THE CHALLENGE:
A manufacturer of steel products was concerned about the number of “lost sales” through stock outs.
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 clearly 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 RESULT:
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 dead stock was reduced by a factor of 10
- 38x return on investment.