The big picture is a sprawling mass, and finding an entry point is one of our most significant challenges. In Business Strategy For Data Scientists, I teach a data science maturity assessment framework. The process looks at the business and data organization. It is an honest self-assessment of where the business is right now and the capabilities that exist today.
We must identify a baseline to move forward, which is the obvious starting point. Forward to where? Assessing the industry and marketplace answers that question and is the obvious step 2. With those, the business understands where it is, where competitors are, and what opportunities exist to deliver value or gain an advantage.
In the last post, I explained where I get brought in by my clients. It is never at step 1. Pieces have been implemented in a disconnected way. In a perfect world, we would get a clean slate. Ten years into mainstream data science adoption, few businesses are a clean slate. Immature companies treat transformation as a one-time event and build roadmaps with a finish line.
The big picture shows transformation is continuous, which changes everything. This post and this part of the series explain how to inherit and modernize a legacy transformation process because that's our reality.