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Record W327429792

Outsourcing Success: It's All in the Governance: Making Deals Work Daily Takes a Long-Term View

2006· article· en· W327429792 on OpenAlexaboutno aff
Lauren Bielski

Bibliographic record

VenueABA banking journal · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsOutsourcingBusinessDiversification (marketing strategy)Work (physics)MarketingCorporate governanceMarket economyPublic relationsEconomicsFinancePolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Outsourcing is of those topical perennials that bloom, wither, and rebloom in the business landscape. Deal styles evolve, then change. Traditional approaches involving simple information technology services are tried, ended, and retried in-house, or with other vendors. Or business transactions take on a global cast, emerging in firms scattered amid the sacred cows of India, in the upstart capitalist hubs of China, the tropics of the Philippines, or in Eastern Europe's workhorse zones, only to be brought closer to home in Mexico or Canada. And yet a few traits stay constant. One of them is that many firms fail to maintain a sourcing strategy overall. Another is that many deals unravel, even among well-schooled bank management, as if entropy were engrained in their structure. Like a garden prone to being overtaken by weeds, recent findings suggest, many outsourcing arrangements seem unable to sustain an organized cultivation. London-based PA Consulting conducted a survey of senior management at a mix of companies earlier this year. It found that when it comes to IT deals anyway, a lack of planning, mishandling of day-to-day activities, and general neglect all contribute to so-so results. Conversations with other experts left the impression that non-IT business process outsourcing faces similar challenges. And yet those who are bullish on offshoring--exotically situated outsiders doing work for you--point out that it is a growing market, which suggests something else is going on. If most deals didn't work themselves out and yield results, you wouldn't see the growth in international markets, says Jeff Gullo, senior executive, financial services, with Accenture, based in Dallas. This isn't for the faint of heart, but for many, it is working. Brian Smith, partner, financial services industry, TPI, The Woodlands, Tex., agrees. He says the deals that fail are the flash and burn stuff of news, while successful situations often go under-reported. Once again a routine option Why the perception of trouble might linger around outsourcing, we'll get to in a minute. For now, consider that in this country, despite recent political rhetoric and media theatre, having another firm take over non-differentiating process or technology work is once again a routine executive management decision. The financial services industry isn't tentative about new locations and shifting terms of engagement. One in three financial services firms may be turning their backs on global sourcing, according to Deloitte Consulting, yet many are taking steps to extend their commitment for labor savings and quality enhancement. JPMorgan Chase made headlines earlier in the year, when CNN Money reported that the bank was one upping other capital market rivals that had taken on BPO vendors. How? It booted key stock analysis and report writing functions to India. And there are ample statistics indicating that outsourcing in all forms will likely be a hearty plant, inclined to appear, if not always thrive, wherever it finds itself. Research firm IDC, for instance, says that U.S. spending on payments-related BPO spending reached $3.3 billion in 2005 and will experience growth at a five year compound annual growth rate of 5.5%. Meanwhile, the Asia Pacific BPO market is projected to reach $14 billion by 2010. Gartner Research says that retail banking deals around ATM handling, network management, and check processing are also getting traction into 2006, albeit with outsources closer to home. Cheap to manage and other myths Co-existing with the upbeat stats is a reality that has shades of quiet alert. One bad practice underpinning deals that unravel, it turns out, is poor governance aided by miscommunication. It's not a problem limited to the banking industry but it is shared by it. …

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0130.013
Scholarly communication0.0230.016
Open science0.0010.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.002

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 head0.025
GPT teacher head0.259
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2006
Admission routes1
Has abstractyes

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