Prioritization Matrices
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Steven Bonacorsi
Aug 17, 2011, 12:23:07 AM8/17/11
to Lean Six Sigma
This tool 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.
This tool can also help you make a decision in situations where the
criteria for a good solution are known or accepted, but their relative
importance is either unknown or disputed. For example, a
prioritization matrix might be used to help decide the purchase of a
major piece of equipment or the selection of a single-source supplier.
Depending on how much time you have and how complex your problem is,
there are a number of options for constructing a prioritization
matrix.
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:
1.Low investment cost
2.Maximum use of existing technology
3.High potential dollar savings
4.High improvement potential for process speed
5.High improvement potential for defect reduction
6.High customer satisfaction potential
7.Minimum impact on other processes
8.Ease of implementation
High probability of quick results Note the way the criteria are
worded. They should clearly convey the desired outcome. Low investment
cost is a much clearer criterion than cost would be.
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.
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.
•Now that you know the relative importance of each criterion, the next
step is to evaluate how well each of your possible choices meet each
of the weighted criteria. Those possible choices could be such things
as which improvement steps to take first, which piece of equipment to
buy or which supplier to use.
To complete this step, make a new L-shaped matrix with all your
possible choices on both the horizontal and the vertical legs. If you
are considering which improvement steps to take, your possible choices
might look something like this:
A. Error prevention training
B. Purchase new equipment A
C. Purchase new equipment B
D. Refurbish existing equipment C
E. Refurbish existing equipment D
F. Rewrite procedures for clarity
G. Implement barcoding
H. Cellularize operation 1
I. Cellularize operation 2
•Pick the first criterion you wish to consider and compare each
possible choice with every other possible choice by asking how well it
will deliver that criterion or characteristic. For example, if the
first criterion you were considering was high potential dollar
savings, you would compare each option with every other option, in
terms of its potential to deliver high monetary savings. Build the
matrix as you did when initially evaluating the relative importance of
the criteria by putting numeric values in the matrix intersections:
1.0 = The choice being considered is equally able to deliver the
desired criterion or equally preferred when judged against the choice
you are comparing it to.
5.0 = The choice being considered is significantly more important or
more preferred.
10.0 = The choice 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. Complete the
matrix; add the rows and columns and calculate the percentages as you
did with the criteria matrix.
The example above is what a matrix comparing the possible choices for
high potential for dollar savings might look like.
•In the same way; complete a matrix comparing each of the possible
choices for each of the remaining criteria. If we did that for all our
criteria, we would have to create a total of nine matrices comparing
every combination of possible choices for its relative ability to
deliver on each of the identified criteria.
You may choose to simplify this process by eliminating some criteria
that had a very low percentage weighting. (In our example, we limited
ourselves to the five highest-ranking criteria. Besides the matrix for
high potential dollar savings, we would create additional matrices for
high improvement potential for process speed, high improvement
potential for defect reduction, high customer satisfaction potential
and high probability of quick results. These additional matrices are
not shown here.)
•The final step in the Full Analytical Criteria Method is to merge the
relative ability of a possible choice to deliver a desired criterion
with the relative weighting of that criterion. To do this, make a new
L-shaped matrix with all the options or possible choices on the
vertical leg and all the criteria considered on the horizontal leg.
Make the columns fairly wide to allow some calculation.
Again, in our example, we eliminated some of the criteria to make
things simpler.
•Under each criterion, in the weight row, note the percentage
weighting you got from your first matrix, the one that compared each
criterion with every other criterion.
•In each criterion column, enter the percentage numbers you got when
you compared each option with every other option for that criterion.
(The actual matrices for criteria d, e, f and i are not shown.) Enter
these numbers as the first numbers in each column of the completed
prioritization matrix.
•Multiply each option percentage by the criterion percentage weight
for that criterion. (The results are the second numbers, the ones
after the equal signs in our example.)
•Add the results of your multiplication down each column. The result
for each column should be approximately the same as that criterion's
percentage weight (the number in the weight row).
•Add the column total row to come up with a grand total.
•Now, add the results of your multiplication across each row, and add
the row total column. The result should be the same as the grand total
you got by adding the column total row.
•Divide each row total by the grand total to get the percentage for
each option. (Add the percentage scores as a check. The sum should be
approximately 100 %.) This is the answer to your question.
•These numbers show the relative value of a number of options or
possible choices when considered against a collection of independent
criteria or critical to quality (CTQ) characteristics.
Now what?
Any time a choice must be made, some form of prioritization occurs.
Those responsible for making the choice may play a hunch, take a vote
or analyze for some specific impact they think is important, but they
will decide what they think is best, most important or should be done
first. If the prioritization process is incomplete or arbitrary,
chances of success are lessened.
The discipline of a prioritization matrix allows you to avoid setting
arbitrary priorities that have less likelihood of helping you reach
your desired objectives. The Full Analytical Method does take
considerable time and effort, however, and should be used only if the
risks or potential benefits make it worthwhile.
Steven Bonacorsi is a Certified Lean Six Sigma Master Black Belt
instructor and coach. Steven Bonacorsi has trained hundreds of Master
Black Belts, Black Belts, Green Belts, and Project Sponsors and
Executive Leaders in Lean Six Sigma DMAIC and Design for Lean Six
Sigma process improvement methodologies. Bought to you by the Process
Excellence Network the world leader in Business Process Management
(BPM)
Author for the Process Excellence Network (PEX Network / IQPC)
Process Excellence Network
Steven Bonacorsi, President of International Standard for Lean Six
Sigma(ISLSS)
Certified Lean Six Sigma Master Black Belt
47 Seasons Lane
Londonderry, NH 03053
Phone: +(1) (603) 401-7047
E-mail: sbona...@islss.com
Process Excellence Network: http://bit.ly/n4hBwu
ISLSS: http://www.islss.com
Article Source: http://EzineArticles.com/?expert=Steven_Bonacorsi
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.
This tool can also help you make a decision in situations where the
criteria for a good solution are known or accepted, but their relative
importance is either unknown or disputed. For example, a
prioritization matrix might be used to help decide the purchase of a
major piece of equipment or the selection of a single-source supplier.
Depending on how much time you have and how complex your problem is,
there are a number of options for constructing a prioritization
matrix.
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:
1.Low investment cost
2.Maximum use of existing technology
3.High potential dollar savings
4.High improvement potential for process speed
5.High improvement potential for defect reduction
6.High customer satisfaction potential
7.Minimum impact on other processes
8.Ease of implementation
High probability of quick results Note the way the criteria are
worded. They should clearly convey the desired outcome. Low investment
cost is a much clearer criterion than cost would be.
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.
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.
•Now that you know the relative importance of each criterion, the next
step is to evaluate how well each of your possible choices meet each
of the weighted criteria. Those possible choices could be such things
as which improvement steps to take first, which piece of equipment to
buy or which supplier to use.
To complete this step, make a new L-shaped matrix with all your
possible choices on both the horizontal and the vertical legs. If you
are considering which improvement steps to take, your possible choices
might look something like this:
A. Error prevention training
B. Purchase new equipment A
C. Purchase new equipment B
D. Refurbish existing equipment C
E. Refurbish existing equipment D
F. Rewrite procedures for clarity
G. Implement barcoding
H. Cellularize operation 1
I. Cellularize operation 2
•Pick the first criterion you wish to consider and compare each
possible choice with every other possible choice by asking how well it
will deliver that criterion or characteristic. For example, if the
first criterion you were considering was high potential dollar
savings, you would compare each option with every other option, in
terms of its potential to deliver high monetary savings. Build the
matrix as you did when initially evaluating the relative importance of
the criteria by putting numeric values in the matrix intersections:
1.0 = The choice being considered is equally able to deliver the
desired criterion or equally preferred when judged against the choice
you are comparing it to.
5.0 = The choice being considered is significantly more important or
more preferred.
10.0 = The choice 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. Complete the
matrix; add the rows and columns and calculate the percentages as you
did with the criteria matrix.
The example above is what a matrix comparing the possible choices for
high potential for dollar savings might look like.
•In the same way; complete a matrix comparing each of the possible
choices for each of the remaining criteria. If we did that for all our
criteria, we would have to create a total of nine matrices comparing
every combination of possible choices for its relative ability to
deliver on each of the identified criteria.
You may choose to simplify this process by eliminating some criteria
that had a very low percentage weighting. (In our example, we limited
ourselves to the five highest-ranking criteria. Besides the matrix for
high potential dollar savings, we would create additional matrices for
high improvement potential for process speed, high improvement
potential for defect reduction, high customer satisfaction potential
and high probability of quick results. These additional matrices are
not shown here.)
•The final step in the Full Analytical Criteria Method is to merge the
relative ability of a possible choice to deliver a desired criterion
with the relative weighting of that criterion. To do this, make a new
L-shaped matrix with all the options or possible choices on the
vertical leg and all the criteria considered on the horizontal leg.
Make the columns fairly wide to allow some calculation.
Again, in our example, we eliminated some of the criteria to make
things simpler.
•Under each criterion, in the weight row, note the percentage
weighting you got from your first matrix, the one that compared each
criterion with every other criterion.
•In each criterion column, enter the percentage numbers you got when
you compared each option with every other option for that criterion.
(The actual matrices for criteria d, e, f and i are not shown.) Enter
these numbers as the first numbers in each column of the completed
prioritization matrix.
•Multiply each option percentage by the criterion percentage weight
for that criterion. (The results are the second numbers, the ones
after the equal signs in our example.)
•Add the results of your multiplication down each column. The result
for each column should be approximately the same as that criterion's
percentage weight (the number in the weight row).
•Add the column total row to come up with a grand total.
•Now, add the results of your multiplication across each row, and add
the row total column. The result should be the same as the grand total
you got by adding the column total row.
•Divide each row total by the grand total to get the percentage for
each option. (Add the percentage scores as a check. The sum should be
approximately 100 %.) This is the answer to your question.
•These numbers show the relative value of a number of options or
possible choices when considered against a collection of independent
criteria or critical to quality (CTQ) characteristics.
Now what?
Any time a choice must be made, some form of prioritization occurs.
Those responsible for making the choice may play a hunch, take a vote
or analyze for some specific impact they think is important, but they
will decide what they think is best, most important or should be done
first. If the prioritization process is incomplete or arbitrary,
chances of success are lessened.
The discipline of a prioritization matrix allows you to avoid setting
arbitrary priorities that have less likelihood of helping you reach
your desired objectives. The Full Analytical Method does take
considerable time and effort, however, and should be used only if the
risks or potential benefits make it worthwhile.
Steven Bonacorsi is a Certified Lean Six Sigma Master Black Belt
instructor and coach. Steven Bonacorsi has trained hundreds of Master
Black Belts, Black Belts, Green Belts, and Project Sponsors and
Executive Leaders in Lean Six Sigma DMAIC and Design for Lean Six
Sigma process improvement methodologies. Bought to you by the Process
Excellence Network the world leader in Business Process Management
(BPM)
Author for the Process Excellence Network (PEX Network / IQPC)
Process Excellence Network
Steven Bonacorsi, President of International Standard for Lean Six
Sigma(ISLSS)
Certified Lean Six Sigma Master Black Belt
47 Seasons Lane
Londonderry, NH 03053
Phone: +(1) (603) 401-7047
E-mail: sbona...@islss.com
Process Excellence Network: http://bit.ly/n4hBwu
ISLSS: http://www.islss.com
Article Source: http://EzineArticles.com/?expert=Steven_Bonacorsi
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