Business Services
| Function: | Products: |
| Budgeting | IBM Planning Analytics |
Challenge
An accounts receivable provider that offers collection and contact center services had a very large model that led to slow-performing scripts and reports.
Solution
We analyzed their model and determined that much of the data was associated with historical information that was no longer needed. This included multiple versions of plans dating back to 2015.
Results
We worked with our client to determine an asymmetrical approach to removing data (example: keep three years of budget data, one year of forecast data and remove all historical reforecast data) and reordering the dimensions in the model. These changes reduced the four largest cubes from 56% to 70% and removed more than 8.5GB of memory. This optimization led to faster reports calculated in seconds instead of minutes.