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Today’s Lesson: Finding a Useful Definition for ‘Big Data’

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Looking back, 2015 was finally the year that every professional service firm leveraged Big Data to drive remarkable results.

OK, that’s an exaggeration. But could it be that 2015 was the year in which everybody agreed on a definition of Big Data? In recent years, Big Data has become a buzz-term in search of a clear meaning. Yes it involves data of such magnitude that it is so hard to manage or manipulate that it requires sophisticated data-management tools to translate it into the kind of useable guidance and illuminating insights that every business needs. And the cost of such tools, like the price of computing power and storage costs, had dropped to the point where Big Data capabilities are within reach of small companies.

Certainly it’s a given that every company—or at least those where management is eager to trounce any and all competitors—must learn to master Big Data. Or is it? “We’re not using Big Data, and I’m not convinced we ever will be,” says CFO Bob Scopinich. “I’m not sure what Big Data would be in our business.” No, Scopinich isn’t involved in one of those fashionably nostalgic businesses, such as typewriter repair. The 44 year old serves as CFO for Goddard Systems, a franchisor of childhood education systems. Currently there are 430 Goddard School franchises in almost 40 states, with system-wide revenues of about $600 million.

Based in King of Prussia, PA, the company hasn’t been reluctant to invest in technology. Five years ago, it built its own data-management system from scratch, having found off-the-shelf options lacking. The proprietary system has already yielded insights that have improved decision making. Among other things, the company discovered that its decision to focus its advertising efforts in the first quarter of the year was misguided. Fewer than expected January inquiries, the data revealed, converted into enrollments at back-to-school time. The company shifted additional ad spending to the second quarter, which turned out to be more efficient. “It gave us a little insight into the way our parents buy,” says Scopinich. “It wasn’t a huge shift, but it was a shift.”

With every franchisee’s information entered in the system as of late 2015, Scopinich plans to delve into the data to explore other shift-inspiring insights: What are the early indicators that a customer may be leaving? Does teacher turnover boost the risk that more parents will enroll their kids elsewhere? What happens if the schools invest in a new playground? Last year, Goddard’s schools launched a summer program, aimed at keeping parents connected to the school, if only in-between vacations and camp stints. “Our business is like any business,” says Scopinich. “You don’t want to give your customers—in our case, the parents—a reason to look somewhere else.”

While Scopinich expects the company to benefit from the data in many ways—such as finding the optimal mix of full-time and part-time attendees— he doesn’t perceive any of it as reaching the proportions of Big Data. Key aspects of the educational experience can’t be depicted by data. “There’s no way to capture the daily experience of a child and whether that child had a good day,” says the father of two. “There’s no data around whether a parent dislikes a teacher. It’s just not get-able.”

That said, Scopinich is well-aware of the fact that Goddard’s schools simply don’t produce the reams of data points—about tracking those who dial in to call-centers or analyzing the customers’ online buying process—that combine to form the overwhelming phenomenon known as Big Data. His goal will be met “if we are getting the data we need to do what we want to do.”

That may not be the road to Big Data. Or it may be the best definition of the phenomenon yet.

— Josh Hyatt

The post Today’s Lesson: Finding a Useful Definition for ‘Big Data’ appeared first on Performance.


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