Building an Agile Project Roadmap

Gantt Charts Are Great... and Have No Place in Agile Gantt charts are a timeless classic. Their simplicity and clarity make them the go-to tool for mapping work over time. Whether you're planning a project or explaining timelines to stakeholders, Gantts are intuitive and effective. No wonder they tempt Agile teams! But here’s the catch: Gantt charts don’t belong in Agile. Sure, their visual appeal is undeniable, but their task-orientation and rigidity conflict with Agile’s principles of adaptability, iterative delivery, and customer focus. Why Gantt Charts Are Popular Gantt charts are easy to read and imply certainty. They detail tasks, dependencies, and timelines, making complex projects seem manageable. That's great, but it's an empty promise that gives a false sense of security. Even in Agile, where adaptability is key, the clarity of a Gantt is highly appealing. They provide a structured, simple way to communicate progress. But the precision that makes Gantts shine in Waterfall becomes a liability in Agile. The Problem with Gantt Charts in Agile Agile thrives on adaptability, prioritizing near-term precision while allowing mid- and long-term plans to evolve. Gantt charts, in contrast, assume plans made today will hold true for months (or years). This rigidity makes Gantt charts precise(ly wrong). That's why they conflict with Agile. Agile focuses on delivering value incrementally, prioritizing the next most important thing. Gantt charts encourage locking in sequences that don’t account for evolving needs. Agile plans are intentionally fluid beyond the sprint level. Gantt charts demand precision up and down the line, making them misleading when priorities change. Agile measures success by value delivered, not by tasks completed. Gantt charts focus on tasks and dependencies can obscure the bigger picture. Agile Alternative: Roadmaps Gantt charts don’t fit in Agile, but we can borrow their strengths. Agile roadmaps take the best parts of Gantts (their ability to visualize work over time) and adapt them for Agile teams. Instead of task-level schedules, Agile roadmaps focus on outcomes - and precision scales with time Near-term sprints are detailed, with clear deliverables (e.g., stories, enablers). Mid-term (e.g., quarterly) plans shift focus to features or epics, allowing for easy adjustment. Long-term (e.g., annual) vision roadmaps transition to larger strategic themes, recognizing the inherent uncertainty of the future. This nuanced, layered approach balances visibility with flexibility, empowering teams to adapt while keeping stakeholders aligned. Gantt Charts: Great, but Not for Agile Anyone who denies Gantt charts’ utility for traditional projects isn't paying attention. But their rigidity is incompatible with Agile's flexibility. Agile teams can adapt the best qualities of Gantt charts into roadmaps, preserving their visual clarity, discarding their false promises of certainty, and aligning with a value-orientation.

Let's be honest: extensive cross-team coordination is often a symptom of a larger problem, not an inevitable challenge that needs solving. When teams spend more time in alignment than on building, it's time to reconsider your organizational design. Conway's Law tells us that our systems inevitably mirror our communication structures. When I see teams drowning in coordination overhead, I look at these structural factors: - Team boundaries that cut across frequent workflows: If a single user journey requires six different teams to coordinate, your org structure might be optimized for technical specialization at the expense of delivery flow. - Mismatched team autonomy and system architecture: Microservices architecture with monolithic teams (or vice versa) creates natural friction points that no amount of coordination rituals can fully resolve. - Implicit dependencies that become visible too late: Teams discover they're blocking each other only during integration, indicating boundaries were drawn without understanding the full system dynamics. Rather than adding more coordination mechanisms, consider these structural approaches: - Domain-oriented teams over technology-oriented teams: Align team boundaries with business domains rather than technical layers to reduce cross-team handoffs. - Team topologies that acknowledge different types of teams: Platform teams, enabling teams, stream-aligned teams, and complicated subsystem teams each have different alignment needs. - Deliberate discovery of dependencies: Map the invisible structures in your organization before drawing team boundaries, not after. Dependencies are inevitable and systems are increasingly interconnected, so some cross-team alignment will always be necessary. When structural changes aren't immediately possible, here's what I've learned works to keep things on the right track: 1️⃣ Shared mental models matter more than shared documentation. When teams understand not just what other teams are building, but why and how it fits into the bigger picture, collaboration becomes fluid rather than forced. 2️⃣ Interface-first development creates clear contracts between systems, allowing teams to work autonomously while maintaining confidence in integration. 3️⃣ Regular alignment rituals prevent drift. Monthly tech radar sessions, quarterly architecture reviews, and cross-team demonstrations create the rhythm of alignment. 4️⃣ Technical decisions need business context. When engineers understand user and business outcomes, they make better architectural choices that transcend team boundaries. 5️⃣ Optimize for psychological safety across teams. The ability to raise concerns outside your immediate team hierarchy is what prevents organizational blind spots. The best engineering leaders recognize that excessive coordination is a tax on productivity. You can work to improve coordination, or you can work to reduce the need for coordination in the first place.

Two project management truths: → Your team needs updates → Your leaders need outcomes A one-size-fits-all communication is a fast track to confusion. PMs are the translator between ground-level work and top-floor priorities. If you're saying the same thing to everyone, someone is not hearing what they need. Here's how you tailor your communication AND drive clarity at every level: 👉 Lead with "what this means for you" Customize your opening line based on who's listening/receiving. 👉 Use dashboards for execs and details for doers High-level visuals win at the top, while tasks/dependencies/blockers matter most to teammates. 👉 Talk outcomes over activity Tell leaders what got done and what it unlocks next. 👉 Summarize first, explain second Start updates with a clear summary (think TL;DR). Include details further down for those who want more. 👉 Repeat your message but adapt the framing Repetition builds trust. Repeat the right level of detail to each audience. Effective PMs are more than organized. They're multilingual. 🤙

Most PMs hide behind status reports while elite PMs build in the open. The difference? ... It's not advanced certifications or agile methodologies. It's radical transparency. I've guided hundreds of projects to completion, and here's what I've noticed: - Average PMs share updates on a need-to-know basis. - Elite PMs make visibility their competitive advantage. Let me show you what I mean. When managing deliverables, the typical PM keeps tracking documents in private folders. → They send status reports once a week via email. → They control information flow. But the elite PM takes a different approach. → They maintain a publicly accessible project dashboard that stakeholders and team members can check anytime. See the difference? The first PM creates information bottlenecks. The second PM creates informed teammates who feel trusted and aligned. Or take status meetings. The average PM jumps straight into issues and action items. They rush through updates, highlighting what's off-track and who's behind. The elite PM begins every call showcasing the dashboard and celebrating wins. They heap praise on team members delivering results (and occasionally those who need encouragement). The first PM trains their team to dread status updates. The second PM creates an environment where progress is visible and contributions valued. This pattern transforms how the team handles inevitable obstacles: When facing delays, the typical PM uses vague terms like "𝘴𝘭𝘪𝘨𝘩𝘵 𝘴𝘤𝘩𝘦𝘥𝘶𝘭𝘦 𝘢𝘥𝘫𝘶𝘴𝘵𝘮𝘦𝘯𝘵𝘴" or "𝘳𝘦𝘱𝘳𝘪𝘰𝘳𝘪𝘵𝘪𝘻𝘢𝘵𝘪𝘰𝘯." They downplay issues, hoping executives won't notice. The elite PM directly calls out what's not going well and what's falling behind. They name the problems precisely because you can't mitigate what you won't acknowledge. The common PM breeds uncertainty and backchanneling. The elite PM creates 𝗽𝘀𝘆𝗰𝗵𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝘀𝗮𝗳𝗲𝘁𝘆 and 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺-𝘀𝗼𝗹𝘃𝗶𝗻𝗴. Why don't more project managers embrace this kind of transparency? Three reasons: 1. They fear being judged for variance from baseline plans 2. They mistake information control for project control 3. They underestimate leaders' ability to handle reality But here's the truth: Your stakeholders already sense when projects aren't on track. By being transparent, you're not revealing failures—you're demonstrating that you have the confidence to lead through complexity. That's what separates elite PMs from the rest. Not perfect execution, but perfect clarity even when execution isn't perfect. So next time you kick off a project, resist the urge to gate information and manage perceptions. Instead, build dashboards for all to see. Celebrate openly. Address issues directly. ~~~ PS- Are you still using slide decks to convey status? Or do you leverage real-time tools to provide just-in-time answers? . .

One of the hardest challenges for product teams is deciding which features make the roadmap. Here are ten methods that anchor prioritization in user data. MaxDiff asks people to pick the most and least important items from small sets. This forces trade-offs and delivers ratio-scaled utilities and ranked lists. It works well for 10–30 features, is mobile-friendly, and produces strong results with 150–400 respondents. Discrete Choice Experiments (CBC) simulate realistic trade-offs by asking users to choose between product profiles defined by attributes like price or design. This allows estimation of part-worth utilities and willingness-to-pay. It’s ideal for pricing and product tiers, but needs larger samples (300+) and heavier design. Adaptive CBC (ACBC) builds on this by letting users create their ideal product, screen unacceptable options, and then answer tailored choice tasks. It’s engaging and captures “must-haves,” but takes longer and is best for high-stakes design with more attributes. The Kano Model classifies features as must-haves, performance, delighters, indifferent, or even negative. It shows what users expect versus what delights them. With samples as small as 50–150, it’s especially useful in early discovery and expectation mapping. Pairwise Comparison uses repeated head-to-head choices, modeled with Bradley-Terry or Thurstone scaling, to create interval-scaled rankings. It works well for small sets or expert panels but becomes impractical when lists grow beyond 10 items. Key Drivers Analysis links feature ratings to outcomes like satisfaction, retention, or NPS. It reveals hidden drivers of behavior that users may not articulate. It’s great for diagnostics but needs larger samples (300+) and careful modeling since correlation is not causation. Opportunity Scoring, or Importance–Performance Analysis, plots features on a 2×2 grid of importance versus satisfaction. The quadrant where importance is high and satisfaction is low reveals immediate priorities. It’s fast, cheap, and persuasive for stakeholders, though scale bias can creep in. TURF (Total Unduplicated Reach & Frequency) identifies combinations of features that maximize unique reach. Instead of ranking items, it tells you which bundle appeals to the widest audience - perfect for launch packs, bundles, or product line design. Analytic Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT) are structured decision-making frameworks where experts compare options against weighted criteria. They generate transparent, defensible scores and work well for strategic decisions like choosing a game engine, but they’re too heavy for day-to-day feature lists. Q-Sort takes a qualitative approach, asking participants to sort items into a forced distribution grid (most to least agree). The analysis reveals clusters of viewpoints, making it valuable for uncovering archetypes or subjective perspectives. It’s labor-intensive but powerful for exploratory work.

We have never done annual roadmaps at Typesense all these years. And we're doing just fine. Profitable, serving 10 Billion searches per month, tens of millions of downloads, thousands of customers. And we SHIP impactful stuff all the time. Here's what works for us instead: --- We plan work in a rolling 2-month cycle. We prioritize projects based on the biggest & most popular asks from our customers & community. The key is to then be open enough to reprioritize even within that 2-month cycle, if something else bubbles up as important. --- This regular re-prioritization effort is what keeps us closely aligned with the need of the hour and keeps us nimble. The side effect though is that we have to sometimes pause in-flight projects and context switch. And we're ok with this, because we do not have deadlines. NO DEADLINES?! Yes, I know. Blasphemous! But removing that artificial constraint is the foundation that allows us to be flexible and ship what customers need quickly, when they need it. So as counter-intuitive as it sounds, having no deadlines, enables us to ship faster. --- This is of course not for everyone. I've seen some teams get worked up about frequent changes to the roadmap. This is sometimes deeply rooted in the culture of many companies: You "commit" to a roadmap, and you're held "accountable" to shipping that roadmap, come what may. The problem is that you might be executing something on the roadmap that is based on an outdated assumption. You look good shipping as a team to leadership, because you're meeting your commitment. And if you change your commitment that looks bad to them. And that is how you end up shipping projects... without impact. --- And that is my problem with annual roadmapping. It requires you to be a crystal-ball-reader and conjure up ideas that you think, may be, hopefully, useful to some group of users far into the future. Meanwhile, as the year progresses Underlying assumptions change, users give you more feedback, a promising opportunity comes up, etc, etc And yet teams end up executing on a now-fossilized roadmap project, just because it is on the annual roadmap and committed to. --- Long story short: Plan your roadmap in shorter timeframes Then be willing to throw it all out & come up with a new roadmap, if you find substantially new info Avoid celebrating just shipping what's on a roadmap. Instead celebrate the impact your shipped project has on users.

Your product roadmap shouldn’t be a wish list. It should be a list of hypotheses you’re ready to be wrong about. If you’re not ready to be wrong, you’re not actually ready to prioritize. When you build your roadmap, focus on the outcome you want. For instance, you might say, “We believe Feature X will reduce churn by 10%. We’ll test that for the next two sprints.” That way, you’re tying the feature directly to a measurable result. If it doesn’t work, cut your losses and move on. If it does work, double down. This approach keeps you honest. You stop building features because they “feel right” or because someone on the team has a pet idea. You build them because you have a hypothesis about how they’ll change user behavior, and you’re open to seeing that hypothesis fail. Being wrong is an essential part of finding out what’s actually going to drive the metrics you care about. Here’s a quick example. Maybe you think adding a trial signup link to your pricing page will increase free trials by 20%. That’s your hypothesis. You put it on the roadmap, implement it, then measure the results. If you only see a 5% lift, you’ve learned something. Adjust the page again or try a new tactic. Either way, you’re making decisions based on real data, not gut feel. Another example: you might hypothesize that a chatbot in your onboarding flow will cut support tickets by 30%. Implement it, test it, and see if you’re right or wrong. If you’re wrong, you’ve still learned something about user preferences. That knowledge is gold. You can use it to decide what to build or not build next. By treating your roadmap like a series of experiments, you’ll move faster and waste less time. You’ll also build trust with your team and stakeholders because they’ll see exactly why each idea is there: it’s a hypothesis you’re willing to test. Remember, you don’t want to defend projects because you’ve already sunk time into them. You want to move on if the data says it’s time to move on. Keep your roadmap grounded in reality, always driven by an underlying guess about what will drive real impact. It forces you to put a stake in the ground about what you believe and to be ready to change course when you find out you’re wrong. That’s the whole point: you’re building a product for real people in the real world, and real data trumps wishful thinking every time.

Most SaaS teams are building features users will never adopt. The reason isn't bad engineering. It's bad prioritization. Traditional feature prioritization follows this broken pattern: Executives want it → Competitors have it → Engineering can build it → Ship it But what users actually need gets lost in the noise. User-centered prioritization flips this completely. Instead of guessing what matters, you let user behavior and research drive every decision. Here's how it works: ↳ Start with user research to identify real pain points ↳ Test concepts with actual users before building anything ↳ Prioritize features that solve frequent, important user tasks ↳ Focus on what drives user satisfaction and business outcomes The difference is dramatic. Companies using internal opinions to prioritize features see adoption rates around 12%. Those using user-centered prioritization consistently hit 40% or higher. User-centered prioritization isn't just a method. It's a mindset shift. ↳ Instead of asking "What should we build next?" you ask "What problems are users struggling with today?" ↳ Instead of following competitor features, you follow user workflows. ↳ Instead of building what sounds impressive, you build what creates value. This approach identifies the features that matter most before you waste engineering resources. It reduces development time by focusing on proven needs. It increases adoption because users actually want what you're building. Your roadmap should serve users first. Everything else follows from there.

After working with multiple cross-functional teams, one thing has become painfully clear: 𝐌𝐨𝐬𝐭 𝐀𝐠𝐢𝐥𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐚𝐢𝐥 𝐧𝐨𝐭 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐠𝐚𝐩𝐬 𝐛𝐮𝐭 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐜𝐮𝐥𝐭𝐮𝐫𝐚𝐥 𝐨𝐧𝐞𝐬. We obsess over ceremonies, tools, and metrics, but we often overlook the single most important factor that determines whether a team thrives or burns out: PSYCHOLOGICAL SAFETY Here’s the hard truth: 𝐘𝐨𝐮𝐫 𝐀𝐠𝐢𝐥𝐞 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐢𝐬 𝐨𝐧𝐥𝐲 𝐚𝐬 𝐬𝐭𝐫𝐨𝐧𝐠 𝐚𝐬 𝐭𝐡𝐞 𝐭𝐫𝐮𝐬𝐭 𝐲𝐨𝐮𝐫 𝐭𝐞𝐚𝐦 𝐟𝐞𝐞𝐥𝐬. - You can run flawless standups and still ship broken products. - You can track sprint velocity religiously and still leave your team drowning in burnout. - You can have retrospectives every two weeks and still hear silence in the room. Because when people don’t feel safe to speak up, question assumptions, or admit blockers, “Agile” becomes theater.... busy but brittle. Here's are 5 approaches to bridge the trust gap in your team. 📍T — Transparency in Decision-Making Don’t just hand down priorities. Explain the why. Show your uncertainties. Invite your team into the decision. ↳Start every sprint planning with 5 minutes of context. It changes everything. 📍R — Reward Intelligent Failures High-performing teams don’t avoid failure, they mine it for insights. ↳ Dedicate a section in retrospectives to “productive failures.” Celebrate what you learned. 📍U — Unblock Before You Judge When someone raises an issue, don’t start with “why.” Start with “how can I help?” ↳ Create safe, multiple pathways for people to surface blockers including anonymously. 📍S — Shared Accountability Shift the narrative from “who’s at fault” to “what can we improve together.” ↳ Replace individual blame metrics with team success metrics. 📍T — Time for Reflection Pushing relentlessly without pause kills innovation. Space to reflect is where creativity breathes. ↳ Reserve 30 minutes at the end of every sprint for conversations that are separate from delivery-focused retros. This is crucial because Teams with high psychological safety consistently outperform others with higher #teamperformance, lower turnover, fewer quality issues and higher revenue performance Here's a place to start.... In your next team meeting, take one recent decision and walk your team through your reasoning, including what you were uncertain about. That single act of vulnerability creates space for openness everywhere else. Remember, #Agile isn’t about speed. It’s about creating conditions where teams can thrive under uncertainty. And that begins with TRUST. P.S. How do you build psychological safety in your team? Share in the comments. Your insights could help someone lead better. Follow 👉 Benjamina Mbah Acha for insights that help you plan, execute, and deliver projects with confidence.

Balancing bug fixes, small improvements, and new features is one of product management’s biggest challenges. The key is understanding how each effort ties back to your product and business goals. It’s easy to assume “small” means insignificant, but often those quick wins can have a huge impact on metrics like retention or customer satisfaction. In this Dear Melissa episode, I break down how to navigate this balancing act and prioritize effectively: 1️⃣ Quantify impact: Connect new features, bug fixes, and small improvements to measurable outcomes. Whether it’s retention, adoption, or satisfaction, ask: What moves the needle? 2️⃣ Look beyond time: Don’t dismiss small improvements because they’re quick. A minor UX tweak can have an outsized effect on satisfaction scores or NPS. 3️⃣ Dedicate time for stability: Bug fixes keep your platform healthy and improve retention. Depending on tech debt, some teams allocate 10-20% of their capacity to this work. 4️⃣ Balance your portfolio: Weigh improvements to existing features against building new ones. Both have value, but measuring their impact ensures better decisions. It’s not about splitting time perfectly—it’s about making strategic decisions that deliver impact. If you’re balancing the demands of fixing, improving, and innovating, ask yourself: 'Is this driving meaningful results for our customers and business?' If you’re looking to refine how you connect strategy to execution, our Product Strategy course covers this in depth. You’ll learn how to focus on the right work, align your teams, and deliver outcomes that matter. 🚀 Learn more about the course here: https://lnkd.in/eev8j8UF How do you approach balancing focus on your team? I’d love to hear what works for you—drop your thoughts in the comments! #productthinking #productmanagement #productstrategy #customersatisfaction #businessmetrics #bugfixes #UXimprovements