Big data: massively useful tools or just more hype from overactive vendors, analysts, and vendors? It can be both at the same time. With all the attention on the practice of analyzing large amounts of information to gain critical management insight, it is almost impossible to avoid overanxious marketers. No, working with big data won't automatically increase revenues, raise gross margins, uncover markets clamoring for your offerings, or identify critical delays in your supply chain.
Yet many companies, particularly middle market companies trying to hit the next level of growth, can effectively use large amounts of data to help expand business. The concept is straightforward. By examining patterns within data, executives can learn things to improve their decision making and find or refine opportunities.
For example, Vienna, VA-based software company Eloqua wanted to create a new application category - revenue performance management - to solidify its marketing. So it looked at how people on social media would mention its name and the term "revenue" versus a pairing between revenue and the company's biggest competitor. Even with significant online efforts to establish itself, the other company got twice as many mentions. It was a clue to get a new SEO consultancy and increase the creation of online content. Eventually, Eloqua caught up.
The practical ways in which companies use analysis of large data sets are many. Look at how sophisticated retail chains choose new locations. The idea of using large amounts of data is nothing new in this endeavor. Planners look at neighborhood demographics; work or residence densities; previous customer purchase data; foot and transit traffic patterns; real estate prices; taxes; analysis of local businesses; and other factors to determine which locations offer the best possibility of success.
As researchers recently found, information from social networks such as Foursquare allowed them to consider geography and user mobility and feed that information to machine learning algorithms that could help explain whether a retailer would succeed in a given location. For example, examining locations of Starbucks, McDonald's restaurants, and Dunkin' Donuts restaurants in New York, it became clear that "50 percent of user movements originate from nearby venues within 200 to 300 meters, and 90 percent of movements occur within 1 km." Skip such data and a company might assume a broader consumer reach.
Related to location is the efficient use of resources. Big data analysis could help a CEO and CFO better understand both revenue and profit contributions from different parts of the organization. Once identified, management could better know the bottom-line expectation of investing capital in one division versus another.
Big data can help companies like insurance firms - and others - better recognize which customers are the best fit for corporate strategy. Then you can focus retention efforts where they are most important. Another use of large scale analysis would be to segment existing customers with internal and social media data to model which prospects might also make good customers. Amazon.com is a giant now but wasn't always. One of the reasons it grew as it did was the application of data analysis to operations and customer relations - using big data to fuel growth.
Adopting these techniques is far from easy for a host of reasons:
- Few companies already have their data in clean and usable forms that lend themselves to analytics.
- Old analytic concepts and tools will not necessarily be up to the need because, according to Andrew McAfee and Erik Brynjolfsson from MIT, big data is different from ordinary analytics in three ways: the volume of data, the speed at which analysis is done, and the variety of data types a company might use.
- A business should not attempt such analysis unless it has already mastered incorporating ordinary analytics into effective management, which means a lot more than reading reports.
- A company will need access to expertise both in the tools and in how to draw useful conclusions and form appropriate strategy.
All that said, the results are worth the effort. Middle market companies that want to achieve their potential will need the boost that big data can offer. Otherwise, they will be competing in tomorrow's market with yesterday's tools, leaving them vulnerable to rivals.
Erik Sherman is an NCMM contributor and author whose work has appeared in such publications as The Wall Street Journal, The New York Times Magazine, Newsweek, the Financial Times, Chief Executive, Inc., and Fortune. He also blogs for CBS MoneyWatch. Sherman has extensive experience in corporate communications consulting and is the author or co-author of 10 books. Follow him on Twitter.