What demand sensing is
Demand sensing is short-horizon forecasting: using last week's actual sell-through to correct the next one to four weeks, instead of waiting for the monthly planning cycle to re-plan. On a promoted natural snack SKU at 140 Sprouts stores, that is the difference between shipping against a number locked three weeks ago and shipping against Monday's Retail Link pull.
Sold as short-term demand forecasting, it is the same idea under a plainer name. The statistical forecast sets the shape of the quarter. Sensing adjusts the front of it with signal that arrived after the plan was locked. It does not replace demand forecasting, and a brand that cannot forecast a baseline will not be rescued by sensing a bad one faster.
Demand sensing vs demand forecasting
| Demand forecasting | Demand sensing | |
|---|---|---|
| Horizon | 1 to 18 months | 1 to 4 weeks |
| Rebuilt | Monthly, on the S&OP cycle | Weekly, when POS lands |
| Input | Baseline, seasonality, planned promo | Last week's actual sell-through |
| Answers | How big is the quarter | Is the front of it landing where we said |
| Fails as | Error against actuals over the horizon | A correction nobody has time left to act on |
The volatility that decides whether it pays
Sensing earns its keep on variation, not on level. Seasonality is the part that repeats and is already in the model. Volatility is the week-to-week variation left over once you remove it, and its size decides how much a short-horizon correction can buy you.
| SKU profile | Baseline units/store/wk | Week-to-week variation | Sensing worth it? |
|---|---|---|---|
| Staple, no promo | 9 | ±10% | Marginal |
| Promoted natural snack | 9 to 25 | ±60% | Yes |
| New item, first 12 weeks | 3 to 14 | ±80% | Yes |
| Seasonal, in season | 12 to 30 | ±45% | Yes |
A staple at ±10% does not need sensing. It needs to be left alone. The volatile weeks are where the miss lives, so they are the only weeks a weekly correction pays for.
What a weekly correction actually recovers
Here is a different four-week window on the same 10 oz roasted almond SKU, units per store per week, with a 25%-off TPR in W3. These are not the four weeks demand forecasting scores on that page, and the actuals differ accordingly. The locked plan was set at the start of the month. The sensed forecast applies one rule: carry last week's actual-to-plan ratio forward, damped 50%, so a single soft week does not whipsaw the next one.
Forecasts are shown to two decimals because the error column is computed from the unrounded value.
| Week | Locked plan | Actual | Locked error | Sensed forecast | Sensed error |
|---|---|---|---|---|---|
| W1 | 12 | 9 | 33.3% | 12.00 | 33.3% |
| W2 | 12 | 10 | 20.0% | 10.50 | 5.0% |
| W3 | 25 | 21 | 19.0% | 22.92 | 9.1% |
| W4 | 12 | 11 | 9.1% | 11.04 | 0.4% |
The W2 correction: W1 came in at 9 against a plan of 12, a ratio of 0.75, damped to a 0.875 factor, so 12 x 0.875 = 10.50 against an actual of 10. Carry the same rule through W3 (10/12 damped gives 0.9167, so 25 x 0.9167 = 22.92) and W4 (21/25 damped gives 0.92, so 12 x 0.92 = 11.04).
MAPE on the locked plan is (33.3 + 20.0 + 19.0 + 9.1) / 4 = 20.4%. On the sensed forecast it is (33.3 + 5.0 + 9.1 + 0.4) / 4 = 12.0%. The correction removed 8.4 points of error, about 41% of it.
I never got a sensing process approved on the strength of a vendor's average. What got it approved was running the rule over our own last two quarters and showing which specific weeks it would have moved, which is a much shorter list than the pitch implies.
Note which week did not improve. W1 has no prior signal to carry, so sensing cannot touch it. That is the honest shape of the benefit: sensing buys you weeks 2 through 4 of a window, never the first one, and the vendor deck that shows an even improvement across all four is showing you a backtest, not a forecast.
Lead time is what caps it
A correction you cannot act on is a more current number to be wrong with. Before buying sensing, write down what decisions are still open inside a one-week signal.
| Decision | Typical lead time | Can Monday's signal move it? |
|---|---|---|
| Allocate on-hand DC stock by banner | 1 to 3 days | Yes |
| Expedite a partial truck | 3 to 7 days | Yes |
| Cut in or cancel a retailer promo | 2 to 4 weeks | Sometimes |
| Co-packer production run | 4 to 8 weeks | No |
| Ingredient and packaging buy | 8 to 16 weeks | No |
If the co-packer needs six weeks and the distributor holds four weeks of cover, a signal that arrives on Monday cannot change what ships this month. It can still change allocation between retailers, and on a promoted SKU that is often the decision worth the most. This is the same constraint that separates a forecasting problem from a planning one on the replenishment planning side of the loop.
Where Scout fits
Scout is a demand-side analytics layer. It connects your SPINS, Circana, or retailer POS exports so last week's actual sell-through lands as a series you can compare against the plan you locked, by retailer and SKU, and so you can score whether a weekly correction would have helped before you build a process around it. It is not an S&OP system or a supply-planning engine. It does not place orders, hold your lead times, or generate the replenishment plan. It measures the signal and the size of the error a correction removes.
The short version
- Demand sensing is short-horizon forecasting: correct the next one to four weeks with last week's actual sell-through.
- It pays on volatility, not on level. A staple at ±10% week-to-week variation does not need it.
- On the worked example a damped one-week correction took MAPE from 20.4% to 12.0%, removing about 41% of the error.
- It cannot improve the first week of a window, because there is no prior signal to carry.
- Lead time caps the whole idea. If nothing downstream can move inside a week, sensing buys a more current number and no decision.