A rather surprising development in the aftermarket for Hyperion Planning. Here is an idea that we've kicked around a bit and will probably implement on a large scale.
The basic idea that helps me get my mind around advanced complexity in Essbase and Planning apps is that of Multi-Path. The concept is simple. The sum total of data that you may need to make a decision may have varying levels of volatility and accesibility. So diagram their data paths separately and manage their merging into one application using multple cubes and partitions between them.
We're always talking about 'disparate data sources' and ending our paragraphs with 'one version of the truth'. That's the case, but let's look at a baseball analogy with Essbase as the catcher. Most of the time, you're getting the ball at high speed from the pitcher. You have some control over that and your gear has you prepared for that all the time. Call that the main stream of data. But occasionally, the batter will popup behind the plate. That ball is a very important one to catch but it doesn't come very often. What do you do? As a catcher, you stand up, flip up you mask and move to the spot where you can catch it. Different timing, different expectations, different path. Sometimes the batter bunts. Then you've got to run up on the ball and barehand it and throw it to first or catch the advancing runner. That's another path.
Back in the real world, what we've done is integrate an Actuals Path with a Budget Path with a Forecast Path. The budget path goes through multiple iterations before it's stable. That's low volume user originated information. Forecast data uses some actuals data and does an automatic calculation based on variance to plan and then populates another scenario. This is automated from within Essbase. A second path. Actuals are read only and come through the ETL system. In this case we use an ASO cube which is marked read-only and we view it through a partition.
Using a separate cube viewed through a partition allows Planning to manage, in relatively small cubes, the Budget and Forecast data. We avoid long calcs during the overhead work of Planning refreshes.
It takes a little bit of thought and extra work to synchronize the models and manage the partition, but it does increase the scalability of Planning apps and vastly improves performance. Think about it. Just manage each of the data paths according to their requirements and deliver the proper results on time to your hybrid Planning app. Sweet.
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