Once the relevant costs and benefits have been identified, the next challenge is deciding how to organise and combine that information to support a decision. Different animal health problems have different structures. Some involve short-term changes with immediate consequences, while others unfold over years. Some decisions involve a single action, while others involve a sequence of choices under uncertainty. Selecting an appropriate analysis framework ensures that the way costs, benefits, time, and uncertainty are handled matches the nature of the decision being made.
Importantly, the framework you choose influences not only the numerical result, but also how easily the analysis can be explained to farmers, managers, or policymakers. A simple framework applied well is usually more valuable than a complex framework applied poorly.
Decision tree analysis is used for decisions that involve a sequence of choices and uncertain outcomes. The decision is represented as a branching tree, with decision nodes representing actions under the decision-maker’s control and chance nodes representing uncertain events, such as diagnostic test results or treatment success. Each possible pathway through the tree has an associated cost or benefit, which is weighted by the probability of that pathway occurring.
The basic steps involved are:
This framework is particularly useful when diagnostic testing influences subsequent actions, or when treatments have variable success rates and consequences.
When to use it
Decision tree analysis is most appropriate when:
Information typically required
Advantages
Disadvantages
Partial budget analysis evaluates the economic impact of a single change in management by focusing only on the costs and benefits that differ between the current situation and the proposed intervention. It does not attempt to model the entire farm system, but instead examines marginal changes over a short time horizon.
This approach is well suited to many routine herd health decisions because it is simple, transparent, and quick to apply.
When to use it
Partial budget analysis is appropriate when:
Information required
Advantages
Disadvantages
The basic steps involved are:
| Benefits of Intervention (+) | Cost of Intervention (-) |
|---|---|
|
Additional returns
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Reduced income
|
|
Reduced costs
|
Additional costs
|
Net value = (Additional returns + Reduced costs) − (Reduced income + Additional costs)
Cost–benefit analysis is used to evaluate decisions where costs and benefits occur over multiple years. All future costs and benefits are converted into present values using a discount rate, allowing direct comparison of investments with different time profiles. It works on the basic principle that $1.00 in your hand today is worth more than $1.00 in the future because of inflation. So before adding everything up, we just need to apply a simple formula to convert all future costs and benefits into their present values.
This framework is most commonly used for capital investments, long-term disease control programmes, or policy-level decisions.
When to use it
Cost–benefit analysis is most appropriate when:
Information required
Advantages
Disadvantages
The basic steps involved are:
We also use slightly different metrics to evaluate the outcomes of our recommendations.
Difference between the summation of the present value of future benefits and the summation of the present value of future costs
Find the discount rate or interest rate that would make the NPV equal to 0. It’s a useful figure because you can compare that rate to what might have been earned if the money had been invested elsewhere. These values were historically difficult to calculate by hand, but now there are spreadsheet formula that will do this for you.
Divide the summation of the present value of the benefits by the summation of the present value of the costs:
How long it will take before the flow of benefits has paid off the total investment
Marginal cost–benefit analysis examines how costs and benefits change with each additional unit of input. This is based on the law of diminishing returns, which recognizes that animals have biological limitations and each additional unit of input will yield progressively fewer benefits. We look for the point where the marginal cost (i.e. cost of each additional unit of input) equals the marginal benefit (i.e. extra benefit from that unit of input) to determine the optimal number of units to give.
Rather than asking whether an intervention is worthwhile at all, marginal analysis asks how much of the intervention should be applied.
When to use it
Marginal cost–benefit analysis is appropriate when:
Information required
Advantages
Disadvantages
The basic steps involved are:
Cost-effectiveness analysis compares the cost of achieving a specified outcome across different interventions without converting outcomes into monetary values. Instead, outcomes are measured in natural units such as cases prevented or animals saved
This framework is often used when outcomes are difficult to value economically or when decisions are driven by welfare or public health objectives.
When to use it
Cost-effectiveness analysis is useful when:
Information required
Advantages
Disadvantages
The basic steps involved are:
Simulation modelling explores how systems behave under uncertainty by repeatedly sampling from probability distributions for key inputs. This generates a range of possible outcomes rather than a single point estimate.
Simulation models are particularly useful for complex systems with interacting components and high uncertainty.
When to use it
Simulation modelling is appropriate when:
Information required
Advantages
Disadvantages
The basic steps involved are:
In practice, many analyses draw on elements from more than one framework. The guiding principle is to choose the simplest framework that adequately reflects the structure of the decision. Overly complex analyses can obscure key insights and make recommendations harder to communicate.
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