Business has always been competitive, but never as much as it is now. A global environment ensures that rivals can appear in any part of the world. Mobile capabilities extend where companies and customers expect to interact. Margins, driven down by competitors, get thinner, meaning that efficiency comes at a premium.
Those aren’t solely big company problems. Small business owners will feel the pinch. Just as business has always been competitive, owners and executives have always needed knowledge and know-how to operate effectively. However, what worked and was sufficient even five years ago is no longer enough.
Even people with an MBA are learning that an entirely traditional educational foundation comes short. The reason is big data, particularly when paired, as it increasingly is, with geographic information systems (GIS). Such companies as General Electric and Chevron “use complex data analysis to reduce costs or generate revenue,” as the Wall Street Journal points out. Danish wind turbine manufacturer Vestas Wind Systems has harnessed big data to help customers better place turbines, cutting response time a matter of hours, rather than taking weeks to provide the information customers needed. Small businesses are also using big data.
Ginger.io monitors behavioral information gained from cell phones and then uses the insights to uncover health patterns, including oncoming illness. Big data can provide even more when integrated with GIS systems that use location as a way to tie together otherwise seemingly unrelated information.
Organizations can plan where to place facilities, understand the types of goods and services that might be most wanted in a given neighborhood, better manage maintenance and repair operations, and otherwise significantly improve how they operate. Big data can even fuel predictive analytics, or determine what will happen in the future based on looking at the intricate interplays of data.
For example, automated fraud detection marries many different types of consumer and behavioral data, overlaid with geographic information, to fight criminals even as they are in the process of using someone else’s identity to commit fraud. And yet, sometimes the promise of big data can sound too good to be true.
As data expert Gregory Piatetsky-Shapiro points out on a Harvard Business Review blog entry, even as big data is eyed as a key tool in predictive analytics, sometimes it falls apart. Piatetsky-Shaprio was a co-author of a study that suggested that there were limits on predicting which particular wireless service customers would leave for a competitor. Those limits might mean that a targeted direct marketing campaign might not be successful enough to be cost effective.
Other attempts to predict the outcomes of human behavior, like Netflix determining what films you might like to see or which ads people would click on, can also quickly meet limits.
It’s not enough to grab onto big data and GIS as ways of improving organizational operations. Executives need extensive training and experience — like that provided by American Sentinel’s contemporary MBA online program — to grasp the possibilities and shortcomings of such analytic methods and make them work.