Optimize SAP IBP Calculations with Analyze Data Volume Tool

SAP IBP Analyze Data Volume In Calculations

1. What is Analyze Data Volume in Calculations ?

SAP Integrated Business Planning (IBP) offers a powerful solution for managing advanced supply chain processes. The “Analyze Data Volume in Calculations” application allows you to analyze the data volumes used in specific calculations within SAP IBP. When a calculation runs, it is crucial to understand which data sets are used, how much data is processed, and how this data volume impacts performance. “Analyze Data Volume” makes such information visible, helping you identify optimization opportunities.

This application is specifically used to reduce calculation complexity and processing time. If the amount of data processed in a calculation is too large, it can significantly prolong the calculation time and even strain system resources. The relevant application is designed to analyze this situation.

2. How to Use Analyze Data Volume in Calculations ?

This feature analyzes the data volume of the algorithms or calculations you create in SAP IBP. For example, you can use it to understand the size of the data sets used in a specific supply chain plan or sales forecast. In this way, you can see which calculations are pulling large amounts of data and whether these calculations can be optimized.

First, navigate to the “Analyze Data Volume in Calculations” application. On the screen that opens, click the Create button.

After clicking the Create button, select the planning area, the template where the data calculation will be performed, and the user for whom the report will be created. Then, click the Create button again.

Once the report that the system is requested to generate is completed, its status will be marked as Success, and then the evaluation of the report can begin.

3. Evaluation of the Analyze Data Volume in Calculations Report

In the screenshot, a data volume report generated in the SAP IBP Analyze Data Volume in Calculations application is displayed. The headings and columns included in this report are as follows:

3.1-Group by Key Figures at Request Level:

It determines the level at which you group the report. In this example, grouping has been done at the **Key Figures** level. The report displays key figures at a specific demand level.

3.2-Calculation :

This column specifies the level at which a particular key figure is calculated. For example, entries like **PRODPLANNED@REQUEST** or **STOCKINIT@DAYPRODLOC** are shown. This helps you understand the level at which the calculation is performed and where it takes place.

3.3-Type:

It shows the type of the Key Figure being calculated.

3.4-Data Records :

This field shows us the number of data records processed in the given calculation step. This is an estimated value, meaning that the database may optimize the execution as the query is processed, which can result in different data records for various calculation steps.

It indicates the number of data records used for a specific calculation. For example, 1,202,167 records were used for PRODPLANNED@REQUEST.

3.5-Time Series Records (Total):

**Time Series Records** shows the total number of records processed. In the screenshot, the total of all records is 1,202,384. This is useful for understanding the size of the time series data used.

3.6-Filtering Blocked :

Some modeling techniques prevent stored key figure filtering by using filters on certain attributes. A filter is necessary for these calculations to provide accurate results. For example, filtering of time attributes is not allowed in calculations between periods, as the calculation uses values from multiple time periods.

3.7-Calculation Node Shared :

**”Yes”** indicates that this calculation is used in other processes or can be shared. This is important for understanding whether multiple calculations are working on the same data set.

3.8-Detailed Run Time Results:

This section includes the runtime for all combinations, the number of records in the output data set, and the execution time of the process.

Conclusion:

The “Analyze Data Volume in Calculations” tool in SAP IBP is a critical solution for enhancing the efficiency of calculation processes in supply chains. This tool analyzes the data volume of calculations, identifying which data sets put a strain on performance and offering opportunities to optimize them. As a result, businesses can address bottlenecks in calculation processes and use system resources more efficiently. Organizations that leverage the “Analyze Data Volume in Calculations” tool for performance improvements can achieve sustainable increases in efficiency in their operational processes.

Yazar : Korhan UYANIK
SAP IBP Team Lead & Certified Consultant