Welcome to the Age of Better Data
Topics: Big Data / Analytics
For years now, the popular press has been heralding the coming age of data supremacy in retail. The reports are often framed in Orwellian language and invariably focus on size. It is, after all, the big data revolution.
But new research by Tuck Associate Dean Praveen Kopalle posits that the real revolution depends more on quality of data rather than quantity, and argues that as data becomes ever more voluminous, varied retailers must rely on theory to fully harness its massive potential. In “The Role of Big Data and Predictive Analytics in Retailing,” forthcoming in The Journal of Retailing, Kopalle and his co-authors describe five major data dimensions which, used together, can give retailers a remarkably deep and nuanced understanding of customer behavior.
“What changes the game is not the individual components, but the interplay between time, location, channel, product, and customer,” Kopalle says. “That is the game-changer.”
The same factors that make big data so powerful—its sheer scale and diversity—also make it difficult to harness. That is where theory comes into play. As Kopalle puts it, “The substantive theories in retailing tell us what to look for in the data and the statistical theories tell us where and how to look in the data.”
One of the statistical theories goes back more than 200 years to an English minister named Thomas Bayes who, with quill pens in leather-bound ledgers, worked out the probability theorem that underpins much of today’s data-driven retail world. With Bayesian analysis and ample processing power, managers can turn mountains of raw data into more effective and profitable sales strategies.