This post is the latest post in our new blog series: How We Solve Problems. Each blog post focuses on a real-world client experience where Revelwood was presented with a unique or thorny problem. We’ll explain our approach to how we solved it.
Revelwood Client: An accounts receivable provider that offers collection and contact center services.
Planning Environment: IBM Planning Analytics
Problem: This client had a very large model that led to slow-performing scripts and reports. Revelwood 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.
How We Helped: Revelwood 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.
Do you have a challenge with your Planning Analytics environment? Let us tackle the problem!
