Step 1: Define the Problem

A useful economic analysis begins with a clearly defined problem. If the decision question is vague, or if the baseline is chosen incorrectly, the rest of the analysis can quickly become confusing or misleading. Step 1 is about turning a concern, observation, or opportunity into a specific, answerable decision question with a defined scope, baseline, and set of outcomes. Time spent clarifying the problem at the outset almost always saves time later and leads to more defensible conclusions.

Where Animal Health Economics Can Help

There are many situations on farm where economic reasoning can support better management decisions. These include, but are not limited to:

Investigating disease outbreaks, where decisions need to be made quickly about diagnostics, treatments, and control strategies under uncertainty
Determining which diseases to treat and which drugs or protocols to use, particularly when multiple options differ in cost, effectiveness, or labour requirements
Implementing vaccination programmes, where costs are certain but benefits depend on disease risk and severity
Performing surgery to correct illness or injury, especially when outcomes, recovery times, and long-term performance vary
Changing diets or adding supplements, where responses may be gradual and influenced by other aspects of management
Investing in new facilities or equipment, which often involve large upfront costs and long payback periods
Selecting animals to cull or retain, where short-term losses must be weighed against long-term gains

In all of these cases, the underlying question is the same. Which option provides the best overall value once costs, benefits, timing, feasibility, and uncertainty are considered together?

Common Starting Points for Defining the Problem

Most economic analyses begin in one of three ways:

A performance signal
You review herd or flock key performance indicators (KPIs) and notice one or more are below target. Examples include lower-than-expected growth rates, increased mortality, poor reproductive performance, or rising somatic cell counts. These signals suggest that current management may not be achieving desired outcomes and prompt consideration of alternative approaches.

A clinical trigger
You are called to address a specific animal health problem, such as an outbreak of diarrhoea in week-old calves, a sudden increase in lameness, or an unexpected cluster of abortions. In these cases, the problem is often obvious, but the optimal response may not be, particularly when multiple diagnostic or treatment options are available.

An improvement opportunity
There are also situations where nothing is clearly “wrong”, but new research, technologies, or management approaches suggest that productivity, welfare outcomes, or risk management could be improved. Proactively identifying these opportunities is often valued by clients and can contribute to long-term business growth and resilience.

Better Framing the Problem

1. Write the decision question

The first practical task is to write the decision question in one clear sentence. A well-constructed decision question defines the boundaries of the analysis and keeps it focused.

A good decision question should specify:

Who is making the decision, such as the farm owner or manager
What action or set of actions is being considered
Which animals, management group, or system is affected
The timeframe over which outcomes will be evaluated

Examples include:

Should this farm implement a whole-herd vaccination programme for disease X before the upcoming calving season?
For calves with diarrhoea, which treatment protocol provides the best value under typical farm conditions?
Should the farm invest in improved calf housing to reduce morbidity and mortality, and is the expected return sufficient to justify the cost?

If the decision question cannot be written clearly, it is usually a sign that the problem still needs further clarification.

2. Define the reactive versus proactive context

A critical part of Step 1 is determining whether the situation is reactive or proactive, because this choice determines the baseline for the analysis and how benefits are defined.

Reactive situations
Reactive analyses begin with an existing disease or performance problem. In these cases, the current diseased or underperforming state is taken as the baseline. The benefits of management changes are expressed as the production gains, cost reductions, or risk reductions achieved by correcting the problem.

For example, during an active calf scours outbreak, the baseline reflects current mortality, treatment costs, and growth losses. Benefits are measured as improvements relative to this situation.

Proactive situations
Proactive analyses aim to prevent disease or reduce risk before a problem occurs. Here, the baseline is typically a disease-free or steady-state situation. Benefits are expressed as the losses that are avoided if disease does not occur, weighted by the probability of disease occurring in the absence of intervention.

For example, vaccinating before a known risk period involves certain costs now, with benefits that depend on disease likelihood and severity. Making assumptions about risk explicit is essential in these analyses.

3. Define what outcome(s) matter

Once the decision question and baseline are clear, the next step is to decide which outcomes will be used to compare options. These outcomes should reflect both biological impacts and farm-level objectives.

Animal welfare outcomes may include morbidity, mortality, pain and suffering, recovery time, and the likelihood of complications or repeat treatments.
Production and performance outcomes often include growth rates, milk yield or components, fertility measures, calving or lambing distribution, and culling rates.
Resource and operational outcomes capture practical considerations such as labour requirements, facility use, workflow disruption, withholding periods, and ease of implementation.
Economic outcomes bring these elements together and may include net benefit, return on investment, break-even points, and exposure to downside risk.

Not every analysis needs to include every outcome, but Step 1 is where priorities are set and justified.

4. Set the scope and boundaries

Defining the scope of the analysis prevents it from expanding indefinitely and ensures consistency in how costs and benefits are counted.

Key boundary questions include:

What is the unit of analysis, such as individual animals, a management group, or the whole farm?
What timeframe is relevant, such as weeks, a production season, or multiple years?
Whose perspective is being used, typically the farm business, but sometimes broader societal interests?
Which animals or activities are included or excluded?
What assumptions must be stated up front?

For most farm-level decisions, the primary perspective is the farm business. However, wider implications such as antimicrobial use, environmental effects, or public health risks can still be acknowledged even if they are not fully quantified

5. Gather background information

The final part of Step 1 is to identify the information required to complete the analysis. This list becomes the data plan for subsequent steps.

Typical information needs include:

Baseline disease frequency or performance levels
Expected effects of each intervention
Costs of inputs, labour, and services
Expected changes in production, wastage, or losses
Probabilities of different outcomes where uncertainty exists

Being explicit about information gaps helps determine whether reasonable assumptions and sensitivity analyses are sufficient, or whether additional data collection is justified.

Introduction to AHE

Step 2: List Alternate Interventions

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