How to Answer the "Why" Behind a Data Strategy?

Critical success factors behind a modern analytics landscape lies from the fact that it is not restricted to technical excellence but comes from answering the trickier "why" questions. This includes understanding deep learning models behind business problems; trusting data model predictions and explaining outcomes in a simple yet comprehensive language. Of late, many of the data scientists are more interested to sharpen their skills and unearth interesting nuggets buried in data than engaging themselves to this softer cause. Though this may sound natural with a narrow focus on data and the tools required to explore it, understanding the critical'why' is more mainstream to reach out to more users across the value chain. To understand the nuances of a Data Strategy, let us understand it from a consulting team's point of view who is assisting a large MNC to develop its data strategy.