Variance Analysis
Updated 2026-08-11
INTRODUCTION
English translation pending.
CORE DEFINITION
Variance analysis is a standard tool of management accounting and cost control, closely tied to standard costing and cost-volume-profit analysis. Its core proposition is that the difference between planned and actual performance can be decomposed into controllable components, so the total gap points to specific drivers rather than to a vague shortfall. The key qualification is that decomposition must be disciplined: mixing price and volume effects, or treating the variance as a scorecard rather than a diagnostic, produces numbers that explain nothing and invite gaming.
SCAFFOLDING EFFECT
Reduce cognitive load
- Use baseline setting: fix the budget or standard you will measure actuals against. - Use driver split: break the total gap into price, volume, and efficiency components. - Use ownership mapping: assign each component to the unit or process that can affect it.
Anchor fast decisions
A single total variance tells you that something moved but not what to do about it. Because the total is produced by several independent drivers, each with a different owner and a different remedy, decomposing it separates causes that were previously entangled. Once a component is isolated, it can be compared across periods, traced to a decision, and assigned to the person who controls it. The mechanism converts an outcome measure into a set of process questions, which is why decomposition rather than the raw number does the diagnostic work.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Analysis_of_varianceverified
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