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Malcolm Gladwell, modern problems, and the analytics age

I had the great pleasure last Thursday of hearing Malcolm Gladwell, journalist and author of the books Outliers, Blink, and The Tipping Point, speak at SAS Institute’s Innovators’ Summit in Chicago. I gave one of two keynote presentations in the morning and Gladwell gave the keynote in the afternoon. I believe that Gladwell is one of the great thinkers and communicators of our time, and his words on Thursday afternoon led me to believe this even more fervently.

Gladwell’s topic was well-chosen for a group of people who spend their time making sense of data (mostly statisticians) using SAS’ visual analysis product JMP. He spoke about problem solving and the fact that our problems today are different from those of the recent past. Our former problems were usually solved by digging up and revealing the right information. He used Watergate as an example, pointing out that key information was hidden, and the problem was solved when Washington Post journalists Woodward and Bernstein were finally able to uncover this information that had been concealed. Modern problems, on the other hand, are not the result of missing or hidden information, Gladwell argued, but the result, in a sense, of too much information and the complicated challenge of understanding it. Enron was his primary example. The information about Enron’s practices was not kept secret. In fact, it was published in several years’ worth of financial reports to the SEC, totaling millions of pages. The facts that led to Enron’s rapid implosion were there for anyone who was interested to see, freely available on the Internet, but weren’t understood until a journalist spent two months reading and struggling to make sense of Enron’s earnings, which led him to discover that they existed only as contracts to buy energy at a particular price in the future, not as actual cash in the bank. The problems that we face today, both big ones in society like the current health care debate and smaller ones like strategic business decisions, do not exist because we lack information, but because we don’t understand it. They can be solved only by developing skills and tools to make sense of information that is often complex. In other words, the major obstacle to solving modern problems isn’t the lack of information, solved by acquiring it, but the lack of understanding, solved by analytics.

Gladwell’s insights were music to my ears, because he elegantly articulated something that I and a few others have been arguing for years, but he did so in a way that was better packaged conceptually. Several months ago I wrote in this blog about Richards J. Heuer’s wonderful book Psychology of Intelligence Analysis, and featured his assertion that we don’t need more data, we need the means to make sense of what we have. More directly related to my work in BI, I’ve stated countless times that this industry has done a wonderful job of giving us technologies for collecting and storing enormous quantities of data, but has largely failed to provide the data sense-making tools that are needed to put data to use for decision-making.

The title of my keynote at the Innovators’ Summit this year was “The Analytics Age.” I argued that the pieces have finally come together that are needed to cross the threshold from the Information Age, which has produced great mounds of mostly unused information, to the Analytics Age, when we’ll finally learn how to understand it and use it to make better informed, evidence-based decisions. The pieces that have come together include:

  • plenty of information
  • proven analytical methods (especially statistics enhanced through visualization)
  • effective analytical tools (only a few good ones so far, but this will change)
  • a growing awareness in society that analytics are needed to replace failed decision-making methods, based on whim and bias, that have led us to so much trouble

Although many software vendors claim to sell analytics tools, seeking to exploit the growing awareness that analytics are powerful and necessary, few actually understand this domain. Their products demonstrate this fact as silly imitations of analytical techniques. This is true of every traditional BI software vendor in the market today. As Gladwell pointed out, the paradigm has shifted; the skills and methods that worked in the past can’t solve the problems of today. Only a few software vendors that play in the BI space (none of which represent traditional BI) have the perspective and knowledge that is required to build tools that can help us solve modern problems. Most of these have either evolved from a long-term focus on statistics, such as SAS Institute, or have emerged as spin-offs of academic research in information visualization, such as Tableau and Spotfire. If traditional BI vendors want to support the dawning analytics age, they must retool. They must switch from an engineering-centric worldview, focused primarily on technology, to a design-centric perspective, focused primarily on the human beings who actually work with data. Only then will they be able to build effective analytical tools that take advantage of human visual and cognitive strengths and augment human weaknesses.

Borrowing another insight from Gladwell, I believe we are approaching the “tipping point” when people will no longer be fooled by analytical imitations and will begin to develop the skills and demand the tools that are needed to get the job done. Business intelligence vendors that fail to catch on or to turn their unwieldy ships in time will be left behind. The times are changing and so must they.

If you’re among the minority in the workforce today who understand analytics and are willing to tie your talents to good tools that utilize them fully, you are in for the ride of your life. As Hal Varian, University of California, Berkeley professor and current Chief Economist at Google, recently stated in an interview, “statistician” will become the sexy job of coming years, just as software engineers enjoyed that position for years, beginning in the 1980s. Evidence of this can already be discerned. Even in today’s depressed job market, graduates with degrees in statistics are in extremely high demand and are being rewarded with high salaries. You don’t need a Ph.D. in statistics to be a good data analyst, of course. You must, however, have the soul of an investigator and a flexible, analytical mind. You must be able to think critically. Daniel Pink made this case brilliantly in his book A Whole New Mind (2005). What I’m calling the “analytics age,” he called the “conceptual age.”

Our schools are not geared up to produce this kind of workforce, so if you’ve somehow managed to develop these skills, there’s a place of honor for you in the world that’s emerging. You’ll be appreciated in ways that were rare during those years when I worked in the corporate world. Won’t it be refreshing to actually be thanked when you reveal, through painstaking analysis, faults in your organization’s policies, practices, or assumptions, rather than being ignored or punished? Won’t it be nice to be rewarded when you save your organization millions of dollars by warning against a doomed decision rather than being demoted for speaking a politically unpopular truth? Won’t it feel good to prepare a well-reasoned case for a specific course of action and not have your hard work discarded in the blink of an eye by a manager who says “No, we’ll do it my way, because I’m the boss.” If your heart sings at these prospects, hold your head up and stay true; your day is coming.

Am I dreaming? Can a society and a workplace in which reason and evidence trumps whim and bias really emerge with enough strength to shift the balance? I hope so, but there’s no guarantee. I’m going to do everything I can to help usher it in. The opportunity is now. I don’t want to live in the sad, dumb, unjust society that is our future if this opportunity is missed.

Take care,

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