Les entreprises se préoccupent-elles vraiment de la faisabilité de leurs projets? Révélations de 64 acteurs clés provenant de 14 entreprises variées
Bibliographic record
Abstract
La gestion de projet (GP) vit un déconcertant paradoxe. D’une part, jamais les conditions n’ont été aussi favorables pour sa pratique. La mouvance et le caractère désordonné des contextes managériaux d’aujourd’hui ont contribué à accroitre le nombre, l’importance, l’urgence et le rythme des projets entrepris. Synchroniquement, formations, bureaux de projets, techniques et intervenants se sont multipliés. D’autre part, jamais les résultats obtenus au terme des projets n’ont été aussi misérables. Plusieurs recherches font état de taux très élevés de projets abandonnés ou échoués, qui ne respectent pas ou qui excèdent les contraintes établies. Ce triste constat a inspiré l’objectif principal de cette recherche, soit explorer comment des entreprises du Québec se préoccupent de la faisabilité de leurs projets. Grâce à une approche qualitative instrumentée dans un guide d’entrevue, 64 acteurs clés de l’étude de la faisabilité de projet de 14 entreprises variées ont été interviewés. Leurs révélations éclairent la cruciale question de l’étude de faisabilité des projets, souvent négligée ou éliminée en pariant que temps et argent seront ainsi économisés. Project management (PM) encounters a disconcerting paradox. On one hand, never conditions have been so favourable for its practice. Changing and incoherent character of today's management contexts contributed to increase the number, the importance, the emergency and the rhythm of projects undertaken. Synchronically, trainings, project’s offices, techniques and stakeholders increased. On the other hand, never results obtained at the end of projects have been so poor, so miserable. Several researches reported very high rates of abandoned or failed projects, which do not respect or that exceed established constraints. These sad outcomes inspired the main objective of this research, to explore how of Quebec’s firms are concerned about the feasibility of their projects. Thanks to a qualitative approach instrumented in an interviewing guide, 64 key actors of project’s feasibility studies in 14 various firms were interviewed. Their revelations light critical question of project’s feasibility studies, often neglected or eliminated, betting it will economize time and monney.
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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 | 0.021 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".