PRIORITIZATION FRAMEWORKS for your product | Make better decisions as a product manager?

RICE Framework: RICE stands for Reach, Impact, Confidence, and Effort. It helps in assessing the value of different product features by considering their potential reach, impact on user behavior, confidence in estimates, and the effort required for implementation. Reach is determined by the number of people expected to benefit from the feature. Impact measures the influence of the feature on user decision-making. Confidence evaluates how certain the team is about the provided scores, while Effort gauges the resources needed for implementation. MoSCoW Model: MoSCoW stands for Must have, Should have, Could have, and Won't have. It assists in prioritizing product or project features based on their importance and urgency. Must-haves are essential features for the minimum viable product (MVP). Should-haves are important but not critical, while Could-haves are optional. Won't-haves are deliberately excluded features, to be considered later or not at all. Kano Model: The Kano model classifies features into Must-be Qualities, Attractive Qualities, and Indifferent Qualities. Must-be Qualities are basic necessities that, if lacking, result in a negative user experience. Attractive Qualities are delighters that differentiate the product and elevate it above competitors. Indifferent Qualities don't significantly impact user satisfaction and can be neutral. Value vs. Effort Framework: This framework plots features on a graph based on the value they bring to customers and the effort required for implementation. Easy wins are low-effort, high-impact features. Incremental gains are moderate-effort, high-impact features. Money pits are high-effort, low-impact features. Incremental items are low-effort, low-impact features that add incremental value. Priority Poker: Priority Poker involves team members anonymously assigning priority scores to features on a scale (e.g., 1 to 5). It helps in collectively determining feature priorities and avoids biases. Often used in agile planning, it ensures diverse perspectives and facilitates efficient feature prioritization in a collaborative manner.