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Record W2476131798 · doi:10.2118/03-04-ge1

Squeezing Value Out of Your Information Technology Investment

2003· article· en· W2476131798 on OpenAlexaboutno aff
B. Oxby

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsInformation technologyBusinessOffshoringFinanceOutsourcingMarketingComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.232
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2003
Admission routes1
Has abstractyes

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