The Pugh Matrix was developed by Stuart Pugh, a professor and head of the design division at the University of Strathclyde in Glasgow. It is also called a variety of other names including 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.
As a decision making tool, it is used to choose between a list of alternatives. The important criteria in the decision process are explicitly identified and the alternatives are compared using these criteria.
Is typically used in teams, but can just as easily be used by individuals. An interesting variation in team decision-making is for each individual to create his/her own Pugh matrix and then compare the individual Pugh matrices as a team exercise.
Typically, a Pugh matrix is used to evaluate various alternatives against a baseline. For example, a company has five alternative processes to the one it is using, and it wants to know if any of the five is better or not.
It is also used when only one design solution or choice must be chosen from several alternatives, when only one product from several under development can be brought to market, when financing can be secured for only one option, or where an optimal alternative is required. All decisions are based on ratings against multiple criteria.
It can also be used where there are many alternatives, none of which are completely suitable. The Pugh matrix can be used to choose the best aspects of the various alternatives to produce a hybrid, which may be better than any of the alternatives used alone.
Consider deciding between four alternatives, A, B, C, D. Assume that a system is in place and we want to know if one of these four systems would be better than the existing one.
First, decide upon the decision criteria. Pick the most important criteria, the ones that absolutely must be included and met by the selection. Assume that we have four important criteria, call them 1, 2, 3 and 4. These can be price, time, ease of production, man-hours, whatever is most important. It is an excellent idea to get your customer/client involved at this point to help ensure their satisfaction with the end result.
Now draw the Pugh matrix. Put the alternatives across the top. We will assess the alternatives with respect to the criteria, which we list on the left. Our baseline is the system that is in place at the moment, so score this as 0 against the criteria (NOTE: if there is no baseline in place, such as deciding between 5 microprocessors for a new application, there is no baseline column). The initial matrix looks like this (the Weight column is described below):
| Criteria | Weight | Baseline | A | B | C | D |
|---|---|---|---|---|---|---|
| 1 | 0 | |||||
| 2 | 0 | |||||
| 3 | 0 | |||||
| 4 | 0 | |||||
| Total | ||||||
Now consider alternative A. In relation to criteria 1, do we consider it better, the same as, or worse than the baseline? If it is better then assign it a score of +1, if it is the same then give it a 0, and if it is worse then give it a -1. Say it is better, so assign it a +1.
In terms of criteria 2, assume it is the same as the baseline, against criteria 3 it is better, and against criteria 4 it is worse than the baseline. Total the scores for all the criteria and enter it in the last row. The Pugh chart now looks like this:
| Criteria | Weight | Baseline | A | B | C | D |
|---|---|---|---|---|---|---|
| 1 | 0 | +1 | ||||
| 2 | 0 | 0 | ||||
| 3 | 0 | +1 | ||||
| 4 | 0 | -1 | ||||
| Total | +1 | |||||
Assess each of the alternatives B, C and D in the same way, filling in all the blanks.
| Criteria | Weight | Baseline | A | B | C | D |
|---|---|---|---|---|---|---|
| 1 | 0 | +1 | -1 | 0 | +1 | |
| 2 | 0 | 0 | -1 | 0 | +1 | |
| 3 | 0 | +1 | +1 | +1 | 0 | |
| 4 | 0 | -1 | 0 | 0 | +1 | |
| Total | +1 | -1 | +1 | +3 | ||
Now we know the number of pluses, the number of minuses and the total score for each alternative, allowing us to make a more rational or objective decision. In this case it is alternative D, with three pluses and no minuses.
We can also give each criterion a relative weighting. For example, assign a weight to the first criteria of 2. If the second criteria is twice as important, give that a four. The third criteria is somewhere in between, so assign it a three. And the last criteria is slightly more important than the second, so it gets a five. The specific weighting values are not all that important, the relative weighting values are important.
Once the weights are assigned, multiply the weight of each criteria by the score for the alternative, then total each column. Our weighted Pugh matrix now looks like this:
| Criteria | Weight | Baseline | A | B | C | D |
|---|---|---|---|---|---|---|
| 1 | 2 | 0 | +2 | -2 | 0 | +2 |
| 2 | 4 | 0 | 0 | -4 | 0 | +4 |
| 3 | 3 | 0 | +3 | +3 | +3 | 0 |
| 4 | 5 | 0 | -5 | 0 | 0 | +5 |
| Total | 0 | -3 | +3 | +11 | ||
In our case the end result is the same and alternative D is the best choice, but depending on the number of criteria and the variables, the weighting you use can cause very different end results.
Instead of the three-point scale illustrated here, sometimes the following 5-point scale is used:
With finer scales, such as 7-point scales, the decisions involved with assigning the scores and weighting factors can become unnecessarily complicated.