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In my cost transparency project's Cost model, this month I'm allocating $200,000 from IT Resource Towers object (where IT Resource Tower Name = "Data Centers") to Data Centers object.
I have 8 data centers.
Originally I was just evenly spreading the money: $200,000 / 8 = $25,000 per data center (DC).
Then I read Jenny's post and realized there were better ways to estimate per-DC costs.
Data centers are full of tracked metrics: square footage, occupied volume, rackmount units (RU), power, cooling, and more.
I'm torn between a space-based and a power-based allocation weighting strategy.
I could go with square footage. Or power consumption. Or a hybrid of both. Or something entirely different.
I could instead set up multiple allocations to accommodate different incoming cost types.
My total monthly tracked IT cost is $4,000,000 by the way.
Before I choose a weighting strategy for the $200,000/mo DC cost, my more pressing issue is:
What is the impact of choosing incorrectly?
More specifically: How can I calculate worst-case scenario effects (if my weighting strategy is absolutely the opposite of reality) or sample average error effects (if my weighting strategy is perhaps close to but not 100% reflective of reality)?
I need to be able to show my manager quantitative evidence of why I should or should not spend 2-4 hours researching and improving this specific model allocation.