How wrong was the forecast, ignoring which way it was wrong?
You are reviewing last quarter's demand forecast. For each product, put the size of the forecast error as a share of actual demand in D2:D5 — a miss of 10% is a miss of 10% whether the forecast was high or low.
Solve it on your own to keep the bonus. Each hint gets one step closer to the formula.
The same formula in the other shapes it takes at work.
This is the grid you start with. Cell references in the task — B6, C2 — point at the row numbers and column letters below.
| A | B | C | D | |
|---|---|---|---|---|
| 1 | Product | Forecast | Actual | Error % |
| 2 | Kettles | 1200 | 1350 | |
| 3 | Toasters | 900 | 810 | |
| 4 | Blenders | 450 | 450 | |
| 5 | Irons | 600 | 750 |
Averaging signed errors lets an over-forecast cancel an under-forecast, and a forecast can look perfect while being wrong on every line. Absolute percentage error keeps every miss positive, so a bad forecast always looks bad.