Supply Chain Analytics case study
Multi-echelon demand forecasting and safety stock optimization
An anonymised summary of the challenge, approach and outcome. Client names and measured figures are published only with written consent.
Anonymised client work
We do not publish client names or identifying details without written consent, and we do not publish numbers we cannot substantiate. The summary below describes the shape of the work without exposing the client.
Client
Supply Chain Analytics sector organisation, identity withheld pending consent
Challenge
Supply chain planners relied on static historical moving averages, causing regional stockouts during seasonal demand surges and high holding costs during lulls.
Solution
Acmez developed hierarchical time-series forecasting models incorporating promotional calendars, supplier lead times, weather data, and macroeconomic trends into automated reorder point calculators.
Outcome
Regional distribution hubs aligned stock levels with dynamic demand patterns, lowering safety stock variance and reducing emergency replenishment freight costs.
Capability involved
Next step
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