The idea
Please raise the 1 million cell limit for breakback in Polaris, or rework how that limit is applied so it better fits what Polaris is designed for.
The problem
Polaris lets us build models with many more dimensions than Classic, and sparsity is no longer the constraint it used to be. That is a real strength, but it clashes with the current breakback limit. Once you combine several dimensions with sizeable lists, the number of cells affected by a single breakback can easily pass 1 million.
The result is that breakback loses much of its value in exactly the models where Polaris should shine. End users can only enter values at a more granular level, or with less dimensionality then what they would like.
Potential solutions
- Increase the cell limit. This is the simplest option. There is no change in functionality, only a higher threshold that reflects what Polaris can handle.
- Exclude blocked cells from the count. Cells that are blocked through Dynamic Cell Access (DCA) or Selective Access cannot be adjusted anyway, so they should not count toward the limit. This would let Modellers remove irrelevant intersections up front and stay within the limit by design. It also rewards good model governance, since it encourages to precisely define what can be adjusted.
- Rework the breakback logic. A more advanced alternative is the approach suggested in Constant Disaggregation for Breakback. It would address the underlying scalability challenge rather than just moving the threshold.
Why it matters
- Breakback is a core planning capability, and its usefulness should scale with the model rather than shrink as dimensionality grows.
- Polaris encourages more granular, multi-dimensional models, so the limit becomes more restrictive as adoption increases.
- Options 1 and 2 are relatively contained changes that would deliver immediate value to end users.
If you’ve hit this limit in your own Polaris models, please upvote and/or share your workarounds below.
