Demand forecasting and inventory policy for a pharmacy chain

Kopano Pharmacies runs 38 community pharmacies around Johannesburg and Pretoria, all supplied from one distribution centre in Midrand. The range has about 4,000 lines, from chronic medicines and antibiotics to vitamins and baby products.

Two problems are hurting the business. Customers on chronic medication find their medicine out of stock about one visit in twelve and go elsewhere, and the pharmacist has to call other branches. At the same time, the distribution centre holds about R86 million of stock, of which R7 million expired or was written off last year. Ordering is done by buyers from habit and last month's sales. Load-shedding has also caused two cold-chain failures for insulin and vaccines.

The COO wants a data-based inventory policy for the distribution centre. You will work on a representative sample of 60 SKUs, with two years of weekly demand that you generate in task 1 with realistic patterns: steady chronic lines, seasonal flu and allergy lines, slow movers and a few very erratic items. You will state each SKU's unit cost, lead time from supplier, shelf life and whether it needs cold storage.

You will classify the range, forecast demand, set order quantities, reorder points and safety stock by class, adjust for expiry and cold-chain limits, simulate the new policy against the current one, and present the result.

Done means a policy table per SKU class that buyers can follow, a simulation that shows the change in stock value, write-offs and stock-outs, and a rollout plan for the full range.