European FMCG Retailer · Retail & FMCG
Retail Demand Forecasting Engine
Replaced legacy heuristic replenishment with a probabilistic forecasting system incorporating promotions, seasonality, and local event signals across 3,200 SKUs.
Primary Impact
23% reduction in stockouts
Industry
Retail & FMCG
Engagement
End-to-End Delivery
The Challenge
The Problem We Were Brought In To Solve
The client's planning team was managing over 3,200 SKUs with a static rules-based system that could not adapt to local events or promotional uplift. We implemented a hierarchical Bayesian forecasting model.
Our Approach
How We Engineered the Solution
Our team conducted a rigorous discovery process to understand the client's existing data landscape, systems architecture, and team capabilities. We designed a bespoke solution architecture tailored to the client's constraints — balancing performance requirements against infrastructure cost, regulatory compliance, and maintainability. Every design decision was validated against the primary success metric before a single line of production code was written.
Forecasting
Bayesian
Retail
The Outcome
Measurable Results Delivered
Primary Metric Achieved
23% reduction in stockouts
The solution was deployed to production within the agreed timeline, with full handover documentation, operational runbooks, and a 90-day monitoring period to ensure stability. The client's team was trained on the new platform and the system has continued to perform within SLA parameters since launch.
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