Get your emotions in check: How to make rational decisions with the decision analysis method

Luciano Sulaimon at ERNI Switzerland offices.

By Luciano Sulaimon (ERNI Switzerland)

Discover how to make better decisions using the decision analysis method (DAM). This article explains the theoretical and practical steps in creating a DAM, including working environment, formulating the decision problem, selecting alternatives, collecting decision criteria, and weighting and evaluating criteria. Learn how to calculate the benefit, perform sensitivity analysis and document your results. Make rational decisions with emotional impact using a DAM.


It is common knowledge that most of our decisions are not made consciously but unconsciously, i.e. emotionally. In psychology, the terms ‘system one’ and ‘system two’ are firmly established. The unconscious system one works quickly and automatically, whereas the conscious system two acts rationally. Although most consumers think that all their decisions are made rationally, system one is the preferred system we use when it comes to making decisions (Kahnemann, 2012, p. 33). In summary, this means that our choices are largely made on an emotional basis.

Nevertheless, to maintain some rationality in a decision-making process, decision management provides valuable methods. I want to take a closer look at one specific method in this article: the decision analysis method (DAM) and the procedure for creating it.

Multiple alternatives can make decisions seem complex and make a problem challenging to grasp. With the help of decision analysis, criteria are weighted and evaluated to ultimately select the winner with the highest score (Adler, 2015, p. 400). In theory and practice, this decision analysis can be preceded by a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. The criteria would be determined with the help of the SWOT analysis. However, SWOT analysis will not be discussed in this article.

As already mentioned above, this article focuses on the procedure for preparing a decision analysis method and is structured around the following procedural steps by Kühnapfel (2014).

  1. Working environment
  2. Formulate the decision problem
  3. Select the decision alternatives
  4. Collect the decision criteria
  5. Weight the decision criteria
  6. Evaluate the decision criteria
  7. Calculate the benefit
  8. Sensitivity analysis
  9. Document the results

Theoretical procedural steps in a decision analysis

Working environment

My personal experience is that no prior knowledge of the participants is required when conducting a decision analysis. However, it is vital that only participants who are authorised to make decisions are present. We do not recommend sending deputies; otherwise the acceptance of the decision could be poor. Another critical point is the number of participants. According to the saying, “Too many cooks spoil the broth,” and my personal experience leads me to recommend between 5 and 8 participants in the workshop.

Formulate the decision problem

The DAM can be used for various decision problems. One of them is the problem of deciding on a choice. The table below shows examples of decision analysis questions from practice.

Table 1: Exemplary questions of the decision analysis

Only some clients know their decision problem. In such a case, the decision alternatives can be identified with brainstorming or simple research.

Select the decision alternatives

It is clear that at least two options should be set up for a DAM, as one option competes with another option. Of course, other selection options can be added, but the number should be within a manageable range. From practice, 2–5 options are standard.

Collect the decision criteria

In this step, the focus is on drawing up a catalogue of criteria. The requirements that a criterion must fulfil can be found in the following table.

Table 2: Requirements for a catalogue of criteria

Another question that needs to be answered is how the decision criteria are collected. As already mentioned in the introduction, an analysis of strengths and weaknesses can be used to find the decision criteria. Another possibility would be to brainstorm them.

Weight the decision criteria

The following aspects must be taken into account when weighting the elements listed in the criteria catalogue:

  • Determine the importance of all relevant criteria.
    • Create a common understanding of the importance of the criteria.
  • Meaning is expressed utilising a ratio.
  • The weighting of the individual criteria must always be adjusted to reach 100% total.
  • Solution: Procedure in three steps:
  1. Assign grades that are easy to record
  • From 1 (very important) to 6 (unimportant)
  • Scale from 1–10 or 1–100
  1. Perform the intermediate step
  • Award point value
  • Grade 1 = 6 points and Grade 6 = 1 point
  1. Calculate the proportion of meaning with the rule of three
  • If a more considerable difference in meaning is to be calculated, a scale of 1–100 is recommended.

Alternatively, weighting can be carried out with the help of a pair comparison method. A pair comparison method is used when subjective interest-driven criteria weighting is to be prevented (Kühnapfel, 2014, p.13). In terms of implementation, the pair comparison method pits each criterion against another criterion and checks or votes on which criterion is more important. The pair comparison method is implemented using a pair comparison matrix. The rows are summed, and a weighting is calculated (Table 6).

Evaluate the decision criteria

As with the weighting of the decision criteria, various rules must be followed when evaluating the decision criteria. These are as follows:

  • Set a scale.
  • The scale should be within a reasonable measurement corridor. (1–1,000 would be a bad example).
  • Do not select a scale that is too small.
  • Establish a score corridor that is helpful (see Table 3)
  • Good examples:
    • 10-point scale (1–10) or a rating of 0–4.
    • School grading scale (1–6)

The following table shows an example of a score corridor on a 10-point scale.

Table 3: Score corridor on a 10-point scale

Calculate the benefit

The calculation of the values can occur without the workshop’s participation. The weighting number defined above is multiplied by the rating given. Finally, this calculation is carried out with all specified criteria from the criteria catalogue. Finally, the sum is calculated for each decision alternative. The decision alternative with the highest sum wins the decision selection.

Sensitivity analysis

Now and then, for specific reasons, it is not possible to conduct the DAM in a workshop format, especially if it is foreseeable that the group dynamics or the discussion dynamics between the individual workshop participants will be difficult to control. In such a case, it is advisable to conduct the DAM independently. This means that a DAM does not necessarily have to be conducted in plenary but can also be performed individually with the respective decision makers. In this form, however, a catalogue of criteria must be drawn up in advance. A general consensus should also have been reached in advance regarding weighting. In the sensitivity analysis, the DAMs of all participants are aggregated by adding up the totals.

Document the results

The last step of the DAM is the documentation of the results. There are no limits for the creator. However, it is recommended to keep the presentation as simple as possible. The most important thing is to present the results in tabular form with the totals. A debriefing of the results is also valuable, as it can happen that the spread in the evaluation of the individual criteria is too great. Furthermore, the results of the participating decision makers should be comprehensible to eliminate misunderstandings. Last but not least, the result must be accepted.

Both in theory and through my practical experience, the decision problem could be solved through the DAM. Now, in order to give you an even greater understanding of the DAM and how to use it, the next section deals with a real case study. In this particular study, our customer had to make a decision about the choice of software, and we used decision analysis to do so.

Practice: Case Study

In this underlying practical example, the client faces the decision problem of which software to use in the future for processing claims. Three alternatives are available. The goal is to make a rational decision.

In the first step, a catalogue of criteria was drawn up (see Table 4).

Table 4: Criteria catalogue using the example of software selection

Due to numerous criteria and the fact that a distortion of the results through an interest-driven weighting selection should be prevented, the criteria weighting was carried out using the pair comparison method. For the pair comparison method, the criteria are presented in a cross matrix, and evaluated according to importance (see figure below).

Table 5: Pair comparison method

In the last step, the decision criteria are evaluated, and then the value is calculated. The summation shows that software 1 is the best alternative. Concerning the score corridor, we have deliberately chosen a score scale of 0–4 so that optimists and pessimists do not unintentionally distort the result.

Table 6: Calculation of the utility values


In conclusion, the decision analysis method (DAM) provides a valuable tool for making rational decisions. Following the procedural steps outlined in this article, including formulating the decision problem, selecting decision alternatives, collecting decision criteria, weighing and evaluating criteria, calculating utility, performing sensitivity analysis, and documenting the results, individuals and teams can confidently make informed decisions. It is important to remember that while emotional decision-making is natural, incorporating a rational decision-making process like DAM can lead to more effective outcomes.


Kahnemann, Thinking, Fast and Slow, 10th edition, 2012, p.33.

Andler, Tools for Project Management, Workshops and Consulting, 6th edition, 2015, p.400.

Kühnapfel, Nutzwertanalysen in Marketing und Vertrieb, 2014, p.6.

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