Inventory Planning and Optimization with SAP Advanced Safety Stock Planning and SAP SmartOps

  • by Rajesh Ray, Senior Managing Consultant and SCM Product Lead, IBM Global Business Services
  • September 3, 2014
Read two case studies to learn how to implement SAP APO Advanced Safety Stock Planning (ASSP) and SAP SmartOps Enterprise Inventory Optimization (EIO).
Learning Objectives

By reading this article, you will learn how to:

  • Implement SAP APO Advanced Safety Stock Planning and SAP SmartOps Enterprise Inventory Optimization
  • Compare SAP’s two inventory planning solutions (SAP Advanced Planning and Optimization [APO] Advanced Safety Stock Planning [ASSP] and SmartOps Enterprise Inventory Optimization)
Key Concept
SAP SmartOps Enterprise Inventory Optimization (EIO) provides a comprehensive, enterprise-wide process for optimizing, managing, and monitoring inventory stocking levels for finished product and raw material components across the supply chain. 

Keeping an optimal level of inventory of its products in the supply chain can make or break any manufacturing or logistics company. Anything less than an optimal level can result in stock-outs and subsequent loss of sales, whereas any higher inventory eats away at a company’s profitability. SAP in the past had offered an inventory planning solution as part of its flagship SAP ERP Central Component (ECC) and Advanced Planning and Optimization (APO) solutions. Recently SAP acquired SmartOps, which enabled it to offer a more advanced inventory planning and optimization capability, Advanced Safety Stock Planning (ASSP).

ASSP helps calculate safety stock amounts for all raw materials, intermediate products, and finished products at their respective locations by considering demand uncertainty, supply uncertainty, service level, and the type of service level chosen.

Demand uncertainty refers to errors in forecasting customer demand (i.e., overestimating or underestimating customer demand). The safety stock calculation takes into account the forecast from SAP Demand Planning and the demand variability derived from the historical forecasts and realized demand. To calculate forecast accuracy of its own, the system takes values from two time series key figures in the planning area: planned demand quantity and realized demand quantity (i.e., actual sales). Time series key figures are APO key figures that store values in an InfoCube.

Supply uncertainty arises from disruptions in production (i.e., overestimating or underestimating production output quantity) or fluctuations in procurement lead time (i.e., actual lead time is higher or lower than standard). The lead time for a product at a location is the lead time for the replenishment from an upstream safety stock location.  The system calculates historical performance of lead time variability from two key figures in the planning area: planned procurement lead time and realized lead time (i.e., actual lead time).

 

The safety stock calculation also depends on a service level requirement for the item (i.e., the higher the service level, the more stock that must be maintained to avoid stock-outs). Safety stock calculation also depends on the type of service level chosen. There are two types of service levels to choose: alpha service level and beta service level. The alpha service level is event driven and is calculated as the number of time buckets with complete delivery divided by the total number of buckets. The beta service level is quantity driven and calculated as demands delivered on time divided by total demand. The alpha service level is much more stringent because at this level partial fulfillment is unacceptable and is considered a service failure. Therefore, if the alpha service level is chosen, it may call for a higher safety stock requirement.

This article has four sections:

  • An APO ASSP implementation case study
  • A SmartOps Enterprise Inventory Optimization (EIO) implementation case study
  • An overview of ECC dynamic stock planning
  • Similarities and differences between SAP inventory planning applications

Rajesh Ray

Rajesh Ray currently leads the SAP SCM product area at IBM Global Business Services. He has worked with SAP SE and SAP India prior to joining IBM. He is the author of two books on ERP and retail supply chain published by McGraw-Hill, and has contributed more than 52 articles in 16 international journals. Rajesh is a frequent speaker at different SCM forums and is an honorary member of the CII Logistics Council, APICS India chapter and the SCOR Society. 

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