By now, the idea of agile development and a Minimum Viable Product or MVP is prevalent. The problem is, while most people have the minimum part down, people often haven't mastered the viable…. especially when it comes to analytics.
To quickly recap,a Minimum Viable Product is an approach, where you’re focusing on creating a product with a sufficient level of features to be able to solve a particular problem. This first iteration is used to collect user feedback and develop the complete set of features for the final product to be delivered.
That’s all nice and well, but you may be wondering what the benefits to this approach are as it concerns analytics projects...
Learning, and learning quickly
Is your solution actually delivering the value that you are trying to create? In a typical project, you may be months down the road before what you’re building is actually in front of users. This makes it difficult to determine its viability for solving the business case. The whole point is to prove or disprove your initial assumptions sooner.
What part of your users current process is really frustrating them?
Are the analytics we designed actually guiding them through their workflow and making their life better?
By getting a usable set of features in front of user’s earlier in the process, we can collect feedback and determine if we are in fact on the right track.