Why “small math” is about more than big data

Last week, the Yale Consumer Insights Conference 2014 brought together practitioners and professors of marketing and business to share research, insights and experience with a small, but engaged group of peers and professionals. Amid futuristic talk of personalized, physical environments enabled by emerging technology, big data stood out as one of the most prevalent challenges to businesses and brands of all shapes and sizes. One presenter, clearly unimpressed with this buzz term and all its hype, explained it best, “It’s funny. The bigger the data, the smaller the math.” His bemoaning reinforced the fact that most organizations don’t require the computational power or a numeric-laden arsenal to succeed.

Big data, small math; this juxtaposition has implications far beyond marketing or business alone. More resources, more stuff — none of this guarantees success. And there are plenty of examples to reference: struggling or failing schools with high per-student spending; increased tax revenue with little to no improvement in public services; and a scarcity of hard news amid an influx of new media outlets.

At the heart of this dichotomy is a call to embrace big challenges with existing — sometimes finite — resources. In the case of big data the presenter suggested an alternative: use “big(ger) math” to reveal deeper insights from relatively small stores of information.

Applied to other areas, “big math” characterizes the classic adage that “less is more.” In education this might mean less testing, more interactivity and instruction. For government and other public entities, the need is not more revenue, but smarter utility of civic services. And for news, replace the breadth of zero-calorie content for depth of context.

Yes, the idea of “big math” is a little intimidating, less marketable and certainly less sexy than its buzzworthy cousin big data. Nonetheless, the implied rigor and discipline of this concept is exactly what is required to tap into the opportunities made possible by data, regardless of its size.

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