Jeroen de Mast

Six Sigma and competitive advantage

Abstract It is claimed that the Six Sigma programme brings competitive advantages to companies that implement it. This paper studies the validity of this claim by positioning Six Sigma in the paradigms provided by the literature on competitive strategy. The main functionality of Six Sigma projects is to improve operational effectiveness and efficiency. A continual improvement of operational effectiveness and efficiency is vital in order to avoid competitive disadvantage, however it is all but straightforward to convert the results into sustainable profitability. It is more about staying in the race than about getting ahead. In order to use Six Sigma strategically, a company should do more than just conduct Six Sigma projects by the book, but develop the competencies that the programme can bring to an organization. These competencies – disciplined and effective problem solving and decision behaviour – have the potential to be a source of competitive advantage, when integrated with a companys strategy.Abstract It is claimed that the Six Sigma programme brings competitive advantages to companies that implement it. This paper studies the validity of this claim by positioning Six Sigma in the paradigms provided by the literature on competitive strategy. The main functionality of Six Sigma projects is to improve operational effectiveness and efficiency. A continual improvement of operational effectiveness and efficiency is vital in order to avoid competitive disadvantage, however it is all but straightforward to convert the results into sustainable profitability. It is more about staying in the race than about getting ahead. In order to use Six Sigma strategically, a company should do more than just conduct Six Sigma projects by the book, but develop the competencies that the programme can bring to an organization. These competencies – disciplined and effective problem solving and decision behaviour – have the potential to be a source of competitive advantage, when integrated with a companys strategy.

Agreement and Kappa-Type Indices

Kappa-type indices use the concept of agreement to express the reproducibility of nominal measurements. This article grounds kappa-type indices in statistical modeling, making explicit the underlying premises and assumptions. We critically review whether the interpretation of the kappa index as a chance-corrected probability of agreement can be substantiated. Further, we show that the so-called paradoxical behavior of the kappa index is explained from the fact that it is a measure of predictive association, rather than a pure measure of reproducibility. We discuss a number of alternative forms, critically examining whether they can be translated in tangible real-life interpretations.Kappa-type indices use the concept of agreement to express the reproducibility of nominal measurements. This article grounds kappa-type indices in statistical modeling, making explicit the underlying premises and assumptions. We critically review whether the interpretation of the kappa index as a chance-corrected probability of agreement can be substantiated. Further, we show that the so-called paradoxical behavior of the kappa index is explained from the fact that it is a measure of predictive association, rather than a pure measure of reproducibility. We discuss a number of alternative forms, critically examining whether they can be translated in tangible real-life interpretations.

The CTQ flowdown as a conceptual model of project objectives

The critical quality flowdown (CTQ) is a tool that is the core of the definition phase of most quality improvement projects. It relates high-level strategic focal points to project objectives which in turn are linked to and decompose into CTQs made oper..The purpose of this article is to describe and clarify a tool that is at the core of the definition phase of most quality improvement projects. This tool is called the critical to quality (CTQ) flowdown. It relates high-level strategic focal points to project objectives. In their turn project objectives are linked to and decomposed into CTQs, which are made operational in the form of measurements. In this article the nature of the connections between strategic focal point, project objectives, CTQs, and measurements is elaborated. The CTQ flowdown serves several purposes. It provides clear project definitions, clarifies the business rationale of an improvement project, makes explicit business assumptions behind project definitions, helps to focus on the vital few real business drivers, and facilitates optimally solving trade-off problems. This article provides a theoretical grounding of the CTQ flowdown, and also provides practitioners with a prescriptive template.

Process improvement in healthcare: Overall resource efficiency

This paper aims to develop a unifying and quantitative conceptual framework for healthcare processes from the viewpoint of process improvement. The work adapts standard models from operation management to the specifics of healthcare processes. We propose concepts for organizational modeling of healthcare processes, breaking down work into micro processes, tasks, and resources. In addition, we propose an axiological model which breaks down general performance goals into process metrics. The connexion between both types of models is made explicit as a system of metrics for process flow and resource efficiency. The conceptual models offer exemplars for practical support in process improvement efforts, suggesting to project leaders how to make a diagrammatic representation of a process, which data to gather, and how to analyze and diagnose a process’s flow and resource utilization. The proposed methodology links on to process improvement methodologies such as business process reengineering, six sigma, lean thinking, theory of constraints, and total quality management. In these approaches, opportunities for process improvement are identified from a diagnosis of the process under study. By providing conceptual models and practical templates for process diagnosis, the framework relates many disconnected strands of research and application in process improvement in healthcare to the unifying pursuit of process improvement. Copyright

Measurement System Analysis for Binary Data.

We describe a methodology for the assessment of the repeatability and reproducibility (R&R) of measurement systems that measure on a binary scale, such as pass–fail inspections. We focus on the situation where no reference values can be obtained for the objects in the experiment and consequently model the results of the R&R experiment as a latent class model. We provide estimators based on the maximum likelihood approach and the method of moments, and compare their properties. We also give guidelines for model checking and recommendations for sample sizes. The methodology is illustrated by an example.

Measurement System Analysis for Categorical Measurements: Agreement and Kappa-Type Indices

The standard method for the assessment of the precision of measurement systems that measure on a metric scale is the gauge R&R method, but this method is not applicable for measurement systems that measure on a nominal scale. For nominal measurements, t..The standard method for the assessment of the precision of measurement gauges—the gauge R&R method—is not applicable for measurement systems that measure on a nominal scale. For nominal measurements, the agreement method can be used, which expresses precision in the form of an index named κ. This paper aims to provide a consistent framework for the kappa method, based on statistical modeling. The defined probability models are used to study the statistical properties of proposed estimators. Various alternative forms of κ are discussed, as well as their relationship to the so-called paradoxes of kappa.

Steps and strategies in process improvement

It has been recognized that it is profitable to apply statistical methods in quality improvement projects. The statistical methods that have been developed for that purpose in the 20th century have been made operational in the form of improvement strategies. In the literature various examples of such strategies are described. Although often presented as a uniform approach for problem solving, they are partly differing in terms of the steps and the tools they use. This paper’s objective is to place the available strategies in relation to each other and to study the differences in functionality. We discuss both global differences—differences relating to the functional objectives of the strategies—and detailed differences, that is, differences that concern the steps and the tools that are exploited to arrive at the objectives. The strategies that are taken along in the collation appear to have sufficient similarities to place them in a functional framework. This framework enables one to exploit the complementary functionalities within the strategies and to use it as a generic strategy for statistically based process improvement.

Integrating the Many Facets of Six Sigma

ABSTRACT We seek to provide a unified characterization of Six Sigma by studying the phenomenon from the perspectives of business economics, organizational theory, competitive strategy and industrial statistics, and we pinpoint its core methodological principles. We describe Six Sigma as a prescriptive framework for the routinization of incremental product and process innovation, organized as a decentralized project organization. The methodological basis of Six Sigma consists of principles borrowed from methodology for empirical inquiry, and facilitated by techniques from quality engineering, problem solving and marketing.[This abstract is based on the authors abstract.] A unified characterization of Six Sigma is provided by examining the process from the perspectives of business economics, organizational theory, competitive strategy, and industrial statistics. It is ..

Generic Project Definitions for Improvement of Health Care Delivery: A Case-Based Approach

Background: The purpose of this article is to create actionable knowledge, making the definition of process improvement projects in health care delivery more effective. Methods: This study is a retrospective analysis of process improvement projects in hospitals, facilitating a case-based reasoning approach to project definition. Data sources were project documentation and hospital-performance statistics of 271 Lean Six Sigma health care projects from 2002 to 2009 of general, teaching, and academic hospitals in the Netherlands and Belgium. Results: Objectives and operational definitions of improvement projects in the sample, analyzed and structured in a uniform format and terminology. Extraction of reusable elements of earlier project definitions, presented in the form of 9 templates called generic project definitions. These templates function as exemplars for future process improvement projects, making the selection, definition, and operationalization of similar projects more efficient. Each template includes an explicated rationale, an operationalization in the form of metrics, and a prototypical example. Thus, a process of incremental and sustained learning based on case-based reasoning is facilitated. Conclusions: The quality of project definitions is a crucial success factor in pursuits to improve health care delivery. We offer 9 tried and tested improvement themes related to patient safety, patient satisfaction, and business-economic performance of hospitals.

Gauge R&R studies for destructive measurements

The standard method for assessing a measurement systems precision is a gauge R&R study. Such a study involves an experiment in which each of a number of objects is measured multiple times. From the results, the spread of multiple measurements on a single object (the measurement spread) can be estimated. A serious complication is encountered when objects are affected by the measurement or when the true value of objects is variable. Such measurements are called destructive. Applying the standard gauge R&R set-up to destructive measurements is either impossible or results in an overestimation of measurement spread. This article studies alternative set-ups, which can be applied to destructive measurements if certain conditions hold. Even if required conditions are not completely met, the proposed approaches will at least lead to a smaller overestimation of measurement spread.