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Influencing factors on the optimal internal service level (ISL)

Service Parts are distributed via global networks


Within my master thesis at the university of Stuttgart I've analyzed the advantages and results of a multi-stage inventory optimizer for service parts. Suppliers deliver to a central warehouse (e.g. Walldorf), from there the service parts are transferred via regional warehouses (e.g. Pittsburgh) to the customer facing warehouses (e.g. Illinois, Virtual Pittsburgh, Berlin, Virtual Walldorf).

Inventory allocation is determined by internal service level (ISL)


A multi-stage inventory optimizer considers the interdependency between the warehouses. Keeping only a low safety stock at the central warehouse can be optimal if the customer facing warehouses buffer against supply uncertainty with additional backlog safety stock. At the end the defined target service levels (TSL) towards the external customer have to be reached.

The service level at internal warehouses is called internal service level (ISL). With the SAP solution “Enterprise Inventory & Service Level Optimization” (EIS) the optimal ISL is calculated for each service part and internal warehouse location. The diagram shows for a sample product in a 2-level distribution network how the safety stock allocation for the central warehouse and the customer facing warehouses varies with changing internal service levels. The minimal inventory costs are reached if an ISL of 69,1% is applied.

Potential influencing factors on ISL are evaluated


With the help of a theoretical as well as a practical example different factors have been analyzed in the master thesis regarding their influence on the optimal ISL. For the theoretical example a fast moving service part within a 2-level distribution network has been chosen.  Only one of the potential influencing factors is changed at the same time. Following factors have been evaluated:

  • Inventory holding cost factor
  • Target service level
  • Order quantity
  • Service time
  • 2-level versus 3-level distribution network
  • Lead time
  • Demand uncertainty
  • Supply uncertainty


In the theoretical example all factors have indeed shown an influence on the optimal ISL. The diagram below illustrates for the theoretical example in which direction an influencing factor has to be changed to get an increasing alpha-ISL.

For the practical example I used the data of 200 real service parts provided by an SAP customer in the manufacturing industry. Some factors like inventory holding cost and EOQ have shown a dominating influence: With similar inventory holding costs at all warehouse locations no safety stock at all is stored at the central warehouse. Instead all safety stock is held at the customer facing warehouses. This kind of allocation is known as speculation strategy. Only if the inventory holding cost factor is reduced at the central warehouse, the alpha-ISL becomes greater than 50% for some service parts, i.e. safety stock is held at the central warehouse. In case the EOQ is additionally reduced, the optimal ISL is above 50% for all service parts. Now a combination of the strategies speculation and postponement is optimal.


Finding the optimal mix of speculation and postponement


The multi-stage inventory optimizer can suggest a totally different safety stock allocation compared to the allocations companies apply today. Many companies still have to define a service level in their IT systems not only for the customer facing warehouses but also for the internal warehouses. The system then calculates the safety stock for each location separately without considering the interdependency. This approach is not optimal and can lead to bad delivery performance and inefficient stock allocation. The use of a multi-stage inventory optimizer minimizes inventory stockholding costs by calculating optimal internal service levels. Based on the ISLs sufficient safety stock (including backlog safety stock) is determined for each warehouse. The benefit for the company is that the target service levels are actually reached at minimal inventory cost.

If you have any questions or suggestions please let me know.

Kind regards,

Christian Reuter

SAP Services

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