Before you launch your machine learning model, start with an MVP

I've seen a lot of failed machine learning models in the course of my work. I've worked with a number of organizations to build both models and the teams and culture to support them. And in my experience, the number one reason models fail is because the team failed to create a minimum viable product (MVP). In fact, skipping the MVP phase of product development is how one legacy corporation ended up dissolving its entire analytics team. The nascent team followed the lead of its manager and chose to use a NoSQL database, despite the fact no one on the team had NoSQL expertise.