Cadre de priorisation de fonctionnalités
PROPriorise tes fonctionnalités avec frameworks RICE, ICE ou MoSCoW et justification. Le backlog ordonné rationnellement.
Exemple d'Utilisation
Priorise ces 15 fonctionnalités de notre app avec la méthode RICE et explique le classement.
Comment Utiliser Ce Skill
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Personnalisation Suggérée
| Description | Par défaut | Votre Valeur |
|---|---|---|
| Primary framework to use (RICE, MoSCoW, Kano, Weighted Scoring, Value-Effort) | RICE | |
| Number of features to prioritize in the session | 8 | |
| Percentage of score allocated to strategic alignment (0-1) | 0.25 | |
| Unit for effort estimation (person-months, story points, weeks) | person-months | |
| Minimum confidence percentage for RICE scoring | 70 | |
| Maximum number of large features the team can execute simultaneously | 3 |
Sources de Recherche
Ce skill a été créé à partir de recherches provenant de ces sources fiables :
- RICE Scoring: Framework & Pros/Cons Comprehensive guide to the RICE framework with practical examples and comparison with other methods
- Feature Prioritization Using RICE and ICE Models Detailed comparison of RICE and ICE models with formulas and guidance on when to use each
- 15 Product Feature Prioritization Frameworks Overview of weighted scoring, RICE, value vs. effort, Kano, MoSCoW, and other frameworks
- How to Use the Kano Model to Prioritize Features Step-by-step guide to Kano study design, analysis, and implementation for feature classification
- Common Feature Prioritization Mistakes Analysis of top 7 prioritization mistakes with solutions
- Aha! Feature Prioritization Guide Official PM platform guide covering frameworks, scorecard usage, and cross-functional collaboration
- Product Feature Prioritization Frameworks in Startups Academic systematic review of 54 studies analyzing framework adoption and decision-making
- Product Prioritization Tools & Software Review Evaluation of 10+ tools including Jira, Productboard, and Aha! with feature comparisons
- How do you prioritize features? Reddit Thread Real PM perspectives on S-RICE, value scorecards, and strategic alignment workflows
- AI and ML-Powered Feature Prioritization Research on integrating machine learning and predictive analytics for data-driven prioritization