Core idea: Cost-effectiveness analysis divides cost by a common outcome, such as hours of downtime avoided or units of capacity added.
When this model is useful
Use it when alternatives pursue the same objective but monetizing the benefit would be unreliable or inappropriate.
The method is most useful when the question, alternatives and time horizon are stated before calculations begin. It should clarify tradeoffs and identify which assumptions deserve attention, not merely produce a score.
Inputs and evidence
Comparable life-cycle costs, one clearly defined outcome measure, expected effectiveness, capacity and any threshold for acceptable cost per unit of outcome.
Use consistent units, definitions and periods across options. Mark estimates clearly, record their source and use ranges when precision is not supported. Evidence should be proportionate to the cost, risk and reversibility of the choice.
Step-by-step method
Use the same boundaries and period for every option, calculate average and incremental ratios, then compare the added cost and added outcome when moving to a more effective option.
- Write the decision question and accountable owner.
- List realistic alternatives and eliminate any that fail hard constraints.
- Collect evidence and separate verified facts from assumptions.
- Run a base case and at least one downside test.
- Record the chosen option, accepted tradeoffs and review triggers.
Practical example
Three reliability projects can be compared by cost per downtime hour avoided, while still showing the total budget and the extra cost of each improvement step.
The point of the example is not the exact numbers. It is the discipline of using the same boundaries for every option and making the decision drivers visible.
Common mistake and limitation
One outcome measure may omit quality, fairness or side effects. Add secondary criteria or use MCDA when those differences are material.
Review whether the result changes under reasonable alternative assumptions. A close or fragile ranking should be presented as such rather than converted into false certainty.
Questions to ask before deciding
- What evidence would change the preferred option?
- Which consequence is missing because it is difficult to measure?
- Could a threshold or constraint override the numerical result?
- Who receives the benefits and who bears the costs or risk?
- When should the decision be reviewed?
Professional context: Legal, tax, investment, safety, medical, engineering and regulated decisions require qualified, jurisdiction-specific advice.