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A validation Study of House of Quality key performance indicators
Technical Correlation Matrix
The roof of the House of Quality, shows which HOW’S are interrelated and how strong these
relationships are. The technical correlation matrix shows for which areas close communication and
collaboration is important and for which areas it is less or not important and between which
attributes design bottlenecks may occur (Cohen 1995). Like for the relationship matrix, also for the
correlation matrix symbols are used to indicate mutual improvement (+) or trade off (-) relationships
between the HOW’S.
Technical Matrix
The last part of the House of Quality is the Technical Matrix. This part provides a lot of technical
information that is linked to both customer needs and parts characteristics in the second phase of
QFD (Chan, 2002). First the relative importance ratings of each HOW to all the WHAT’S needs to be
determined by multiplying the final importance ratings and the weightings from the plannin matrix.
Next step is to set the targets for the HOW’S, also called the HOW MUCH’es (American Supplier
Institute 1994). These targets represents levels of performance for the HOW’S in a way that the
organization believes that is required in oder to be competitive in comparison to competitive
products or services. In order to be specific and measurable each target should be quantified. It is
also important that the targets that are set, are reachable according to the technical sources of the
The HOW’S with the highest final rates are moved to Phase II of Quality Function Deployment, the
parts deployment.
2.6 Conceptual model
Previous sections discussed the literature relevant for the present research study. Based on the
literature findings we developed the conceptual model as depicted in Figure - 7. As discussed in the
literature review, new types of interaction are becoming more significant. For the present research
we focus on virtual communities, which nowadays form the basis of the internet. More specifically,
the concept of the online union can be classified as an online community. The present research seeks
to provide new insights on how to create value by matching the needs of the members of the online
union on the demand side and the design of the online union on the supply side. Therefore,
exploratory research followed by a validation study, through a statistically reliable sample of
members of the online union, is applied to identify key performance drivers of the online union.
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