When designing an EPM application like Oracle FCC (Financial Consolidation and Close), it’s tempting to try to fit all data into a single cube. We have several system dimensions like Movement and Data Source to play with along with the four Custom dimensions. But forcing data into places it doesn’t belong can lead to a tangled mess of interdimensional irrelevance, hurting both performance and usability.

What Is Interdimensional Irrelevance?

Interdimensional irrelevance occurs when dimensions intersect in ways that don’t make logical or business sense. This leads to sparse intersections, bloated cube sizes, and confusing user experiences. For example, trying to report on a statistical driver against a legal entity that doesn’t use it creates meaningless intersections that slow down processing and clutter reports.

Our Design Challenge

We faced a situation where certain data elements, while important, didn’t naturally fit into the FCC hierarchy. These were supplemental metrics and drivers that were useful for analysis but didn’t belong in the core consolidation structure. Initially, we considered shoehorning these members into the existing hierarchy, but this quickly proved problematic:

• Adding non-consolidation data to FCC can introduce unnecessary complexity.
• Sparse data intersections may slow down calculations and retrieval.
• Mixing supplemental and core financial data risks confusion and misinterpretation.
• Additional supplemental requirements might create what was coined as a “dumpster dimension”

The Solution: A Supplemental Application

To maintain clarity and performance, I would argue that offloading these supplemental data elements into a separate Planning FreeForm application is a better move. In the on-premises days, we would spin up little analytic cubes all over the place to hold data that really didn’t make sense in a larger cube. I don’t see why we wouldn’t do something similar with EPM Enterprise Cloud customers as well. In my eyes the benefits are:

• Preserve the integrity of the FCC hierarchy by keeping it focused on core financial data.
• Optimize performance by reducing sparsity and irrelevant intersections.
• Enable targeted analysis in the supplemental cube without compromising the main application.
• Stitch the reporting together in Narrative Reporting and/or ad-hoc analysis with Smart View.

This approach gives the flexibility to design each cube for its specific purpose, while still allowing for integration where needed pushing data through data maps or integrations.

Key Takeaways

• Don’t force-fit data into hierarchies where it doesn’t belong.
• Use supplemental applications to isolate non-core data.
• Design with both performance and user experience in mind.
• Interdimensional relevance should be a guiding principle in Essbase architecture.

When we respect the boundaries of dimensional logic, we can create cleaner, faster, and more maintainable solutions.