Prioritization of Six-Sigma project selection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose With increasing choice from a range of programs, improvement project selection within broader supply chain context and resource constraints has become a major research challenge. The purpose of this paper is to investigate the different criteria for selecting Six-Sigma (SS) projects based on previous studies. The study is supported by two grounded theories: resource-based view and institutional norms. The criteria include: first, business drivers for improvement and the common performance metrics deployed; second, the organization’s stakeholders needs; and third, process owner’s needs. Design/methodology/approach To determine the relative importance of influencing factors, opinions were collected from 30 experienced practitioners including SS champions/master black-belts, company directors, consultants, and process owners through a series of interviews in small, medium, and large organizations including multi-national organizations. The evaluation of criteria is based on analytical hierarchy process. Findings The results show that impact on customer, financial impacts, and impact on operational goals are the most significant factors in selecting SS improvement project. Originality/value This study is a first attempt to determine the relative weight among SS project selection criteria, which help the practitioner to allocate their limited resources in implementing SS project.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it