Wednesday, 16 September 2009

Advanced Inventory Optimization with SNP

The optimum inventory balance would be managed via combination of the following key factors and elements driving the level of inventory and supply chain costs:
- buffer stock (safety stock) needed within the market to avoid potential Stock-Out caused by adverse effects of forecast errors and supply chain underperformance
- stock availability or customer service performance required to ensure customer satisfaction with their order fulfillment
- DRP planning parameters driven by manufacturing or 3rd party suppliers costs associated with the inventory (inventory value, storage costs, shipping costs, financial interest of holding inventory etc)
Safety stock is a function of all these factors. To make things more complex, all these factors are interrelated.
At the item level, there are some immediate obvious sources of error and uncertainty:

► Forecast error – the worse it is, the more safety stock you need to cover the uncertainty.
► Production batch size – the larger it is, the less often the stock will be low.
► Production reaction time – the longer this is, the greater the time over which the uncertainty has to be managed.
► Customer service level – the higher this is, the greater the safety stock needs to be.
The APO SNP provides a number of techniques to optimize inventory.
The current offering consists of:

     ► Standard Safety Stock Planning
     ► Extended Safety Stock Profile

Should the above not be suitable, the custom approach can be adopted using advance marco functionality available within the SNP Planning Book.
A particular example wrt to inventory optimization is where SNP planning book was enhanced to manage a complex safety stock formula based on Robert G.Brown instead of using what is available in standard SNP.
The above formula shows safety stock is calculated based on:

Safety stock formula:
LT = Supply Chain Lead time (Total = Production + Transit , and expressed in months)
SR = Std. Deviation over production reaction time
BS = Batch size (Expressed in units as Production Minimum Order Quantity)
CS = Customer Service Level (shown as percentage)

Weighted forecast error calculation

F1 to Fn = Forecasts for weeks 1 to n (13 periods will do), for selected forecast types. The current average forecast over the next three months is.

 AF = Average Monthly Forecast = (Sum (F1 to F13)) / 3

An ‘average’ forecast error determined by SKU.

 WE = Weighted error

The previous 2 years Forecast accuracy percentages by SKU will be exported as 24 discrete monthly values.

The optimal inventory calculations require a single value of forecast error per SKU. The forecast error is defined as follows:

Forecast Error = 100 – Forecast accuracy Percentage.

That is an accuracy of 85% equates to a forecast error of 15%.

The functionality provided allows the error to be calculated on the last six months accuracy figures. The weighting is configurable. A higher weight is likely to be given to the more recent forecast error.


The possible approach would be to use would be:

1. Copy standard SNP supplied Planning Books into Custom Planning Book

2. Add the required custom key fields, custom fields depends on how the macro calculation are carried. If standard macro functions are used then more custom key figures will be used. In the SNP planning, limit the additional field to Safety Stock only and use macro to calculate desired stock levels, other key figures like service level and forecast accuracy can be included for reporting purposes and for macro function to facilitate user mgt. Also handy for alerts. These key figures will be loaded from custom DP planning book which contains the guts of Safety Stock Calculation using Process Chain.

3. Create DP planning book with custom fields (key figures) to contain the fundamental fields needed for SS calculation. The number of Key Figures will depend on using SAP supplied macro’s functions or reducing Key Figures using custom built macro function (see The advantage of creating custom DP planning book is that it provides maximum flexibility and does not have the SNP constraints and simplifies the import from BW to the relevant key figures. Note it is possible to load data from DP planning book to custom SNP using the Process Chain mechanism to Load data from DP Planning Book to SNP planning on a regular basis. This custom planning book will import from DP planning books data such as forecast accuracy.

Concluding remarks: If implementing SNP with release SCM5.1 onwards, then priority would be to exploit the standard functionalities for advanced safety stock (ASS) planning. The ASS allows for the creation of profiles containing rules such as:

• Forecast Error : Percentage to correct demand forecast

• Determination of Replenishment Lead time rules

• Demand type, sporadic or regular demand

• Source determination

• BADI’s (very important to enhance logic) BADI for custom formula’s, replenishment lead time and forecast error.


Shaun Snapp said...


I have written on this extensively and I don't believe that dynamic safety stock meets the technical definition of inventory optimization. To me inventory optimization is the determination of overall stocking level based upon service level. Dynamic safety stock is really just that. I have an article on this at my inventory optimization multi echelon blog. It compares SNP to actual MEIO applications. I think you will find this article of interest.

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