Many companies today still continue to use rather simplistic means with excel to determine stock levels and reorder quantities. We have seen that the most common and most damaging to your business is a simple product segmentation approach in which products are put into three or four classifications, like ABCD for example, based on either volume or value and reordering policies are then set the same across each of these categories. This is not inventory optimisation.
Inventory optimisation requires a different approach to this, especially for today’s complex supply chains. For true inventory optimisation companies have to take their stock policies and approach much further regarding both granularity and cycle times of their inventory.
The quickest path to inventory optimisation is to use many more attributes associated with each of your products to in effect create a much larger number of item classes to which different policies are assigned – well beyond the standard three or four levels most companies still use. These attributes can include lead times, supply and demand variability, consumption patterns, criticality, velocity, and several others. The more dimensions a company uses, the greater the precision a company will have in managing inventories and closers they are to inventory optimisation. Of course with Intuendi you can go as simple or as complex as you want or need to, right down to inventory optimisation not by a class or group but inventory optimisation by SKU.
The type of inventory optimisation obviously requires a lot more work or inventory optimisation software like Intuendi, both in terms of upfront analysis and tweaking of the policy settings over time. Inventory optimisation like this can pay rich dividends in terms of both reducing inventories for the SKUs for which excessive safety stocks are held, and in some cases actually increasing safety stock levels for SKUs that are regularly experiencing out-of-stock conditions and comes out of the box with Intuendi Inventory Optimisation software.
Intuendi Inventory Optimisation software can achieve this because of data and our advanced programme with machine learning identifying the appropriate attributes to use for the groupings, and in understanding how to best apply differentiated inventory policies.