In 2012 SAP announced the so called declustering for time management and payroll data. In March 2014 the last country versions are planned to be delivered and then declustering is available to all SAP HCM Payroll customers world-wide.
Recently I had many conversations with customers in the context of HCM on HANA and Payroll on HANA about the benefits of ‘declustering’. In this post I will try to explain what declustering is and how customers benefit.
What is a cluster?
Let me start with explaining what clustering is before talking about what declustering is. In SAP HCM modules for Payroll and Time Management employee data is stored within database tables known as cluster tables. These cluster tables (PCL1 and PCL2) store data in compressed binary (RAW format) strings. This type of data storage does not allow to access the data directly from the database layer for analytical and reporting purposes. And this is where the pain is for many customers: Running queries on large data sets of thousands of employees, with long history (and maybe even retro calculations) has not been very performing in the past. That changes now.
How does declustering work?
To use the data stored in the cluster tables, data needs to be converted from the nontransparent storage into simple transparent database table storage. This can be performed by declustering, which involves creation of new simple transparent table for each internal table in cluster table and copying the data from the cluster table to the transparent table. These tables are associated with each other through a common primary key for data retrieval or reporting purposes.
To enable declustering the HCM Declustering Tools business function must be activated. To learn more about the SAP delivered tools for declustering check this: link
How can the power be unleashed?
There are 2 ways to switch the declustering on: Generic and Customized declustering.
- Generic Declustering: The declustering mechanism creates new transparent tables for each internal table of the payroll result. This feature allows synchronous updating of new transparent tables during the payroll run. Data archiving and data destruction for new transparent tables are also supported.
- Customized Declustering: Select the payroll results to be declustered based on specific selection criteria. This will adjust the result tables to be declustered when certain data is not needed in the transparent tables. Country-specific lists of transparent tables/structures to be declustered are delivered as standard.
What are the advantages?
There are great advantages that come with declustering. To name a few:
- Process or retrieve bulk data using simple SQL queries
- Perform aggregations on the data directly at the database layer
- Improve performance of the standard reports
- Build highly efficient customized reports
- Merge Payroll data with other HCM data (e.g. PA/OM data, talent data)
How do customers benefit?
To explain a bit of customer benefit around these advantages I want to share what I recently encountered. Recently I talked to a customer with 3,5billion entries in their payroll results table (RT). This customer had 75k employees and 10 years of payroll history (including retro calculation). By declustering the total size of the payroll cluster was reduced from 1Terabyte (on their traditional database) to 600GB on SAP HANA. This means that the total size of the result table was compressed to 60% of it’s former size due to the compression that comes with SAP HANA. This alone makes the processing of data much faster. Add to this the immense reading power of SAP HANA and customers can build very powerful reports. Really unlike anything I had seen before.
On a side note: for now we need both the cluster and the tables in SAP HANA because we still store the initial payroll results in the cluster. However, the cluster does not need to be in the ‘hot-memory’ anymore. This can now also be on disks (which usually is less expensive).
Regarding the improvement of reporting on payroll results I talked to many customers with this requirement. Until now reporting was done either via the Wage Type Reporter or by loading data into SAP NetWeaver BW. This means that either the reporting was slow or it was on older data. With declustering that changes. Directly after the payroll has run the declustering is kicked off (this means real-time data). To utilize that data Virtual Data Models need to be created in the SAP HANA Modeler. One of the biggest benefits is that payroll data can now be merged with other HCM data, like PA/OM and talent management data. This makes this development crucial for value adding HR reporting and analytics. If customers want high speed ad-hoc reporting they can take advantage of the SAP Analysis tools that run directly on these Virtual Data Models. This means slicing and dicing through decades of historical payroll data in a split second. Customers only need to plug-in their BI tool. It’s that simple.
Recently I talked to a customer who had created a report with an aggregation of certain wage types per company code, personnel area and some other dimensions. The report also tracked retro-calculation. This took around 35 minutes as a Wage Type Reporter report and now due to the declustered data and SAP HANA ran in 10 seconds in their BI report. This shows that reading and processing data in SAP HANA makes a huge difference.
In conclusion, with declustering and SAP HANA payroll and time management information is now available real-time and in seconds. This allows HR departments to spend more time on analyzing the data rather than shaping and modelling it.
This means for example that a gross to net reports can now look like this, and can be instantly available after the payroll ran:
Users can immediately zoom in to different time dimensions or any other kind of dimensions. Data exploration really becomes much easier.
An analysis on social security wage spending per payroll area can now look like this:
This allows visualizing trends and correlations in data that so far seemed impossible toanalyze. Payroll administrators can now use ad-hoc reporting tools to provide immediate reasoning behind the numbers to their management. This can be done simpler and quicker based on declustered data and with appealing and easy to use BI tooling on top.
As one customer told me “Answers can now be provided to all those questions that were not asked anymore because it was such a pain to answer them”.
How can customers start the journey?
Declustering allows storing data in transparent tables with columnar storage only on the SAP HANA system from the clustered tables. This provides two scenarios to customers that want to make use of declustering:
- Side-by-Side: This is where a Business Suite system running on any database is connected with a separate SAP HANA box.
A precondition is that those transparent tables on the SAP HANA system are created based on the transparent tables in the Business Suite system by mechanism such as SAP Landscape Transformation (SLT).
- Suite on HANA: Declustering allows to store data in the transparent tables on the Business Suite system directly from the clustered tables.
Thus, declustering allows managing and supporting both the SAP HANA scenario as well as the Business Suite scenario running on any database connected with a separate SAP HANA box.
One word of advice: use this to speed up your analytics and (ad-hoc) reporting, and not to build reconciliation reports because there is cool functionality coming your way in 2014!
If you need more information or if you want to share your experiences please feel free to contact me!