Bibliographic record
Abstract
Abstract Technology might be innovative and exciting but ultimately it's deliveredbusiness value that measures success. Oil and gas companies have made hugeinvestments in ERP systems, land management systems, procurement portals, networks and infrastructure projects. Some have been successful while othershave simply been expensive projects with questionable return. To squeeze valueout of present IT investment companies must examine how they will leveragetechnology in the future. So what's the next big wave? Collaboration? Webservices? Employee Portals?Enterprise Application Integration? Do any of these technologies matter? Thispaper will identify key industry practices for driving value from IT. It willexamine common IT delivery models from the fully outsourced to solely in-house.It concludes with a discussion on how companies in the oil and gas sector canderive more value from their IT dollars. Introduction The next technology wave is unlikely to be a flood of innovative advancements.Collaboration, web services and enterprise application integration, whilesignificant will not garner the attention of IT as new technologies have in thepast. Rather it will be a wave of newfound fiscal management for Information Technology that will steal the limelight. Many oil and gas companies have madehuge investments in IT over the last decade. However, after years of escalatingexpenditures, the results have often been less than stellar. IT departmentshave been marked with the stigma of broken promises, poor customer service andunder delivery. As a result, IT is under pressure. For example:Despite record earnings in the first half of 2001 a major integrated oilcompany recently undertook a multimillion dollar cost reduction programslashing IT costs by an estimated 20'.A pipeline company is significantly reducing spending in all operations. ITis among the areas hardest hit. Initiatives are being scaled back and servicecontracts not renewed. An outsourcing deal was curtailed in an effort tostreamline processes and reduce costs.A multinational engineering company halted the implementation of a runaway SAP implementation at the border stranding Canadian operations on a legacymainframe application to avoid capital costs. However, the Canadian divisionwas still hit with layoffs in IT.Despite these challenges, information technology is at the heart of theevolution of every company in the energy sector. CREATING ENDURING VALUE WITH INFORMATION TECHNOLOGY With the glamour of the dot com era behind us, we are now entering a maturingphase of IT. The recent explosion and subsequent implosion of dot com mania hasserved many purposes, one of which was to educate broader numbers of people onthe use of technology and it's limitations. Gone are the days when IT managerscan say "will build it and you will come - trust me " while asking for morefunding. Sophisticated customers now demand to know the magnitude and timingfor business benefits from IT projects. With technology firmly in themainstream of our lives, customers understand the value of informationtechnology. Increasingly, IT will be measured by the business results theygenerate (i.e. the benefits to be gained that the customer is willing payfor).
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".