Demand planning for FMCG, where the history lies to you
Promotions, distributor loading, festive peaks and launches all move your numbers for reasons that have nothing to do with demand. Likwid forecasts every SKU and region with those causes modelled rather than averaged over — then nets it into what to make and buy.
Planning pharma instead? See demand planning for pharma.
| Item | Per Day |
|---|---|
| Detergent Powder 1kgHome Caresmooth | 2,747 |
| Hair Oil 200mlPersonal Caresmooth | 1,563 |
| Biscuits · Glucose 300gFoodssmooth | 3,733 |
| Toilet Soap 100gPersonal Careintermittent | 2,143 |
| Face Cream 50g · WinterSeasonallumpy | 297 |
What makes FMCG demand planning different?
The maths isn't the hard part. The record you forecast from is distorted — and by things you did on purpose.
Every scheme, every bit of distributor loading, every festive week and every launch leaves a mark on sales history that looks exactly like demand. FMCG demand planning is the work of separating those causes from the underlying baseline, across thousands of SKUs and every region — then turning the result into a plan for what to make, hold and buy.
Four ways an FMCG forecast goes wrong
None of them are arithmetic errors. They're all the same mistake — treating a caused number as an ordinary one.
Every promotion rewrites your history
A scheme month sells three times the baseline. Next year the model reads that spike as ordinary demand and plans for it — so you build to a number that only existed because you discounted it. Unless the promotion is recorded as a cause, the uplift quietly becomes the forecast.
You forecast dispatches, not offtake
Primary sales tell you what left your warehouse. Secondary sales tell you what the consumer actually bought. When the distributor is loaded, primary looks healthy while offtake is flat — and the correction arrives as returns and a dead month.
The festive peak moves every year
Diwali, Eid and the wedding season don't sit on the same dates twice, and they don't scale evenly by region. A month-on-month model built on last year's calendar plans the peak a fortnight late — which in FMCG is the whole peak.
A launch quietly eats its neighbours
The new variant hits its number, and nobody notices that most of it came out of the SKU next to it on the shelf. Both forecasts stay wrong until someone reconciles the category by hand.
From a forecast to a purchase order
The same three screens every cycle — what demand looks like per SKU with the pattern named, what it nets to once stock and open orders are counted, and the order that goes out.
| Item | Forecast | Conf | Pattern |
|---|---|---|---|
| Detergent Powder 1kgFG-DET-1K | 82,400 No | 88% | Promo |
| Hair Oil 200mlFG-HRO-200 | 46,900 No | 84% | Seasonal |
| Biscuits · Glucose 300gFG-BIS-300 | 1,12,000 No | 86% | Trending |
| Toilet Soap 100g · SandalFG-SOP-100 | 64,300 No | 79% | Steady |
| Face Cream 50g · WinterFG-FCR-050 | 8,900 No | 61% | Lumpy |
Model the cause, then forecast the baseline
Promotions modelled as a cause, not noise
Scheme periods are marked and their uplift held separately from baseline demand, so the promotion explains the spike instead of becoming next year's plan.
Forecast on secondary, plan on primary
Where secondary sales are available, demand is sensed from offtake and the distributor's stock position is netted off — so you plan against consumption rather than loading.
The festive calendar, not the month number
Seasonality is tied to the actual event dates and their regional spread, which is why the peak lands where the peak lands rather than where last year's cell sat.
Every SKU, including the long tail
Thousands of SKUs across branches each get their own method and confidence — including the slow and lumpy ones nobody had time to plan in a spreadsheet.
Built on Likwid's demand forecasting engine, feeding S&OP and procurement.
Illustrative of how the platform is designed to behave — actual figures depend on your catalogue and data.
FMCG demand planning, answered
Food & beverage specifically? See ERP for food & beverage manufacturing · inventory · pricing.
Explore the rest of the platform
See it forecast your own catalogue
A 30-minute walkthrough on your SKUs — promotions separated from baseline, the festive peak where it actually falls, and the buy that follows.
