L'impact de la digitalisation des systèmes d'information sur le métier des contrôleurs de gestion : une revue de littérature
Bibliographic record
Abstract
Résumé L'introduction des technologies de l'information et de la communication (TIC) a transformé les méthodes de travail et les pratiques de gestion au sein des organisations. Traditionnellement, les contrôleurs de gestion se concentraient sur la collecte et l’analyse des données financières, des tâches lourdes et chronophages. Toutefois, la digitalisation des processus financiers et l'émergence des progiciels de gestion intégrés (ERP) ont révolutionné cette fonction. Ces outils automatisent la gestion des données, permettant une prise de décision plus rapide et efficace. Ainsi, la digitalisation a non seulement amélioré les outils de gestion, mais a aussi redéfini le rôle des contrôleurs de gestion, les tournant vers des missions plus stratégiques et proactives. Cet article propose, à partir d’une revue de littérature, d'examiner l’impact de la digitalisation des organisations et l’intégration des ERP sur cette profession en constante mutation. Mots clés : le contrôle de gestion ; transformation digitale ; ERP, changement organisationnel, système d’information. Abstract The introduction of information and communication technologies (ICT) has changed how organizations work and manage their activities. Traditionally, management controllers focused on collecting and analyzing financial data, which was time-consuming and demanding. However, the digitalization of financial processes and the rise of enterprise resource planning (ERP) systems have changed this role. These tools automate data management, making decision-making faster and more efficient. As a result, digitalization has not only improved management tools but has also changed the role of management controllers, making it more strategic and proactive. This article, based on a literature review, aims to look at the impact of digitalization in organizations and the integration of ERP on this profession, which is constantly changing. Keywords : management control; digital transformation; ERP, organizational change, information system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".