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• Paired Comparison Analysis -
Working Out the Relative Importance of
Different Options |
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Paired Comparison Analysis helps you to work out the importance of a number of options relative to each other. It is particularly useful where you do not have objective data to base this on.
This makes it easy to choose the most important problem to solve, or select the solution that will give you the greatest advantage. Paired Comparison Analysis helps you to set priorities where there are conflicting demands on your resources. |
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| • How to Use Tool |
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To use the technique, first of all list your options. Then draw up a grid with each option as both a row and a column header.
Use this grid to compare each option with each other option, one-by-one. For each comparison, decide which of the two options is most important, and then assign a score to show how much more important it is.
You can then consolidate these comparisons so that each option is given a percentage importance.
Follow these steps to use the technique:
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List the options you will compare. Assign a letter to each option. |
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Set up a table with these options as row and column headings. |
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Block out cells on the table where you will be comparing an option with itself - there will never be a difference in these cells! These will normally be on the diagonal running from the top left to the bottom right. |
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Also block out cells on the table where you will be duplicating a comparison. Normally these will be the cells below the diagonal. |
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Within the remaining cells compare the option in the row with the one in the column. For each cell, decide which of the two options is more important. Write down the letter of the more important option in the cell, and score the difference in importance from 0 (no difference) to 3 (major difference). |
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Finally, consolidate the results by adding up the total of all the values for each of the options. You may want to convert these values into a percentage of the total score. |
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| • Example |
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As a simple example, an entrepreneur is looking at ways in which she can expand her business. She has limited resources, but also has the options she lists below:
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Expand into overseas markets |
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Expand in home markets |
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Improve customer service |
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Improve quality |
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Firstly she draws up the Paired Comparison Analysis table in Figure 1:
| • Figure 1: Example Paired Comparison Analysis Table (not filled in): |
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Overseas Market (A) |
Home
Market (B) |
Customer
Service (C) |
Quality
(D) |
Overseas Market
(A) |
Blocked Out
(Step 3) |
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Home Market (B) |
Blocked Out
(Step 4) |
Blocked Out
(Step 3) |
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Customer Service
(C) |
Blocked Out
(Step 4) |
Blocked Out
(Step 4) |
Blocked Out
(Step 3) |
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Quality
(D) |
Blocked Out
(Step 4) |
Blocked Out
(Step 4) |
Blocked Out
(Step 4) |
Blocked Out
(Step 3) |
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Then she compares options, writes down the letter of the most important option, and scores their difference in importance. An example of how she might do this is shown in figure 2:
| • Figure 2: Example Paired Comparison Analysis Table (filled in): |
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Overseas Market (A) |
Home
Market (B) |
Customer
Service (C) |
Quality
(D) |
Overseas Market
(A) |
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A,2 |
C,1 |
A,1 |
Home Market
(B) |
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C,1 |
B,1 |
Customer Service
(C) |
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C,2 |
Quality
(D) |
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Finally she adds up the A, B, C and D values, and converts each into a percentage of the total. This gives these totals:
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A = 3 (37.5%) |
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B = 1 (12.5%) |
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C = 4 (50%) |
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D = 0 |
Here it is most important to improve customer service (C) and then to tackle export markets (A). Quality is not a high priority - perhaps it is good already. |
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| • Key points |
Paired Comparison Analysis is a good way of weighing up the relative importance of different courses of action. It is useful where priorities are not clear, or are competing in importance.
The tool provides a framework for comparing each course of action against all others, and helps to show the difference in importance between factors. |
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| • Grid Analysis - Making a Choice Where Many Factors Must be Balanced |
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| • How to Use Tool |
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Grid Analysis (also known as Decision Matrix analysis or Pugh Matrix analysis) is a useful technique to use for making a decision. Decision matrices are most effective where you have a number of good alternatives and many factors to take into account. The first step is to list your options and then the factors that are important for making the decision. Lay these out in a table, with options as the row labels, and factors as the column headings.
Next work out the relative importance of the factors in your decision. Show these as numbers. We will use these to weight your preferences by the importance of the factor. These values may be obvious. If they are not, then use a technique such as Paired Comparison Analysis to estimate them. The next step is to work your way across your table, scoring each option for each of the important factors in your decision. Score each option from 0 (poor) to 3 (very good). Note that you do not have to have a different score for each option - if none of them are good for a particular factor in your decision, then all options should score 0.
Now multiply each of your scores by the values for your relative importance. This will give them the correct overall weight in your decision. Finally add up these weighted scores for your options. The option that scores the highest wins! |
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| • Example |
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A windsurfing enthusiast is about to replace his car. He needs one that not only carries a board and sails, but also that will be good for business travel. He has always loved open-topped sports cars. No car he can find is good for all three things.
His options are:
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A four wheel drive, hard topped vehicle |
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A comfortable 'family car' |
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An estate car |
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A sports car |
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Criteria that he wants to consider are:
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Cost |
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Ability to carry a sail board at normal driving speed |
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Ability to store sails and equipment securely |
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Comfort over long distances |
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Fun! |
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Nice look and build quality to car |
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Firstly he draws up the table shown in Figure 1, and scores each option by how well it satisfies each factor:
• Figure 1: Example Grid Analysis Showing Unweighted Assessment of
How Each Type of Car Satisfies Each Factor |
Factors: |
Cost |
Board |
Storage |
Comfort |
Fun |
Look |
Total |
Weights: |
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Sports Car |
1 |
0 |
0 |
1 |
3 |
3 |
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4 Wheel Drive |
0 |
3 |
2 |
2 |
1 |
1 |
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Family Car |
2 |
2 |
1 |
3 |
0 |
0 |
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Estate Car |
2 |
3 |
3 |
3 |
0 |
1 |
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Next he decides the relative weights for each of the factors. He multiplies these by the scores already entered, and totals them. This is shown in Figure 2:
• Figure 2: Example Grid Analysis Showing Weighted Assessment of
How Each Type of Car Satisfies Each Factor |
Factors: |
Cost |
Board |
Storage |
Comfort |
Fun |
Look |
Total |
Weights: |
4 |
5 |
1 |
2 |
3 |
4 |
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Sports Car |
4 |
0 |
0 |
2 |
9 |
12 |
27 |
4 Wheel Drive |
0 |
15 |
2 |
4 |
3 |
4 |
28 |
Family Car |
8 |
10 |
1 |
6 |
0 |
0 |
25 |
Estate Car |
8 |
15 |
3 |
6 |
0 |
4 |
36 |
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This gives an interesting result: Despite its lack of fun, an estate car may be the best choice.
If the wind-surfer still feels unhappy with the decision, maybe he has underestimated the importance of one of the factors. Perhaps he should weight 'fun' by 7! |
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| • Key points |
Grid Analysis helps you to decide between several options, while taking many different factors into account.
To use the tool, lay out your options as rows on a table. Set up the columns to show your factors. Allocate weights to show the importance of each of these factors.
Score each choice for each factor using numbers from 0 (poor) to 3 (very good). Multiply each score by the weight of the factor, to show its contribution to the overall selection.
Finally add up the total scores for each option. Select the highest scoring option. |
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