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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners. Design/methodology/approach -Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation. Findings -The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. The method of validation depends on the practitioners' knowledge on the relationship between cause and effect and controllability of the causes. Originality/value -The roadmap thus evolved for the validation of root causes will be of great value to the practitioners as it is expected to help them understand the ground reality in an unambiguous manner resulting in a superior strategy for cause validation and corrective actions.

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PurposeThe purpose of this paper is to develop a criterion for selection of critical sub‐processes when all the sub‐processes cannot be taken up simultaneously for improvement. There exist various methods but the practitioners get utterly confused because of the existence of these multiple options. In this paper, the goal is to assist practitioners in the selection of the critical sub‐processes.Design/methodology/approachThe authors discuss various statistical methods such as correlation and regression, simulation, basic statistics such as average, standard deviation, coefficient of variation % (C.V.%), etc. for the selection and identification of the critical sub‐processes. The strengths and weaknesses of these methods have been compared through empirical analysis based on real‐life case examples.FindingsThe stepwise regression and simulation have been found to yield identical results. However, from the perspective of application, stepwise regression has been found to be a preferred option.Originality/valueThe roadmap thus evolved for the selection of the critical sub‐processes will be of great value to the practitioner, as it will help them understand the ground reality in an unambiguous manner, resulting in a superior strategy for process improvement.