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Figure 36. Completed Top-Level Comparison Matrix
Easy to Easy to Internet Works well Easy to
learn use connectivity with other maintain
quickly software
Easy to learn 4 1 3 1
Easy to use quickly 0.20 0.33 0.25
after I’ve learned it
Internet connectivity 3 3
Works well with other 0.33
software I own
Easy to maintain Incon: 0.05
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Numerically, the importance weights for each attribute are as follow:
• Easy to learn: 0.264 (26.4%)
• Easy to use quickly after I’ve learned it: 0.054 (5.4%)
• Internet connectivity: 0.358 (35.8%)
• Works well with other software I own: 0.105 (10.5%)
• Easy to maintain: 0.218 (21.8%)
These relative importance weights can be used in QFD as well as in the AHP process
that we are illustrating here. In our allocation of effort, we will want to emphasize those
attributes with high importance weights over those with lower weights.
Subcategory Importance Weights
The process used for obtaining category importance weights is repeated for the items
within each category. E.g., the items ‘interactive tutorial,’ ‘good documentation,’ and
‘intuitive interface’ are compared pairwise within the category ‘Easy to Learn.’ This
provides weights that indicate the importance of each item on the category. For
example, within the ‘Easy to Learn’ category, the customer weights might be:
• Interactive tutorial: 11.7%
• Good documentation: 20.0%
• Intuitive interface: 68.3%
If there were additional levels below these subcategories, the process would be repeated
for them. For example, the “intuitive interface” subcategory might be subdivided into
“number of menus,” “number of submenus,” “menu items easily understood,” etc. The
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See the Appendix for an example of how to derive approximate importance weights using Microsoft
Excel.
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