CRO Guide to Data Science Whitepaper

5

8

DATA UNAVAILABLE OR DIFFICULT TO ACCESS

PRIVACY ISSUES

30.2%

19.8%

The success of data science also relies on getting your hands on the right kind of data. With infor- mation often scattered across different lines of business, gaining access to a sufficient range of data in appropriate formats can challenge the most dogged data scientist. 23

Concerns about the security of data and the threat of identity theft, privacy invasion, and social media stalking have never been greater. So, it’s critical to determine if and how you can gain permission to use and process the data that might yield the most useful insights. 24

6

9

RESULTS NOT USED BY DECISION MAKERS

LACK OF DOMAIN EXPERT INPUT

24.3%

19.6%

Even the most instructive insights will go to waste if they aren’t acted upon by decision makers. That’s another reason for getting board-level support from the start and ensuring that business requirements guide your strategy at every stage, from what problem you are solving to how results will be used.

Data science is all about computer wizardry, right? Wrong: you need to underpin every data science strategy with sound knowledge of the business domain under scrutiny. Think of data scientists as a bridge between the IT department and top management, bringing together the business requirements of the strategy with the technical know-how to make it happen.

7

EXPLAINING DATA SCIENCE TO OTHERS

22.0%

10

CAN’T AFFORD A DATA SCIENCE TEAM

17.8%

There are two aspects to this particular obstacle. First, the business leaders that are paying for the data science strategy must appreciate the point of the project and the value it will deliver. Second, the results must always be presented in a way the business understands. In both cases, the CRO can help cut through the complex concepts and potentially baffling jargon of data science to show the concrete objectives and bottom-line benefits.

With their skills in short supply (see barrier 2), the ongoing rise in demand for data scientists can make them expensive to hire. Currently, in fact, they can earn base salaries up to 36% higher than other predictive analytics professionals. 25 But as many early adopters have shown, the business benefits can ultimately well outweigh the costs.

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