EMC Shows the Power of Big Data Analytics
Your company is doomed to fail if 'the biggest jerk at the table' makes all the decisions in spite of comprehensive data analysis. EMC and its customers are taking analytics seriously, CIO.com columnist Rob Enderle says. You should, too. It's a lesson Mitt Romney learned the hard way.
Fri, November 16, 2012
CIO — This week I attended EMC's analyst briefing, but before things started I had dinner with Jim Bampos, EMC's vice president of quality. Bampos is arguably the technology industry's leading expert in the area of customer care, with one patent in hand and two more in process.
I'd also just finished a review of the use of data analytics in the U.S. election and in that exercise had been fascinated by the fact that Mitt Romney didn't use analytics properly and President Barack Obama did.
Romney had better tools but outsourced the effort, while Obama created the capability internally, and the result is now history. What fascinated me was that the candidate who was a former CEO and widely believed to be the more capable manager clearly didn't know how to successfully use analytics—and likely mirrored many executives who use the buzzword but don't really understand what it means.
EMC, in contrast, is using analytics from its Green Plum acquisition to not only provide better service but to shift resources to areas where they can provide the greatest return. EMC is about to implement this competitively to focus customer acquisition efforts on area where its competitors are the most exposed.
Why Most IT Executives Hate Valid Data
What is fascinating about how analytics are used--and I think this played out in the recent election--is that they often fail against the common practice I call "biggest jerk at the table." The Argumentative Theory argues that people care more about winning an argument than they do about being right. When applied to business, this means that decisions are often made based on who is the most powerful person at the table. While the practice assures personal power, it also leads to a lot of mistakes.
Big data analytics can provide information that puts the data scientist in the position of power. The executive, to preserve his power, must resist. Rather than assure the accuracy of the data, efforts are made to make the results conform to the beliefs that powerful people already have. Not only are the decisions increasingly wrong, but data analytics is made redundant.