Decision Matrix Analysis – An In-depth Elucidation

Decision-Matrix-Analysis

Introduction

Sometimes life presents you with situations where more than one good option is available. In that case you are required to analyze all the available options along with all the factors that need to be accounted for and choose the best option among the lot. Under such circumstances where there is no such thing as preferred option, it is most appropriate to use the Decision Matrix Analysis method for making the right call. In this article, we will learn about this effective model.

About Decision Matrix Analysis

Decision Matrix Analysis is the simplest form of Multiple Criteria Decision Analysis (MCDA) and involves highly complex modeling of the various potential scenarios with the help of advanced mathematics. The efficient use of this technique requires confidence and rational thinking. Mastering this method will take you that extra mile when others give in to indecision. Especially for business leaders, it often gets difficult to make the right decision with the risk of losing all that is riding on it. Such conditions require the Decision Matrix Analysis method for evaluating and prioritizing all the available options.

Decision Matrix Analysis goes by various names, including the following.

  • Pugh method
  • Pugh analysis
  • Decision matrix method, decision matrix
  • Decision grid
  • Selection grid
  • Selection matrix
  • Problem matrix
  • Problem selection matrix
  • Problem selection grid
  • Solution matrix
  • Criteria rating form
  • Criteria-based matrix
  • Opportunity analysis

How Does Decision Matrix Analysis Work?

A decision matrix is a collection of rows and columns showcasing the important values allowing analysts to systematically identify, analyze and rate the performance of relationships between sets of values and information. This method was first developed by Stuart Pugh, Professor and Head of the Design Department at the University of Strathclyde in Glasgow, who with the help of decision matrix took the subjectivity out of the decision which is generally made after carefully weighing all the factors and criteria. The matrix presents to you all the available options in rows and the corresponding factors that need to be considered in columns. After this, every possible option and factor is tried out and keeping in mind the relative importance of the factor,an overall score is appointed for each alternative. This might sound very complex, but the entire model can be summarized in few easy steps stated as follows:

  • A matrix is drawn. The size of the matrix depends entirely on the number of available options and the factors affecting the scenario.
  • All the possible options are appointed as rows of the table whereas the factors that need to be brought under consideration are chalked down under columns.
  • After this is done, every viable alternative is judged based upon all the available factors. These scores are written down the column corresponding to their respective options. The scoring is usually done between 0 (poor) to 5 (very good) and if none of the available possibilities satisfies your needs, you may as well discard them all with a 0.
  • When the scoring is done, the relative importance of each and every factor is scrutinized. Relative importance is generally ranked from 0 to 5 where getting a 0 will mean it is completely unimportant whereas fetching a 5 will prove that it is of utmost importance. Two factors might have the same relative importance. These values can be estimated using paired comparison analysis technique if it isn’t obvious.
  • In this step, the values that you assigned to the factors are multiplied by their corresponding relative importance value. Thus, the weighted score for every option-factor combination is obtained.
  • Finally all the weighted scores are added and the one option with the highest ratings is usually chosen as the best alternative. In case you doubt whether the best option is the one with the highest score, repeat the entire process checking the rates you previously assigned to the factors and their relative importance value and make any correction if needed. It may be so that a certain factor you thought was not that important turns out to have a higher importance value and vice versa.

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What is the Decision Matrix Analysis used for?

  • This method is used to evaluate different options compared against a common baseline.
  • This method is also used even if there is only one possibility. The various aspects of the option are thoroughly weighed. This is done to make sure that under the lack of options, you don’t end up making the wrong decision.
  • This method can also be used in situation where many alternatives are available and none of which are up-to-the-mark. Here, Decision Matrix Analysis is used to find out the best aspects among the available options and then, to come up with a hybrid which is better than any of the available alternatives.

An Example

Let us assume that there are four viable alternatives and let us call them A, B, C and D. Then, the criteria are to be decided and often the most important ones are chosen. Let us denote these notable factors as 1, 2, 3 and 4. A scale of 0 to 5 is chosen where 0 denotes ‘poor’ and 5 marks ‘very good’. For choosing relative importance, another scale is used which is again from 0 to 5 and only this time, 0 denoting ‘not important at all’ and 5 making it the ‘most important’ factor. The baseline is taken as zero as the comparison is done on a same level. The points and the relative importance value of the available option A, B, C, D are formulated accordingly. Finally, the table is constructed and all the gathered information and ratings are inserted into it. The assigned values are multiplied with their corresponding relative importance number and the weighted value is found out. These values are then added to figure out the best course of action i.e. the best choice among A, B, C, and D.

Conclusion

Decision Matrix method is used on an individual level. In case decision making requires group effort, individual decision matrixes are created and then they are compared among the group. The option having most of the votes among the members of the group is selected.

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