Challenge
Fragmented demand signals and a centralized-only stocking model meant constant stock-outs, expensive emergency air-freight, and dealers losing customers to independent shops.
All selected work
Supply Chain Africa
Redesigning parts supply to protect uptime in Africa
A service-network operator was losing dealer trust as parts stock-outs stalled repairs across the region.
- 94%
- parts fill-rate
- −63%
- emergency air-freight spend
- 12 → 4 days
- average parts lead time
Approach
Introduced a three-tier stocking model (central / regional / dealer), built demand-forecasting tied to installed-base data, and set dealer min-max levels with replenishment automation.
Result
Parts fill-rate reached 94%, average lead time dropped from 12 to 4 days, and emergency air-freight spend fell 63% — protecting both dealer margin and customer uptime.
Facing a similar challenge?
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