- What Is Pugh Analysis
- Why Is It Important
- Decision Matrix Procedure
- Decision Matrix Example
What Is Pugh Analysis
Pugh Analysis is very similar to the pros vs. cons lists. These charts are used for evaluation of multiple options, factors, indicators against each other, in relation to a main baseline option. The Pugh matrix helps determine which items or potential solutions are more important or ‘better’ than others. The method was created by Stuart Pugh from Scotland as an approach for selection of concept alternatives.
Why Is It Important
This chart is great for use due to time needed for creation. To create the chart takes a development team to analyze the scores and weighting factors is usually much shorter and cheaper compared to deploying the wrong solution to a project. The next step ranking the criteria further helps focus the team’s efforts on the critical few.
The Pugh matrix allows an individual or team to:
- Compare different concepts
- Create strong alternative concepts from weaker concepts
- Create an optimal concept that may be a combination or variant of the best of other concepts.
When to Use a Decision Matrix
To list the positive and negative aspects of each option, one by one, to create a matrix of the needs vs. concepts helps address multiple factors at the same time and gives the team a holistic view of the needs vs. alternatives at hand.
- When a list of options must be narrowed to one choice
- When the decision must be made on the basis of several criteria
- After the list of options has been reduced to a manageable number by list reduction
Decision Matrix Procedure
- Develop a set of criteria according to the customer’s requirements.
- Enhance these criteria by including any item of functional nature.
- Generate a group of design concepts which are meant to satisfy the criteria.
- Using a simple matrix – list criteria on the left and the concepts across the top. Use simple sketches to illustrate each of these concepts.
- Set one of the concepts as a baseline.
- Evaluate each concept against the datum for each of the criteria. Determine whether it is better (+), the same (0) or worse (-) than the baseline. Alternately, one could assign a -1, 0, +1 based on where each choice would stack up against a set of the agreed-to criteria. We could give each of these criterion a weight and get the composite score of the alternate*criterion to determine the better alternative.
- Record the team’s decisions on the matrix.
- For each column, determine the total number of pluses, minuses and sames. Alternately, take the sum of the alternate score multiplied by weight of the criterion.
- Work to improve those concepts that scored best by incorporating strong ideas from other concepts.
- Continue the process of synthesizing concepts.
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Decision Matrix Example
The example bellow shows a decision matrix used by the customer service team at the Parisian Experience restaurant to decide which aspect of the overall problem of “long wait time” to tackle first. The problems they identified are customers waiting for the host, the waiter, the food, and the check.
| Problem | Customer Pain (×5) | Ease to Solve (×2) | Effect on Other Systems (×1) | Speed to Solve (×2) | Total Score |
|---|---|---|---|---|---|
| Wait for host | High — Nothing else for customer to do 3 × 5 = 15 | Medium — Involves host and bussers 2 × 2 = 4 | High — Gets customer off to bad start 3 × 1 = 3 | High — Observations show adequate empty tables 3 × 2 = 6 | 28 |
| Wait for waiter | Medium — Customers eat breadsticks 2 × 5 = 10 | Medium — Involves host and waiters 2 × 2 = 4 | Medium — Customer still feels unattended 2 × 1 = 2 | Low — Waiters involved in many activities 1 × 2 = 2 | 18 |
| Wait for food | Medium — Ambiance is nice 2 × 5 = 10 | Low — Involves waiters and kitchen 1 × 2 = 2 | Medium — Might result in extra trips to kitchen for waiter 2 × 1 = 2 | Low — Kitchen is design/space limited 1 × 2 = 2 | 16 |
| Wait for check | Low — Customers can relax over coffee, mints 1 × 5 = 5 | Medium — Involves waiters and host 2 × 2 = 4 | Medium — Customers waiting for tables might notice 2 × 1 = 2 | Low — Computerized ticket system is needed 1 × 2 = 2 | 13 |
The criteria they identified are:
- Customer pain – How much does this negatively affect the customer? Higher values mean greater frustration or dissatisfaction.
- Ease to solve – How easily can this issue be addressed, logistically and operationally? A high score here means the problem can be fixed without heavy changes.
- Effect on other systems – Will solving this issue improve or burden other parts of the operation (e.g., waitstaff, kitchen, seating flow)? A higher score indicates broader positive impacts.
- Speed to solve – How quickly can the solution be implemented? High-speed solutions are more attractive for quick wins and early improvements.
Summary:
- Highest Impact & Easiest Win: Customers waiting for host – Easy to fix, highly disruptive to customer experience.
- Mid-Level Issues: Waiting for a waiter or food are moderately painful and harder to solve.
- Lowest Impact: Waiting for the check is least disruptive and less urgent to address.
Decision Matrix Considerations
A very long list of options can first be shortened with a tool such as list reduction or multivoting.
Criteria that are often used fall under the general categories of effectiveness, feasibility, capability, cost, time required, support or enthusiasm (of team and of others). Here are other commonly used criteria:
For selecting a problem or an improvement opportunity:
- Within control of the team
- Financial payback
- Resources required (for example; money and people)
- Customer pain caused by the problem
- Urgency of problem
- Team interest or buy-in U
- Effect on other systems
- Management interest or support
- Difficulty of solving
- Time required to solve.
For selecting a solution:
- Root causes addressed by this solution
- Extent of resolution of problem
- Cost to implement (for example, money and time
- Return on investment; availability of resources (people, time)
- Ease of implementation
- Time until solution is fully implemented
- Cost to maintain (for example, money and time)
- Ease of maintenance
- Support or opposition to the solution
- Enthusiasm by team members
- Team control of the solution
- Safety, health, or environmental factors
- Training factors
- Potential effects on other systems
- Potential effects on customers or suppliers
- Value to customer
- Potential problems during implementation
- Potential negative consequences.
This matrix can be used to compare opinions. When possible, however, it is better used to summarize data that have been collected about the various criteria.
Sub-teams can be formed to collect data on the various criteria.
Several criteria for selecting a problem or improvement opportunity require guesses about the ultimate solution. For example: evaluating resources required, payback, difficulty to
solve, and time required to solve.
Therefore, your rating of the options will be only as good as your assumptions about the solutions.
It’s critical that the high end of the criteria scale (5 or 3) always is the end you would want to choose. Criteria such as cost, resource use and difficulty can cause mix-ups: low cost is highly desirable! If your rating scale sometimes rates a desirable state as 5 and sometimes as 1, you will not get correct results. You can avoid this by rewording your criteria: Say “low cost” instead of “cost”; “ease” instead of “difficulty.” Or, in the matrix column headings, write what generates low and high ratings.
For example:
When evaluating options by method 1, some people prefer to think about just one option, rating each criterion in turn across the whole matrix, and then doing the next option and so on. Others prefer to think about one criterion, working down the matrix for all options, then going on to the next criterion. Take your pick.
If individuals on the team assign different ratings to the same criterion, discuss this so people can learn from each other’s views and arrive at a consensus. Do not average the ratings or vote for the most popular one.
In some versions of this tool, the sum of the unweighted scores is also calculated and both totals are studied for guidance toward a decision.
When this tool is used to choose a plan, solution, or new product, results can be used to improve options. An option that ranks highly overall but has low scores on criteria A and B can be modified with ideas from options that score well on A and B. This combining and improving can be done for every option, and then the decision matrix used again to evaluate the new options.
Conclusion
The decision matrix is a powerful tool for selecting the best option when multiple priorities compete for attention. In the restaurant example, it helped identify that improving host wait times offered the most customer value with the least implementation friction. By weighting key criteria like customer pain, ease of solving, system impact, and speed to resolve, teams can focus on what truly matters instead of relying on gut instinct or group debate.
Whether you’re prioritizing problems, choosing between solutions, or planning your next product launch, a decision matrix brings clarity and structure to complex decisions. It’s especially useful when only one initiative can move forward or when diverse stakeholders need to align quickly. With clearly defined ratings and weights, the matrix not only highlights the best option, it fosters informed discussion and smarter trade-offs.
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