Imagine being in the company of loved ones from around the world, watching your favorite baseball team play while simultaneously enjoying classic ballpark snacks – all from the comfort of your living room sofa. This was the business idea that took Cassie Dai, Erik Chen and Fabio Daiber, all Cornell Tech M.B.A. candidates, to the final round of the 14th Adobe Analytics Challenge.
The Adobe Analytics Challenge invites students to solve a business challenge for one of Adobe’s major clients. This year’s client was Major League Baseball, which drew in a record number of applicants. Over 1500 students from across the country were tasked with one question: How can the MLB bring the excitement of the in-stadium experience to its online platform?
Armed with Adobe’s suite of data analytic tools, teams of three submit projects to be judged by a panel of experts, explained Kevin Fu, Senior PR Manager for Adobe.
The first-ever Cornell Tech team to place into the finals — Dai, Chen and Daiber — placed fourth out of the six finalist groups with their project “Kratos”. They received an award of $3000.
The platform of Kratos is simple: make digital baseball a group experience rather than an individual one. For the MLB TV experience, they proposed setting up “a virtual box,” from which individuals could interact with their friends, family and people around the world. Other key features included fan-made highlight reels and a dual-sided referral program to encourage friends and family to join. They even added the ability to order food right from the platform, just as you would at Fenway Park.
Dai launched Kratos at Cornell Tech after hearing another student discussing the challenge with a professor. Having spent years working in digital marketing, she felt this was right up her alley. She quickly pulled Daiber and Chen together, and joined the challenge under an advisor.
“We knew data alone would not give us the answer. We had to think deeply about the human elements, the fans, and that intuition guided many of our decisions,” Chen said.
The team looked to the Internet and their friends to troubleshoot how to digitally reconstruct the marvel of a roaring stadium and the excitement of watching a game in person.
“The magic of the stadium game comes from friends, family, and even strangers,” said Chen. They would have to figure out how to translate this “magic” into the online experience.
“We did not expect that much after [our] initial submission,” Daiber remarked, but it soon became evident that the judging committees liked their idea.
As they began rising through their ranks, it was their “faith in the idea and faith in each other that kept [them] coming back and putting in the work,” Chen explained.
The team said that the final round was incredibly rewarding. In addition to the presentations, the members got to network with the other finalists and meet with industry bigwigs, including Adobe CMO, Ann Lewnes and Director of Digital Experience, Marc Eaman. These business leaders, specializing in public speaking, gave the team tips on “how to tell a story, deal with unplanned disasters while on stage, as well as build comfort on stage.”
Dai, Chen and Daiber agree that the rigorous and practical curriculum at Cornell Tech prepared them for the challenge. Chen explained that “the core aspects of the M.B.A. curriculum is the core team concept.”
“Very early on, we were put into teams and forced to work on ambiguous questions under tight, timed deadlines,” Chen explained, “so by the time we started, we were ready.”
Since the MBA program at Cornell Tech is all about networking, Dai added, the team was adept at gathering vital information from their peers. Dai continued that a lot of their consumer research about baseball came from their peers since the team didn’t know much about baseball, but Chen interrupted in his own defense. After a quick laugh, Dai conceded – Chen knew his baseball.
Ultimately, the team “enjoyed participating in this challenge and learned a lot about creating and presenting an analytics case while under ambiguous conditions, limited data and time pressure,” Daiber said.