"Big data" and predictive analytics demystified

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The tornado of press, media, and commentary in the last year around "big data" as the cure all for what is ailing today's enterprises -- from stagnant top-line growth to flat bottom-line productivity --  has been fascinating, confusing, and complex. I keep waiting for the clouds (no pun intended) to open up and a house to fall.

While "big data" is an important enabler, it is robust analytics combined with a CPG manufacturer's (or retailer's) organizational ability to apply insights across product development, store layouts, media and consumer engagement, trade and promotion, and related functions that will drive the sales and market share uplift that will in turn drive profits.

Big data and predictive analytics demystified

Don't take my word for it, SymphonyIRI recently completed research of 160 senior executives representing CPG and retail companies in the U.S. and Europe as part of its new Analytics2020 initiative. Those companies with "above average" analytics capabilities enjoy operating income 14 percent higher than those with less developed analytics practices.

Focus on "good" instead of "great"

Today's hyperventilation about "big data" is reminiscent of past trends when managements convinced themselves that the latest and most expensive enterprise information management systems would cause revenues, profits, and margins to grow, ROI to soar, and the stock price to skyrocket. I was reminded of this a month ago when a client made plans to hold off modifying their price and trade strategy because "big things" were happening in the next 18 months --integrators were on the cusp of completing phase 1 deployment of a new "big-data" system. Waiting years to address current challenges and opportunities just seems absurd. This is especially true when managers can successfully address many of today's challenges with robust analytics delivered in near-real time that leverage multiple and integrated sources. "Big data" shouldn't be the speed bump that slows down practical and strategic execution and activation -- it should be the lubricant to move analytics-based decisions forward. We must remember the warning by that famous IT expert Voltaire, "the perfect is the enemy of the good."

I believe advanced analytics -- available across the enterprise -- will drive innovation over the next decade, if freed from behind the desk of the market research manager. The combination of advanced technology, predictive analytical models, and the proliferation of consumer and shopper data is enabling decision makers to address and anticipate the changing desires of consumers and shoppers, thereby generating more relevancy, personalization, and engagement. De-averaging the marketplace to uncover new growth opportunities is only possible with advanced analytics in the hands of capable talent with the courage to deviate from the practices of the last several decades. "Big data" will be one enabler, but only in so far as it supports an analytics agenda and an organizational capability to commercialize analytical insights across the value chain -- that is, sales and marketing through to supply chain.

 

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