Why do so many data science efforts still fail organizations' In many cases, there is a gap between the models that data scientists produce and the information that business managers need. Data science work must do more than model data: It must connect to the specific decisions managers face. Here's how leaders can sharpen their focus on decision science. Imagine that, as an operations manager at a global retailer, you have invested heavily in data science. Your data science team has built sophisticated models that produce demand predictions for the company's products with impressive accuracy. Yet, when the CEO, seeking to increase profit, asks you how much inventory should be held and where, the answers are not clear. The models predict demand but do not tell management what to do with those predictions. After investing millions of dollars in data science solutions, the company realizes it has many insights about demand but few decisions to act upon. This is not a unique scenario....
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