Makes sense. Look for the needs, and also create them by letting people understand the possibilities. I also like the fact that they are calling it 'decision sciences', rather than data science, because it's about the decisions. Which is where the improvement need is.
In McKinsey:
" ... To realize the full potential of data analytics, start with your people and their needs, says Cameron Davies, the company’s head of corporate decision sciences.
The most effective data-driven decisions are often the ones in which the users themselves drive data demand. As a general rule, frontline employees know more than data scientists, even the most brilliant ones, about the problems they need help solving. Those same employees are also the ones who must embrace—but sometimes ignore—the data-analysis tools and interfaces companies provide them. Cameron Davies, head of corporate decision sciences for NBCUniversal, recently sat down with McKinsey’s Kayvaun Rowshankish and David Schwartz and described how these demand-side dynamics operate at his company. To be sure, analytics leaders can and should push employees to stretch their thinking, and they should provide better tools to help generate faster, more insightful solutions. But at the end of the day, says Davies, it’s the users’ needs that are being solved for. Leaders striving to make data a source of competitive advantage must respect this reality and strive for a culture where people across the organization are driving demand for data, instead of the other way around. .... "
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