Inventory Optimisation- Case StudySteel Manufacturer, Warehouse & Supply Chain - NSW, Australia
The Challenge
A manufacturer of steel products was concerned about the number of “lost sales” through stockouts. This prompted an assessment of the level of inventory, which returned several things:
• High levels of total inventory, but individual lines were experiencing shortages
• Demand trends were not known
• The total value of inventory was high
• There was a large amount of slow-moving and dead stock.
The challenge was to understand, “What is the level of inventory required to service our customers?”
The Solution
The existing sales and operations planning process was further optimised and enhanced through the application of various statistical tools. This was achieved by:
• Gathering and analysing customer demand data was to determine the required distribution of product levels by SKU (Stock Keeping Unit)
• Seasonal buying patterns were identified and added to the forecast
• Variation in demand was quantified and modelled
• Trends in demand were determined and demand forecast processes were constructed
• Service levels were reviewed and applied to product categories
• Safety Stock levels were determined
• Inventory data was analysed to determine re-order points
• Lead times and re-order quantities were reviewed and adjusted where possible and appropriate.
The Results
Statistics unlocked the value contained in the data already available within the organisation.
• Optimising inventory levels by product category achieved savings in the order of $4,000,000
• Slow-moving, and the dead stock was reduced by a factor of 10
• 38x return on investment