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Enregistrement W812790882

How to Meet the Challenge of the Open Workforce

2015· article· en· W812790882 sur OpenAlexaboutno aff
Jack Hagel

Notice bibliographique

RevueJournal of accountancy online/Journal of accountancy · 2015
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueCollaboration in agile enterprises
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWorkforceGlobalizationGlobeBusinessMarketingWork (physics)Talent managementAgile software developmentPublic relationsEconomic growthManagementEconomicsPolitical scienceEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Companies across the globe are embracing the open model, a trend that has been fueled by globalization and digitization. Firms increasingly rely on external staff as well as their permanent in-house employees to meet their business needs. flexibility of the model enables organizations to be more agile, react faster to new opportunities, and drive competitive advantage. But the shifting talent base also brings challenges, with new approaches to performance management, risk management, and decision-making required to meet them, according to New Ways of Working ... Managing the Open Workforce, a CGMA report based on a survey of more than 1,100 senior executives. [ILLUSTRATION OMITTED] The workforce is evolving into a mixture of full-time employees, contractors, freelancers, and, increasingly, people with no formal ties to your enterprise at all, Girish Bhat, FCMA, CGMA, the CFO of Gammon India, told researchers. You have to work with people who move more freely from role to role across the organization and across geographical boundaries. trend is most established in the Americas. Thirty-eight percent of respondents in the United States and Canada said that at least half of their workforce was made up of external talent, followed by 36% of those polled in Latin America. In Europe, this was the case for 27% of the companies represented in the survey, 21% in Asia, 17% in the Middle East and North Africa, and 14% in sub-Saharan Africa. shift looks set to continue over the coming years, with 45% of those in the United States and Canada and 36% of respondents in Latin America and Europe predicting that more than half of their workforce will be external in five years. Cost is considered to be the main benefit by leaders in Europe and North America, while respondents in Asia Pacific gave greater priority to the increased exposure to new ideas and specialist knowledge that the model brings, as well as improved organizational agility. CHALLENGES AND RISKS Managing a complex and constantly shifting network of employees, collaborators, and business partners also poses significant challenges. risk of data security breaches was of greatest concern to respondents, followed by disclosure of competitively sensitive information. potential for cultural mismatches and communication difficulties v among the workforce was a further issue highlighted in the study, while some respondents were worried about the effect on their organization's ability to make timely decisions. capacity to retain oversight and control over the performance and productivity of the external workforce is a significant challenge for managers. Of those polled, just 32.6% said that their company had struck the right balance between control and empowerment. key to achieving that balance is being able to articulate the vision of the organization very clearly to everyone, making sure that the staff are on board and that they understand the organizational goals, said Merike Henneman, CPA, CGMA, controller at Destination DC. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,270
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0020,007
Science ouverte0,0050,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,059
Tête enseignante GPT0,301
Écart entre enseignants0,242 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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