Statistical thinking and its role for industrial engineers and managers in the 21st century

Miltiadis Makrymichalos · Jiju Antony · Frenie Jiju Antony · Maneesh Kumar

41 citations0/0 files storedManagerial Auditing Journal

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Quality and Supply Management Management and Optimization Techniques Management Systems and Quality Improvement

Abstract

Purpose The purpose of this paper is to demonstrate the vital linkage between six sigma and statistical thinking. The paper also explains the key characteristics required for statistical thinking and some of the common barriers in the implementation of the key principles of statistical thinking. Design/methodology/approach The objectives of the paper have been achieved in several ways. The paper provides the key principles of statistical thinking and then discusses the possible reasons for lack of statistical thinking in modern organizations. The paper then illustrates the linkage between the statistical principles and six sigma. The tools and techniques of six sigma used within statistical thinking are also highlighted in the paper. Findings The key findings of this work include the relationship between the two key powerful methodologies: six sigma and statistical thinking, reasons for lack of applications of statistical thinking in organizations, the future role of managers and engineers in companies with regard to statistical thinking era and the commonalities in the application of tools and techniques between these two methodologies. Research limitations/implications The paper needs more justification through surveys and case examples and this will be the future step of this study. In fact, one of the co‐authors is currently conducting a survey in the UK organizations to investigate the relationship between statistical thinking and six sigma. Practical implications The paper is very practical in nature and it does yield a great value to those people who are currently embarking on six sigma program, especially at senior manager and executive levels. Originality/value Very little is published in the field of statistical thinking in the UK academic world. In fact, there is a cognitive gap in this field and this paper certainly forms a good platform for further research that will enable to bridge the gap.

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References

1982Out of the Crisis 1985What is total quality control the japanese way 2000The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance 2002Six Sigma: a goal‐theoretic perspective 2000Implementing Six Sigma: Smarter Solutions Using Statistical Methods 1972Organizational Behaviour: An Introductory Text 1989Statistical Methods for Quality Improvement 1995Using quality tools and techniques successfully

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