Case Study: SpartanNash (U.S. food distributor & retailer) achieves accurate daily demand forecasts and exception‑driven replenishment with SymphonyAI

How AI helps you focus on what matters in your demand forecast

Spartannash, a U.S. food distributor and retailer operating across four channels, faced rapidly shifting shopper demand and large volume transfers from traditional wholesale to growing national accounts. To move from weekly, manual replenishment planning to more accurate, daily forecasts and exception-driven workflows, Spartannash piloted SymphonyAI’s AI demand forecasting and AI‑driven warehouse replenishment capabilities.

SymphonyAI implemented channel segmentation, AI forecasting and replenishment that surfaced exceptions, enabled just‑in‑time inventory and gave Spartannash actionable feedback for customers and suppliers. The result: more accurate daily forecasts, major time savings from exception‑based workflows, the ability to push more volume through the same‑size distribution network, and improved labor, sourcing and network planning driven by positive pilot outcomes with SymphonyAI.

Spartannash

Jeannette Buck

Director Demand Planning