ISyE Seminar Series: Abhishek Roy

"CORTX - Optimization as a service"

Presentation by Abhishek Roy
Senior Data Scientist

Wednesday, November 6
3:15pm - Refreshments, Lind Hall 305
3:30pm - Graduate Seminar, Lind Hall 305



Cargill's Feed team provides "Feed as a Service.” This means that the team has to move 3 million tons of feed from corn milling plants to some of the world's largest feed customers across the Midwest and Texas in the most efficient way. There is just one rule: "Never run out of feed." The feed team must follow this rule while managing its systems for variable demand, variable supply, and drivers. They want to keep their customers at a target inventory while accounting for variable feed usage, shrinkage and degradation. Corn milling assets provide them with the raw material to prepare feed which can vary depending on the milling business throughput. And, they want to maximize the drivers’ time to do maximum deliveries in the shortest time window.

The objective is to decouple the feed business from the variability in different components of their supply chain. To accomplish that, Roy's data science team in collaboration with Digital Labs has broken down the problem into different optimization modules. Currently, they have finished foundational work on two modules. The KIX (Customer Inventory Execution) optimization module has two key features: Usage Model and Recommendation Model. The usage model ingests driver estimated inventory readings across all the 130 feed customers to calculate the current, and customer feed inventories and usage rates. The recommendation optimization model takes the usage model numbers to create a recommended loads of deliveries for next seven days. This list can range from 300-350 truckloads and 70 different customers per day to optimally fulfill the most urgent customer's needs considering different constraints such as customer closed days and gate hours, target inventory and plant capacity.



Abhishek Roy has approximately 10 years of consulting experience in data analytics, data strategy, and machine learning and has worked on many data science projects across industries such as consumer packaged goods, retail, insurance, finance and manufacturing. He also co-founded the Social Data Science group, which works with nonprofits such as Generation NEXT, Avivo, and the Science Museum of Minnesota to apply data science for social good.

Roy has a master's in predictive analytics from Northwestern University in Chicago and is currently working as a senior data scientist at Cargill. In his free time, he enjoys playing basketball, cricket, and badminton.


Seminar Video:

Start date
Wednesday, Nov. 6, 2019, 3:15 p.m.

Lind Hall
Room 305