Businesses that operate multiple warehouses or distribution centers often end up with too much stock in one location and not enough in another, with both revenues and customer service levels suffering as a result. Fortunately, there’s a way to minimize the problem.
DRP vs. Inventory Optimization
Traditional methods such as Distribution Requirements Planning (DRP) aren’t equipped to handle this challenge. This is because they assume static supply relationships, and usually don’t help in balancing out shortages against surpluses.
An Inventory Optimization solution, on the other hand, will determine the optimal quantities to move between warehouses, so that target service levels are met with a minimum amount of stock.
When should you move stock?
There are a few factors that impact whether a move of stock between warehouses is warranted. The first being supply lead times – the longer the lead times, the more important it is to consider redistributing excess stock. This is simply because if you have long supply lead times, you are more likely to get shortages. And once you have a shortage on your hands, those long lead times will only compound the problem.
Secondly, it’s usually more beneficial to redistribute products that are small and cheap to transport, and expensive to produce or purchase.
How can optimization help?
Inventory Optimization will work out the optimal quantities to move between warehouses and also balance the total cost of being out of stock versus the cost of moving stock. A range of parameters are considered for the optimization:
- future demand –customer orders and forecast
- sales prices
- min/max stock level targets
- transportation costs
- customer priorities
Once generated, the optimized plan is sent back to the ERP system as a firm planned distribution proposals. The next planning cycle can now make use of this information to achieve improved delivery service and lower supply costs.
If you’re interested in this topic, you should also check out our White Paper, Setting the Optimal Safety Stock.