MétaCan
Menu
Back to cohort

The Application of IT for Competitive Advantage at Keane, Inc.

2000· book-chapter· en· W184258459 on OpenAlexaboutno aff
Mark R. Andrews, Raymond Papp

Bibliographic record

VenueCases on information technology series · 2000
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingOutsourcingService (business)Information technology consultingProject managementOperations managementEngineering managementBusinessEngineeringManagementMarketingEconomicsManagement information systemsInformation systemInformation technology management

Abstract

fetched live from OpenAlex

The Keane Company, founded in 1965 by John F. Keane, has grown from a local software service company into a national firm which has three operating divisions and over 45 branches throughout the United States, Canada and the United Kingdom. Within these operating divisions are multitudes of consulting opportunities, ranging from supplemental staffing, project management and application outsourcing. This case will focus on Keanes approach to Project Management and how they provide this service to their clients. This includes not only how Keane is hired for Project Management but how they train their clients on how they too can implement the Keane philosophy of Productivity Management. Instead of focusing on any one client of Keane, their overall technology strategy will be highlighted, from their early days through the present to illustrate how Keane has successfully incorporated information technology and Project Management to become a major player in the software service and consulting field. The goal of this case is to provide the student with an example of business-technology strategy in action and allow them to explore future paths that Keane may take based on how they use technology today and in the decade to come.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.913
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 studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.211
Teacher spread0.204 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCases on information technology seriesSame topicInformation Technology Governance and StrategyFrench-language works237,207