Executives Say Big Data Pays Off, But Implementation Is ‘Oversimplified’

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    Everybody wants to explain technology in terms that business leaders can understand. Generally, that’s a good thing, but it can have a downside.

    When you oversimplify the technology, it can help sell in the short term, but in the long run, it leads to unpleasant surprises, scope creep and skeptical business leaders.

    That’s what seems to be happening with Big Data analytics, according to eight executives from companies heavily vested in data and analytics.

    I know eight isn’t a significant sample size, but this wasn’t research. It’s a McKinsey & Company discussion group featuring leaders from companies such as Samsung Mobile, Wal-Mart and American Express.

    The McKinsey directors actually asked if data and analytics were overhyped. Surprisingly, the answer was a qualified “no.” Big Data analytics really are delivering, but “too often senior leaders’ hopes for benefits are divorced from the realities of frontline application.”

    For the most part, these executives recommend the same best practices that research firms suggest, including creating a center of excellence and allowing customers to opt in or out of data collection, sharing and use. But they also add hard-learned lessons to these best practices.

    For instance, the participants felt a data analytics center of excellence was only worth the effort if it is located in the part of the company where data analytics could have the most significant and visible impact on business strategy.

    They also said the center of excellence should evolve, taking on increasingly ambitious work and helping spread analytics best practices across the company.

    One major takeaway from the discussion is that even these large, analytics-driven companies have trouble finding and recruiting data scientists and analytics experts, even when they recruit at elite universities and MBA programs. Apparently, there just aren’t enough institutes offering the correct combination of courses to develop the necessary skills.

    Experts say organizations are managing without data scientists, though. One way to do this is to build data science teams that collectively have the needed skills, but several of these executives say their companies are recruiting from leading Internet companies (did you catch that, Google?). Others are investigating whether they can find the talent offshore.

    Overall, the McKinsey article is a nice reality check on what it takes to really squeeze value from Big Data analytics. The good news, though, is that most companies agreed that Big Data investments do pay off in process efficiencies and improving basic predictive business analytics, such as price optimization, and sometimes in both.

    Loraine Lawson
    Loraine Lawson
    Loraine Lawson is a freelance writer specializing in technology and business issues, including integration, health care IT, cloud and Big Data.

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