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BEST Practice #4: Use Decision Matrices to Make Team Decisions

Designers tend to over value their own ideas. A team of designers, especially novice designers, is doomed if they don’t begin with some protocol for making objective decisions.

I admit that stereotypes must be taken with a  grain of salt. But, this “designer self-love” idea is probably one you’ve encountered already.  Our preconceptions and biases run deep and emotional attachments to ideas are more common than we let on. A team needs a way to make tough choices without crushing the fragile egos of the budding designers on the team. Making decisions with a “majority rules” paradigm is sure to fracture your team.


What is a Decision Matrix?
A Decision Matrix is a simple mathematical tool to help insulate our decision process from our shallow biases. It also provides the huge service of helping us make choices in the presence of many independent design factors which have bearing on the quality of the final design.


How does it work?
Let’s say the team has reduced the broad range of alternative designs down to six reasonable solutions and we need to distinguish the most likely to succeed. However, as with any realistic design challenge, there are lots of different factors (or scales) that impact the overall quality of the solutions. For example, we may be concerned with the following factors:
(A) cost to produce,
(B) expected lifespan,
(C) ease of transporting device,
(D) marketability, and
(E) expected liability for warranty repairs.

Though all of these factors are important, we assign a relative weighting to each of them and make the total equal 100%. After some team discussion, we agree that the relative importance for each factor is as follows:
(A) cost to produce, (importance = 12)
(B) expected lifespan, (importance = 8)
(C) ease of transporting device, (importance = 20)
(D) marketability, and (importance = 40)
(E) expected liability for warranty repairs. (importance = 20)

We create a simple table with the design alternatives (ideas 1-6) listed on the rows and the important factors listed across the headers of the columns.

 
Important Factor
idea #
A
B
C
D
E
Total
1
 
 
 
 
 
2
 
 
 
 
 
3
 
 
 
 
 
4
 
 
 
 
 
5
 
 
 
 
 
6
 
 
 
 
 
12
8
20
40
20
100

The maximum score that an alternative can get in a particular factor is whatever the level of “importance” that we assigned to that factor. These maximums are listed on the very bottom row and, as you see, sum to 100 total points.

Now, we decide what score each idea gets for each factor. But, we only allow scores of high, medium, low. For example, when grading for Factor A, an idea can only score 0, 6, or 12. Here are the numbers that the imaginary team came up with:

 
Important Factor
idea #
A
B
C
D
E
Total
1
12
8
10
20
0
50
2
12
8
0
40
0
60
3
12
8
0
0
10
30
4
0
4
20
40
20
84
5
6
4
10
40
10
70
6
6
0
20
20
20
66
12
8
20
40
20
100

The apparent winner, when all factors are considered, is idea #4 with a total score of 84. Perhaps, idea 5 should be given another look as well. But, clearly the lowest scoring ideas can be dropped. Now, don’t get me wrong. There is still a lot of heated debate around the scoring of each idea in each factor. But, the decisions tend to be less biased at that level (or, at least, more apparent to reasonable observers).

What would have happened if we hastily made a decision only considering Factor A (cost to produce)? Right, we would have only pursued Ideas 1-3. Which, in reality, are probably the worst overall candidates and we would have carelessly discarded what are likely the best candidates (Ideas 4 and 5).


Summary
Don’t you think it is worth giving math a chance to save the friendships within your team? It may even lead you to an unexpected (and better) solution.

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