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42 The Real Work of Data Science

evaluated the impact of this policy based on data on discipline, student social acclimation,
student–teacher relationships, dropout rates, exam scores, and matriculation, under a strict
privacy protection regimen. Data from adjacent cities, where the free choice option was not
enforced, was used as a control.
Lavy’s analyses showed that those who were given the choice of their schools showed an
increased enrollment in academic colleges and a 5% increase in annual earnings at age 30.
V{D}, the value of the data; V{PS}, the value of the problem solved; and T(I}, the time for
which these benefits last, are all exceptionally high in the Lavy study.

Implications
Not surprisingly, most data scientists prefer to analyze data rather than to engage in an
internal political debate. But the cold, brutal reality is that everything about data science is
contentious – for example, there are plenty of smart, well‐meaning people who believe data
science is just the latest management fad. There are also plenty of others who believe that
they will lose their power, position, even jobs if data science takes over. So, they fight it tooth
and nail. Finally, many people trust their intuitions over data science findings, and they can
rightly cite untrusted data as the rationale. Data scientists and CAOs ignore these realities
at their peril!
Thus, the real work of data science includes selling it in a tough market filled with other
good ideas, powerful special interests, and fear. Your best sales tool is solid results that advance
the company, government agency, or nonprofit. This aspect of the work may prove uncomfort-
able for many. Our best advice is this: get over it!