SAP Standard Application Benchmarks
Retired Benchmarks
Demand Planning (DP)
The Demand Planning Benchmark is one of three benchmarks in the SAP APO Benchmark suite. Demand planning enables supply chain partners to forecast and plan demand in consideration of historical demand data, causal factors, marketing events, market intelligence, and sales objectives. Results from the planning process can be automatically fed to other nodes of the supply chain.
Production Planning and Detailed Scheduling (PP/DS)
The Production Planning and Detailed Scheduling (PP/DS) Benchmark is one of three benchmarks in the SAP APO Benchmark suite. The component Production Planning and Detailed Scheduling (PP/DS) enables companies to plan and optimize multi-site production, while simultaneously taking into account product and capacity availability.
Supply Network Planning (SNP)
SAP APO enables organizations to create a very close match between supply and demand by integrating purchasing, manufacturing, distribution, and transportation into one consistent model. By modeling the entire supply network and related constraints, SAP APO is able to synchronize activities and plan material flow throughout the entire supply chain. The results are feasible plans for purchasing, manufacturing, inventory, and transportation.
SAP APO also includes functionality to enable organizations to dynamically determine how and when inventory should be distributed. The system draws on the data universally available in liveCache to optimize deployment plans based on available algorithms, as well as user rules and policies. In the benchmark, we use mass processing, which allows you to run the heuristic planning for large numbers of product-location combinations, with mass processing jobs running concurrently in the background.
E-Selling
The benchmarks focus on typical online catalog activities as performed by regular Internet catalog users (B2C) and direct order input by professional users (B2B).
User Interaction Steps of the Business-to-Consumer (B2C) Benchmark Scenario With a focus on consumer behavior, this scenario is characterized by high browsing activity and low shopping/ordering activity, as reflected by recurrent browsing in a catalog. Out of ten users, nine users execute browsing activities, while shopping (for example, adding items to the shopping basket and ordering) is executed by one user, resulting in a ratio of browsing to shopping/ordering of 9:1. In one sequence, the system thus creates one shopping cart and one order with five line items.
Interaction Center
The SAP CRM Interaction Center Benchmark focuses on typical interaction center activities, using the functions designed for the IC WebClient.
Assemble to Order
The Assemble-to-Order (ATO) Benchmark integrates process chains across SAP Business Suite components.
The ATO scenario is characterized by high volume sales, short production times (from hours to one day), and individual assembly for such products as PCs, pumps, and cars. In general, each benchmark user has its own master data, such as material, vendor, or customer master data to avoid data locking situations. However, the ATO Benchmark has been designed to handle and overcome data locking situations – the ATO benchmark users access common master data, such as material, vendor, or customer master data.
Cross Application Time Sheet (CATS)
The Cross Application Time Sheet (CATS) can be used by employees or personal administrators to track employee working times. Time data is recorded with information referring to orders and cost centers, for example, and can be transferred to corresponding applications and components of the SAP Business Suite.
Financial Accounting (FI)
In this scenario, four financial documents with three line items are posted, with the line items in the fourth posting displayed. Following that, 44 open items of one debtor, including the previously posted documents, are displayed, and four are balanced. At the end of each run there are exactly 40 open items for each debtor, which serve as the basis for a new run.
Human Resources - Payroll (HR)
In contrast to online benchmarks, the Human Resources - Payroll (HR) Benchmark is a report with variants that is run as a batch job on the basis of events. The report, called RPCALCD0, exercises the German payroll program.
Material Management (MM)
The Materials Management (MM) Benchmark takes you through a series of steps to create a purchase requisition for five materials (transaction ME51N), a purchase order for the five materials (ME21N), a goods receipt (MIGO), and an invoice (MIRO) for the purchase order.
Production Planning (PP)
The Production Planning (PP) Benchmark consists of the following transactions:
Create a production order. (CO01)
Change the amount on the production order, release order for production, and print order. (CO02)
Create two completion confirmations for the production order (milestone confirmation with back flush and final confirmation). (CO11N)
Post goods receipt for the order. (MB31)Settle the production order. (CO02)
PLM - Project System (PS)
The Project System (PS) Benchmark consists of the following transactions:
Create a project using a project profile. (transaction CJ01)
Execute the cost planning for the project. (CJ40)
Approve the project. (CJ02)
Plan the budget necessary for the project. (CJ30)
Start a report on cost evaluations. (CJ62)
Sales & Distribution (SD) Benchmark
The SAP Sales & Distribution (SD) Benchmark retired in December 2025.
The Sales and Distribution (SD) Benchmark covered a sell-from-stock scenario, which includes the creation of a customer order with five line items and the corresponding delivery with subsequent goods movement and invoicing.
It consists of the following transactions:
Create an order with five line items. (VA01)
Create a delivery for this order. (VL01N)
Display the customer order. (VA03)
Change the delivery (VL02N) and post goods issue.
List 40 orders for one sold-to party. (VA05)
Create an invoice. (VF01)
Each benchmark user had his or her own master data, such as material, vendor, or customer master data to avoid data-locking situations.
SCM - Warehouse Management (WM)
In the Warehouse Management (WM) Benchmark, a transfer requirement (transaction LB01) is created to put three materials into stock. This transfer requirement is used to create a transfer order (LT04). Because the number of items per material in the transfer requirement exceeds the number that can be placed into one storage location, the transfer order has seven line items. The process continues to confirm this transfer order for seven items (LT12). For goods removal, these transactions are called again in the same sequence.
Transaction Banking (TRBK)
The Transaction Banking (TRBK) Benchmark is divided into two business scenarios.
The first scenario, day processing, reflects usage by users and integrated systems that generally occurs during the daytime.
The second scenario, night processing, reflects account balancing that generally occurs overnight in batch mode. This benchmark replaced the Bank Customer Accounts Benchmark.
SAP for Utilities (ISU)
The SAP for Utilities Benchmark as the predecessor of the Customer Care and Service (IS-U/CCS) Benchmark simulates typical processes of a deregulated utility company.
The benchmark contains the main batch process of a typical utility company in a deregulated market and an additional online simulation. The batch process starts with metering and covers billing, revenue collection (FI-CA) and data transmission to market partners.
Customer Care and Services (ISU/CCS)
The Customer Care and Service (ISU/CCS) Benchmark simulates typical processes in a utilities company.
The core business processes can be divided into two main processes: consumption and revenue collection. For the consumption process, three batch jobs are utilized for collecting information – meter-reading orders have to be created and printed, and the results have to be uploaded into the system. To collect revenues, additional batch jobs – billing the customer, invoicing, and printing the bill – produce load on the system.
Retail - POS Inbound
The POS Inbound Benchmark measures the throughput of the point-of-sale (POS) interface-inbound for aggregated sales data. This is a critical time process in a real business scenario. The data will be ported to materials management, sales and distribution, or financials and is the basis for replenishment.
Retail - Store Replenishment
The Store Replenishment Benchmark is more comprehensive than the POS Inbound Benchmark. It comprises a pre-step for point-of-sale (POS) upload that provides the sales data for the replenishment process.
Advanced Mixed Load (BW-AML)
The SAP BW Advance Mixed Load Benchmark (BW-AML Benchmark) is the successor of the popular BW-EML benchmark which was retired recently. The new BW-AML meets the most current demands of typical business warehouse customers.
Data-mart (BI-D)
The data mart scenario is one use of the Business Intelligence capabilities of SAP NetWeaver. The data mart contains a static snapshot of operational data. Multiple users run queries on this data in 10 InfoCubes which contain 2,500,000,000 records. The key figure is the number of query navigation steps/hour.
Mixed Load (BI-XML)
The mixed load scenario is one use of the Business Intelligence capabilities of SAP NetWeaver.
In this scenario, query activity and load/update activity are executed in parallel. Multiple users run queries on data in 10 SD InfoCubes. You can choose from the following size categories for the initial data load:
300 million records
1000 million records
3000 million records
In three phases during high load activity, static operational data is extended with delta data.
The key figure of this benchmark is the number of query navigation steps/hour.
The BI mixed load benchmark can be run with or without BI Accelerator.Employee Self-Service Portal (EP-ESS)
The Employee Self-Service Portal (EP-ESS) Benchmark is part of the SAP Standard Application Benchmark suite for SAP NetWeaver Portal.
The suite consists of two representative business cases that are highly visible in the market and allow for the testing of high numbers of concurrent users on the portal. Each scenario is a standard application benchmark in its own right and can be run separately.
People-Centric CRM Portal (EP-PCC)
The People-Centric CRM Portal (EP-PCC) Benchmark is part of the SAP Standard Application Benchmark suite for SAP NetWeaver Portal.
The suite consists of two representative business cases that are highly visible in the market and allow for the testing of high numbers of concurrent users on the portal. Each scenario is a standard application benchmark in its own right and can be run separately.
The People-Centric CRM (EP-PCC) Benchmark uses the Business Package for SAP CRM: Business Productivity Pack. This business package provides a number of iViews that display sales information from SAP Business Information Warehouse (SAP BW) and SAP Customer Relationship Management (SAP CRM) systems for employees in sales, marketing, and service who need to make the correct decision quickly and effectively at all times. This benchmark focuses on concurrent users in the sales representative role and their top-level navigation behavior in the portal. From a technical point of view, this benchmark tests the performance of the portal platform (running on the SAP NetWeaver Java stack), while launching business transactions, rendering the presentation output, and caching SAP BW business content. The SAP BW and SAP CRM back-end responses are simulated to avoid the influence of back-end load on the portal performance.
Enhanced Mixed Load (BW-EML)
The SAP BW Enhanced Mixed Load Benchmark (BW-EML Benchmark) meets the current demands of typical business warehouse customers. These demands are mainly coined by three major requirements:
Near real-time reporting
Getting instant results from analytical applications on last minute data nowadays is crucial for timely decision making. Typical examples for real-time data analysis include smart metering or trade promotion management.
Ad-hoc reporting capabilities
During the last few years, data volumes in data warehouses have dramatically grown. One reason for this growth is the increased complexity and detail level of the data, which in turn requires much more sophisticated and complex analysis methods. As a result, analytical applications are supposed to facilitate navigating through huge amounts of data by providing extensive slicing and dicing functionality. This makes it inherently difficult to foresee frequent navigation patterns and pre-calculate intermediate results to speed up reporting performance. Ad-hoc type query capabilities are required to satisfy these demands.
Reduction of TCO
Typical sizes of today's data warehouses comprise tens or hundreds of terabytes of data. It is therefore crucial to keep data redundancy at a low level, but still be able to maintain layered data models. SAP NetWeaver BW 7.30 helps reduce the total cost of ownership by allowing reports to run directly on DataStore objects which are the core building elements of a layered warehousing architecture, often eliminating the need to maintain data redundantly in multi-dimensional InfoCube data structures.
Like its predecessor the BW-MXL Benchmark, the EML Benchmark focuses on a mix of multi user reporting load and delta data that is loaded into the database simultaneously to the queries.