A Prioritization Matrice can help you decide what to do after key
actions, criteria or Critical-To-Quality (CTQ) characteristics have been
identified, but their relative importance (priority) is not known with
certainty. Prioritization matrices are especially useful if
problem-solving resources, such as people, time or money, are limited,
or if the identified problem-solving actions or CTQs are strongly
interrelated.
To create a matrix, you must judge the relative ability of each possible action to effectively deliver the results you want compared to every other identified action. The product of your work is a weighted ranking of all the possible actions you are considering. The finished matrix can help a team make an overall decision or determine the sequence in which to attack a problem or work toward an objective.
Prioritization matrices are especially useful in the project bounding and analyze phases of Lean Six Sigma quality.
What can it do for you?
You should consider creating a prioritization matrix if:
You cannot do everything at once,
You are uncertain about the best use of your resources or energy or
You are looking toward specific improvement goals.
How do you do it?
The first step in applying the Full Analytical Criteria Method is to ensure that the people working on the matrix agree on the ultimate goal they are trying to achieve.
Next, create a list of criteria or characteristics needed to achieve the goal or meet the objective. (The idea is simply to list the criteria without considering their relative importance. That happens later.) The team can do this by discussion or brainstorming. The purpose is to list all of the criteria that might be applied to all of the options. For example, if the team is considering which improvement step to attack first, some of their criteria might be:
To create a matrix, you must judge the relative ability of each possible action to effectively deliver the results you want compared to every other identified action. The product of your work is a weighted ranking of all the possible actions you are considering. The finished matrix can help a team make an overall decision or determine the sequence in which to attack a problem or work toward an objective.
Prioritization matrices are especially useful in the project bounding and analyze phases of Lean Six Sigma quality.
What can it do for you?
You should consider creating a prioritization matrix if:
You cannot do everything at once,
You are uncertain about the best use of your resources or energy or
You are looking toward specific improvement goals.
How do you do it?
Step 1: Agree on the ultimate objective
The first step in applying the Full Analytical Criteria Method is to ensure that the people working on the matrix agree on the ultimate goal they are trying to achieve.
Step 2: List Criteria Needed to Meet the Goal
Next, create a list of criteria or characteristics needed to achieve the goal or meet the objective. (The idea is simply to list the criteria without considering their relative importance. That happens later.) The team can do this by discussion or brainstorming. The purpose is to list all of the criteria that might be applied to all of the options. For example, if the team is considering which improvement step to attack first, some of their criteria might be:
- Low investment cost
- Maximum use of existing technology
- High potential dollar savings
- High improvement potential for process speed
- High improvement potential for defect reduction
- High customer satisfaction potential
- Minimum impact on other processes
- Ease of implementation
- High probability of quick results
Step 3: Compare Relative Importance of Criterion
Once the total list is developed, the next step is to judge the
relative importance of each criterion compared to every other criterion.
To do that, make an L-shaped matrix with all the criteria listed on
both the horizontal and the vertical legs of the L.
Compare the importance of each criterion on the vertical side of the
matrix to each criterion listed along the horizontal side using these
numeric weightings:
1.0 = The criterion being considered is equally important or equally
preferred when judged against the criterion you are comparing it to.
5.0 = The criterion being considered is significantly more important or more preferred.
10.0 = The criterion is extremely more important or more preferred.
0.2 = It is significantly less important or preferred.
0.1 = It is extremely less important or preferred.
5.0 = The criterion being considered is significantly more important or more preferred.
10.0 = The criterion is extremely more important or more preferred.
0.2 = It is significantly less important or preferred.
0.1 = It is extremely less important or preferred.
Although these specific numeric ratings are to some extent arbitrary,
by applying them consistently in a prioritization matrix, you will
generate a valid understanding of relative importance. When completing
or interpreting the matrix, read across the rows (not down the columns).
For example, if criterion a was significantly more important than
criterion b, where row a intersects column b write 5. Remember that, if
criterion a is significantly more important that criterion b, criterion b
must be significantly less important than criterion a. Where row b
intersects column a write 0.2.
Continuing in a similar manner, compare each criterion to every other
criterion, reach a decision about relative importance, and enter the
appropriate values. Do this until the matrix is full. Remember that,
whenever you compare two criteria, you should mark the rating where the
row of the criterion being compared intersects the column of the
criterion you are comparing it to. The inverse of this value should be
entered where the column of the criterion being compared intersects the
row of the criterion you are comparing it to. That is, you should enter 1
and 1, 5 and 0.2, or 10 and 0.1 for each comparison.
Add the values recorded in each column; then add the column totals to get the grand total.
Add the values recorded in each row, then add the row totals to get the
grand total. The grand total across the columns should agree with the
grand total down the rows. If it does not, check your work. Divide each
row total by the grand total. This percentage is the weighting that
shows the relative importance of each criterion.
Another example
Another example
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