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Record W4240683105 · doi:10.2118/2002-149

Squeezing Value Out of Your Information Technology Investment

2002· article· en· W4240683105 on OpenAlexaboutno aff
B. Oxby

Bibliographic record

VenueCanadian International Petroleum Conference · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsnot available
Fundersnot available
KeywordsValue (mathematics)Investment (military)Computer scienceBusinessPolitical sciencePolitics

Abstract

fetched live from OpenAlex

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).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.061
GPT teacher head0.254
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2002
Admission routes1
Has abstractyes

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