These days, everyone talks about big data and how it can solve all of a business' problems from reaching customers to cutting costs. But when you get right down to it, most people don’t really know how to use big data. While it is clear that the abundance of information presents great opportunities, it is equally clear that most companies have no idea how to take advantage of those opportunities.
Over the summer, I had seen this juxtaposition of benefits and it piqued my interest in data analysis, which landed me in the K513: Data Mining class during the first block of fall classes. As the class was winding down last month, our professor, Vijay Khatri encouraged all of us to participate in the annual Data Challenge, hosted by the IU Institute for Business Analytics (IBA) and sponsored by IBM, Deloitte, and other companies.
I and a few classmates; Susana Zazueta, Isa Fung, and Brian Anderson, decided to form a team and enter the competition. The case we were presented with asked us to find a way for hospitals to reduce patient readmissions to improve overall patient outcomes and decrease hospital expenses. We used IBM SPSS Modeler software to do an initial analysis of the data and create a decision tree that identified patients at high risk of being readmitted, then we did additional analysis in Excel to determine the right cut-offs for the important variables and quantify the savings that would result from using this solution.
The number crunching was relatively straightforward but we knew that the key to our success would be our ability to connect the numbers to a solution that had real impact on the business and the people involved. Though our solution would save the hospitals a relatively small amount in direct costs, it makes a large difference when looking at the whole picture of indirect and intangible costs.
|Our challenge was to convert the raw numbers into a solution that meant something for real people|
On October 31, we presented our solution to a team of judges. They liked the human angle and the balance of data and industry context. There were more than 20 teams who participated in the challenge, including both MBA and MSIS students. Each team presented to one of three sets of judges. In the end, the judges deliberated and declare a three-way tie for the winner. Our team was honored to be named one of the winners along with the team of Reesha Padmanabh, Ramanuja Atur, Sahil Sandhu, Bhupesh Bharuka and the team of Danny Oviedo, Drew Cekada, Ellen Gartner-Phillips, and Gauri Nayak.
This challenge was a great opportunity to put in practice many of the principles I have learned so far at Kelley. The key takeaway for me was that in order to find data-based solutions, you have to first, know how to run the numbers, second, understand the problem and all its consequences, and third, make it real and relatable. As I move forward in finishing my MBA and entering a new career, I’ll keep this in mind.
Thanks to Vijay Khatri, Frank Acito, the Institute for Business Analytics, and all the staff, judges, and sponsors who helped make this challenge a great experience!
|Our team with the IBA directors (L-R Kimberly Barker, Susana Zazueta, Frank Acito, Vijay Khatri, Brian Anderson, Isa Fung )|