SAP Commissions
SAP HANA
Testing strategy

After the acquisition of Calliduscloud.com by SAP in 2018 it’s only natural that the flagship Incentive Compensation Management product, dubbed now SAP Commissions, is getting a full architecture rewrite to core SAP technologies (and will be called SuccessFactors Incentive Management, or SFIM for short).

The previous architecture, based on Oracle, won’t be supported beyond 2026 and the customers face a choice of either upgrading to HANA on Google Hyperscalers or moving to a different ICM/SPM platform vendor.

One of the common mistakes when selecting the target platform and an implementation vendor is an assumption that “they will do the job”.

In the end it’s only natural that after migration (regardless if the target platform will be SuccessFactors Incentive Management or a new platform like CaptivateIQ, Anaplan or Varicent) the new system will produce exactly the same results as the old one.

But how to prove it? 

Critical for success – the testing strategy

Testing strategy heavily depends on the approach taken for historical data migration.

There are a few strategies here, ranging from not migrating any history at all, through migration of aggregated payout results, through full system migration along with data to recalc historical results.

All these approaches have pros and cons and should be carefully considered, but they have tremendous impact on the testing strategy.

A common testing approach is to take a period or two of historical data, run both the old and the new system, and expect the same results.

There are however quite a few things that need to be taken into account: Compensation rules might have changed, the current data looks differently in the past etc. If history is not migrated (and even if – how?) this kind of testing may be even impossible to execute. 

Another (very important!) consideration should be data loading testing.

How many files should be loaded and compared between platforms?

Only recent ones or also historical?

A full year worth of data?

All these considerations should be discussed with your implementation partner.

A few practical hints from Sands Partners:

  • Do insist on the testing strategy defined in migration SOW in great detail. This should include description of tests, their scenarios and breadth in terms of number of periods.
  • Parallel runs are critical to prove that both systems produce the same results from live data. Do consider that this may incur dual license cost for the duration of tests.
  • Infinite quality requires infinite budget. Do think about number of tests to execute.
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