How do you use build-measure-learn for product road mapping?

One way around the cycle constitutes an Iteration. If you are operating in an environment where you have a Known Problem, but an Unknown Solution, one of the most important things you need to do is to optimize for your speed of iteration. In my experience, in order to reach product market fit for a well defined narrow problem, teams typically need at least around 150 full iterations. So if you plan to do 2 week "sprints", then expect to fail, or spend 6 years finding PMF.

The Build->Measure->Learn loop is all about figuring out whether customers will like and use the product, and if we can actually build the product idea we have. Think of it as checking our product's market fit. To do this, we create a Prototype or an MVP (in the case of product discovery). This helps us answer the questions: Do customers want this (~value)? Can they use it without getting lost (~usability)? Can our eng team make it happen (~feasibility)? Does it align with our business strategy (~business)? After we build and test it with users, we dive into the data. We check how results match our goals and KPIs. If things look good, that's fantastic! If not, we need to determine what's not working or perhaps consider a pivot.

The Build-Measure-Learn loop is a dynamic approach to product road mapping, focusing on iterative development and learning. ?? Build: Integrate MVP development into the roadmap, focusing on key features that test the value proposition. Measure: Include metrics and feedback mechanisms in the roadmap. Collect and analyze both quantitative and qualitative data from early adopters. ?? Learn: Use insights to decide whether to pivot (alter strategy) or persevere (continue current plan). This makes the roadmap a flexible, evolving document, adapting to real customer needs and market feedback.

Utilizing the Build-Measure-Learn loop in product road mapping fosters a more agile, customer-centric approach. It enables real-time learning from customer feedback, ensuring development focuses on valuable, in-demand features. This method reduces time and resources spent on less impactful features, aligning closely with market needs. It also allows for quick adaptation to changing customer preferences and market conditions, based on evidence rather than assumptions. Ultimately, it increases the chances of creating a market-fit, customer-satisfying product. ??

In Jira, leveraging the build-measure-learn framework for product road mapping involves iterative cycles of building, measuring, and learning to refine and prioritize product features. Initially, teams outline a high-level roadmap in Jira, breaking down initiatives into smaller tasks or epics. As development progresses, they continuously measure outcomes against predefined metrics, gathering data on user engagement and feedback. Insights gleaned from these measurements inform subsequent iterations, guiding adjustments to the product roadmap in Jira. By embracing this iterative approach, teams optimize product development, ensuring alignment with user needs and market demands while fostering continuous improvement and innovation.

To leverage build-measure-learn for product road mapping: - Design MVP: Build a Minimum Viable Product focused on core value to test key assumptions with target users. - Measure with Metrics: Use specific metrics (e.g., user engagement, conversion rates) to evaluate MVP performance and gather actionable feedback. - Learn and Adapt: Analyze feedback to learn about market fit; decide to pivot (change direction) or persevere (enhance and expand current features) based on insights.

Define Vision and Value Proposition: Clearly outline what your product aims to achieve and its benefits to the target audience. Identify and Prioritize Assumptions: List and rank hypotheses about your product’s market fit and customer needs. Design and Build MVP: Develop a Minimum Viable Product with essential features to test these hypotheses and deliver value. Define Metrics and Experiments: Establish key performance indicators and experiments to measure the MVP’s effectiveness. Launch and Measure: Introduce the MVP to target customers and collect data on its performance and user feedback.

When it comes to defining the hypothesis, let's consider a few key points: ?? What's the outcome we're aiming for? ?? Who is our target audience? ?? What are the benefits we expect? ?? And how do we believe we can make it happen? Answering these questions will help you create a better hypothesis.

To make sure we nail execution and iteration, I like to include these activities right in the roadmap. Without clearly defined success metrics shared with the leadership, we run the risk of becoming a "Feature factory".

I've embraced the Build-Measure-Learn cycle to navigate the intricate world of product roadmapping, here's my take: Build: Start with a robust foundation. Collaborate with your team to create a roadmap that aligns with the company's vision and customer needs. It's not just a plan; it's a blueprint for innovation. Measure: Set clear KPIs to quantify success. Regularly assess the impact of your roadmap. Are you hitting your milestones? Are users engaging as expected? Embrace data; it's your compass in the product wilderness. Learn: This is where the magic happens. Analyse the data, listen to customer feedback, and be open to iteration. Learn from successes and failures alike.