Wednesday is Pratt Statistics Day!
OK, that title is a lame reach on the old Prince tagline, but as you’ll read in this second of a series on Big Data and Analytics, I’m just a “king or queen of hype.” So says today’s guest blogger, Lisa Pratt. You met Lisa last week, and today she explains how “Big Data” may be big, but it’s not new… Oh, and since although Lisa works in Marketing, she definitely doesn’t consider herself a “hype queen,” so let me just say… Workforce Analytics.
As someone who has built a successful career in mining data to drive marketing decisions, I am stumped by how marketers – the kings and queens of hype – missed the opportunity to take credit for Big Data and Analytics. Recently, other than the word Cloud, there are few words that generate more buzz than “Big Data and Analytics”. What Big Data and Analytics really mean is taking large amounts of data, finding meaning in the data using statistical techniques and, for those who do it well, translating that meaning into a “so what” that can be acted on. None of these elements are new. Large amounts of data, statistics, hypothesis testing, and business tactics have been around for a very long time. They just didn’t have a fancy name.
In fact, back in the late 1960s Bob and Kate Kestnbaum first applied financial models and customer lifetime value to prioritize direct marketing contacts. By the 1980s, database marketing was a well-established way to assure that the expensive piece of glossy marketing material was being mailed to the customers and prospects that had the highest likelihood of responding. Credit card companies use Big Data and Analytics to detect credit risks so they can avoid sending offers to those likely to default, and banks leverage data and analytics to identify potential high net worth customers for special treatment. This has been standard practice for decades.
Big Data and Analytics strategies are not new or risky. They just weren’t sexy until recently. And, of course, because so many things can, and are, tracked, there has never before been such a wealth of data. With the increased interest resulting from re-branding Big Data and Analytics, companies are taking notice and finding that they can leverage both internal and external data as a strategic asset in many parts of their organizations. For companies thinking about getting their feet wet with Big Data and Analytics, I say, “Come on in, the water is fine. But it is starting to get crowded in here, so hurry up.”