Short shelf life, promotional spikes and seasonal swings make food the hardest inventory to get right. DemandIntel forecasts the waves and sizes stock on your own data, so less spoils and less sells out.
In food and beverage, a miss costs you on both sides. Over-order and it spoils, a total write-off, not a markdown. Under-order and the shelf is empty, and in grocery an empty shelf is not a delayed sale, it is a basket that switches to a competitor and may not come back.
Between those two cliffs sit weekly promotions, hard seasonality and relentless SKU proliferation. A smoothed average is always late to all three.
Perishable overstock spoils. It is destroyed, not discounted, so every over-order is paid in full.
Weekly promo drops create sharp, short-horizon demand that a moving average never sees coming.
Ramadan, the holidays, summer: basket mix and volume shift for weeks, across every SKU at once.
Every new flavour, format and private-label line multiplies the forecast, and the obsolescence risk.
You plan the supplier’s production, not just the shelf. Upstream variability is yours to absorb.
A stockout is not a lost sale, it is a lost customer. In grocery the basket switches and often stays switched.
median demand-forecast error in food and beverage
of surplus food from US manufacturing every year
in lost revenue across US food producers and businesses
Sources: Gartner, via ISM (2024); ReFED, 2025 US Food Waste Report (2023 data).
DemandIntel forecasts promotional, seasonal and intermittent demand reproducibly, modelling the spikes instead of averaging them flat. On short-dated lines, the pre-obsolescence view flags what will not sell in time, while it still has value.
Safety stock is sized on real forecast error per SKU, so you hold less of the slow movers and protect the fast ones. The result is less spoilage and fewer stockouts from the same working capital. It reads your existing ERP data and runs on-site.
Because every decision is reproducible and auditable, your planners can defend the plan in the S&OP meeting instead of arguing about whose number to trust.
Yes. Promotions are modelled as the demand drivers they are, so the forecast anticipates the spike rather than being surprised by it.
Then you own the demand signal end to end, which is exactly where reproducible forecasting pays off. It plans the supplier production, not just the shelf.
Yes. Short-dated and shelf-stable lines are planned with the right shelf-life and service logic for each, in one place.
That is the first thing the pre-obsolescence view targets: short-dated stock that will not sell in time, flagged early enough to act.
Picture your next S&OP meeting: one number on screen that nobody argues with. See it free, on your own data, in 45 minutes; and if it does not hold up, we part as friends.