Variance analysis shows how past deviations affected Operating Income. Differential analysis shows how future deviations might affect Operating Income. Both the similarities and differences between these two formulations are informative.
Similar independent and dependent variables (deviations and Operating Income) suggest that the formulaic approach used for variance analysis also applies to differential analysis. The expected impact of decisions can indeed be estimated using the formulas introduced in Chapter 6.
Different times and levels of certainty imply however different underlying sources of information and approaches. Variance analysis is oriented towards explaining the impact of past events which were recorded. Differential analysis is oriented towards predicting the impact of future decisions which have yet to be designed and implemented.
Differential analysis thus builds on the techniques of variance analysis to compute the impact of alternative courses of action on Operating Income and adds a layer of complexity: unlike past events, decisions alternatives are potentially infinite and have uncertain outcomes.
This is the reason why I address differential analysis after variance analysis, even if in practice it usually precedes: by reference to the control cycle proposed by Deming (plan-do-check-act), budgeting supports planning, differential analysis supports doing (and in part acting), and variance analysis supports checking.