A growing fresh food business needed a smarter way to manage demand, production and distribution across multiple stores. Because the business runs on perishable products, getting the right products to the right stores at the right time — while reducing returns and operational inefficiencies — is critical.
Traditional order capture alone couldn't manage daily production, warehouse movement, cold-storage planning, van loading and store-wise product mix. The business needed a connected, intelligent process to support decisions across the supply chain.
Store-level, SKU-level demand was hard to estimate from orders alone.
Daily production needed to reflect expected demand, not guesswork.
The right suggested quantities had to reach warehouse and cold storage.
Each van needed a recommended SKU mix for the stores it served.
Overstocking and mismatched demand drove avoidable return pickups.
Availability needed to improve without relying only on manual planning.
We implemented an AI-enabled demand forecasting approach that goes beyond basic order capture — turning forecasts into actionable recommendations across production, dispatch, van loading and store-level SKU mix.
Expected demand by SKU and store.
Recommended quantities to make.
Structured inventory movement.
Recommended load per route.
Right mix on every shelf.
The solution improved planning accuracy, reduced manual dependency, and aligned distribution with real store-level demand.
By using AI-led demand forecasting and automated planning recommendations, the fresh food business improved how products move from production to store shelves. Each store receives a more relevant SKU mix, while production planning, van loading and operational efficiency all improve — a stronger foundation for reliable availability across a fresh food supply chain.
The SalesDiary modules that keep this forecasting-led flow running day to day.
The SalesDiary platforms this forecasting solution is built on.