AI and Analytics for Business


Analytics is Everywhere

You can watch the presenters from this event talking about the value and importance of applying analytics everywhere in this video. Read more about the event below.


At a recent event hosted by AIAB, an audience of industry practitioners heard presentations from professors across the University about how they are using data and analytics in their respective fields of research. The result was an insightful display of analytics at work in unrelated areas with one underlying common theme: analytics is everywhere.


Analytics can be everywhere because, as Professor Eric Bradlow notes, analytics is industry agnostic. In other words, any challenge can be broken down into simple questions that always lead you to the answer:

  • What does the data contain?
  • What is the business problem?
  • What is the method to analyze?
  • What needs to happen in order to implement the solution?

It’s because of these universal and fundamental questions that analytics is so powerful. It’s why a room full of industry practitioners from a luxury beauty retailer; a major chocolate manufacturer; a credit agency; and a marketing agency found presentations about people analytics; political science; sports analytics; machine learning; and marketing experiments — amongst others — all valuable. Because what unites all of these business’ endeavors is an understanding of their data to gain a competitive advantage using the same fundamental analysis methods. Which, as Statistics Professor, Adi Wyner put it, “is a Moneyball Moment.”

In a unique comparison, Political Science Professor Marc Meredith and Marketing Professor Raghu Iyengar want to understand their unique populations within their respective work. Professor Iyengar talked about how marketers spend a lot of time thinking about customers: who they are and how marketers describe them using better data and better models. He said, “if businesses step back and look at the bigger picture, these aren’t just problems in marketing these are problems that are everywhere.” Following Professor Iyengar, Marc Meredith described his work regarding duplicate voters and identifying different people who happen to have the same name and birthdate. These are two objectives of different fields of research, marketing and political science, that are further advanced by similar methods of analytics.

In another example of using similar methods, Cade Massey, OID Practice Professor and Faculty Co-Director at Wharton People Analytics, spoke about the methods used by the winners of the 2016 Wharton People Analytics Case Competition. The winning study used a modified version of a churn model to predict retention of volunteers with Doctors Without Borders. Students modified the Buy ‘Til You Die Model developed by Bruce Hardie, Professor of Marketing at the London Business School and Pete Fader, a Wharton Marketing Professor. Instead of modeling customers, the students modeled volunteers’ assignment lengths and frequency. They found that volunteers who have longer assignments will go back out into the field for longer and more frequent assignments. These findings directly conflicted with the organization’s assumption that volunteers who have shorter and more infrequent assignments stay with the company longer.

This event was an enlightening opportunity of academia and industry coming together to illustrate that analytics isn’t a passing fad but a new era of business strategy. It was an event that helped achieve AIAB’s perpetual goal: to strengthen this bridge of academia and industry and continue to offer innovative ways to bring them together.