Forecasting pad usage: seasonality in a fresh department

Week fifty-one uses 40 percent more pads than week eight, and the ordering system treats both as a normal week. That gap is why stores run out in the ten days before Christmas and sit on three months of stock in February. The pads are not the problem. The forecast is a flat line applied to a seasonal business.

Fresh departments have a usage curve, and it is more predictable than most managers think. It follows the product mix, the trading calendar and the weather, in that order.

Where the swing comes from

Three drivers, and they stack. The first is protein mix: a Christmas lamb and beef week moves far more trayed product than a January week of mince and chicken portions. The second is the calendar: bank holidays, school terms and local events change the number of trading days and the shape of the peak. The third is weather, which moves barbecue demand within a fortnight.

The mix driver is the biggest and the least measured. Pads per case varies by species and cut, so a shift from whole birds to fillets changes pad consumption even when case volume is flat.

Pads per case is the number to learn first. On a tray of steaks it might be one sheet per two packs. On whole birds it can be two per pack. If you know that single ratio for your top ten lines, you can forecast a promotion in five minutes without any software.

Building a three-line forecast

Keep it simple enough to maintain:

• Base usage: the average pads per week over the last eight quiet weeks.
• Seasonal index: last year’s pads in the same week divided by last year’s average.
• Promotion uplift: pads per case for the promoted lines times the expected case lift.

Multiply base by index, add the promotion line, and you have a number you can defend. It will be wrong by 10 percent most weeks and right enough to avoid a stockout. That is the correct standard for a fresh department forecast.

The December stockout

A store ran out of pads in the week before Christmas and bought retail packs from a nearby cash and carry at three times the contract price. The order had been placed on the previous year’s December average, which included the quiet days after the holiday. The peak week itself was 60 percent above average, and the order covered 15 percent.

The lesson is not to order more. It is to forecast by week, not by month, for the six weeks around the peak. A monthly figure smooths out exactly the spike that causes the problem.

Suppliers have the same problem in reverse. A pad plant running flat out in November will allocate stock to the customers who gave it a weekly forecast, and the ones who sent a monthly average will be told the lead time is six weeks. The forecast is not only an internal document.

Stock cover against pad shelf life

Pads keep well in a dry store, but they do not keep forever in a damp one. Holding six weeks of cover in a back room with a cold wall is how a store ends up with cockled sheets in January. Two to three weeks of cover is enough for a normal period, and four for a peak, provided the store is dry and the cartons stay closed.

There is a second constraint that catches people in a good year: cash. Pads are a small line but they are bought in cartons, and a four-week peak order ties up money in a product that will still be there in March. Four weeks is the sensible ceiling for both reasons.

Write the index on the same sheet as the order and review it every quarter. After a year you will have your own curve, which is worth more than any national average. If you are setting pads per case for the first time, the product pages list sheet counts per carton, which is the unit you actually order in.