What makes an analytics project great?

Published: October 2, 2020

From large scale analytics projects that have a lifesaving impact, or realize millions of dollars in savings, or transform an entire industry, to those that simply help an organization better utilize its data and improve its day-to-day functionality, how is success measured?

Joining me for this episode are Pooja Dewan, Vice President and Chief Data Analytics Officer with Otis Elevator, and Carrie Beam Teaching Associate Professor at the University of Arkansas and Principal of Carrie Beam Consulting.

Both Pooja and Carrie have played a pivotal role in the Franz Edelman Award competition over the years. Pooja served as the 2019 and 2020 Competition Chair and Carrie coached the 2019 winning team and will be the 2021 Competition Chair. They both have also served as competition judges on multiple occasions.

Some of the big factors I like to see are, is it a new domain? Are we having a new problem, either a new business opportunity or a new data set, or a new algorithm which has just become available? So is this something new? We are also looking very much to define the problem correctly and understand what success looks like. If you don’t have the problem properly defined, you’re going to solve the wrong thing and end up on the wrong road at the wrong destination. And then the last thing I would say a great analytics project has, is understanding its almost never once and done.

Interviewed this episode:

Pooja Dewan, Carrie Beam

Otis Elevator, University of Arkansas and Carrie Beam Consulting

Pooja Dewan is the Vice President and Chief Data & Analytics Officer for Otis Elevator Company. In this critical role, she leads the company’s data science and analytics capabilities, identifying opportunities to accelerate growth and efficiency. She is responsible for driving the data and analytics vision, strategy, and execution. She owns the Otis data management roadmap driving sustainable business growth and profitability, as well as internal efficiencies through improved data structures, constant data cleanliness and insight, and efficient data governance and processes. Prior to this role, Pooja spent more than 20 years at BNSF Railway where she served as the Chief Data Scientist. There she led the Operations Research and Advanced Analytics group for 16 years. Her team received international recognition through an INFORMS award as the Best Advanced Analytics Team in 2019. Pooja has been a member of INFORMS (Operations Research Society) since 1993. During this time, she led several initiatives offered by INFORMS, including the Edelman competition, and she has also been instrumental in championing activities that help bridge the gap between academia and real-world application. Pooja earned a master’s and doctorate in industrial engineering from Pennsylvania State University. She is also the author of several research publications in various scientific journals.

Carrie Beam is a Teaching Associate Professor for the Department of Industrial Engineering at the University of Arkansas. She holds a Ph.D. in Industrial Engineering and Operations Research, and has taught Introduction to Operations Management, Intro to Decision Support Systems, Introduction to Analytics, Probability and Statistics, Lean Six Sigma, Maintenance and Reliability, Risk Management, and a variety of other operations management topics since she began with the program in 2012. She has been teaching online since 2007. She also works as a consultant, specializing in data science and analytics. Projects include descriptive and predictive analytics, and help inform such decisions as market segmentation, direct marketing strategy, customer churn analysis, and coupon/pricing analysis.