This is the first part of a faculty interview series where I interview a faculty member of the MSBA program to learn more about their research, teaching and more importantly for all of us, steal some information about how to be a better data driven story teller.

1. Is it naive to say that analytics was only just discovered as quite a few believe it to be?

Discovering insights from data goes back a very long time, but it was primarily happening in academia. But there is a new realization in most businesses today that we can compete better with data and evidence based decision making. Today’s Information Technologies allow for massive quantities of diverse data as well as tools to analyze them. Text mining in the 1970s
was restricted to research and universities. But these days, due to social media and other user generated content, there is an explosion of unstructured data which are being exploited by many companies to gain deep insights into many aspects of their business.

2. How did you start out doing what you are doing now?

When I was a Ph.D student at CMU, there was a software ( quite a sophisticated one at the time ) called TETRAD, along with its theoretical underpinnings. It actually went beyond correlations, and focused on discovering causal relationships. I was fortunate to work with it in my research to demonstrate that you can discover new relationships in data. Not unexpectedly, there wer
e a lot of academics who were highly critical of the approach of data driven discovery, and dismissed it as “blind empiricism.”

3. Could you talk a little more about your research?

One that I am excited about is about the “financial value of a like”. One huge advantage of social media is that we can run real world experiments. We convinced a retailer to add like buttons on its page to increase sales. We designed an experiment where a large number of students in the treatment group were randomly instructed to like a product, and where we observed how many of their Facebook friends actually bought the product. We quantified effects of the like in two ways – those in the close contact circle of the person who liked the product (effect was stronger ) and the count of likes in popularity (this had a weaker effect ). There was a dramatic increase in sales in the treatment group, stemming primarily from “in network” effects.

Another topic of my current research involves a digital advertising supply chain. Aided by a massive data set with billions of digital impressions, we could study the decisions made by various players in this supply chain (e.g., ad agencies, publishers, brokers, etc.), and show that by accounting for cross-channel synergies, the supply chain can increase its profit by 356%. This wouldn’t be possible if we didn’t have access to such a massive quantity of data – you can theorize all you want to, but without data there is no way to validate your ideas!

4. What advice do you have for students who are starting out in this field?

Well, you guys (our MSBA students) have an incredible technical and quantitative foundation, and are being exposed to the most advanced theories and practices in these areas. I would advise you to pay close attention to the business details. All that you are learning now would be worth even more if you develop the business acumen to solve the problem in a real-world context. This is a skill that takes time to develop, but is a critical one. Read a lot of business issues in online magazines, blogs and social media in general. Be comfortable in understanding business strategy and processes. The combination of technical, quant and business skills is quite rare, and hence highly valued in the industry.

– Akshata Mohan