MVPs are often used as a way to chunk up our full feature scope into manageable parts that we can implement one step at a time. This approach does not really help us much in deciding what should be in scope or out of scope, and what should be high priority or low priority.


The true power of MVPs is facilitating fast learning. Will our proposed solution actually bring the business impact and value we think it will? What assumptions need to be true to achieve this impact? What is the data from actual users and customers telling us?

This talk

  • will introduce MVPs as minimal validations rather than feature sets;
  • will offer some examples of techniques to identify and prioritise assumptions and validate them by running experiments capturing real-life data;
  • will demonstrate we should not design the version of a product we can go live with upfront, but rather give ourselves the freedom to stumble upon it during a series of deliberate experiments.

Learnings

  • Analyse requirements as assumptions
  • Understand different validation techniques
  • Rethink scope as something to be discovered rather than defined

Trainer