Closer Look: SAP HANA and CPM - In-Memory Technology Enables Faster Allocations, Better Analysis

Marco recently posted a blog on why Finance should care about SAP HANA. I’m going to expand a little bit more on the why SAP HANA is so much faster, especially as it processes large amounts of data, as is often the case with allocations.

Processing large amounts of data in traditional databases takes a lot of processing, both on disk and the application server.  Leveraging SAP HANA’s massive data processing  and real-time aggregation and transformation capabilities, it is possible to lighten this application server overload.

A good real-world example of this is the processing of a cost allocation. Let assume we want to allocate 20 Overhead Accounts for 5 different Divisions in 100 Entities using a driver with 1,000 products (see image below):

Cost allocation process


In a classic implementation we would calculate the 10 million rows in memory and then persist them in disk storage, potentially deleting (in the case of a recalculation) and rewriting  10 million rows. Many companies often then replicate the 10 million rows in a separate OLAP engine for analysis and reporting.


2014-04-15 saphana2


Using SAP HANA we are able to calculate the allocation at runtime, avoiding storing to disk the 10.000.000 rows, greatly increasing processing speed and reducing disk space. At the same time an analysis cube is automatically generated for analysis.


Cost allocation process


This is just one example of how CPM solutions benefit from running in-memory technology like SAP HANA. As companies take advantage of this technology we will start to see further uses, such as more detailed planning at an operational level and  predictive analytics.  I’m excited about the work we at Tagetik have done with SAP HANA, and am looking forward to implementing the next wave of CPM with our clients!   

What are your thoughts? How do you see in-memory technology helping your processes?


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