Inventory Optimisation
A premium UK automobile manufacturer struggled with excess inventory and legacy practices that pushed the organisation toward leasing additional storage. Decision Studio redesigned inventory strategy using hybrid forecasting, delivering $5.6M in direct cash inflow and $1M in annual lease savings.
Decision Studio partnered with the client to redesign its inventory strategy using proprietary problem-solving frameworks to map the interconnected supply-chain problem space. Working closely with the client's core engineering and design release teams, the engagement uncovered a critical gap: demand data was available only at the part level, not at the core component level. By obtaining detailed bills of materials and establishing part-to-core ratios, part-level demand was translated into core-level demand. Demand was further segmented by model year to improve forecasting precision. A hybrid forecasting approach was implemented, using regression models driven by Vehicles in Operation (VIO) data for near-term accuracy, and ARIMAX models for long-term, five-year forecasts that accounted for seasonality and volume changes. These forecasts enabled the definition of inventory banks with clear minimum and maximum thresholds, factoring in lead times and demand variability, resulting in a scalable, demand-driven inventory management framework.
$5.6M
$5.6M
direct cash inflow
$500K
annual savings from avoided lease
$500K
savings from terminated lease
17.6K
excess core units disposed
The analytics-led transformation positioned the inventory function as a strategic driver of efficiency and value across automotive operations.
