Data Science Maturity Model

Data Science Maturity Model

Jan 1, 2019

Many organizations are underwhelmed by the return on their data science investment. A narrow focus on tools, rather than a broader consideration of how data science teams work and how they fit into the larger organization have hampered their ability to reliably and sustainably deliver value.

The Data Science Maturity Model was developed to help data science practitioners and leaders identify capability gaps and direct future investment.

This paper:

  • Describes the model’s four levels of organization maturity and five evaluation dimensions: Structured
  • Discoverability, Analytical Speed, Breadth and Depth Organizational Process, and Organizational Cohesion.
  • Presents case study examples of teams at each of these levels.
  • Offers actionable advice for improving the function of your data science team.