Demand Forecasting
A leading European consumer goods manufacturer whose forecasts were too unreliable to plan around.
Sales data, promotions, market signals and supplier lead times in separate systems. Operations and commercial teams working from different numbers. Every forecast error paid for in stock-outs, urgent transport and wasted production capacity.
-15%
reduction in logistics costs from more accurate demand forecasting
8 months
to first measurable improvement in forecast accuracy and logistics cost reduction
Zero
ungoverned or incomplete data sources feeding the demand model
WHAT IT DELIVERS
A forecast the supply chain can actually act on.
Sales history, promotions, weather, market data and supplier lead times all feed the model. Nothing is left out because it was hard to connect.
Different approaches are tested per product and category. The best performer is selected, explained and monitored continuously.
Every forecast comes with an explanation. Teams can see why the model predicted what it did and adjust it with business context.
Anyone in the business can ask a question about demand in plain language and get an answer immediately. No analyst dependency, no ticket queue.
What the organisation gains
01
Safety stocks are reduced. Stock-outs become less frequent. Urgent transport becomes the exception. Each percentage point of forecast improvement has a direct impact on the cost base.
02
When the forecast is trusted, production plans align with actual demand. Waste falls, production scheduling becomes more efficient, and the entire supply chain operates with less buffer.
03
Each new product introduction is supported by a demand model informed by the full portfolio history. Launch volumes and placement decisions are based on evidence, not assumptions.
Governed data, tested models, continuous improvement.
The numbers, conservatively phrased
-
–15%
Reduction in logistics costs
From more accurate demand forecasting across the product portfolio.
-
8 months
To first measurable improvement
In forecast accuracy and logistics cost reduction from go-live.
-
Zero
Ungoverned data sources
Every input to the forecast model is connected, validated and monitored end-to-end.
Where demand forecasting creates the most impact
Seasonality and external signals make demand hard to predict accurately. Stratio selects and governs the best forecasting model per product cluster.
Production planning and procurement depend on forecasts that account for supply chain complexity. Stratio governs the data those forecasts are built on.
Grid and emissions data shared across operators, regulators and market participants, governed for CSRD compliance.
Seasonality and external signals make demand hard to predict accurately. Stratio selects and governs the best forecasting model per product cluster.
Production planning and procurement depend on forecasts that account for supply chain complexity. Stratio governs the data those forecasts are built on.
Grid and emissions data shared across operators, regulators and market participants, governed for CSRD compliance.
Ready to build a demand forecast the supply chain can act on?
Request a demonstration using your own demand data. We work with consumer goods, retail, and manufacturing organisations across Europe and LATAM.
