The hype around data and analytics has reached a fever pitch. From baseball to biomedical advances, the media highlights one money-making or money-saving corporate experience with analytics after another. Stories abound about data scientists applying their wizardlike talents to find untapped markets, make millions, or save lives. Pundits have been talking up the promise of data in grand terms for several years now: Data has been described as the new oil, the new soil, the next big thing, and the force behind a new management revolution.1
Despite the hype, the reality is that many companies still struggle to figure out how to use analytics to take advantage of their data. The experience of managers grappling, sometimes unsuccessfully, with ever-increasing amounts of data and sophisticated analytics is often more the rule than the exception. In many respects, the hype surrounding the promise of analytics glosses over the hard work necessary to fulfill that promise. It is hard work to understand what data a company has, to monitor the many processes necessary to make data sufficient (accurate, timely, complete, accessible, reliable, consistent, relevant, and detailed), and to improve managers’ ability to use data. This unsexy side of analytics is where companies need to excel in order to maximize the value of their analytics initiatives, but it is also where many such efforts stall.
Moving past the hype takes a measure of resolve that few companies demonstrate. A 2015 survey of more than 2,000 managers conducted by MIT Sloan Management Review and SAS Institute — as well as more than a dozen interviews with executives at global companies — reveals insights about the unglamorous but necessary actions required to improve decision making with analytics.
Five key findings came from this research: