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Herbert Simon once wrote that “the central concern of administrative theory is with the boundary between rational and nonrational aspects of human social behavior.” Simon’s comment is especially pertinent to the still-emerging field of business analytics. The human dimension of business analytics might facetiously be called the discipline’s “dark matter”: it looms large while tending to remain hidden from view.
In many and diverse domains, human experts must make decisions that require weighing together disparate pieces of information and are made repeatedly. Unfortunately, we are not very good at this. We rely on mental heuristics (rules of thumb), which as psychological research shows, have surprising biases that limit our ability to make truly objective decisions. The implication is society is replete with inefficient markets and business processes that can be improved with business analytics.
Analytics projects are often bedeviled – or simply stopped in their tracks – by challenges emanating from organizational culture, misunderstanding of statistical concepts, and discomfort with probabilistic reasoning. Compounding these challenges is the fact that data scientists often “speak a different language from” the business domain experts that they are charged to help. In our experience, these challenges can be among the most difficult ones faced in an analytics project, and are ignored at one’s peril. This talk will provide a number of case studies and vignettes; relate these examples to relevant ideas from the decision sciences; and offer practical tips for achieving organizational buy-in.
John Lucker, a principal with Deloitte Consulting LLP, leads Deloitte’s Advanced Analytics & Modeling practice, one of the leading analytics groups in the professional services industry. He has vast experience in the areas of advanced analytics, predictive modeling, data mining, scoring and rules engines, and numerous other advanced analytics business solution approaches.
John serves clients across multiple industries including insurance, health care, banking and financial services, retail, consumer products, telecomm, media and hospitality, where he provides end-to-end business, operational and technical consulting services.
John has developed unique advanced analytic business solutions and methods as well as the technical implementation tools to help realize the value of advanced analytics. He speaks and writes often on these topics at numerous trade and professional organizations and in a variety of publications. He is a co-inventor of three predictive modeling patents which are pending.
He holds a BA and an MBA from the University of Rochester.
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