Retail Out-of-Stock and Write-Off: Decision Tree Diagnosis

Akshay worked on a retail supply chain engagement where the client was experiencing two simultaneous problems: high write-offs from spoilage and wastage, and persistent out-of-stock situations that customers were flagging. The challenge was that the available evidence was largely qualitative: store managers reporting weekly product disposal, customers reporting empty shelves, and a consistent gap between what stores ordered and what they received.

His approach was to build a decision tree before touching the data. For the out-of-stock problem, he mapped the branching logic from the shelf backward: was the product on the shelf, in the backroom, or genuinely not in the store? If it was not in the store, was that a demand forecasting failure, a logistics failure, or a supplier fulfillment failure? Each node of the tree pointed to a different root cause and a different fix.

For the write-off problem, he structured a parallel tree: which categories were driving spoilage, and was the spoilage caused by late deliveries, products arriving with insufficient shelf life remaining, or inventory levels that exceeded the realistic days-of-sale before expiry?

By mapping the qualitative feedback from customers and store managers to specific nodes in each tree, the team was able to identify which branches were actually driving the problem and prioritize the interventions accordingly. The structured approach converted a noisy set of anecdotal inputs into a clear set of levers the client could act on.