Bibliographic record
Abstract
Abstract This paper reviews existing project management delivery performance in the North Sea oil and gas industry and explores a successful alternative approach through Mission Command Project Management. Poor project delivery has in recent years been a hallmark of the North Sea oil and gas industry. Studies show that the downward trend of project performance continues. Newspaper headlines signalling project delays and cost over-runs back up the statistics. This failure to deliver projects in a timely and cost effective manner has had, and continues to have, a direct impact on investment and the opportunity to maximise reserves on the United Kingdom Continental Shelf (UKCS). Unless a new approach is employed then the continued trend towards; more centralised control, process driven systems and bureaucratic delivery models, in tandem with substandard project implementation will be a major contributor to the premature demise of the basin. In the mid-80's the North Atlantic Treaty Organisation (NATO) was forced to re-think its strategy and adopted Mission Command as an approach. Its successful implementation revolutionised NATO's performance and this philosophy is now embedded in its modern warfare fighting competence. Mission Command has leadership and empowerment at its core and not the management of processes to drive projects to completion. The key principles of Mission Command are: Unity of effort (across the organisation). Decentralisation (formal delegation/empowerment). Trust (mutual, deep and enduring). Timely and effective decision-making. Freedom (and speed) of action. Employment of initiative. Mission Command is now gaining traction in the civilian project management community in concert with other concepts such as lean and agile project management, where its application has seen significant benefits. One North Sea Operator has now been employing Mission Command on all its projects over the last 4 years to great effect; out stripping its peers in terms of; safety, cost, schedule and quality of delivery. Mission Command Project Management is transformational in the art of project delivery and if more widely implemented could bring a renaissance to the North Sea. This paper highlights the failings of the present project management methodology, outlines the Mission Command approach and details its successful implementation by a North Sea Operator, thereby allowing others to employ this most efficient and effect delivery model.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.027 |
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".