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Also known as:
decision-making matrix,
solutions prioritization matrix,
cost/benefit analysis matrix, problem/solution matrix,
options/criteria matrix,
vendor selection matrix, criteria/alternatives matrix, RFP evaluation matrix,
COWS decision matrix,
C.O.W.S. decision matrix,
supplier rating spreadsheet,
comparison matrix template,
importance/performance matrix,
criteria-based decision matrix, importance/performance-based
decision matrix, weighted score matrix, proposal evaluation matrix,
criteria/alternatives matrix,
software selection matrix, or bid decision matrix.
Use templates and samples provided in your FREE RFP Letters Toolkit to create your own Decision Matrix.
A decision matrix allows decision makers to structure, then solve their problem by:
As is, a decision matrix is a decision tool used by decision makers as part of their Decision-Support Systems (DSS) toolkit.
In the context of procurement, which is the solicitation and selection process enabling the acquisition of goods or services from an external source, the decision matrix, also called scoring matrix, helps determine the winning bid or proposal amid all those sent in response to an invitation to do so that, depending of the best-suited solicitation process, could either be a:
A decision matrix is basically an array presenting on one axis a list of alternatives, also called options or solutions, that are evaluated regarding, on the other axis, a list of criteria, which are weighted dependently of their respective importance in the final decision to be taken. The decision matrix is, therefore, a variation of the 2-dimension, L-shaped matrix.
The decision matrix is an elaborated version of the measured criteria technique in which options are given, for each criterion, satisfactory or compliance points up to a maximum (usually from 0 to 100) that is predefined per criterion and may vary between criteria depending on its relative importance in the final decision.
The Decision Matrix is also called:
Should you be involved in creating a decision matrix, here is the activity you will be engaged in. Use the COWS method, shown below, that describes all the information you should come up with in order to make an impartial decision:
| C | Criteria. Develop a hierarchy of decision criteria, also known as decision model. |
|
| O | Options. Identify options, also called solutions or alternatives. |
|
| W | Weights. Assign a weight to each criterion based on its importance in the final decision. |
|
| S | Scores. Rate each option on a ratio scale by assigning it a score or rating against each criterion. |
For our decision matrix example, let's consider the information below. Let's say we've identified criteria C1, C2, and C3 playing a role in the final decision, with a respective weight of 1, 2, and 3. Moreover, we've found 3 prospective providers A, B, and C, whose offer may constitute a good solution.
It's critical to rate solutions based on a ratio scale and not on a point scale. For instance, the ratio scale could be 0-5, 0-10, or 0-100. Should you feel you must use a point scale (for instance, maximum speed, temperatures, etc.), you must then convert rating values on a ratio scale by assigning the maximum ratio to the estimated maximum value, which could be, for instance, 5 (for a 0-5 scale), 10 (0-10), or 100 (0-100). Indeed, a point scale with high values introduces a bias even if it's of less importance in the final decision.
We've laid out the information into a 2-dimension, L-shaped decision matrix as shown below, and then compute the scores for each solution regarding the criteria with the formulas below:
Score = Rating x Weight
and then
Total Score = SUM(Scores)
The result is the following:
Scenario #1
| ALTERNATIVES | |||||||
| Option A | Option B | Option C | |||||
| CRITERIA | Weight | Rating | Score(1) | Rating | Score(1) | Rating | Score(1) |
| Criterion C1 | 1 | 3 | 3 | 3 | 3 | 3 | 3 |
| Criterion C2 | 2 | 2 | 4 | 1 | 2 | 2 | 4 |
| Criterion C3 | 3 | 1 | 3 | 3 | 9 | 2 | 6 |
|
Total |
6 | 4 | 10 | 7 | 14 | 7 | 13 |
(1) Score = Rating * Weight
For a better interpretation, we can visualize the data in histograms. To do so, let's consider, as the data source, the ratings and scores of evaluated solutions. Here is the result:
|
WEIGHTS: W1 = 1 W2 = 2 W3 = 3 |
|
||||||||||||||||||||||||||||||||||||
Solution Ratings
When we sum up the ratings, both solutions B and C are equivalent and
outperforming solution A. While similar globally, options B and C present
different intrinsic strengths and weaknesses. Indeed, option B is better
than option C for the criterion C3, but weaker on C2, while option C distribute
more evenly its forces.
Therefore, Option B is usually called a best-of-breed solution, while Option C is a typical suite or integrated solution.
Let's apply the weights to the ratings now to obtain the...
Solution Scores
While both options B and C were initially equivalent rating-ly speaking,
weights applied to their ratings exacerbate the strength of option B in
criterion C3. Indeed, a higher weight was applied to its strength and a lesser
to its weakness, resulting in a first place. In this particular context, the
better the solution breed, the higher rank the solution gets.
We have here an interesting example of a battle opposing two alternatives at first sight equivalent, but one showing an explicit, differentiated strength against an other solution seeming spreading its strengths more evenly. Extrapolated, this battle is also called:
To solve this dilemma, there's no answer. Rather, the answer is "It depends". Indeed, depending on the contextual needs, one kind may be selected over the other. But, whatever the path chosen, the decision matrix won't be of any help in this matter but raising the concern. You will have to decide what's best for your organization's future. You could even build a meta decision matrix to help you answer this question...
Let's take a look at what would happen should your priorities change, and then find out the...
In order to discuss about the relative importance or effectiveness of weights coupled with ratings in the final decision, let's use the same aforementioned example and play with the weights, given the ratings won't never change.
In the first scenario, the weights were distributed as 1, 2, and 3 respectively for criterion C1, C2, and C3. Let's increase the second weight from 2 to 3. Here is the result:
Scenario #2
| ALTERNATIVES | |||||||
| Option A | Option B | Option C | |||||
| CRITERIA | Weight | Rating | Score(1) | Rating | Score(1) | Rating | Score(1) |
| Criterion C1 | 1 | 3 | 3 | 3 | 3 | 3 | 3 |
| Criterion C2 | 3 | 2 | 6 | 1 | 3 | 2 | 6 |
| Criterion C3 | 3 | 1 | 3 | 3 | 9 | 2 | 6 |
|
Total |
7 | 4 | 12 | 7 | 15 | 7 | 15 |
(1) Score = Rating * Weight
|
WEIGHTS: W1 = 1 W2 = 3 (+1) W3 = 3 |
|
||||||||||||||||||||||||||||||||||||
Solution Ratings
Based on an initial, fair, and impartial evaluation, the ratings don't
change since solution capabilities remain the same. In some cases -we hope
there're rare-, evaluators may be tempted to change the ratings to give a favor
to a so-illegitimately selected solution.
Then we obtain the new...
Solution Scores
Because they are globally equivalent in their ratings, and given identical
weights, both options B and C are now ex aequo. But, still, as you may
notice, their internal differences remain.
Now, let's keep the second weight at 3, and decrease the third from 3 to 2. Here is the result:
Scenario #3
| ALTERNATIVES | |||||||
| Option A | Option B | Option C | |||||
| CRITERIA | Weight | Rating | Score(1) | Rating | Score(1) | Rating | Score(1) |
| Criterion C1 | 1 | 3 | 3 | 3 | 3 | 3 | 3 |
| Criterion C2 | 3 | 2 | 6 | 1 | 3 | 2 | 6 |
| Criterion C3 | 2 | 1 | 2 | 3 | 6 | 2 | 4 |
|
Total |
6 | 4 | 11 | 7 | 12 | 7 | 13 |
(1) Score = Rating * Weight
|
WEIGHTS: W1 = 1 W2 = 3 (+1) W3 = 2 (-1) |
|
||||||||||||||||||||||||||||||||||||
Solution Ratings
Ratings still don't change, since the solution features and benefits are the
same.
Now, let's keep the second weight at 3, and decrease the third from 3 to 2. As a result, these are the new...
Solution Scores
While both options B and C were initially equivalent rating-ly speaking,
the new weights applied to their ratings inhibit what appeared to be a strength for option B in
criterion C3. Indeed, a lesser weight was applied to its strength and a higher
to its weakness, resulting in losing the first place in favor of option C. In
this particular context, the more integrated the solution, the better its rank
is.
Here is a recapitulation of the three scenarii with their respective weights:
|
|
|
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So, be careful in your interpretation of the result you get using a decision matrix. Indeed, you have to question the validity of the path you took to reach the conclusion you found. To challenge each step of your decision cycle, some features like sensitivity analysis and robustness analysis are helpful.
A decision matrix template and a decision matrix example are provided in your FREE RFP Toolkit. The decision matrix template is a Microsoft Excel spreadsheet that you customize based on your needs (criteria vs. alternatives). Thus it becomes a business object you can use not only in your RFP evaluation process -which would be better called proposal evaluation process- but, more generally, in any decision-making cycle.
The MS Excel decision matrix template spreadsheet contains, in fact, two worksheets:
Both Excel decision matrix template and example can be opened with any MS Excel-compliant application.
You will also find in your FREE RFP Toolkit, amongst others, templates and samples of RFP letters, including:
Use templates and samples provided in your FREE RFP Letters Toolkit to create your own Decision Matrix.
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"The decision matrix streamlines the decision cycle"
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