Building Value through Sustainable Project Management Offices
Bibliographic record
Abstract
Organizations’ attempts to implement and gain value from investments in project management have resulted in the rapid growth and, in some cases, demise of project management offices (PMOs). The recent research literature on PMOs provides an ambiguous picture of the value case for PMOs and suggests the tenuous nature of their current position in many organizations. In studying project management implementations for the Value of Project Management project, we chose to use three detailed cases and comparisons with the remaining 62 organizations in the value project to study how PMOs are connected to value realization for organizations investing in project management. Specifically, we sought to understand how PMOs deliver sustained value to organizations. Using the theories of Jim Collins (Collins, 2001; Collins & Porras, 1994) as an interpretive framework, we explore these cases to understand how to create and sustain project management value through investment in PMOs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".