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As we've discussed in a recent A2 Radio program, multi-channel revenue attribution is tough. But Alex Cosmas and his team of data scientists at Booz Allen Hamilton's Strategic Innovation Group (SIG) think they've found a way. And it comes from the bottom up, said Cosmas, chief scientist.
Working for a hospitality client, the SIG applied a Bayesian network technique to determine whether it could "quantify the amount that a promotion drove in incremental sales vs. other factors like weather, differences in rates and fares, or just regular cyclicality of the peaks and valleys of travel," Cosmas told me in a phone interview that followed from a presentation he delivered at this week's INFORMS Conference on Business Analytics & Operations Research conference. He described the project in a session called "Monetizing Bayesian Networks: A Case Study in Evaluating Promotional Campaign Effectiveness." As I mentioned yesterday, the SIG has been doing lots of work lately using a Bayesian framework for business. (See Taking Bayesian Networks Into the Business.)
Analytics team leaders from a variety of industries gathered at the INFORMS Conference on Business Analytics and Operations Research this week for a panel discussion on how to build a well-rounded data-analytics team and manage data professionals: where to position them; how to keep them challenged, engaged and motivated; and what it takes to lead them.
The panel was moderated by Julia Kirby, editor at large at the Harvard Business Review, and included team leaders from major corporations, including Brian Eck, quantitative analyst at Google; Kerem Tomak, vice president of marketing analytics at Macy’s; Erica Klampfl, global future mobility manager at the Ford Motor Company; Dayana Cope, manager of operations research engineering at Disney; and Jeanne Harris, managing director of IT research at Accenture.
At the INFORMS analytics conference in Boston this spring, the lineup was stellar as analytics experts looked at major trends in the way that analytics professionals find their place at their organizations. Here was the lineup:
Moderator: Julia Kirby, Harvard Business Review
Accenture: Jeanne Harris
Disney: Dayana Cope
Google: Brian Eck
Macys.com: Kerem Tomak
With the explosion of analytics in business and society, there is obviously a great need for people who can analyze data effectively and support analytical decisions. But if you’re hiring someone to help with analytics and you don’t know much about the field yourself, how do you know if they are good enough? Degree programs and majors in analytics are proliferating in universities, but how do you know if they teach the right content? We have well-established standards for plumbers and welders, but not for quantitative analysts or data scientists—until now.
INFORMS, a non-profit association of quantitative analysts and academics, has established a certification program called Certified Analytics Professional, or CAP. INFORMS was originally comprised primarily of operations research (OR) folks, who typically focus on methods like optimization, simulation, and decision tree analysis. But the association’s leadership has made great progress in addressing all types of business analytics. I just attended the 2014 conference on “Business Analytics and Operations Research,” and specialists in marketing analytics, web analytics, and Big Data analytics were all in evidence along with the OR folks.
What bugs people the most about grocery shopping? It's not the in-store Muzak or the occasional squished loaf of bread. It's the dreaded wait at the checkout line, according to Kroger customer surveys, prompting the supermarket chain to test a variety of technical solutions over the years. Kroger thinks it finally has the right mix of technology: QueVision, which combines infrared sensors over store doors and cash registers, predictive analytics, and real-time data feeds from point-of-sale systems.
From the moment customers walk through the door of a Kroger store, the QueVision technology works toward one goal: ensuring that they never have more than one person ahead of them in the checkout line. The technology, now deployed at more than 2,300 Kroger stores across 31 states, has cut the average wait time from more than four minutes to less than 30 seconds, the company says.
Kroger was doing data analytics simulations on the queuing problem as far back as 2007. "We asked a question: If we could open up a lane exactly when we needed it, what would happen?" says Doug Meiser, operations research manager. "We just wanted to ask the question from an analytics standpoint. And we found we could dramatically improve customer satisfaction." From there, he says, it became a matter of "the math is sound; how do we go do this?"