Data Tech

Problem
Cargill's Feed team provides "Feed As a Service". This means that the team has to move 3 million tons of feed from the corn milling plants to some of the world's largest feed customers across MidWest and Texas and do that in the most efficient way. There is just one rule "Never run out of feed" which we have to follow while managing our systems for:

1. Variable Demand - We want to keep our customers at a target inventory while accounting for variable feed usage, shrinkage and degradation
2. Variable Supply - Corn milling assets provide us with the raw material to prepare feed which can vary depending on the milling business througput
3. Drivers - We want to maximize the driver's time to do maximum deliveries in the shortest time window.

Solution
The objective is to decouple the feed business from the variability in different components of their supply chain. To accomplish that the data science team in collaboration with Digital Labs has broken down the problem into different optimization modules. Currently we are working on the foundational piece of our solution which is the KIX(Customer Inventory Execution) module.The KIX optimization module has two key features:

1. Usage Model - Ingests driver estimated inventory readings across all the 130 feed customers to calculate the current customer feed inventories and usage rates.
2. Recommendation Model - The recommendation optimization model takes the usage model numbers to create a recommended loads of deliveries for next 7 days. This list can range from 300-350 truckloads to 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.

Benefits

• The business used to spend days to get the right usage and inventory and then use that information to schedule fulfillment orders. By automating all of it using the KIX module, the business now spends more time with customers.
• KIX model can run at the snap of finger at any time of the day to readjust the delivery plan on the basis of changes in customer demand
• KIX enables the business to respond to changes in demand more accurately and efficiently and at the same time also plan for any future events such a snow storms or planned plant downtimes
• The business more efficiently manages for variable supply and variable demand by raising/reducing the target inventory at our customers automatically using the KIX module. This means that the business can use customers as distributed warehouses in case of excess supply and vice versa
• KIX has laid the foundation to develop DAX(Driver Assignment Execution), which will maximize driver utilization by dynamically assigning delivery loads to drivers based on driver availability, customer gate hours, plant capacity and other critical constraints in the system