Retail & E-commerce
6 optimization problems
Dozens of SKUs from the Same Supplier — At What Frequency Do I Order Each So Trucks and Stock Cost Are Minimum Together?
This page is for an SMB wholesaler, importer or manufacturer pulling 50-500 SKUs from the same supplier — typically across 3-15 main suppliers. The weekly question is the same: from this supplier, which products should ship today and which can wait until next week? If every product triggers its own order, the same supplier ends up sending three trucks and three customs filings a week; one truck, one customs filing and one setup cost can cover all of it if the groups are right. Manual planning falls apart past 50 SKUs: some weeks a half-empty truck, others three back-to-back orders — fixed costs come back as 5-15% of unit product cost.
How Much of Each Product Should I Order So I Neither Run Out Nor Pile Up?
Written for retail, e-commerce, or manufacturing SMBs managing 500-5,000 SKUs. If your purchasing team still places orders every month from a spreadsheet using last-three-months average plus ten percent, and yet you see empty shelves and clogged warehouses at the same time, you are in this problem. When the same company carries both stockouts (5-15% lost sales) and dead inventory (10-25% capital tied up), intuition has hit its limit: seasonality, lead-time uncertainty, and slow-moving SKUs cannot be corrected by hand item-by-item. Systematic forecasting paired with an inventory policy typically frees 1.8-5.4M TRY/year of working capital on 50M TRY revenue and lifts the service level from roughly 85% to 95%.
Stock Is Not Clearing as the Season Ends — When and How Deep Should I Mark Down So That Margin Holds and Dead Stock Stays Low?
This page is for you if you run a seasonal-collection fast-fashion retailer, a 30-100 store apparel/shoes/accessories chain, or a fresh-food chain (greengrocer, bakery, butcher). The classic pain: a 200-1,000 SKU collection sells for 4-12 weeks and then the unsold stock becomes a problem — discount too early and you erode the gross margin, discount too late and you sit on a pile of dead stock at the end of the season. The decision: which item, when, and by what percentage to mark down? In a mid-size fashion chain run on gut-feel rules, 20-35% of end-of-season stock ends up as salvage; a proper markdown schedule lifts the gross margin by 5-15%, cuts dead stock by 20-30%, and adds 15-60 million TRY of operating margin a year on a typical revenue base.
When to Reorder, and How Much?
A retailer, e-commerce store, or distributor holding 200–5,000 SKUs. For each SKU the question is: when do I reorder from the supplier, and how much? Suppliers deliver 3–21 days after the order (lead time), demand swings day to day, some products expire, warehouse space is finite, and most suppliers impose a minimum order quantity (MOQ). The decision: which SKU to order, when, in what quantity, so that 'out of stock' (lost sales) and 'over-stocked' (cash trapped, expiry) are both kept in check. Manual tracking works up to ~50–100 SKUs; above that, 'I keep it in my head' breaks down — either you over-order or you go out of stock on something critical.
Which Products Stay on the List, and How Much Shelf Do They Each Get?
Written for an SMB retail chain with 30-200 stores or an e-commerce operator running 500-5,000 SKUs. If every month you fight over which products stay on the shelf, how much space each one gets, and which existing item to drop to fit a new supplier, this is your problem. Intuitive listing and hand-drawn planograms quietly erode category margin: bestsellers get too little facing, dead SKUs hog space, and the substitution effect (a customer leaving for a competitor when their pick is missing) stays invisible. A systematic store- and category-level decision process typically swings annual margin by 2-6M TRY on a 50M TRY category.
Which SKU on Which Shelf, and Along What Route Should the Picker Walk?
An e-commerce warehouse or omnichannel retail DC stores 15,000-200,000 product codes (SKUs) and picks 2K-30K order lines a day. A picker walks 200-800 m per order and 15-30 km a day in total. Fifty to seventy percent of that walking is non-value-adding. Two coupled decisions must be made: (a) **slotting** — which SKU is stored on which shelf and at which height, given pick frequency, co-order pattern and ergonomic load; (b) **picking routing** — for a given pick list, the picker's aisle sequence and the chosen routing rule (S-shape, return, midpoint, largest-gap, combined). Add-on decisions: collect multiple orders in one trip (batch picking), split the warehouse into zones (zone picking), merge at a sort station (sort-merge). When both decisions are solved together, walking distance per picker can drop 25-40%.