Academics
  /  
Undergraduate Program
  /  
Client Project Challenge
  /  
Project
Building a Forecast-Informed Min/Max Algorithm for Equipment Parts

 

Spring 2026

 

Snapshot

  • Client: Coca-Cola Consolidated
  • Project: Building a Forecast-Informed Min/Max Algorithm for Equipment Parts
  • Student team: Aidan McLaughlin, Evan Le, Jasmine Ong, Naavya Sheth
  • Main client contact: Christopher Holmes
  • Faculty advisor: Barry Nelson

 The challenge:

Coca-Cola Consolidated manages service parts across plants, trucks, and warehouses while balancing three competing goals: keeping critical parts available, limiting inventory value, and avoiding excessive replenishment orders.

Existing min/max policies were manually set and did not always reflect recent demand patterns. Some active part-site pairs had null or outdated min/max levels, while others held inventory where demand had declined, creating an opportunity to improve service and reallocate inventory more efficiently.

 The solution:

The student team developed a min/max recommendation algorithm that:

  • Forecasts part-site demand using recent demand history.
  • Classifies demand patterns to tailor recommendations to different types of parts.
  • Proposes candidate min/max policies for each part-site pair.
  • Evaluates those policies through historical simulation.
  • Produces a recommended min/max table supported by diagnostics on service level, fill rate, inventory value, and order frequency.

The result is a repeatable decision-support framework that gives Coca-Cola Consolidated a consistent way to compare availability, inventory, and ordering tradeoffs before changing policies.

Value delivered

Across three pilot plants, the recommended policies improved service outcomes while reducing inventory investment and keeping ordering manageable.

Voices from the client

"I really appreciate the partnership with the Northwestern team. We saw this as a big success. The students exceeded expectations and clearly put a lot of thought into the work. They are a strong group, and it shows."

— John Crooks, Coca-Cola Consolidated

"The students took a complex service-parts planning challenge and turned it into a practical, data-driven framework. Their work helps us understand where min/max levels should be revisited and how inventory can be better aligned with demand while maintaining service to the business."

— Christopher Holmes, Coca-Cola Consolidated

"The team did an impressive job getting up to speed on a complex problem in a short amount of time.  I would highly recommend this kind of partnership to other companies—it creates value while also giving students meaningful exposure to the types of challenges businesses are working through every day."

— Ontrell Hicks, Coca-Cola Consolidated

What's next

  • Validate the recommendation framework on additional plants and part-site pairs.
  • Refine inputs and business rules as additional demand history becomes available.
  • Explore how the framework can be incorporated into standard planning workflows.
  • Use the diagnostics to identify where manual review is most valuable before policy updates are implemented.

About Coca-Cola Consolidated

Read about Coca-Cola Consolidated on their website.