Lean Six Sigma framework for developing doctoral research problem statements outlined in white paper

Lean Six Sigma framework for developing doctoral research problem statements outlined in white paper Sadie Harley Scientific Editor Andrew Zinin Chief Editor University of Phoenix College of Doctoral Studies has published a new white paper, "Building a Lean Six Sigma–Based Background of the Problem and Problem Statement," by James C. Rice, DM/IST, MBA, and Scott A. McCalla, DM, MA. The paper presents an author-developed framework that adapts the Define and Measure logic of Lean Six Sigma to help doctoral practitioner researchers develop a defensible background of the problem and problem statement grounded in authoritative evidence. Designed for beginning researchers and experienced researchers who are new to practitioner research in business, the framework organizes problem development around five connected elements: an observed condition, normative condition, issue, associated effect and practitioner research problem. It also distinguishes the practical problem being investigated from the separate academic knowledge gap that establishes why new research is warranted. "Defining the problem is one of the most consequential steps in practitioner research because every decision that follows depends on that foundation," said Rice. "Our framework gives researchers a disciplined way to move from an observed condition to a researchable problem using evidence that can be examined, compared and verified." How can Lean Six Sigma be applied to doctoral research problem development? Lean Six Sigma commonly uses the Define, Measure, Analyze, Improve and Control, or DMAIC, process to examine performance and improvement. The white paper focuses specifically on Define and Measure as tools for framing and substantiating a practitioner research problem. In the authors' application: - "Define" specifies the population, setting, process, indicator, stakeholders and boundaries of the problem. - "Measure" documents the observed condition and an authoritative normative condition using comparable evidence. The paper draws on quality-improvement guidance, management-system standards and research-design literature to connect the practical logic of identifying a performance gap with academic expectations for evidence, methodology, validity and inference. "Practitioner researchers often bring substantial professional experience to the questions they study, and that experience is valuable, but it can also make it easy to simply begin with an explanation of what we think is wrong," said McCalla. "Using Define and Measure as procedural constraints encourages researchers to establish the condition and evidence first. That helps preserve an open research process rather than building the study around a preferred explanation or solution." What is the five-element evidence chain? The central contribution of the white paper is an evidence chain that provides a decision rule for moving from an observed difference to a consequential practitioner research problem: - Observed condition: What is occurring in the relevant population, organization, sector or location. - Normative condition: An objective, authoritative comparison point, which may be temporal, spatial, comparative or standards-based. - Issue: A defensible difference between the observed and normative conditions. - Associated effect: Credible evidence that connects the issue with a meaningful negative or positive effect. - Practitioner research problem: The issue considered together with its documented associated effect. Under the framework, a disparity alone is not automatically considered a consequential research problem. Researchers also must establish why the discrepancy matters through credible evidence of an associated effect, while avoiding causal language unless the supporting research design warrants a causal conclusion. How does the framework support research rigor and dissertation development? The authors emphasize that a practitioner research problem and an academic knowledge gap are related but distinct. Establishing the background of a problem and a problem statement helps the researcher establish the practical discrepancy and associated effect, while the literature review establishes what remains unresolved in scholarship. The study purpose, research questions, methodology and design then should align with the knowledge the research is intended to produce. The paper also proposes an evidence-screening process. Researchers are encouraged to assess sources for authority, currentness, methodological transparency, comparability and relevance. For the observed condition, the authors propose using authoritative primary-source evidence released within the preceding five years, while recognizing that applicable standards or historical benchmarks may appropriately be older. To translate the conceptual framework into practice, Rice and McCalla provide a recommended sequence for developing the background of the problem. The authors also include a model formulation and hypothetical business example showing how researchers can apply the evidence chain while preserving comparability and limiting conclusions to what the evidence supports. About the white paper "Building a Lean Six Sigma–Based Background of the Problem and Problem Statement" is a conceptual and practitioner-focused white paper by Rice, DM/IST, MBA, and McCalla, DM, MA. The authors synthesize Lean Six Sigma DMAIC gap logic, quality-management guidance and research-design scholarship to propose an evidence-chain framework for developing a doctoral dissertation background of the problem and problem statement. The framework emphasizes authoritative evidence, comparability, methodological alignment and restraint in causal inference. The white paper does not report results from an empirical study or present a validated research instrument. Its principal contribution is a proposed conceptual and drafting tool, and the authors state that its usefulness should be evaluated through application across different practitioner research settings and study designs. More information James C. Rice, Scott A. McCalla. Building a Lean Six Sigma–Based Background of the Problem and Problem Statement, www.phoenix.edu/content/dam/ed … lem-rice-mccalla.pdf Provided by University of Phoenix