Retailer Improves Lead Time Accuracy by 55% with AI Control Tower

Introduction

A global retailer offers a wide assortment of products across 2,000 retail locations and is a major importer in North America with over 100,000 SKUs and 65 distribution centers. The company’s mission is to deliver the best customer experience at the lowest prices in its retail category.

Challenges

The company operates a highly complex supply chain, with a vast volume of purchase orders, suppliers, and extensive network of distribution and retail sites. Keeping orders on time and avoiding stockouts is especially critical for business success in a market where the retailer’s high-quality customer experience is a key differentiator.

Prior to engaging with C3 AI, the company faced challenges in accurately predicting lead time for inbound purchase orders and evaluating supplier performance. The existing approach relied on static and one-size-fits-all lead time estimates, which failed to account for supplier-specific uncertainties and the dynamic nature of the broader supply chain.

Solution

To address these challenges, the company decided to partner with C3 AI to deploy C3 AI Supply Network Risk (SNR), an end-to-end visibility and control tower AI application, to enable holistic visibility across its supply network, starting with orders coming from international suppliers. To deliver high inventory service level and avoid stockouts, the company required uncompromised visibility into inbound purchase orders and sourcing delays for downstream transportation, capacity, and labor planning.

Results

By deploying C3 AI SNR to improve lead time visibility and prediction accuracy for its import orders, the company increased lead time prediction accuracy by 55% and daily in-transit lead time prediction accuracy by 25%. When deployed to all import orders, the company expects to realize up to $30 million in annual economic benefit through reductions in inventory, transportation, and labor costs.

About the Company

• $150+ billion annual revenue
• 2,000 stores worldwide
• 65+ distribution centers worldwide
• 500,000+ employees

Project Highlights

• 4.5 years of historical data integrated —
  including 13 billion rows from 3 external
  data sources
• 200+ timeseries analytics developed for
  machine learning models and application
  interface
• 480+ machine learning models developed,
  trained, and evaluated
• C3 AI Supply Network Risk application
  interface configured