A Method to the Madness?

With the NCAA men's basketball tournament tipping off soon, talk of brackets and bubble-busters is reaching fever pitch. Three business professors cum sports fanatics are not only taking some of the madness out of March – they're using it to show how analytics solves critical business problems.

The three – operations management professor Jay Coleman (University of North Florida), Associate Dean Allen Lynch (Mercer University)  and Mike DuMond, principal consultant with Charles River Associwill again apply analytics software from SAS to predict "at-large" teams, those not earning automatic tournament bids..

The "professors" (DuMond is an adjunct professor in labor economics and computer programming at Florida State University) have been perfecting their NCAA "Dance Card," powered by SAS^® software, for nearly 20 years.  Over the last three years, the model averaged an impressive 94 percent accuracy rate. At its best in 2010, it predicted 33 of 34 at-large teams. "If the Dance Card's last-team-in and first-team-out had been reversed, it would have been dead solid perfect," noted Coleman.

Follow the latest analyses at NCAA Tournament "Dance Card"

The professors say the Dance Card, with its factors and weights, suggest that the tournament selection committees are remarkably predictable – despite barbs from fans, teams and the media.

Predictive analytics at work

In addition to basketball picks, analytics software such as SAS helps businesses succeed every day. Business analytics help predict what will happen: which customers will respond to a bank's direct mail on home equity loans, what floor plan will help a retailer sell more shoes, or which combination of medical treatments will keep a diabetic healthy and out of intensive care?

"SAS analyzes huge amounts of information, pulls out what's important and ignores what's not. SAS predicts what's coming in the future, as opposed to simply describing what happened in the past," says Coleman, who says the Dance Card reflects the trend in analytics toward more prediction and less description.

"Predictability is a key part of business analytics that helps companies move from information to a decision, from the descriptive to the predictive," says Coleman. "With forecasting, data mining, optimization and other advanced predictive software from SAS, businesses can go beyond simply reporting on what has already happened and instead understand what will happen and where to go next."

"We're going to use basketball as a metaphor here."

This is how Coleman begins his guest lecture in a Supply Chain Management class. Just as SAS analytics are used to forecast teams in the tournament, businesses use a forecasting model to improve supply chain management.

"If you have an idea of what your product demand will be, you can manage supply chain more efficiently – reducing inventory levels, scheduling fewer deliveries and saving resources," says Coleman. 

College professors Jay Coleman (left) and Allen Lynch use SAS to predict which teams will earn "at-large" NCAA tournament slots.