By using BearingPoint’s Inventory Navigator, a global automotive supplier client benefits from a sustainable inventory optimization approach resulting in full cost transparency for logistics planners and material managers. This empowers them to make data-driven decisions, adapt to changing market demands, and achieve an inventory level that meets liquidity constraints and targeted service levels.
Companies need to accurately balance their inventory levels to ensure liquidity and profitability. At the same time, supply-chain resilience must be secured, as companies need to keep their warehouse stocks at optimal levels to support production and supply to customers.
Our client, a global automotive supplier, was challenged by the lack of transparency across its inventory. This prevented them from having an accurate view of how the actions the company took impacted its required level of stock regarding raw materials, work in progress, and finished goods.
With 100+ manufacturing units in more than 30 countries, the company needed to balance the trade-offs between inventory resilience, liquidity, and earnings before interest and taxes (EBIT), and then align the outcome to its management strategy.
BearingPoint leveraged its AI-driven Inventory Navigator software solution to support the client with managing their inventory. The solution derived insightful information from the company’s ERP data and optimized relevant inventory processes to formulate the management strategy. This enabled transparency across different pain points, which caused either shortages or excess inventory, and provided recommendations for improving the inventory levels.
Safety buffers were then used to address the exchange between the needed liquidity and the inventory resilience, based on a target service level. Lead-time parameters, such as the goods receipt processing time, were measured and adapted to the required “time to perform”, allowing for better supply chain planning. Finally, lot-sizing parameters calibrated the trade-off between liquidity and EBIT, covering the transportation, inventory holding, and capital tie-up costs. Several optimization scenarios were then calculated to meet the desired management strategy. The client could then choose a suitable optimization scenario in line with its strategic decisions.
The global automotive supplier has successfully identified excess stock, leading to 20% inventory reduction. At the same time, high resilience targets for supply-critical parts, such as semiconductors, are being achieved by implementing the Inventory Navigator.
The client’s inventory management has been optimized using artificial intelligence technology that enables them to use complete data, update information in near-time, and develop calculation scenarios aligned to their strategy. At the same time, the company now has complete cost transparency across all its manufacturing plants, empowering them to make data-driven decisions, adapt to changing market demands while securing the optimal inventory levels and liquidity.