Rank by Valuing the Learning

Sometimes it’s worth learning more about a feature before you decide how to manage the roadmap or rank the entire feature set. In that case, consider these three approaches:

• Instead of valuing an entire feature set, decide what you want to learn from an MVP or an MVE.

• Spike the work to understand the feature set.

• Try something quite risky to understand the risks more.

Learn from an MVP or an MVE

Back in ​Consider Minimum Viable Products and Experiments​, I suggested you might want to consider what was the minimum requirement for products and experiments. Especially if you are thinking about creating small MVPs or experiments, you might value some of those features higher than others.

If you know what you want to measure and learn, you can create small experiments that provide you value. I’m not suggesting you work on an entire feature set, one small experiment at a time. I suggest you consider the smallest experiment you can to try to create some data that will help you learn what to do next.

Spikes Can Help Everyone Understand the Value

Sometimes you need to value something you’ve never done before. You can’t know how long it will take, so you can’t use Shortest Job First. You might not even be sure of what the entire feature set is.

In that case, you might consider timeboxing a little work to understand what the entire feature set is. You might even learn enough to be able to estimate it. That timebox is a spike.

Back in ​Experiment and Spike to Explore​, you learned about how to use spikes. Consider timeboxing your spikes to not more than one day. Your team might want to make it several hours instead of an entire day. I encourage the entire team to work on the spike, swarming or mobbing to complete the work. At the end of that timebox, the team can see what it completed and what is left to complete for an MVP. (See Predicting the Unpredictable [Rot15] for more details.)

Use Risk to Assess Value

Sometimes you want to try something that’s quite risky, because you can learn more about the risks. In that case, consider taking one story from a feature set, or create an MVE to try. Rank that story or experiment high because the learning from finishing that one story will help inform the team and the product owner about the rest of that work.