Useful paths for identifying Lean Six Sigma improvement opportunities
School of Data Science and Analytics
Purpose: The goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects. Design/methodology/approach: Using a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis. Findings: Seven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification. Research limitations/implications: Any starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list. Practical implications: Learners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities. Originality/value: Any successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.
International Journal of Quality and Reliability Management
Digital Object Identifier (DOI)