Imagine reporting to work on a Monday at Fiserv Forum. Giannis Antetokounmpo is your professional colleague. And you must attend every Milwaukee Bucks game of the season.
As the director of basketball research for the Milwaukee Bucks, Seth Partnow understands the fascination with his job. But it doesn’t reflect the whole picture.
“We’re certainly not living the glamorous life. It’s a lot of long hours, a lot of hard work. The players work insanely hard,” Partnow told the audience during an open forum at the Wisconsin School of Business. “What we are doing is taking the best information possible and using it to enable better decision-making and to ensure more favorable long-term outcomes.”
Now in his third season with the Bucks, Partnow shared how he uses analytics on a daily basis in a competitive sports environment in his talk, “Sports Analytics and Impacting Decisions with Data.”
Partnow says the team is using metrics to look at issues such as roster optimization, injury prevention, and fatigue management. Regardless of the issue, he starts by prioritizing the question he hopes to solve, aiming for “a clear vision of what I think is important before I start the analysis.”
“The numbers don’t speak for themselves,” Partnow stressed. “As an analyst, you put them together.”
Envisioning a learning community
The second half of Partnow’s visit included a student workshop in the Finance and Analytics Lab in WSB’s Learning Commons. Students from nearly all BBA majors had the opportunity to put their data analytics skills to work via a challenge: as an analyst for a WNBA team, select a player that will add the most value to your team. Students brought their analyses and selections to the workshop and presented their findings to each other. They then worked in groups to identify and present the one player they thought was most valuable. The class got feedback from Partnow, WSB faculty, and special guest Keaton Nankivil (MBA’20), a first-year Wisconsin MBA student in corporate finance with five years’ experience playing professional basketball overseas.
Ron Cramer, a senior instructional designer and learning technology consultant at WSB, says there was always a bigger, broader vision for exactly these kinds of cross-disciplinary, cross-industry events when the Learning Commons was first proposed. The idea was to include alumni and corporate partners—an inclusive learning community—not solely faculty, staff, and students.
“This workshop in the Finance and Analytics Lab was an embodiment of that community coming together for an innovative, co-curricular learning experience,” says Cramer, who is part of the School’s educational innovation team that sponsored Partnow’s visit. “It helped students focus on dealing with ambiguous business problems and providing effective communication of statistical information for decision-making.”
Bringing Partnow to campus was made possible thanks to a partnership between WSB and the University of Wisconsin–Madison’s Center for Humanities. The idea behind the collaboration is about strengthening the links between business and the humanities, says Justin Sydnor, associate professor of risk and insurance who introduced Partnow before his talk.
“As we increase our attention in business on analytics, there’s significant benefit to be gained from having a stronger appreciation of the humanities,” Sydnor explains. “They provide context and grounding for how we think about processing and navigating uncertainty, but also with how we learn to communicate and learn to interact with one another.”
Learning to communicate with analytics
Interpreting and communicating analytics is not an exact science; it means getting comfortable with some degree of uncertainty. Below are three maxims Partnow says he uses in his work to guide him in analyzing and communicating results:
- Be selective and succinct. Avoid the information dump. Understand the decision-making context and give only the analysis that’s asked for. He takes a first pass at the data, removing what’s unnecessary so that he doesn’t overload the recipient.
- Be accurate, not necessarily numerical. Sometimes using a visual metaphor, a stoplight to explain the data (red, yellow, green), for example, may communicate better than saying “Sam has a 32.4 percent chance of being injured.”
- Be humble yet confident. It’s key to recognize and respect subject matter expertise. Question your own results first—“be careful about leaping from A to B” —and know how to read the room. “You have a very high bar to clear if you think you’re going to do something better than what they’ve already done.”
Accept that mistakes will be made along the way, Partnow says. “In basketball, like everything else, you’re not always going to get it all right.”
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