Survey Finds Barriers That Prevent Organizations From Realizing Data Science Return on Investment

With the growth, change, and perhaps excessive hype in data science today, many in the field are interested in better understanding how their data science management programs compare with programs in other companies. To help  provide this insight, Domino Data Lab conducted a survey of more than 250 data science leaders and practitioners  across organizations of all sizes and a variety of industries. The survey, which ran from November 2017 through January 2018, looked at their capabilities, concerns, and priorities. In this document, we provide both the results of  the survey as well as an analysis of responses to help guide organizations on their journey to become model-driven.

Almost all organizations believe that data science can dramatically change their competitive position in the market,  and become one (if not the) key factor in their future success. However, the stark reality is that most organizations are  unable to make data science a core capability and are therefore making large investments without the ability to show  return. Many companies start with the idea that data science is a technical practice. They need to grow to develop data science as an organizational capability. The few that have successfully created a data science discipline are reaping  returns; they are model-driven. The survey revealed four major themes amongst the backdrop that data science as an  organizational capability is relatively immature.