Purpose -This paper seeks to present a way of estimating DisPMO, DePMO, left-side and right-side Sigma levels (as the "mutations" of DPMO and Sigma level when applied on customer satisfaction measurements), where all critical attributes (CTQs) contain data sets that are non-normally distributed. Design/methodology/approach -The calculation of DisPMO, DePMO, left-side and right-side Sigma levels is based on dynamic-multiple CTQs without the need for assuming 1.5 Sigma shift from the mean. Using step-wise multiple regression, CTQs are then the attributes that significantly influence overall customer satisfaction. This further developed method no longer takes normality assumption for granted, which means that, prior to calculating DisPMO, DePMO, left-side and right-side Sigma levels, the data should be proven as being normally distributed. To fulfil the assumption of normality, the primary data are being "replicated" by first generating random numbers that follow normal standard distribution and then adjusting (re-calculating) these random numbers with the mean, standard deviation, and the skewness of the primary data. Simulation technique is then applied to generate a larger amount of secondary data as the basis for estimating DisPMO, DePMO, left-side and right-side Sigma levels. Findings -The application of the method in a Swedish house-building construction project suggests that: the use of multiple CTQs may reduce the risk for under-/overestimation of Sigma levels, and DisPMO and DePMO are each other's "mirror" and both of them should be considered when calculating Sigma levels. The calculated Sigma levels suggest that the developer's performance is still quite far below Six Sigma level of performance. Originality/value -Using the replica of the primary data as a way of approaching normality may be regarded as the main contribution of the paper in addressing one of the challenges in Six Sigma theory.
Purpose -The purpose of the paper is to develop existing tools or methodologies to measure customer value during acquisition and use, in such a way so that the measures concurrently indicate the level of performance and more "accurately" identify the improvement opportunities. Design/methodology/approach -Customer value is indeed perceived by customers in the market (external customers) during acquisition, use, until the end of the product's lifetime. The producer is the entity that creates the products that the customers acquire or consume. Therefore, the producer needs to be aware, to interpret, and being actively involved in the creation of customer value. This view makes the "general agreement" that customer value is nothing else than customer perception in the market no longer relevant. Therefore, ValMEA (Value Modes Effects and Analysis) offers a "balanced" perspective on customer value, by recognising that customer value exists in different "modes" on different stages of the product's life cycle. The link between different "modes" of customer value becomes an important basis to understand the contributions of producer activities on customer value. Findings -Measuring customer value is necessary to capture the essential meaning of quality. However, the existing tools to measure customer value do not adequately manifest the concept of customer value itself. Therefore, the modification of these tools becomes the prerequisite to continuously improve quality performance. The measurement of customer value during acquisition and use is based on intangible aspects (cognitive judgement). Along the value stream, these measures are translated (transformed) into tangible aspects, which comprise aspects such as shorter lead-time, reduced defects, and lower costs. Originality/value -The customer value measures complement the existing methodology such as Six Sigma, Lean Production, and Quality Function Deployment (QFD). The integration of customer value measures with these methodologies lead to the development of a customer-value-driven quality improvement framework, where improvement opportunities can be captured repetitively. The continuous quality improvement efforts can then be categorised into reactive (based on "waste" identification) and proactive (based on customer value measurements). Keywords Customer value, performance indicator, improvement indicator, ValMEA, value map, P-I matrix. Paper type Conceptual paper IntroductionDefining quality as fitness for use (Juran, 1962) rather than conformance to specifications implies an interpretation that products or services are meant to satisfy customer needs. It means that quality performance measures are no longer the monopoly of engineering in comparison with standards (i.e. product orientation) but they should also consider customer opinions (i.e. people orientation) since customers are the ultimate judges of quality (Garver, 2003). Therefore, Dahlgaard and Dahlgaard (2002) present the new TQM (Total Quality Management) metrology to measure quality from a cu...
PurposeThe purpose of this paper is to establish a link between Six Sigma and organizational change theory. Specifically, a framework that aligns Six Sigma critical success/hindering factors and the antecedents of successful organizational change process.Design/methodology/approachA theory‐derived framework containing Six Sigma's critical success and hindering factors at each stage of Lewinian change process is first proposed. Then, the framework is compared against the findings from a case study of Six Sigma improvement project in a UK, make‐to‐order, small to medium‐sized enterprise (SME).FindingsThere is a great deal of congruence (consistency) between Six Sigma's critical success factors and the antecedents of successful organizational change. Addressing people's “soft” skills (e.g. commitment, involvement, and communication) is necessary to “unfreeze” the equilibrium. The actual change and confrontation, which occur during “move” stage, requires a combination of both “software” and “hardware” of the organization (i.e. teamwork, methods/tools, organizational structure and culture). It is important for SMEs to provide resources during the “freeze” stage and justify the benefits of change, in order to sustain the change efforts.Research limitations/implicationsThis research was based on a single case of Six Sigma improvement project. However, future research will be conducted as a longitudinal study, to capture richer insights from the change process.Originality/valueThis paper offers a practical overview of how Six Sigma can be utilized as a change driver in SMEs and the enablers and barriers of success to be considered, especially during the early stage of adoption.
Purpose -The purpose of this paper is to further develop a method to convert (dis)satisfaction on critical attributes (critical to qualities, CTQs) in the customer satisfaction survey into performance measures that are equivalent to defect per million opportunities (DPMO). Design/methodology/approach -Stepwise multiple regression analysis is applied to identify the CTQs, where the overall satisfaction is the dependent variable and the attribute-related (dis)satisfactions (i.e. performance score minus importance score) are the independent variables. To simulate the attribute-related (dis)satisfaction for the identified CTQs, random numbers that follow normal standard distribution are generated and returned into random numbers that have similar characteristics (properties) with the primary data. The proportion of returned random numbers below the lower six sigma limit (SL) and above the upper six SL is adjusted into dissatisfaction per million opportunities (DisPMO) and delight per million opportunities (DePMO), respectively. Findings -Applying the logic of DPMO outside the boundary of an organisation (i.e. in the market) leads to two distinct measures, DisPMO and DePMO. These two measures can be transformed into two types/variants of sigma levels, i.e. left-side (approximated from DisPMO) and right-side (from DePMO), which may describe organisational effectiveness in the market from two different but complementary approaches. Originality/value -DisPMO and DePMO provide a basis for assessing the effectiveness of an organisation (manufacturing/non-manufacturing) according to six sigma methodology, where the "importance" and "performance" dimensions are considered simultaneously. Hence, the applications of DPMO (as six sigma's main performance measure) within and outside the boundary of an organisation are consistent and comparable.
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