Two stores, opposite problems
A neighbourhood store in your network runs out of bread by four every afternoon. Customers ask, hear “finished”, and leave. Across town, another store has dairy piling up, a week from its date. It will be discounted, returned to the supplier if you are lucky, or thrown away.
When you review the numbers, the chain looks fine on average: total stock about right, sales about on plan. The average hides the fact that stock is in the wrong places.
What it costs
Imagine a food chain with ten stores. A store loses ₹4,000 of bread sales a day for twenty days a month because it runs out in the afternoon; at a 25 per cent margin that is ₹20,000 a month of margin lost, in one store, on one product. If four stores have a similar pattern, it is ₹80,000 a month, or about ₹9.6 lakh a year.
On the other side, if each of the ten stores writes off ₹6,000 of dairy a month, that is ₹60,000 a month, or ₹7.2 lakh a year. Together, about ₹17 lakh a year on two product groups, from figures small enough to be easily overlooked in any single month. Add the customers who stop checking your stores for bread.
Why it happens
Both problems come from the same cause: each store orders from its own rough impression of demand, and nobody sees the whole network.
Store managers tend to follow the last bad experience. After a stockout, they over-order. After a write-off, they under-order. The pattern swings, and the swing is worse for items with a short shelf life. There is also a gap between how often the store counts and how often it orders. If the store counts weekly and orders daily, it is ordering blind most of the week.
What is usually missing is a shared view of three things:
- What is in stock at each store today
- How fast each item actually sells, by day of the week
- Where surplus in one store could cover a shortage in another
What changes it
The operating fix starts with a rule for each perishable item: a minimum, a maximum, and a day-of-week pattern that reflects how it sells. Bread that sells out by four needs a second delivery or a larger morning order. Dairy that expires needs a lower maximum and a fixed rule for when it is marked down.
Next, make one person responsible for rebalancing. Each day, that person looks at the stores that are about to run out and those holding too much, and moves stock where distance and shelf life allow. In many chains this role does not exist, so surplus simply waits for a write-off.
Third, review the write-off and stockout list weekly, by store and by item, and change the rule for the worst five. This is a better use of a manager’s hour than reviewing total sales.
Systems help by keeping stock and daily sales current, and by flagging items likely to run out before the next delivery. They are only as good as the rules behind them, so settle the rules first.
What this does not fix
You cannot sell stock that never reaches the shelf, and no system can predict a sudden local event, a weather change or a competitor’s offer. Rebalancing also has limits: moving fresh dairy across a city costs fuel and time, and for some items it will never be worthwhile. Expect fewer surprises, not none.
Working out how much cash these buffers hold is a useful first step; the working capital tool is built for that.