Wholesale: Precise Demand Forecasting – Never Too Much or Too Little

An industrial wholesaler with 600 employees and 180,000 articles holds average annual inventory of €28 million. Of this, 22% is classified as slow-moving or dead stock — items over-purchased because demand planning relied on experience and spreadsheets.

At the same time, there was approximately 8% non-availability on fast-moving lines — items under-ordered. Both have costs: excess stock ties up capital; non-availability loses clients.

Sales Data and Supplier Terms Are Crown Jewels

Sales data by product and client, and the terms negotiated with suppliers, are among the most sensitive business information for a wholesaler. Analysis by external cloud services was not considered.

Local Demand Forecasting with SoverIQ

SoverIQ Stack is connected to ERP and inventory management system — locally. The model analyses:

• Historical sales data by article, client, region, season
• Open order backlogs and known client projects
• External signals: construction index, industrial output, commodity prices (locally as a data feed)
• Supplier lead times and minimum order quantities

The output: weekly purchase proposals with confidence intervals — for every article automatically, with reasoning.

Results

Slow-moving stock rate fell from 22% to 11% within 18 months. Capital released from reduced excess stock: €3.8 million. Non-availability on fast-moving lines fell from 8% to 2.1%. Purchasing now spends time on supplier negotiations instead of manual inventory management.