How to create and sustain a Data Science Centre of Excellence?

Creating a Data Science Centre of Excellence takes more than just funding and hiring data scientists. But while it takes vision and time, keeping in mind a few core principles can keep your journey on track and effective. These principles include (1) collaboration/integration with the rest of the business, (2) building technical support areas and (3) being an effective talent hub. In this discussion, we discuss in a bit more detail some of these pillars

(1) Collaboration/Integration with the rest of the business : How the goals of this centre of excellence connect with the rest of the business is the most critical factor driving this success and directions. Questions to think over are (a) is this a key driver of strategy or enabler ? (b) what are the critical KPIs of this business (c) where is the voice of the data scientist in the day to day ops

(2) Engines of support : Depending on the scale of your ambition, there are technical support areas which can make or break your operations. These areas are multiple – Data Engineering, Data Science toolkit development, etc.

(3) Talent hub : A data science centre of excellence with all its automation and best machine learning capabilities is nothing without the data scientists, i.e. the "team". So creating a strong culture is probably the strongest enabler that you can have and often under-invested in.