Bibliographic record
Abstract
Abstract Technology might be innovative and exciting but ultimately it's delivered business value that measures success. Oil and gas companies have made huge investments in information systems, networks, and infrastructure. Some projects have been successful while others have been expensive investments with questionable return. So what's the next big wave? Collaboration? Web services? Employee portals? Enterprise application integration? Do any of these technologies matter? To squeeze value out of their IT investment, energy companies must examine how they will leverage technology in the future. Introduction The next technology wave is unlikely to be a flood of innovative advancements. Collaboration, web services, and enterprise application integration may be significant developments, however they will not garner the attention that new technologies have in the past. Rather a wave of newly found fiscal management for Information Technology (IT) will steal the limelight. Many oil and gas companies have made huge investments in IT over the last decade. However, after years of escalating expenditures, the results have often been less than stellar. IT departments have been marked with the stigma of broken promises, poor customer service, and under delivery. IT is under pressure. For example:Despite record earnings in the first half of 2001, a major integrated oil company recently undertook a multimillion dollar cost reduction program slashing IT costs by an estimated 20%.A multi-year IT outsourcing deal at a major pipeline was curtailed to reduce costs.Amultinational engineering company halted the implementation of a runaway ERP implementation at the border, stranding Canadian operations on a legacy mainframe application. Despite these challenges, IT is at the heart of the evolution of every major company in the energy sector. Delivering Value With Information Technology With the glamour of the dot com era behind us, we are now entering a maturing phase of IT. Gone are the days when IT managers can say to business units: "IT will build it and they will come-trust me." Sophisticated consumers of information now demand to know the magnitude and timing for business benefits from IT projects. Strategic Resource or Cost Centre? Many IT departments in the energy sector are managed as cost centres. This reflects positioning in an industry where production activities take precedence. To become a strategic resource, the role of IT must be clearly articulated towards enabling growth. Figure 1 illustrates the three sides of an approach for IT to deliver strategic value: Growth, Productivity, and Cost Reduction. IT has finite capacity and resources. An IT department focused solely on cost reduction will be incapable of effectively capitalizing on opportunities to enable growth or increase productivity. To proactively position as a strategic resource, IT departments must excel in four key areas:Structure for SuccessMeasurable ResultsDefined ServiceDetermined Leadership Structuring For Success Effective models to strategically deliver IT services have been elusive. In many organizations, a CIO role has been created to provide standards, overall direction, and high-level budget control. Services are commonly distributed through business unit IT departments.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".