SAP Planning Function Performance Calculator

Analyze the efficiency of a calculated key figure used in a planning function to inform your SAP data archiving strategy.

Performance Index Calculator

Planning Function Performance Index (PFPI)

—

---

Total Processing Load

—

(Record-Seconds)

Data Throughput

—

(KB/s)

Records per KB

—

(Ratio)

About the Calculated Key Figure for Planning Functions

What is a calculated key figure used in planning function site archive.sap.com?

In SAP Business Warehouse (BW), Integrated Planning (IP), and Business Planning and Consolidation (BPC), a calculated key figure used in a planning function is a dynamic metric computed to assess the performance and resource consumption of data manipulation processes. Unlike stored key figures, which are static values in a database, a calculated key figure is derived using a formula that often involves other key figures or system parameters. Its primary purpose in the context of data archiving is to provide a quantitative basis for decision-making. By analyzing these figures, administrators can identify which planning functions are most resource-intensive, process the most data, and are therefore prime candidates for data archiving to improve overall system performance and reduce storage costs.

The Planning Function Performance Index (PFPI) Formula

This calculator uses a model called the Planning Function Performance Index (PFPI) to represent a typical calculated key figure for performance analysis. The formula is:

PFPI = (TotalRecordsProcessed * AverageExecutionTimeInSeconds) / DataBlockSizeInKB

This formula generates a unitless index where a higher value signifies a more resource-intensive process. It balances the sheer volume of data (records), the processing time required, and the memory footprint (data block size) to provide a holistic performance score.

Formula Variables

Variable	Meaning	Unit	Typical Range
Total Records Processed	The number of individual data records handled by the function.	Count (unitless)	10,000 – 50,000,000+
Average Execution Time	The time taken for the function to complete its task.	Seconds (s)	5 – 1,800
Data Block Size	The chunk size of data processed in memory.	Kilobytes (KB)	512 – 65,536

Practical Examples

Example 1: High-Volume Sales Planning

• Inputs:
  • Total Records Processed: 20,000,000
  • Average Execution Time: 300 seconds
  • Data Block Size: 4096 KB
• Result: This scenario yields a very high PFPI, indicating a heavy-duty planning function. The high record count and significant execution time suggest that the data it processes is a strong candidate for an aggressive BPC archiving strategy to maintain system health.

Example 2: Low-Volume Master Data Update

• Inputs:
  • Total Records Processed: 50,000
  • Average Execution Time: 15 seconds
  • Data Block Size: 1024 KB
• Result: This scenario results in a very low PFPI. The function is lightweight and fast. The data it processes is likely operational and not a priority for archiving. Focusing optimization efforts elsewhere, such as on SAP BW performance tuning for larger processes, would be more effective.

How to Use This Calculator

1. Enter Total Records: Input the total number of records the planning function typically processes in a single run.
2. Set Execution Time: Enter the average time the function takes to run and select the correct unit (seconds or milliseconds).
3. Define Data Block Size: Input the memory block size used for processing and select the unit (KB or MB).
4. Calculate: Click the “Calculate Performance Index” button to see the PFPI and other derived metrics.
5. Analyze Results: Use the PFPI to compare different planning functions. A higher PFPI indicates a greater need for performance review and potential data archiving. The chart helps visualize which input factor contributes most to the workload.

Key Factors That Affect Planning Function Performance

• Data Volume: The most direct factor. More records mean more work.
• Complexity of Calculation: Complex formulas, especially those using nested logic or ABAP routines, increase CPU load and execution time. A tool like an ABAP Optimization Analyzer can help identify inefficiencies.
• Data Sparsity: If the data is sparse (many empty cells), the system may still need to process empty blocks, leading to inefficient I/O.
• Hardware Resources: CPU speed, available RAM, and I/O speed of the underlying disk subsystem are critical. Insufficient resources will bottleneck any function.
• Database Indexing: Proper indexing on the underlying InfoProvider (e.g., aDSO) is crucial for fast data retrieval.
• Aggregation Levels: Running a function on a highly aggregated level is much faster than running it on the lowest granular level.
• Locking and Concurrency: High user concurrency can lead to lock waits, significantly slowing down planning sequences.
• Code Efficiency: For custom functions (like FOX or AMDP), inefficient code can be a major performance killer. Proper SAP performance best practices should be followed.

Frequently Asked Questions (FAQ)

1. What is a “good” or “bad” PFPI score?

The PFPI is relative. There is no universal “good” score. Its value comes from comparing multiple planning functions within your own system. A function with a PFPI of 1,000,000 is a higher priority for archiving than one with a score of 500.

2. Why are units important in this calculation?

Units ensure the calculation is consistent. Mixing up seconds and milliseconds, or KB and MB, would produce a meaningless result. This calculator standardizes inputs to ensure accuracy.

3. Does this calculator apply to both SAP BW and BPC?

Yes, the concept is generic. Both BW Integrated Planning and BPC use planning functions that operate on data sets. The principles of measuring performance based on data volume, time, and memory are applicable to both.

4. Can I use this for real-time InfoCubes?

Yes, the logic applies. However, performance on real-time InfoProviders has unique considerations, such as frequent compression needs to maintain query performance.

5. How does data archiving actually improve performance?

Archiving moves historical, less-frequently-accessed data from the primary high-performance database to a cheaper, near-line storage solution. This reduces the size of the main database, allowing planning functions and user queries to run faster because they have less data to scan.

6. What is the difference between archiving and deleting?

Archiving is a structured process where data is moved to a separate, accessible storage location before being deleted from the source system. Deletion is permanent removal. Archived data can still be queried for reporting, albeit with slightly slower performance.

7. Does running this calculation impact my SAP system?

No. This is an offline tool. You must gather the input metrics (records, time, block size) from your SAP system’s monitoring tools (like ST03, BW Cockpit, or HANA Studio) and enter them here for analysis.

8. My planning function uses FOX code. Is that handled?

The performance of a FOX formula is reflected in the “Average Execution Time.” A poorly written FOX script will increase this time, which in turn increases the final PFPI score, correctly identifying it as a performance-intensive function.

Related Tools and Internal Resources

Explore these resources for more advanced analysis and strategy development:

• SAP Data Volume Estimator: Predict future database growth based on current trends.
• Guide to BPC Archiving Strategy: A comprehensive look at creating a long-term plan for SAP BPC data management.
• SAP BW Performance Tuning Dashboard: An interactive tool to diagnose common BW performance issues.
• SAP Performance Best Practices: A guide covering key principles for optimizing SAP applications.
• ABAP Optimization Analyzer: Check your custom ABAP code for performance bottlenecks.
• Understanding HANA In-Memory Execution: Learn how PAK and AMDP can dramatically improve planning function speed.