In today's world of Big Data, the rewards go to the companies that are able to gather the most data, right?
Not so fast. Companies that can succeed in today's fast-moving marketplace should learn to process information like a hockey player. Not just any hockey player, but the Great Wayne Gretzky.
That's the premise put forth by Vivek Ranadive, founder and CEO of TIBCO, and Kevin Maney in their latest book, The Two-Second Advantage: How We Succeed by Anticipating the Future – Just Enough.
Gretzky's secret was in the wiring of his brain – he was able to store “whole symphonies of complex movements in single chunks.” In another analogy, while other players look at the ingredients of the game from one play to another, Gretzky was able to see “the whole cake.”
So how does this apply to the insurance business? Ranadive and Maney argue that successful people get that way because they are able to make informed decisions much faster than the norm. While most people do not have the cranial wiring of Wayne Gretzky, they can build systems that can help them quickly make informed decisions, based on the best available information. And this doesn't necessarily require having access to every piece of information out there – rather, a la Gretzky’s brain – they need to merely have wholesome “chunks” of relevant data.
“Instead of constantly having to access all the information he had stored about hockey during games – which wouldn't take too much computational time and effort – Gretzky was able to access whole chunks of information that he'd already assembled, analyzed and understood... all Gretzky had to do during a game was reference his mental model and then let the information unfolding in the game flow through his senses... That would in turn generate a prediction: this is what's probably going to happen...”
The lesson here, the authors relate, is not to try to build or maintain a gargantuan information system capable of constantly sorting through terabytes and petabytes worth of data – that would be a never-ending, thankless, Herculean task. Rather, the goal should be to develop systems that can access just enough of the right data when needed to deliver real-time insights. Ranadive and Maney refer to this kind of system as one that engages in “chunking” and “predicting" – capable of constantly categorizing data and seeing relationships, and then using that to build chunks and an ever-evolving model. As the authors so aptly put it:
“Predictive, talented systems will be built around the idea that a little bit of the right information just ahead of time can be more valuable than a boatload of information later.”
Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.
Readers are encouraged to respond to Joe using the “Add Your Comments” box below. He can also be reached at firstname.lastname@example.org.
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