Faculty in Focus: Savoring every byte of data
The explosive growth of data has created an on-demand world where navigating the complexities of analytics and decision-making can be a daunting task. But amid the sea of numbers and statistics, Professor Joel Shapiro, a clinical associate professor of managerial economics and decision sciences at Kellogg, sheds light on the nuanced interplay among data, decision-making and effective leadership.
“One of the key competencies for managers or business leaders in this data-heavy world is not only understanding the problem but also knowing how much they’re willing to invest in solving that problem,” says Shapiro, an expert in analytics and AI. He explained that when business leaders can define the problem with precision and clarity, it becomes an economic opportunity. Only when they can pinpoint the exact question or problem that needs addressing can data teams then step in with tailored solutions.
But investing in data solutions is not just about financial capital; it's also about intellectual capital. “Real value from data comes when we ask good questions, think critically, use good tech and communicate effectively,” Shapiro says. In fact, he maintains that communication is key in the realm of data analytics. “Just like anything else, data is information,” he shares. “You need to be able to make sense of it, extract relevant trends and uncover the story.”
When teaching students, he emphasizes the importance of conveying insights in a way that adds value without overshadowing people. “It's not merely about presenting raw numbers; it's about crafting a narrative — a storyline that resonates with the audience and drives actionable insights.” Data by itself doesn’t tell you how to solve your problem, but it gives you a start.
With a wealth of experience in data analytics and deliberate decision-making, he encourages his students to discern between using quantitative and qualitative data methodologies and analysis. “I often hear people claim that you need to know the ‘why’ in order to use data well, but you don't always. Sometimes you just need to know that something will happen. A grocery store that wants to keep the right amount of each product on the shelf doesn't need to know why people do or don't buy - they just need to accurately predict demand,” he explains. “But, if I want to get people to change their behavior then I start to need to understand the ‘why’ to influence alternate behaviors.”
Merging two interests: data and sports
One of his latest research projects is leveraging predictive AI within the world of sports to analyze players’ performance and help build strong, successful teams. Technology and AI have been influencing the world of sports for the last couple of decades by predicting outcomes, player performance and even the likelihood of player injury. Shapiro is particularly interested in how AI could potentially create a more tailored approach to building optimal teams.
“We want to understand how players are likely to perform and how likely they are to be unavailable due to injury. And even if we could predict injury, we can't necessarily prevent injury,” he explains. “I'm working on understanding the synergies among performance, availability, player salaries and team success.”
For Shapiro, embracing uncertainty to make informed decisions is a key component of effective leadership because he acknowledges that even with data, there are often no right answers. So, he challenges his students to focus on developing a solid base of evidence to drive their choices. “I can't always tell you whether a decision is the right one, but I can help assess whether the reasoning is good,” he explains. “And that's what I really try to instill in students: What did you decide and why, and do those hold together?”
He shares one particular classroom anecdote that stands out to him during his 10 years of teaching at Kellogg — a project from his Analytical Consulting Lab. A client approached Shapiro seeking to understand why turnover rates were high among their salespeople. Shapiro's students did a deep dive and found that the data confirmed what the company already thought was happening — and the students were somewhat disappointed from their analysis that they hadn’t unearthed anything else. “That's not a failure at all," he emphasized. “Sometimes data confirms what you believe to be true, and that's super valuable.”
Shapiro explains that in the real world, there isn’t always a diamond in the rough. Instead, it's often the absence of that 'aha' moment that holds the true insight. “Sometimes people create classroom exercises that are meant to be to find that 'aha’ moment,” he shares. “But the real world often doesn't have those ‘aha’ moments. Sometimes it’s the lack of ‘aha’ that becomes the ‘aha.’” That experience also reminded Shapiro of the importance of managing people’s expectations and recognizing the incremental value that data brings to decision-making.
It can be easy to overlook the value of incremental progress in a world that places emphasis on breakthrough discoveries and fast-moving innovation. But, he asserts, “Sometimes data helps us make tiny little decisions better. And if we do that regularly and incrementally over time, we can build a lot of value with it.” Navigating the data landscape is not just about crunching numbers or uncovering hidden insights — it's also about dealing with ambiguity and leading through uncertainty for maximum impact.