Chapter 13. Data Science and Business Strategy

Fundamental concepts: Our principles as the basis of success for a data-driven business; Acquiring and sustaining competitive advantage via data science; The importance of careful curation of data science capability.

In this chapter we discuss the interaction between data science and business strategy, including a high-level perspective on choosing problems to be solved with data science. We see that the fundamental concepts of data science allow us to think clearly about strategic issues. We also show how, taken as a whole, the array of concepts is useful for thinking about tactical business decisions such as evaluating proposals for data science projects from consultants or internal data science teams. We also discuss in detail the curation of data science capability.

Increasingly we see stories in the press about how yet another aspect of business has been addressed with a data science-based solution. As we discussed in Chapter 1, a confluence of factors has led contemporary businesses to be strikingly data rich, as compared to their predecessors. But the availability of data alone does not ensure successful data-driven decision-making. How does a business ensure that it gets the most from the wealth of data? The answer of course is manifold, but two important factors are: (i) the firm’s management must think data-analytically, and (ii) the management must create a culture where data science, and data scientists, will thrive.

Thinking ...

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