivery team, you also have to double the leadership team, which places strain on existing internal delivery leadership. Your leaders will be saddled with more people to onboard and manage, and it takes time for the people added to actually be productive. There is also the issue of how outsourcing or augmenting your product development team affects quality. None of this is adding value to your company portfolio - it’s adding risk. ### The solution is in choosing a strategic development partner. You don’t need your portfolio companies to burn precious cash by permanently scaling their product leadership to temporarily accelerate their roadmap. Working with a strategic development partner, like Propel, gives your portfolio company instant access to the appropriate product and technology leaders and delivery team with the capability to deliver - without placing undue management burden on the existing leaders in the business today. At Propel, we hit the ground running with leaders and teams that are already well-structured and performing. We work autonomously within the business, giving the business full visibility and control without taking up valuable managerial bandwidth. Most importantly, our specially assembled team of product and delivery practitioners do more than develop products. Propel teams guide the business through the development cycle, focusing on building the right product to capture market opportunities quickly. Because our team is there through every stage, unlike an outsourced team of product developers, we can stay close to customer feedback so there’s never a risk of missing the market fit with unnecessary features and wasted development. So, you can add real value to your company portfolio and, most importantly, maximise the value of your investment, faster. ### Are you a VC looking to create better value add? If you are a VC who wants to help your portfolio company to capture a clear market opportunity, or if you would like some help with technology or product due diligence for a target company, contact our founders Ben or Paul from Propel Ventures to find out how we can work together. # 6 strategies for accelerating product delivery Source: https://www.propelventures.ai/blog/6-strategies-for-accelerating-product-delivery Meta: 2021-09-29 · Paul Greenwell The Propel Way™ to accelerate product delivery is a framework for onboarding, managing, and optimising resources that scales with you. Time to market is an extremely important factor when it comes to product success. How quickly can you build, refine, test and roll out a product? Can you do it before a competitor does? To counter rapid progress from your competitors, your organisation must be able to speed up product delivery as quickly as possible. We see many organisations try to do it themselves, and they usually run into trouble. One mistake we often come across is when a company rushes headfirst into a product development project without a clear idea of the exact problem they are aiming to solve and for whom. A common mis-step is to start by looking for a development bodyshop that can quickly hack together a minimum viable product. In both cases, the mistake is leaping straight into the software development  phase without a clear view of the problem to be solved, the customer segment, the unique value proposition of your solution and your go-to-market approach. Without answering these key questions market success is unlikely. Without a clear product strategy, you’ll find that costs quickly blow out and any time advantage you could have gained evaporates. With these challenges in mind, there are a few proven strategies Propel has developed that help sidestep the common issues we see which prevent you from gaining traction when you need to accelerate. The following is your high-level guide for accelerating product delivery effectively, and efficiently. ## The 6 key strategies for accelerating product delivery ### 1. Don’t burn out your existing managers While you're thinking about taking on the adventure to capture an attractive new market opportunity, your managers are likely already at their managerial capacity. You can’t just add more people to a project and expect your managers to handle managing the new team members on top of their current workload. You need a sustainable way to add horsepower to your development efforts without burning out your existing managers. That means you need to be able to scale the ability of your managers and leaders to manage teams in proportion to your growing resources. Software development is a time and cost-intensive enterprise, and bigger teams mean bigger spend. The best way to reduce that spend is to support your managers with the right mix of skilled roles—e.g. product management, engineering, quality assurance, UX—to ensure that the work being done is focused, and minimal effort is misdirected or wasted. ### 2. Identify the right areas to accelerate Accept that some parts of the business will not yet be ready to accelerate. You need to focus on the part of the business that is best positioned to accelerate without slowing down the others. For example, many businesses have an older core of technology that’s only well understood by a small number of senior staff. The higher degree of difficulty involved in accelerating an older tech stack means it’s less fruitful to start your acceleration efforts in the area of code that is least understood. Instead, it is usually more effective to expose specific functional elements of the core first, enabling related parts of the business to move faster. For example, exposing core APIs to open up new ways for the business to engage with the data held there. At Propel Ventures, we have a pedigree of highly experienced technical process managers, skilled at identifying the optimum candidate pieces of work ripe for acceleration. We start by considering the technology used, the client’s organisational structure, and the business opportunity involved, then sketch out a roadmap for accelerating by area, in stages. ### 3. Ensure your scaling efforts focus on the right goals Acceleration is most effective when it’s focused on aspects of the business where immediate and obvious value is clearly visible. A clear business case with a discrete deliverable to aim for is a great place to start your acceleration journey. For example, we recently developed a tablet app for a client, and the delivery of the app was a precondition for a lucrative renewal of the annual license fee for a large client. Having clarity around the business objective enabled us to reach the goal more quickly and efficiently, with great outcomes for the end user and our client. ### 4. Strike the right deal It can be challenging to iron out the right deal with your product development partner, but only if you haven’t done the appropriate groundwork. If the business and customer problem is clear, the APIs to deliver are available, and the development pathway obvious, it's a lot easier to align incentives with your development partner in commercial terms. Signing a fixed price deal to deliver specific functionality, with an agreed level of customer satisfaction, will strongly align your interests with those of your development partner. When the mission is larger, more innovative or experimental, and the journey is more likely to vary, a time and materials arrangement is likely to work best. Any agreement should have the appropriate level of governance and agreed milestones to track progress. Since Propel is founder-owned and led, we can take a more flexible approach to the typical commercial relationship. We like to partner with our clients, sharing the risk of delivery and aligning our interests with theirs. That means while we can always work with you on a daily rate, we prefer to aim for the same goal that you have. ### 5. Accelerate with the right governance Always make sure you have the right governance mechanisms in place. This makes sure stakeholders have input and can course-correct if necessary. Lightweight check-in meetings with stakeholders to get timely feedback and identify issues early are also essential to nip any problems in the bud. Propel teams prefer to work alongside the existing practices and rituals of your in-house teams. This allows us to share our way of working and ensure that the applications we are developing are in accordance with your standards, can co-exist in your technology stack and will stay supportable long after the initial acceleration to bring them to life. ### 6. Accelerate with a tight belt too The traditional approach to scaling through outsourcing or augmenting teams may look financially attractive at first glance, but comes with a host of micro-decisions and hidden costs that can quickly spiral out of control and crash your acceleration efforts. This is not due to technical capability or intent; it's simply due to the nature of the process and the product managerial oversight involved. Propel’s strategic development partnership approach with intact product teams has been developed specifically to address this problem and keep the cost of development down. The proof is in the pudding: Propel has delivered 8 of our last 9 projects on time and all of them on budget (one project ran for 19.5 months instead of the estimated 18, however the project was still delivered on budget because Propel picked up the cost for the final 1.5 months). ## These 6 strategies are built into Propel’s way of working With Propel as a strategic partner, your product and development leaders won’t lose control of the product or development process. Instead, their role becomes one of managing the strategy, development, and quality standards that their teams can then follow. Your leaders can be confident that the right product is developed to the right standards, while Propel product leaders and teams manage the day to day of your product development. Every one of the strategies outlined above are powerful ways to accelerate your product delivery, while keeping a tight grip on all the factors that can cause cost blowouts or delays. Talk to us about how we can support your project and help you accelerate when and where it’s needed most. # Micro decisions killing your product development (and your golf game) Source: https://www.propelventures.ai/blog/micro-decisions-killing-your-product-development Meta: 2021-09-23 · Paul Greenwell On the surface, offshoring or augmenting your existing teams can look like a cost-effective approach to accelerating product delivery. However, most companies don’t realise the cost of compounded poor micro-decisions can be huge. Traditional approaches to accelerating product development often involve augmenting your existing teams with additional developers or outsourcing under the direction of your product and development leaders. This initially looks like the cheapest option to accelerate product delivery, particularly if you outsource overseas, and budget is a concern. However, augmentation and outsourcing can end up costing you a lot more than you originally planned. In most cases, the initial top line figure does not reflect the accurate final cost because it assumes that an offshore or augmented approach to scaling will produce the right product features and the right level of quality in the timeframe you need — this is usually not the case and below I will explain why. ## Compound interest of poor micro-decisions As your product and development leaders are stretched across more development capacity, it becomes more challenging for them to maintain context and alignment across offshore or augmented teams. Stretching leadership bandwidth across outsourced or in-house augmented teams leads to unintentional and unhelpful micro-decisions which add hidden costs to your development project. The cumulative impact of misjudged micro-decisions has a negative compounding impact on the cost of software projects. You can consider the impact of micro-decisions similar to the impact of a small imperfection in your golf swing on your overall golf score. A small slice on a golf swing can result in the ball being further away from the pin, adding an extra stroke or two to each hole. At the end of each round, the extra strokes add up. Instead of going around the course in 100 strokes, it could be more like 120. That extra 20 shots are what reflects the impact of incorrect micro-decisions with each swing. When you focus on the top line figure for an offshore or augmented team, you must also consider the impact of the sum of thousands of discretionary micro-decisions made during day-to-day coding undertaken by developers of your product. There is no way for your managers to oversee or control each of these micro-decisions, so even when the small proportion of those daily micro-decisions are incorrect, it adds weeks and thousands of dollars to your development and supportability expenses. ## How a strategic development model helps you accelerate Propel Ventures has a record of delivering better quality products in less time and at a lower overall cost because we understand the compounding impact of these micro-decisions. Our last nine major projects were all delivered on time and budget, demonstrating that Propel Ventures delivers more cost-effectively than the traditional approach to scaling due to the process, context and experience of the Propel Ventures team. To ensure the correct micro-decisions are made, Propel Ventures has a product management culture and process, which ensures that our team members are laser-focused on building the right thing, well. As part of the Propel Ventures software development process, the teams continually test, distil and disperse client feedback into the team members, leading to continuous course correction and refinement. Without this course correction, you increase the risk of your end product not being user-friendly, missing the product-market fit and increasing costs. Additionally, we augment your current team by fitting inside your program of work by working inside but adjacent to your business to ensure maximum efficiency without distracting the existing team too much. The Propel Ventures model also serves to build upon your existing internal structure and technology in your teams — which means less disruption and more productivity, and final savings. If you want a solution that won’t cost you even more money over the long term, contact Propel Ventures today. ## Hear how Propel is different from other development partners # How The Propel Way™ steers you away from product failure Source: https://www.propelventures.ai/blog/how-the-propel-way-steers-you-away-from-product-failure Meta: 2021-09-11 · Paul Greenwell Product launch failures give us key insights into where others went wrong, so that we can avoid the same mistakes. A lot of time, cost and effort goes into bringing a new product to market. In many cases, the launch of a product can make or break an entire business. There’s a tendency for many stakeholders to tune out negativity so they can cultivate a winning attitude within organisations. But closing your ears to any unwelcome input risks cognitive dissonance, turning into a situation where no one wants to voice concerns for fear of upsetting the apple cart. It's no surprise when environments like this fail to launch a winning product. To gain insights about the path to success, it’s important to deeply understand why products fail and the factors that lead to product failure. ## Why do products fail? It’s difficult to nail down every type of product failure in one article, given the vast range of factors that can contribute to an unsuccessful launch. However, we can define several broad categories of failure that these product launches generally fall into. ### Poor execution leading to a failure to meet the customer’s needs Even a good product idea can fail if its execution misses the mark. In practice, that means that the need for the product or problem exists, but the solution is either poorly designed or poorly built. Generally this is a product that hasn’t been tested with users throughout the development process, and fails to address real-world user needs. In other words, when expectations for the product don’t match the reality of the user. Potential customers who have a legitimate need may even check out the product, but still decide there’s not a compelling enough reason to change from an existing solution. ### Technology looking for a problem Many products are influenced (or in some cases, blinded) by a “data point of one”—an influential leader whose own opinions and ideas guide development without user testing or validating with the market. The HIPPO (Highest Paid Person's Opinion) in the room is a very real phenomenon, and can easily lead down the path to failure. For example, a well-meaning but misguided VP may become enamoured with a particular technology, and are now looking for a problem to solve with it. It’s remarkably common for even experienced, mature companies to get excited about a technology and then try to carve out a market for it, while struggling to find a real customer need. ### Poor company fit In this case, there may be a real customer need to address, but the solution is not a good fit for the company’s strategy, its positioning or its area of expertise. That means the product will not get the priority or long-term support it needs to make it a success either during development or at the go-to-market stage. ### Ineffective marketing ‘Build it and they will come’. If only that was true in the world of product development. It’s a highly competitive market out there, which means your product needs to stand out and make waves in the right crowd to get any traction. You can have the most effective and well-designed product in the world, but if no one has heard of it, it’s not likely to succeed. Many companies underestimate the sheer amount of time, resources and effort it takes to reach audiences in a crowded market. ### Tactical instead of a strategic approach Short-termism has led to the premature death of countless products. A short-term, non-strategic mindset encourages a scattergun approach, leading to managers throwing a series of product ideas at the wall to see what sticks, with no real intent to commit to further developing any specific one unless they find success by chance. Not only does this line of thinking cripple the chances of product success, but it’s also a huge blow to a company’s reputation. Any trust that the company can effectively deliver and support products is all but eroded by abandoned product lines. ## A successful strategy helps avoid failure A well-thought-out plan that factors in immediate, mid-term and long-term goals serves as a great compass for product development. Strategising at every step minimises the small risks that accumulate along the way such as time and cost blowouts. It also offsets the chance of overall product failure by ensuring key benchmarks of user acceptance and market-fit are met consistently along the development pipeline, informing and guiding it with time to course-correct. We often assess need by looking at the gap between the importance of the customer’s job to be done and their satisfaction with the current solution. If the job is important and satisfaction is low with the current solution, then there is an opportunity to strike gold. A solid product development strategy should align to the business strategy, solving a valuable and validated customer need where there is a big enough opportunity to make the investment worthwhile. ## The ROI of strategic product development A strategic partner helps design the qualities that are critical to product success into the development process itself. They can steer efforts from a higher level vantage point, drawing from a wealth of experience launching similar products. As specialists, they have rich experience of what works and what doesn’t, and can foresee and pre-empt the countless number of traps, risks and assumptions inherent in any product development initiative. Strategy alone is not sufficient though. The need to execute well is paramount, and the key to turning a great blueprint into a successful product. Execution encompasses iteration, learning, and closing the feedback loop to ensure that the product strategy continues to align with user insights. Product leaders must be involved and across everything needed to evolve product design and strategy along the way. A strategic partner doesn’t only help to create the strategy, but ensures its successful execution too. Talk to us about how to build a more effective product strategy, and how we can work together to steer your development process away from common pitfalls and toward success. # How to choose a development partner who will help you scale Source: https://www.propelventures.ai/blog/how-to-choose-a-development-partner-who-will-help-you-scale Meta: 2021-09-04 · Paul Greenwell Your next product can benefit from applying The Propel Way™ to scaling challenges, optimising for a trajectory of long-term success after launch. Many businesses often view getting a great product to market as the finish line, without realising that the window for compounding initial success to dominate their space can close quickly. Creating successful products and scaling successfully can seem like very similar disciplines, but they’re two distinct objectives that can sometimes pull your teams in opposing directions. ## Planning for what comes after success Becoming successful overnight is a common trope in tales of catastrophic failure. Many product leaders have a detailed blueprint of how to push their project up the mountain but don’t anticipate that their strategies must quickly realign to remain at the pinnacle. The different skill sets needed when transitioning from disruptor, luring the earlier adopters, to incumbent, where you convert the early and late majority, can take some by surprise ― particularly when the whole organisation has been laser-focused on product launch for so long. Many very successful products have left their creators with the dilemma of how to allocate resources to support production while maintaining the required focus on the customer to scale. Too many resources diverted to supporting production can throttle innovation, which lessens the impact your product has on the market and derails launch momentum, however not addressing the production issues and feedback of the existing users can result in churn and loss of goodwill. By thinking that the product launch is the finish line, businesses often reduce capacity at the time that demand becomes greater due to these needs to support existing users while continuing the development, optimisation, and marketing of the product to attract the next cohort of users required for scaling. The result is often that staff are spread too thin across multiple activities leading to diminishing returns in productivity. The shift in momentum, moving from launch to scaling, can either be turbulent, or a seamless change of altitude, depending on how effectively you manage scaling operations alongside the growth of your business. That’s where it helps to have a strategic partner with experience optimising leading businesses and products for success at scale. ## How a strategic development partner helps you scale effectively A strategic development partner with proven success in your space and a broader view of the marketplace lets you hit the ground running with a skilled pool of already-structured talent and subject matter experts. Your strategic partner helps you plan for success by ensuring that the products being built are scalable and supportable once the products are in market, reducing the production support burden and allowing more capacity for you to remain ahead of competitors who will come for a slice of your niche. The insights gained from bringing similar solutions to market are an invaluable asset and help you hedge against many of the risks that your new product will face. Key to the scaling challenge is the way a strategic partner can help carry the load both pre and post launch without a lengthy onboarding or integration period. Many businesses attempt to address internal resourcing challenges by outsourcing product development to a service provider whose remit covers only delivery of the product but do not stick around to help support and scale the product post launch. Technology “body shops” that code to order without a strategic vision or interest in market success often lack the knowledge and incentive to ensure that the product is supportable as it scales. They also lack a rigid internal project management structure, burdening your team with additional management overhead. Without the strategic vision and history of delivering products like yours to market, technical resources become more cumbersome to manage at scale. This touches on one of the key reasons that businesses fall short when attempting to scale rapidly. It’s easy to scale up your technical brain-trust by throwing more smart people at the countless micro-tasks that arise to support and scale a product. In the case of standardised, modular repetitive technical effort, it’s true that many hands make light work. But only up to a point. It’s a much finer art to put a cohesive management scaffolding around bigger cross-functional teams and shepherd them towards a cohesive product vision. Scaling effectively then isn’t determined by resources, but how well you can continue to manage all the increasingly complex moving parts as they multiply. ## The Propel Way™ to scale We often get a call when our clients need to accelerate to capture a particular market opportunity. A lot of factors can come into play to bring about that scenario. Perhaps a startup has arrived on the scene to threaten an incumbent, or there’s been an extraordinary amount of investment by a particular player in the space. It may be private equity coming into an industry, or natural disruption like we see in the energy industry with the move to renewables. Megatrends, black swan events, shifting sentiment, economic and commercial interests can all begin to align in ways that create a fertile environment for accelerated innovation to achieve early market capture. That’s where Propel tends to be engaged, and where we do some of our best work. We’re an advocate for the end user, and for the business problem to be solved at the same time. A problem we’ve encountered with other service providers in our space is that they tend to rush into building without fully understanding the customer and the business opportunity. Where we have most success is where there’s a clear idea of the problem that the client is trying to solve. They may not have a solution, or see the path to solve it yet, but they have the resources to chase a particular market opportunity. How we differ is the cultural drive at Propel to first validate the problem and business opportunity, then validate whether the product idea as proposed is going to achieve product-market fit. We have the capacity to iterate and innovate, informed by constant feedback from the customer. ## Grow your management to manage your growth The story of your product doesn’t end at launch, it simply turns a corner. Propel’s plan for long-term product success takes into account not just how to launch successfully, but how to translate that momentum into continued growth. Therefore our engagements generally do not stop at the technical delivery. We stick around to see the product become successful in the market and scale. This means our incentives are aligned with yours to ensure the product is supportable and scalable as it will be our problem to deal with if it is not. Successful product scaling however is not just about technical scaling, but optimising business processes around that aim as well. The single most important aspect of evolving your business operations around the logistical requirements of scaling is growing your capacity to manage at scale. Throwing technical resources at a problem will work, up to a point. Without building in the management structure and skilling up managers to direct a growing pool of valuable talent, you will under-utilise and ultimately lose that talent to attrition. Propel Ventures has helped clients address challenges of scale across a range of industries and disciplines. We believe in a management-focused approach to scaling, and that’s why we’ve applied those principles internally. We’re eager to share our insights about why this works, and happy to discuss how it can help you. Get in touch if you’d like to know more. # Building Products The Propel Way™ Source: https://www.propelventures.ai/blog/building-products-the-propel-way Meta: 2021-08-30 · Paul Greenwell Your next product can benefit from applying The Propel Way™ to its development process. Propel Ventures is laser-focused on making products that solve real user problems, positioning them to stand out in a crowded marketplace. We do this by partnering with our clients to apply The Propel Way™ of Product Strategy, Development and Management for building products that people love to use. ## What is “The Propel Way™”? The Propel Way™ is a structured approach to developing technology solutions, shaped by our experience delivering successful products to market for a range of clients, and driven by our award-winning people-first culture. It’s a collaborative approach that allows for maximum adaptability and creativity, within a rigorous framework optimised for launching successful products. The methodology addresses three key areas when embarking on a product development journey: Strategy, Development, and Management. ## Product Strategy Propel helps clients identify opportunities and articulate strategies that the whole business can rally behind. We back-test new ideas against real-world conditions and help our client narrow down the trajectory of product development to achieve its maximum potential in the marketplace. ### Testing & Alignment The clients we partner with come to us with brilliant ideas, but before they invest they need to test their hypothesis in-market. This is where Propel’s experience and high-level view of the technology space can help. We use data gleaned from user-testing to show our clients exactly how their idea stacks up with the competition, and help them focus on the areas with the highest value-to-effort ratio. ### Confidence & Buy-In Our clients pursue their new product opportunities with confidence, knowing that Propel has validated product-market fit and their desired outcomes. We clarify the opportunity for our clients and crystalise it into a compelling value proposition that will resonate with the intended customer. ### How does it work? Our clients first engage with our strategy practice, which is made up of expert practitioners, who each have a depth of experience in financial and SMB services. Then, we use best-practice tools to distill exactly what the opportunities are for a proposed product, and a hypothesis covering the best way to leverage them. Some of the activities we may carry out while providing our Product Ideation service are Exploratory research using the four-diamond discovery framework, Hypothesis formulation and testing, Technical due diligence and asset review. By helping you figure out the answers to your questions and producing these outputs, we gain a shared, contextual understanding of your idea, your business and your intentions. Common outputs you will receive from this process include four-diamond research findings, a set of confirmed or disproved hypotheses, Propel's hypothesis governance framework, and a clear and decisive set of recommendations. ## Product Development Propel and our Product Delivery teams get our client’s live product into the hands of customers on schedule, helping to iterate and find that sweet spot for perfect market fit. ### Design & Management Propel's dedicated team of experienced Product Managers drive the end-to-end product lifecycle, from inception through to launch and rapid growth in market. Propel’s 1st class Product Delivery capability is supported by our team of customer-obsessed User Experience Designers and Service Designers. ### Accelerated Development Propel’s software development practices have been fine-tuned through diverse partnerships and ongoing collaboration with some of Australia’s most successful software brands. Propel development teams rapidly deliver software to market, ensuring it runs as intended and iterating rapidly to achieve the perfect market fit for our client’s product. ### How does it work? Our clients have a range of business goals and success benchmarks to reach. Some are facing new challenges, entering new markets, or simply adjusting to the new normal. Propel will hand-pick the perfect team to help deliver best-in-class software that aligns with your technology infrastructure and resonates with the end-users. Propel teams are the perfect blend of big picture thinkers and technical experts, all focused on delivering the best outcomes possible. Through their customer obsession, craftsmanship and drive, they strive to make a real-world impact with the work they do. Our clients can capture product market opportunities faster with the support of Propel product delivery teams. We apply our bias for action to achieve their business objectives and let the result speak for itself. Having the ability to act fast on new market opportunities enables our team to identify new opportunities during development as they arise. Propel teams don’t silo knowledge and insights to generate future work or keep clients dependent on our services. We document processes effectively, socialising product and technical thought leadership to upskill our client’s teams, supporting their autonomy as needed. ## Product Management Propel's dedication to product management and the experience of our Product Managers guide your product through all of the development stages with a practised, methodical approach based on data, feedback, and real-world conditions. ### Design & Depth Propel’s industry-leading product management capability is supported by our team of User Experience Designers and Service Designers. We keep our eye on trending tastes and market sentiment, stay across new insights and best practices, and lean into challenges that let us devise novel solutions. ### Accelerated Deployment The Propel Way advocates releasing frequently and iterating rapidly in response to user needs, to continue optimising and always ensuring continued market fit. ### How does it work? Propel takes the risk alongside our client by being responsible for a product’s ongoing iteration and development in response to market feedback and conditions. When we partner with a client, we commit to long-term success to not only ensure the product makes it to market, but grows from strength to strength. The Propel Way™ is about guiding products through all stages of the development process, then closing the feedback loop by diving deep into user experience and converting responses to actionable steps for our client. This process needs a deep understanding of market conditions and the ability to sort essential features from the nice-to-haves. ## Ask us about The Propel Way™ If you would like to ensure your next product gains fast traction in the marketplace, or just need an experienced hand to guide it to long-term success, contact us to discuss how The Propel Way™ can elevate and optimise your development process. # How your development partner can make or break the success of your product Source: https://www.propelventures.ai/blog/how-your-development-partner-can-make-or-break-the-success-of-your-product Meta: 2021-08-23 · Paul Greenwell Many development partners will build your product to order, but a strategic partner also helps optimise for market-fit and long-term success. ## The Product Development Journey If you’ve previously set out on a journey of product development, you may have stumbled upon a disconnect between your ambitions and the learning curve involved to make it happen. The battle to bootstrap a product from good idea to industry disruptor is fought and won in the details. First, there’s the obvious surface-level detail; the customer pain points to solve, and the technical challenges you intend to overcome with new thinking. Then there are the hidden details that lurk beneath the surface, such as product-market fit. If left unchecked, they might end your product journey before it begins. When entering a new market or creating something entirely new, product development needs an experienced navigator right from its inception. Choosing a development partner that has a high-level view of the landscape and a proven track record of bringing successful products like yours to market is key to getting it right the first time. ## What to Consider When Choosing a Product Development Partner One of the biggest things to be aware of when you begin vetting product development partners is how widely the various types of development and consultancy firms in this space differ. It’s important to know whether you’re dealing with a strategic partner who cares about the fit and ongoing success of your product, or a “body shopping” operation that will build your product to spec without taking on any of the risk involved in its success. For this broader analysis, we can break down the types of partners you might engage on a product development journey into three distinct categories: Here are some of the questions to consider before committing to any development partnership: ### How will your partner help determine product-market fit? The first steps you take toward a minimum viable product will be determined by how real people want to use it. Will it align to expected user experience norms or completely overhaul how people expect to interact with it? What do real users in your market think about that decision? When they eventually test a proof of concept, does the reality line up with those initial expectations? Who interprets and actions this information? How do they measure its value and impact on development? These questions only scrape the surface of what’s needed to effectively progress your product blueprint through the initial steps. By chipping away at the unknowns, it helps you to build a more comprehensive pathway to product success. Without progressing through a process of seeking useful answers during this process, you may be left with a fuzzy or inaccurate picture of what your intended users want. Does your prospective development partner have a process to structure surveys, conduct testing sessions, probe user responses effectively, and deliver actionable advice to engineering teams based on human feedback? Are they invested in setting up your product for market success? Make sure your expectations from your product development partner are clear before committing. ### Is your partner technical, strategic, or both? Technical agencies and body shops are skilled at making applications to order, but lack the strategic vision and skin in the game to course-correct if needed. This may be the ideal type of engagement for a strategic business with experience in the market and existing products generating insights about next moves, with minor gaps to fill. Using body shops can augment an already effective team, but as stop-gap resources increase, more strain is placed on the existing internal delivery leadership. Without the turnkey management and administrative capacity of a strategic partner, additional resources will only burden your leaders with more people to bring up to speed and manage. For anyone setting out on their first product journey, or for incumbents entering an unfamiliar market, it’s important to have a strategic development partner who has proven success in evaluating product-market fit, on top of raw product development capacity. Your partner should understand and buy into your vision from the beginning, guiding it through the development stages toward a clear goal. The experience provided by a strategic partner with hands-on knowledge of your market is invaluable to the development of any new product. Most time and cost blowouts that occur in this phase of the development cycle come from going down the wrong path without being able to see in advance how the market will respond to it. Another key benefit of a strategic development partner is having a robust, scalable structure in place that can seamlessly inject a specialist team fully formed and performing into the existing production flow. The approach enables a shorter time to spin up teams to full productivity under their own manager, removing the overhead of additional people management from your development efforts. ### Will your partner support the product’s ongoing development? Technical body shops may be a great choice if your vision is wholly formed, mature and market-ready out of the box. What they are not well equipped to do is provide guidance or strategic vision for the ongoing success of your product. Some development firms prefer to focus only on build, which can leave their clients without much strategic support once the product goes live. In many cases, new owners of the product don’t have the keys to the engine room. They lack the desire or know-how to continue development post-launch, iterate on user feedback or even fix the product the first time it breaks. This can lead to a situation of increasing costs and diminishing returns where having to make major changes to your product after the fact can blow out budgets and timeframes. ### The managerial overhead of body shops vs intact teams Using body shops can quickly fill gaps in an existing team, but it places more strain on the existing internal delivery leadership. Your leaders will be saddled with more people to both onboard and manage, shepherding new teams which need to go through the process to form, storm and norm, then perform. The benefit of a strategic development partner is in how they can hit the ground running, with proven teams that are already well-structured and performing. This provides a more favourable time-to-productivity scale, and allows work to filter in through a project manager who leads their team independently. It removes the people and product management workload, saving on the managerial overhead needed to deliver. ## Developing Products the Propel Way Propel is an industry-leading development partner with a history of shepherding successful products to market alongside our partners. We set up clients for long-term success and share the risk, lending projects both our world-class technical expertise and unique understanding of the technology marketplace. We guide our partners over hurdles and around pitfalls throughout the development cycle, from successful launches to finding a profitable business-as-usual rhythm. We steer clear of double-handling and development cul-de-sacs, finding additional cost efficiencies along the way. Our depth of experience in determining product-market fit, validating development progress with user testing and feedback, and supporting ongoing growth make us the ideal strategic partner for developing a commercially successful product. Founded in 2016, we’ve assembled a team of entrepreneurial product strategy, design and development leaders with a track record of building businesses, creating and expanding markets, and developing new technologies that benefit millions of people across the globe. Speak with us before you embark upon your next product development journey, and find out why Propel is a safe pair of hands to steer your product to market success. # The secret to creating and launching a successful product Source: https://www.propelventures.ai/blog/the-secret-to-creating-and-launching-a-successful-product Meta: 2021-07-27 · Paul Greenwell Product market fit can make all the difference between a spectacular product success and a spectacular failure. It’s easy to get swept up by the excitement of a new idea and creating something that will disrupt the industry. Many well-intentioned organisations start out their product development journey by hastily diving right into the build stage, usually because they feel pressured to get to market as quickly as they can. However, this is a recipe for failure. Many of these organisations soon discover their product doesn’t gain any traction in the market or even worse, it outright fails its customers. That’s why having a well-defined, and validated, product strategy before kicking off the development stage is so important. ## Is your product strategy market-ready? A product strategy is a high-level plan for creating value for the customer and your organisation. It should explain what kind of a product you will develop, who it's for, how it creates value for its users, where it fits into the market and how it will help your organisation achieve its goals. Having this strategy validated and market-tested before you start building is critical to realising the full ROI potential of your product. In practice, your product strategy should address four key areas: A validated product strategy serves as the foundation for successful product scoping, design, development and execution, as well as its success in-market. Without a product strategy in place, you will always be in crisis-mode, trying to put out fires at every stage of the product lifecycle, with no certainty of its success in-market. ## If you don’t test for product market fit, your product will crash and burn Making sure you’ve done your due diligence for product-market fit is essential to creating valuable, usable, and marketable products. That means the biggest part of any product strategy is ensuring it's well-grounded in market insights and customer validation. Does the product address an underserved user need? Are the current solutions in market sub-par? If so, then you have a strong window of opportunity for your product to succeed in. But you need to move quickly. If the need for the product is real, other players are likely to pick up on it, and it won’t stay underserved for long. Carrying out research, testing and validation for product-market fit will not only help you iron out any wrinkles in your product plan, but it will also help you shape the tangible, compelling features your customers will fall in love with. Defining these features in concrete terms at the strategy stage gives you an early indication of whether the product aligns with your organisation's goals, as well as visibility into the kind of technical infrastructure and resources you will need to make sure the product can deliver on its promise. Testing for product-market fit involves developing a prototype based on the hypothesis about your customers, their needs, and the differentiators that set you apart from other offerings in the market. This stage is iterative, as you’re validating your hypothesis and altering your course of action based on the feedback you get from your test customers. Based on the input you receive, you might decide to pivot or persevere with the current product strategy. Once you have the findings from your product-market fit research, you will be in a better position to iterate and refine your product, de-risk the product development cycle, optimise its features and its design, all of which greatly increase its chances of becoming a hit with your customers. ## How to accelerate product success and boost ROI Ensuring a new product’s success in-market is challenging. Not only does your product-market fit need to be on-point, but you also must make sure the right customers get the right message at the right time. Let’s look at the key levers involved in a product’s success and how they impact product ROI. ### 1. Testing the need in the market The size of the market opportunity, current state of play and customer needs all have a major impact on how well-received your product is likely to be. Having a rich picture of the market will help you frame the product in a way that resonates with your audience. Customer surveys, testing, and polling are just some of the techniques you can use to gauge the appetite the market has for your offering. ### 2. Framing the product’s benefits If you’re a team leader neck-deep in product development, it can be hard to put yourself in the shoes of the customer. You might reason that the product’s features speak for themselves, and it’ll be a no-brainer for your audience. But the reality is, customers can have very different expectations from the product than the ones you’re envisioning. Far too often, there is a disconnect between what the product offers and what the customer expects, which can lead to frustration on both sides. Marketing can provide some support here, but ultimately, the quality of your product-market fit will determine how well you’ve framed the product for your customer. ### 3. Creating differentiation To maximise your chances of commercial success, you need to stand out from the competition while still being clear about the benefits you offer to your customer. You need a clear market positioning grounded in competitor analysis and differentiation. If you’re launching a product in a crowded market, customer decisions can become very arbitrary, and turn into a matter of perception as much as product function. Creating a singular, simple customer value proposition that sets you apart from your competitors is key to winning them over. ### 4. Generating buzz They say advertising is dead...until, that is, you need to make a sale. Sales, marketing and promotion have a huge influence on a product’s commercial success. Choosing the right message and the right media is going to be a critical driver for product adoption. Far too many products have died a premature death because of poor marketing. Market testing and customer feedback is invaluable for making sure your advertising and sales messages do your product justice and resonate with your customer. But promotion is a dual-edge sword; your product must deliver exactly what’s advertised, otherwise the bad publicity around failed expectations is toxic to nascent products. ## If you’re shooting for the moon, you need a proven navigator Creating and launching a product are enormous challenges under even the best conditions. And making sure it’s commercially successful on top of that is a very tall order. However, having a well-informed product strategy in place can go a long way to minimising the inherent risk involved, and dramatically improves the chances of creating the next big success story. Having an experienced product development partner to support you from product inception to launch and beyond can be a tremendous asset to have on your side. If you’re looking for help in creating your next ground-breaking product, we should talk. # Accelerated Development Source: https://www.propelventures.ai/blog/accelerated-development Meta: 2021-07-13 · Paul Greenwell Corporate compliance becomes an unexpected battleground. Prior to February 2017 MYOB were unchallenged in the market for corporate administration software. MYOB were able to maintain a considerable market share for over ten years with a desktop solution that had first been developed in 2003. Prior to February 2017 MYOB were unchallenged in the market for corporate administration software. MYOB were able to maintain a considerable market share for over ten years with a desktop solution that had first been developed in 2003. This would change in early 2017 when BGL released their corporate compliance product CAS 360, a modern cloud solution that would enjoy rapid growth on release. By July 2017, just six months after the launch of CAS 360, BGL was already managing close to 90,000 companies on their platform and as that number began to climb, customers began leaving MYOB’s own solution. Corporate administration platforms are designed to make the processes and workflows involved in an accounting practice lodging forms with ASIC and managing the official details concerning a legal entity easier. This is the kind of platform that benefits greatly from orders of scale, where the greater the percentage of the market a single platform holds, the more they are seen as the source of truth and the more data driven features can be enabled to build a defensive moat around the product. With the explosive growth of BGL, MYOB faced a real risk that they would be unseated as the source of truth among corporate administration platforms – something had to be done. As of 2017, MYOB did have plans to modernise their corporate administration offering, scheduled roughly four years out. Propel Ventures with a depth of experience and insight into the accounting domain could see the rapidly changing landscape and knew that waiting four more years would be too little too late. The proposal was made for Propel Ventures to partner with MYOB and time-shift the corporate administration modernisation from the back of MYOB’s delivery roadmap to the front of Propel’s delivery roadmap. By doing this, Propel Ventures could promise to accelerate delivery and ensure that a timely response to a growing threat would keep MYOB competitive. ### Challenges MYOB faced competitors whose cloud solution they had effectively been promoting over their own desktop solution, allowing them to present their products at MYOB events By allowing another company to gain control of corporate administration client lists, MYOB were allowing their market position to become diluted. MYOB were busy developing a new cloud-based practice management suite, they had their top-10 priorities and corporate administration was priority number 12 on the roadmap. Without a partner to time-shift delivery of a modern corporate administration solution forward, MYOB were not going to be able to get a competitive product into market in time to maintain their position in the market. ## Propel must accelerate delivery to keep MYOB competitive From the onset, Propel Ventures knew that it had taken BGL roughly four years to build their corporate administration offering from the ground-up. Four years was always going too late of a response for MYOB, so Propel identified a way that they could accelerate delivery and get a response in market a whole two years earlier. At the start of 2018 Propel began a technical assessment of a small corporate administration company called CompanyIQ. The technology in Company IQ would act as a solid foundation for MYOB’s new cloud corporate administration offering, the team building it had unrivalled domain expertise (ie, a developer with 12 years of corporate administration experience) and the work needed to get it production ready for MYOB could conceivably be compressed into two years – Propel had found their pathway to accelerating delivery. MYOB embraced the race to respond to BGL in market and critical to the success of the joint efforts of MYOB and Propel Ventures, they began to communicate with the market very early on about what was coming down the pike for MYOB’s corporate administration offering. This slowed the movement of customers away from their desktop offering and signalled to the market that MYOB were throwing down the gauntlet and ready to update, upgrade and fight to win. ### The Plan Acquire CIQ, to capture technology assets (ie, backend connections to with ASIC), legal IP (ie, resolutions, minutes, certificates etc.), intellectual IP (ie, key developers with experience in corporate admin). Begin re-development of the CompanyIQ user interface to be more user friendly and more consistent with MYOB design standards, using common MYOB Felix components etc. Migrated the infrastructure from Azure to MYOB preferred cloud infrastructure Migration onto MYOB’s application scaling and deployment environment. Improved the scalability of pipelines, queues, and integration touchpoints. Conducted a complete security overhaul, raising it to levels consistent with MYOB standards Beta to coincide with handover back to MYOB and product release. ## How Propel delivered a four-year project in two years No other company, including MYOB themselves could have delivered a new cloud corporate administration solution to market within two years. It was only made possible by Propel Ventures accelerated delivery strategy. Propel would purchase CompanyIQ and begin the painstaking process of modernising MYOB’s corporate administration offering at speed. Propel would not only inherit the technical foundations of the future MYOB corporate administration solution from CompanyIQ, but they also gained a depth of subject matter expertise that could never have been acquired elsewhere. The original CompanyIQ team, with their years of practical experience working with challenging ASIC interfaces, understanding the different ASIC forms and having the relationships and contacts within ASIC were a critical to Propel’s successful acceleration of delivery. By the end of the project the founding developer team of two, would help seed and grow a team of ten corporate administration developer experts. In addition to the technical and intellectual assets Propel inherited several CompanyIQ’s corporate secretarial customers. Propel’s development team continued to operate this corporate secretarial business as a means of cultivating a group of corporate administration customers that would allow the Propel Ventures’ product teams to conduct rapid user research, test features and get feedback from their own real customers. Acting as corporate administration employees also allowed Propel’s developers to deepen their domain expertise, putting themselves into the shoes of the people who would one day be using the platform they were building. ## Propel help time-shift a response to a growing market threat In early 2017 BGL began to grow exponentially, threatening the position of MYOB’s own corporate administration solution. With the support and partnership of Propel Ventures, MYOB were able to move a substantial road-map items slated for 2021 forward to 2018. Propel then accelerated a four-year build into just two years, with the first beta release of the product occurring in May 2019. Propel did this by identifying CompanyIQ as a technically asset in market that would act as a foundation for the product and provide the domain expertise necessary to seed a full development team. By June 2020 MYOB’s new cloud corporate administration solution operates in parallel to the pre-existing desktop solution. As of July 2020, over two hundred customers have already migrated over to the new experience bringing upwards of fifty thousand companies with them. MYOB can expect to see exponential growth in these numbers as a testament to the success of this accelerated modernisation of their corporate administration product offering. # Innovations in Artificial Intelligence Source: https://www.propelventures.ai/blog/innovations-in-artificial-intelligence Meta: 2021-07-13 · Paul Greenwell MYOB have a long history of empowering accounting practices, always exhibiting a clear understanding of the role that accountants play as... MYOB have a long history of empowering accounting practices, always exhibiting a clear understanding of the role that accountants play as trusted advisors to business owners. Despite there being many attempts throughout the industry, for over twenty years, accountants have struggled to find the tools they needed to break into the advisory market. The options available to them were simply too complex or cost prohibitive. In 2018 MYOB would partner with Propel Ventures to create an AI powered solution that would be accessible in terms of ease of use and cost. Propel Ventures would set out to give an unfair advantage to those practices who were ready to explore the role of AI powered advice within their practice. The aim of this advisory tool, which would be name MYOB Advisor, would be to allow an advisor to generate a report filled with insights in less than ten minutes. Accountants have an important role to play in providing advisory services to small businesses. Before MYOB Advisor accountants were hamstrung in their abilities due to provide these services the complexity and inaccessibility of other reporting products and most critically the lack of time spare to prepare. The manual analysis of a company’s accounting data takes a great deal of time and accountants had been forced to choose which of their customers were going to receive a high quality advisory experience or a low quality one. In the broadly homogeneous market of accounting services, a failure to differentiate on the quality of a practice’s service can be a critical failure. Providing a practice with a means of generating meaningful insights for an advisory discussion in under 10 minutes would prove to be a revelation. ### Insights Identifying meaningful advisory insights is too skill and labour intensive to do manually at scale. Accountants differentiate their services through the quality of their advisory engagements. Customers receive inconsistent levels of advisory support from accountants who simply do not have the bandwidth to provide anything beyond baseline levels of service to most of their customers. The baseline level of advisory service from accountants can be superficial and is a vulnerable point in the retention strategies of most practices. Accountants need to be able to prepare for an in-depth advisory discussion in under ten minutes if they were going to raise their standard of services across their entire customer base. ## Propel identify the opportunity for AI generated advisory reports Propel Ventures have a deep understanding of the accounting industry, acquired through years of experience leading Australia’s largest accounting platforms. The challenge of improving the advisory capabilities of MYOB’s customers was a problem that was simple to solve in concept, but technically challenging in practice. It was clear conceptually that if accountants were not able to find the time to prepare advisory reports for their customers, then an algorithm could be built to do the work for them. This would see Propel Ventures treading unbroken ground in the field of ‘natural language generation’ and would risk bringing the customer dangerously close to the pitfalls of direct customer-AI interactions. With an innovative and creative vision of an AI advisory assistant in mind, Propel Ventures set out with a plan of intensive user testing, development and research that aimed to see this new advisory solution released to market by MYOB in six months. ### The Plan Develop an AI algorithm to codify accounting knowledge, identify insights and learn. Develop a world class natural language generation engine to relay AI insights to a human operator. Avoid the common pitfalls of customer-AI interactions. ## MYOB Advisor is launched in March 2018 The AI solution designed by Propel Ventures scrutinises accounting data, identifies insights and crafts those insights into sophisticated natural language reports – advisors are then able overlay their own commentary onto those reports and focus their time on having insightful conversations with their customers. MYOB Advisor’s has given MYOB customer’s the tools they need to realise efficiencies and improve their quality of service. They can now spend more time having meaningful discussions with their clients that deliver real value and insight. MYOB CEO at the time Tim Reed said that MYOB Advisor was the first step towards helping accountants, bookkeepers and their clients to unlock more of their business goals. “We know that accountants and bookkeepers want to grow their advisory services, and MYOB Advisor is one way they can offer greater value to their clients,”Mr. Reed said. “MYOB Advisor frees accountants and bookkeepers’ time while also assisting with actionable business outcomes.” MYOB Advisor also won an award from the Australian Financial Review as one of Australia and New Zealand’s most innovative companies of 2018. ## Propel innovate around the challenges to creating AI user experiences Artificial intelligence within a modern business context tend to appear as background utilities. The feedback loops and neural networks that drive modern AI algorithms are abstracted away from the customer interactions that they enrich. Research shows that without a great deal of care, a smart strategy and an expert implementation AI assistants and other AI constructs with regular human interaction, can evoke irrational negative emotional responses from users. Failing to avoid the ‘uncanny valley’ effect is one of the most common pitfalls of customer-AI interaction design, something Propel Ventures indevoured to avoid during the development of MYOB Advisor. This effect of the negative emotional response to the emulation of human traits is known as the ‘uncanny valley’ hypothesis. The idea was first stated by the roboticist Mashahiro Mori, and as applied to robotics it asserts that human’s respond to the imitation of human traits in a manner described by a particular curve (figure1), where any slight degree of human-ness evokes a positive response, such as simple expression, or ordering objects to another human’s preference. These positive emotions then begin to turn negative as more sophisticated human traits are imperfectly emulated, such as can be found the emotional responses of fear or revulsion to robot-human analogues. This negativity lasts for as long as it takes for the system to mimic the traits of a human more perfectly. This ‘uncanny valley’ hypothesis, while focused on human likenesses in robotics does seem to also describe the reception of AI algorithms by humans. Where the AI algorithm that mimic a few, quite simple human traits (i.e., ordering content to another human’s preference) are more warmly accepted by customers than those that endeavour to take on more sophisticated traits (i.e., chatbots). With the broad acceptance of an AI algorithm rising as the quality of the emulation increases (i.e., Siri). As AI steps closer, moving from the background into the foreground of customer engagement, few innovators have succeeded in producing AI customer experiences that can shed this Uncanny Valley effect, and it is a non-trivial impedance to realising the full potential of AI for business. For this reason, a great deal of innovation was required when designing the interaction model for the ‘MYOB Advisor’ solution, a revolutionary AI ‘advisor in the loop’ design pattern (figure 3) that allows the algorithm to step forward and assume a collaborative role in adding value to customer engagement. Working in favour of the ‘MYOB Advisor’ solution was the fact that accounting data is extremely high quality. Accounting data can be interpreted according to known rules, and the data is stewarded consistently by Accountants who also play the advisory role within the ‘advisor in the loop’ AI pattern. Perhaps the most critical fact was that accounting data insights can be described adequately in terms of descriptive statistics (i.e., x has risen by n between y and z meaning…). In fact, the written description of the insights proved to be far more readily comprehensible than just having the data presented in a chart or table. ### The Plan The combination of natural language generation, with generally accepted accounting principles and AI algorithms are complimentary and capable of producing value results. Propel Ventures identified the power of placing the accountant who plays the roles of data custodian and advisor into the AI loop, to great effect.