Often, organizations build roadmaps based on gut feelings, what stakeholders want, and urgent business needs. While experience is important, it can be biased, lack info, or have conflicting priorities. Using data for roadmapping offers a clearer, more objective way to decide what to build, when, and why. When decisions are based on engineering data, product and engineering leaders can focus on results instead of opinions.
Olumide Peter Obasa, a renowned software engineer with a lot of experience building systems that can handle lots of growth, has seen how engineering data can change how things are prioritized.
He knows that data alone isn’t enough, but when you understand it right, it’s a great way to put resources where they matter most. Olumide has used data to find problems, decide where to invest in features that matter, and shield engineering teams from unimportant requests.
One great use for engineering data is understanding how fast things are being developed and how often they’re being released. By watching things like cycle time, lead time, and how often changes cause problems, teams can spot inefficiencies. Olumide says that without seeing these numbers, a roadmap can easily become unrealistic. Engineering data helps make sure goals are achievable by showing what the team can actually do without sacrificing quality.
Also, it’s helpful to track how people are using existing features and how well they’re working. Some features may seem important but aren’t used much, while others might be surprisingly key to keeping users happy or bringing in money. Olumide has worked with product managers to use this info to move resources around, improving or cutting back on features that don’t do well and investing more in those that do. This way, the roadmap reflects what’s actually valuable.
Using data for roadmapping is also important for handling technical debt. If ignored, debt can slow down feature releases and make it harder to reach goals. By measuring the impact of debt with things like how many defects there are, how often problems occur, or how long it takes to fix them, engineering leaders can clearly show why it needs to be addressed. Olumide has led efforts where these numbers were used to get time set aside for fixing things and improving infrastructure, making sure things are sustainable in the long run while still delivering in the short term.
Working together is key to making this work. Olumide says that data shouldn’t just be for engineers but for everyone to use when making decisions. When product, design, and engineering all look at the same data, trade-offs become clearer, and discussions move from opinions to facts. This not only makes the roadmap better but also builds trust between teams.
In the future, data-driven roadmapping will become even better as engineering data tools get more advanced. Machine learning and being able to spot problems early could help teams see risks before they happen, test out roadmap decisions, and keep priorities up to date in real time. Olumide thinks that leaders who invest in these things will be able to adapt quickly to changing markets while staying realistic.
For engineering organizations, using data for roadmapping isn’t just a good idea; it’s important for growing well. By using data along with good judgment, leaders can focus on initiatives that have the biggest impact while keeping things moving forward. Olumide Obasa’s experience shows how this can change not just the roadmap but also the conversations, culture, and confidence behind it.
