Framework de Priorização de Features
PRODomina frameworks RICE, MoSCoW, Kano e pontuação ponderada para priorizar features de produto. Toma decisões de roadmap data-driven com alinhamento de stakeholders.
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Personalização Sugerida
| Descrição | Padrão | Seu Valor |
|---|---|---|
| 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 |
Fontes de Pesquisa
Este skill foi criado usando pesquisa destas fontes confiáveis:
- 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