Wharton@Work

May 2024 | 

Analytics Participants Return to Wharton as Panelists

Analytics Participants Return to Wharton as Panelists

For Kati Stratos and Toni Donovan, their Wharton experience didn’t end on the final day of Analytics for Strategic Growth: AI, Smart Data, and Customer Insights. Both women recently returned to campus to participate in a panel discussion that gave even greater insights into the real-world applications of analytics.

Stratos, executive director of data services at Comcast NBCUniversal, says she initially enrolled in the program because “I'm always looking for ways to enhance my knowledge of analytics and data and stay on top of trends in the industry. There's so much training that is video-based and online, which is great. But I love the in-person, immersive nature of the Wharton Executive Education format, networking with other data leaders, and learning something new from Wharton professors.”

Analytics has become the bedrock of informed business decision making and key to staying competitive in today’s digital world. Organizations are leveraging data analytics to develop strategies, optimize operations, enhance financial performance, and improve their customer experience. That means understanding the latest insights and trends is now an imperative.

That lesson is not lost on Stratos. “Inherent in being an analytics leader is a requirement to stay informed and on top of new technology, new tools, new methods, new capabilities,” says Stratos. “Data and analytics move so quickly. For example, when I attended Analytics for Strategic Growth: AI, Smart Data, and Customer Insights, it had a different name because we weren't even talking about AI at the time. Now it is front and center. That means continuing education is table stakes.”

Toni Donovan — assistant vice president of commercial organization for PINC AI, the research, data, and analytics division of Premier Inc. — says she chose the program “to become more comfortable working with the technical data experts and to gain a greater ability to ask the right questions to get the outputs needed. I wasn’t looking to be a tech expert but knew there was more to learn and understand about big data and AI to positively influence business outcomes. I also wanted to understand the opportunities with AI that might come into play when working with larger data sets.”

Donovan continues, “Attending the program was quite valuable, and I draw on the learnings regularly as I lead a team of strategic account leaders who develop customized solutions for life sciences business problems every day, using data and AI. The program gave me greater confidence as we work with AI to better understand how we can use it to expand what is possible.”

Theory Takes You Only So Far

Both Stratos and Donovan say there is a lot of accessible information about the technical aspects of working with data and AI — but it’s rarely helpful when you need to apply it to a real-world business challenge.

“What I really liked about the program was the ability to go from the theoretical to practical applications,” says Stratos. “I was surprised by how practical it was and how quickly we were able to get from the macro to the micro and also to learn how we can actually apply this in our day-to-day work starting Monday morning. We first learned a theoretical framework of customer analytics from Raghu [Iyengar, professor of marketing at Wharton], and then towards the end of the week we applied it to a case study. We were in the data, actually computing and running models and running analysis, and then finally presenting it.”

She continues, “Outside of school, which I haven't been in for many years, it's rare to be able to go through that journey. Anyone who's done analytics knows there is a really big gap from the theoretical to the practical application. I've done courses where I've learned in theory how to do propensity score modeling or a certain analytical technique, and it all makes sense until you sit down at your computer and try to run the data. You think, ‘How do I treat outliers? What do I do with bad data? How do I interpret the output?’ So to be able to learn the theoretical and then practice and apply it to a tactical case study was an amazing model for learning that I can actually take and apply and remember in a really clear and meaningful way.”

Donovan particularly appreciated sessions with Neil Hoyne, chief strategist at Google, and Wharton’s Pete Fader, a world-renowned expert in customer centricity. “The highlight from these sessions was seeing how customer analytics applies to the real world though business case examples. Neil stayed with us late, and there was such a rich discussion that could have easily continued all evening. After Pete’s session on customer lifetime value, I went out and bought his latest book so I could continue to learn from him.”

The Data-Human Collaboration

“The program reinforced that our decisions should be data-informed rather than solely data-led,” says Donovan. “You rarely have 100 percent of the data you would like to have, so it doesn’t always get you to your desired outcome. You need human insights in the loop. And those humans need to appreciate how to use the data to inform their decisions.”