On normalizing the relationship matrix in quality function deployment

Abstract

Purpose This paper aims to investigate the need of normalizing the relationship matrix in quality function deployment (QFD), especially when it leads to rank reversal, and eventually provide a guideline to know when it should be done. Design/methodology/approach The research was carried out based on some empirical observations and previous research data. Findings A rule of thumb is proposed to know when the rank reversal, as a result of normalizing QFD relationship matrix, can be desirable or undesirable. Research limitations/implications Since the rule of thumb is based on empirical basis, it might not work perfectly for every single case, especially for large‐sized QFD matrices. Hence, this opens up a new challenge for future research to complement the current findings. Practical implications This paper shows that any QFD practitioner should be aware of the fact that normalization in the QFD relationship matrix is not a trivial issue, especially when it causes rank reversal. Ignoring normalization might cause potentially misleading results. However, using normalization does not always guarantee that one may obtain reliable results. Originality/value There are two novel findings in this paper. First, it is the exposition of the pros and cons of normalization in QFD relationship matrix. Second, it is the proposed rule of thumb which may serve as an important guideline for any QFD practitioner when dealing with the relationship matrix.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.