Big data shouldn’t mean business as usual

The big data gold rush has become a stampede. Technology vendors are racing to bring big data solutions to the market, and companies with a never-ending flow of data are looking to big data to make better sense of their business—and to generate better value as a result.

The challenge is that amidst all this hype, the true value of leveraging big data may be lost as companies continue to operate as “business as usual.” As Tom Davenport, Fellow with the MIT Center for Digital Business, shared in a Booz & Company article, “A lot of [companies] aren’t really thinking differently about what to do with Big Data. Instead, they’re simply asking, ‘How can we use these technologies to save money?’”

Davenport makes the argument that the true value of big data is in its ability to help companies harness, analyze, and actualize external data. “One of the great advances is that so much of the data now comes from external sources: from social media, or macroeconomic data, or weather data, for instance. The fact that companies are becoming able to incorporate it into their planning and decision-making processes is a healthy development. If companies can include this kind of data in their models, they’ll have a much better idea of how successful they might be with a particular product or marketing campaign.”

How would that change of viewpoint play out in industry today? Think about the airline industry. Nearly every student of business has heard the story of American Airlines removing one olive from every dinner salad, resulting in an annual savings of $40,000. Yes, it made an impact on the bottom line, but it wasn’t really a business innovation. It was simply looking inward to see what could be cut.

Today’s airlines still struggle with profitability. They try to increase profitability by analyzing their routes, optimizing loads, reducing the number of flights and other “internal” activities. This is all well and good, but what benefits could airlines see if they used big data technologies and analysis on external data? The possibilities are endless.  In fact, just turning big data to “crunch” the information available on Twitter could be very interesting. Many airlines today conduct sentiment analysis on Twitter—mining the platform to determine how their customers feel and what they can do to respond to or change those sentiments. But what if, instead, they used big data to analyze consumers’ tweets about the competition, and then asked a product strategy group to come up with offerings that would capitalize on a competitor’s unhappy customer base?

“It still strikes me how few companies pay attention to such data in terms of looking at their markets and their customers and their competitors. I think the external focus is a great idea, and it’s the direction in which a lot of big data analysis is going,” said Davenport. “The ability to analyze the external environment is going to be a real point of differentiation from one company to another.”

So, as you begin to incorporate big data in your company, make sure you are not simply using a new tool in an old way.

Tom Davenport

is a Fellow with the MIT Center for Digital Business, a President’s Distinguished Professor of Information Technology and Management for Babson College, and a Co-Founder of the International Institute for Analytics. Davenport teaches in MIT Sloan’s upcoming Executive Education program, Big Data: Making Complex Things Simpler, occurring July 9–10, 2014.

This entry was posted in Big Data on Wed Apr 30, 2014 by MIT Sloan Executive Education

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