Every company wants to have the right amount of the right inventory in the right place at the right time, and that has been the primary focus of Material Requirements Planning (MRP) software and its successors and descendants including Enterprise Resource Planning (ERP), and Distribution Requirements Planning. Traditional planning systems use traditional logic that calculates a time-phased replenishment plan. But very few professionals have been totally satisfied with the MRP approach. While the MRP approach does develop a reasonable and logical plan that’s far better than guesswork, min-max, or order point strategies, it is entirely dependent on the accuracy of the forecast and does not recognize or react to anything outside of the “normal” – like supply chain disruptions, delays in production or distribution, or changing costs, availability, or priorities.
Optimization (for a more general discussion of optimization see the previous blog, Why is Optimization Important for Supply Chain Planning? ) is designed to take those dynamic factors into consideration by comparing different strategies in order to determine a “best” approach among all the alternatives. The user sets the priority by defining what “best” means – lowest overall cost, best customer service, minimum transportation cost, staying within warehouse capacity limits – or more likely some combination of these. Lowest overall cost to maintain 95% service level without exceeding warehouse capacity anywhere in the network, for example.
The system will then try many, many different combinations of replenishment opens (quantity and timing), transportation choices (truck is faster but rail is cheaper), warehouse inventory strategies (it’s more economical to store a larger quantity at a feeder warehouse serving more distribution points but transportation costs will likely be higher and customer service will suffer), and other trade-offs to find the best combination within whatever restrictions may exist – like warehouse size or container volume limits.
Understand, of course, that all these factors are changing constantly. Fuel and transportation costs are notoriously volatile as are taxes, duties, and capacity availability. Likewise, customer demand is always changing, often unpredictably, and there are those supply chain disruptions mentioned previously. The good news is that optimization routines can be rerun as often as you like. Even though you don’t want to be changing strategies minute-by-minute, it’s really useful to see the impact of any disturbance that takes place and be able to quickly identify and react to an issue that might affect customer service…and to know the best way to react.
Inventory optimization in the supply chain is focused on where to hold inventory in the distribution network to deliver the desired level of customer service at minimal cost within any limits or restrictions that exist. That may mean that some items are stored in larger quantities closer to the source and distributed in smaller quantities more often down the chain while others are more likely to be held closer to the customer for quick delivery. Optimization brings all those considerations together in a comprehensive plan that delivers the desired performance at minimal cost.
This post originally appeared on Navigate the Future, the Dassault Systemes North America blog
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