Introduction to Financial Modelling
Principles of Excel as a Modelling Tool
Essential Operations and Short-Cuts
Introduction to Excel Functions
Building Models: Common Structures and Best Practice Principles
Planning Models for Decision Support

12.7. Capturing, Evaluation and and Using the Decision Criteria

One of the core objectives of modelling is to provide the information that decision-makers will need. There are several aspects to this:

  • Identifying the direct decision-makers as well as the general stakeholders.
  • Identifying the decision criteria.
  • Evaluating the decision criteria (i.e. within the model).
  • Being aware of potential biases.
  • Decision criteria. This covers the decision criteria to be used, and the consequences for the model in terms of variables to include, data requirements, level of detail, and others. It also relates closely to the types of sensitivities and scenario analysis that will be required to support decision-making or reporting purposes.

Stakeholders and Their Objectives

In addition to direct decision-makers, there may be multiple other stakeholders or influencers: Each of these people or groups may have different objectives, criteria, values, priorities and constraints. Further, some of these may be hidden or not made explicit for political or social reasons, or only become apparent when the “hard reality” of a decision strikes.

The modelling process can provide a framework which allows for various interests to be brought together in an integrated way. Therefore, it is important to try to identify the relevant actors or decision influencers, and to elicit their interests, objectives and decision-criteria as explicitly as possible.

Identifying the Decision Criteria

One of the core objectives of modelling is to provide the information that a decision-maker will need: This requires that that the modeller should identify and evaluate the decision criteria, and establish which can be included within a quantitative model, and how non-modelled (out-of-scope) criteria should best be dealt with.

Of course, many decisions involve multiple criteria, and some of these may not always be able to be evaluated quantitatively or objectively. The model should aim to evaluate as many as are realistic; however, the model results will be an input into a decision-making process that may take other factors into account, and may involve making judgements in relation to moral, political or other issues.

In general, the process to evaluate a specific decision involves some assessment of its advantages and disadvantages. Of course, there are many specific ways that these can be expressed and compared (or weighed) against each other, resulting in many different approaches. This section begins with a brief introduction to decision-making criteria in general and then mentions some key criteria used in economic modelling.

In general, the starting point for identifying possible decision criteria is based on the general concept of “advantages-disadvantages”. This can be expressed in a variety of similar ways, including:

    • Creating a list of the advantages and disadvantages.
    • Conducting a SWOT assessment (strengths, weaknesses, opportunities and threats).
    • Considering the benefits and the cost (cost-benefit analysis).

These types of analysis resemble each other closely, and when applied to a specific situation, each could give the same results as the other. For example, the advantages identified could be categorised into those based on strengths and those based on opportunities

 In practice, each method may result in slightly different items being identified, simply due to the various focusses that the wording of each implies. Indeed, all methods could be considered in parallel, as a way to try to make this important phase of the analysis as complete as possible.

Evaluating the Decision Criteria: General Comments

Given a set of decision criteria, one would need a way to compare or evaluate them. The following mentions some key approaches.

Gut-feel, Intuition and Judgement

The use of “gut feel” means that a decision is taken with no or limited analysis, other than intuition or what one feels (or judges) to be right.

Of course, there are several positive points about such approaches:

  • It involves limited investment of time or resources.
  • It can be sufficient for day-to-day decisions, which may be simple, or small in nature, with limited downside, or be reversible. It may also be useful when a decision is similar to others that have already been analysed in detail, or which conforms to a well-known pattern from previous experience.
  • There are typically some decision elements (e.g. ethical or moral issues) that may not lend itself to a form of analysis that can be integrated automatically in a decision rule, and which may therefore require judgment to be used in any case.

However, in situations which are complex or with large and irreversible investments to be made, this approach is likely to be sub-optimal at best. The modelling process can help to create insight and overcome an excessive focus on gut feel; it can bring an alternative perspective and help to  balance the use of judgment and analysis – when both are used correctly together, the result is generally a more powerful and robust decision process.

Principles-Based Methods

These methods are based on the application of some dominant principle, such as:

  • To minimise the risk, or avoid the possibility of a specific outcome.
  • To fully utilise a specific resource.
  • To minimise the cost of the activity or project.
  • To respect social, moral or political aspects.

The key aspect of these approaches is that the method chosen relates to a single criteria which is considered to dominate all other considerations.

For example, if using cost-minimisation, one would choose the cheaper of two contractors (or training courses, or investment projects), even if the more expensive one could have greater benefits.  Similarly, a risk-minimisation approach would choose a course, contractor or project that has the the smallest risk or downside outcome, even if the other options could have far greater benefits or upside returns in almost all scenarios.

Integrated Approaches (and Optimisation)

Whilst a principles-based method could be used to choose a decision which “maximises the benefit”, such an approach would not take into account the cost of doing so. Thus, often it makes sense to use integrated approaches, where multiple items can be compared or traded-off within a single framework. The decision is taken based on finding the optimum balance.

These approaches are inherently quantitative, in order to be able to compare and integrate the items. Much economic analysis is conducted in this way. For example, the concept of “benefit” could be translated into sales revenue, and “cost” could be operating costs or investments, and so on. The cost-benefit analysis could measure profit (net benefit), cash flow, and so on.

The particular decision is then made by choosing the one which maximises an objective (such as profit) subject to some constraints (such as total investment). For example, when buying a car, one could fix a cost budget, and search for the best car that one can find for that money. Alternatively, one could first identify the cars that meet our requirements and then buy the one which has the lowest cost.

Evaluating Decision Criteria: Economic Perspective

There are many possible ways to evaluate a decision from an economic perspective. In principle, most of these involve using quantitative (integrated) methods. These include:

  • Breakeven analysis (such as time to break even).
  • Net present value (NPV) analysis.
  • Rate of return, and the internal-rate-of-return (IRR).
  • Ratio measures (e.g. of profitability or operating performance, such as operating profit, asset turnover, return on capital, and so on.)

Often, it is also required to also perform a sensitivity analysis of such items, to see the effect of different scenarios or assumptions on these measures. These are all covered in detail in later materials.

Interpretation of Criteria and Biases 

A bias is a general outlook, preference or inclination that is held by an individual or group, and which may influence the way that the person or group evaluates information that is provided to it. In other words, a bias is a lens through which information is viewed, and which may result in some types of information being given an inappropriate weight or importance (range from important information being discarded or ignored to unimportant factors being given prominence). Therefore biases act as a form of filter, and so “objective” information that is provided to decision-makers (such as the numerical evaluation of decision-criteria using a model) will be interpreted or used by them in accordance with their biases.

The effect of biases can be partly reduced if one is aware of them, and if there is a process to recognise potential biases and make them more transparent.

Biases can broadly be classified into three categories: motivational, cognitive, and structural biases.

Motivational biases are those which result from personal or group incentives, corporate politics, and general situations where there may not be full alignment between overall corporate goals and the goals of participants in the decision process.

Cognitive biases are those which are of a psychological or evolutionary nature. There are many sub-categories of these, including: 

  • Anchoring. This is the tendency to stick to existing beliefs in the face of new information, and to require overwhelming or disproportionate evidence in order to consider to change one’s views.
  • Framing. This is tendency to act differently depending on how a question is posed. For example, if an investment (e.g. shares) has reduced in value, one may be unwilling to sell it. However, given the chance today to buy into the same investment at the current reduced price, one would be unwilling to do so. One is unwilling to realise a loss (and so holds onto the investment), even as one would be unwilling to invest to create the same situation. Similarly, in a business situation, one may be tempted to continue with a project that has made losses or performed badly, even as one would not contemplate the initiation of such a project if offered as a new investment opportuniity.
  • Optimism. This is a belief that things will generally work out for the best.
  • Controllability. This is the belief that past good outcomes were a result of good choices and actions, but poor outcomes were due to bad luck or unforeseeable events.
  • Information avoidance. This is the tendency to avoid seeking information which we fell may challenge our existing beliefs or views.

Cognitive biases can result in insufficient analysis being conducted, or the results ignored or de-emphasised.

Structural biases are those created by the process or methodology used. For example, and over simplified methodology may overlook certain key elements or risks and biases the results in a favorable way.

Modelling can help to reduce biases by increasing transparency, and by creating the capability to challenge assumptions with logic and robustness, and to test hypothesis or the effect of alternate assumptions.

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