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This paper aims to present an innovative research methodology that enables a company to realign its quality cost elements in order to improve implementation of its quality system.

The methodology combines the following methods: the house of quality costs (HOQC) method, which translates the desired improvement in failure costs (internal and external) into controllable efforts (prevention and appraisal costs) and ranks them by relative importance, the analysis of variance method, which supports selection of vital quality costs, and the enhanced control chart method, used to validate the strong causal linkages in HOQC.

Two case studies are presented to illustrate the application of the developed methodology. In the furniture firm, there are basically two vital sources of defects that could affect the overall cost of quality – raw materials and production process. In the food firm, traditional quality control is not enough to eliminate quality problems from the production processes. Hence, the hazard analysis critical control point is implemented.

The methodology applied in this paper proved itself capable of effectively handling realignment of quality cost elements. The methodology emphasizes adopting a systemic approach for selecting the vital controllable efforts in response to vital failure costs, as well as for detecting changes in the quality cost structure.

The American Society for Quality provides good coverage of quality cost types, but offers no mechanism for building and maintaining the relevance of these costs.

The purpose of this paper is to develop a methodology for building a causality process to dynamically investigate system performance linkages, as implied by a strategic frame such as a quality management frame or the balance scorecard frame.

The causality process develops aggregated process control tools in a data mining structure. The method identifies significant performance improvements by means of Cumulative Sum control charts, uses binary variables to mark them and time bounded search cycles as dictated by the causality constraints.

The methodology was implemented in a manufacturing enterprise and thus enables to better understand causality at the operational (tactical) level as well as at the strategic level.

Additional research issues for further investigation are expressed by questions such as follows: what other data mining tools may be appropriate? How to methodically construct learning performance indicators?

The causality process and its assisting process control techniques are suitable to a variety of managerial situations where techniques for monitoring and testing given frames of hypothesized performance linkages are needed.

The methodology enables an individual organization to dynamically investigate its performance in order to improve the implementation of its strategy.