| In the original Japanese N7 tools, the equivalent of this tool is Matrix Data Analysis. Although Matrix Data Analysis is an excellent tool, it is not easy to use given its heavy statistical emphasis. It has applications in other areas of process and product design, such as QFD, but it does not quite fit with the rest of the tools. Mizuno provides excellent coverage of Matrix Data Analysis.[14] Michael Brassard has come up with three alternatives to Matrix Data Analysis that he calls prioritization matrices. He defines them as follows: These tools prioritize tasks, issues, product/service characteristics, etc., based on known weighted criteria using a combination of Tree and Matrix Diagram techniques. Above all, they are tools for decision making.[15] Brassard provides the following three prioritization matrices as part of the 7 MP tools: The Full Analytical Criteria Method is pretty much based on the Analytic Hierarchy Process (AHP). Chapter 8 introduces AHP and its deployment using Expert Choice software. The Consensus Criteria Method is pretty similar to the Full Analytical Criteria Method in that both assume that the criteria for prioritization are known. The major difference, however, is that in the Full Analytical Criteria Method, the prioritization matrix consists of numbers that represent pair-wise comparison, and the relative rankings are obtained by summing the scores for the various components. In comparison, the Consensus Criteria Method does not use pair-wise comparison and thus is simpler and saves time. For issues that are not absolutely critical, the Consensus Criteria Method can be used. The Combination I.D./Matrix Method is used simply to prioritize various options to eliminate root problems and bottlenecks. I.D. does not distinguish the strength of the cause-and-effect relationship. This method is designed to overcome this weakness by determining an influence's direction and strength.
Although these three methods are useful and historically significant, they are tedious, time-consuming, and less accurate than AHP. We therefore emphasize AHP as a multiple-objective decision-making methodology (see Chapter 8). |
