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Teach, Teach, Teach 61

decision‐makers appreciate how difficult even the simplest measurement can be and is usually
great fun. The second exercise aims to help participants develop a deeper appreciation for data
science and is considerably more demanding. Finally, the starter set of questions aims to help
decision‐makers ask good questions. In the short term, this experience may not be so pleasant.
But the long‐term benefits, as decision‐makers become more comfortable, both with specific
analyses and data science more generally, may prove enormous.
In parallel, they can also improve everyone’s quantitative sophistication. Think about this for
a moment – imagine how powerful a company would be if everyone, across the entire company,
did just a little more basic data science every day! You will probably benefit from a comprehen-
sive program covering variation and the distinction between correlation and cause and effect,
A/B testing, and contemporaneous topics specific to HR, marketing, drilling for oil, and so forth.
We’ll build on these exercises in the next chapter, which focuses on the InfoQ framework.
To conclude, the real work of data scientists and CAOs involves helping colleagues and
decision‐makers grow more comfortable with data science. Thus, teach them the basics in
easy, engaging ways when you can and confront more difficult issues as opportunity permits.