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We'll follow up Oct 4 with the answer and badge winners. Make sure to get in the game before then by reviewing Premier CSM Christopher Davidson's scenario below and clicking the button to submit your answer.
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.