Inventory Optimization is not a Project…
..… it’s a process!
Projects have a beginning and an end, Inventory Optimization does not. When I talk about effective materials planning (in case you attend the ASUG Fall Focus in Philadelphia this year, I will speak on that subject on Friday, September 27), I point out four parts:
1. Portfolio Management and ‘house cleaning’ of basic data and supply elements
2. Policy setting after Segmentation and Classification of your materials portfolio
3. Exception Monitoring
4. Inventory Optimization
The last part – Inventory Optimization – is the ongoing effort to provide maximum availability with minimum stock holdings for any given demand situation. And since the demand situation changes all the time, the policies that were driving that balance when you went live with the SAP system back in the days, may not hold water anymore.
What’s keeping your inventories optimized is the adjustment of basic data – lot size procedures, safety stock settings, forecast parameters, lead times and more – to the situation the individual item is under. Do we have consistent consumption and are able to forecast the demand? Does the item contribute a lot of value to our business or not? Does it have a short lead time? These and other questions will have to be answered before you can set the optimal parameters that drive automation and inventory optimization.
But if you answer the questions only once and don’t adjust the parameters as the answers to these questions change over time, your parameters will not support that automation or optimized inventory levels any more. The MRP run will generate supply proposals which do not conform to the paradigm of good service with minimum stock.
What usually happens during an SAP implementation is that because of the limitations in budget and time to Go-Live, only the most basic parameters are being set so that you can start using SAP. Typically this is MRP type PD (maybe a manual reorder level procedure VB), lot size procedures EX and a few periodic ones like WB and a static safety stock that’s guesswork. The planned delivery time is a big unknown and will be set generously, so that you will usually receive the item way ahead of its requirements date.
Then, after you have been using SAP for your materials planning for a while, the ‘Inventory Optimizers’ come in and sell you a 6 months project to get your basic data straight. This is a noble effort and yes, your planners need to understand all the parameters and how to set policy. But if you go through the tedious task to analyze and set up each individual part, your MRP Controllers will learn a great deal about all the fields in the material master record, but they will also divorce their spouses and move into the office.
And once all the materials are finally set up with the right policy, the situation changes – what was consistent consumption is no more, the material is procured from a different supplier and therefore a different replenishment lea time, the item becomes a slow mover because it’s replaced by another part etc. – you will have to start from the beginning. By that time the Inventory Optimizers are long gone. But don’t worry… they will come back in two years and sell you a new project.
So what should you do? Implement Effective Materials Planning with portfolio management, automated policy setting on a periodic basis, continuous exception monitoring within the framework of the Exception Minded Business and Inventory Optimization will be the byproduct of an automated process that will become second nature to your MRP Controller.
Automation is key here, and so is ‘managing by exception’. If you have to look at each item every day and set up each item manually, you will not be able to keep control over your inventory and service levels.
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Good summary of a typical SAP implementation. Although now, Inventory Optimizers are part of SAP with the acquisition of SmartOps in 2013. but this should help because the data necessary to run an inventory optimizer is maintained as part of routine, as you say, automated business practices. This will allow you to manage by exception and adjust your data as the business evolves over time.