Value-driven prioritization training

In this training, you'll learn how to make better choices for your backlog, roadmap, or portfolio. You'll work with techniques like WSJF, MoSCoW, RICE, and Kano, and discover how AI can help structure input and options.

You'll leave with a practical approach to make priorities value-driven, transparent, and explainable.

Value is more than just revenue or business impact. We examine customer value, organizational value, strategic value, risk reduction, learning value, and opportunity value.

You'll learn how to make value tangible for backlog items, features, roadmap initiatives, and portfolio items. We differentiate between output and outcome: focusing not just on what you deliver, but primarily on the effect you aim to achieve.

You'll become familiar with practical prioritization techniques such as MoSCoW, RICE, Kano, impact/effort, and WSJF. You'll learn when each method is appropriate, what its limitations are, and how to prevent prioritization from becoming a deceptively precise calculation.

The focus isn't on blindly applying a single model, but on choosing an approach that fits your specific context: whether it's a backlog, roadmap, MVP scope, product discovery, portfolio, or PI Planning.

WSJF helps prioritize work based on economic value and relative size. You'll work with Business Value, Time Criticality, Risk Reduction / Opportunity Enablement, and Job Size.

You'll learn how to make Cost of Delay practical, how to estimate Job Size, and how to discuss differences in scores. Afterwards, you'll apply WSJF to example items or your own cases, experiencing firsthand how the method helps make priorities more transparent.

WSJF is not a replacement for discussion. It's a way to facilitate better conversations about value, urgency, risk, and effort.

AI is changing how Product Owners, Product Managers, and Agile teams analyze information and prepare decisions. In this section, you'll learn how AI can assist with value-driven prioritization, without AI making the decisions for you.

You'll practice with applications such as:

• clustering customer feedback;
• making assumptions and risks visible;
• formulating backlog items or features more precisely;
• exploring arguments for and against priorities;
• structuring stakeholder input;
• preparing initial prioritization criteria;
• comparing scenarios for backlog, roadmap, or portfolio.

‍

We also address limitations: bias, data quality, loss of context, and the risk of false certainty. AI supports thinking, but valuable choices remain human work.

Prioritization is not a spreadsheet exercise. The value lies in the conversation. You'll practice how to discuss differences in scores, manage stakeholder pressure, and make decisions explainable without every wish automatically rising to the top.

You'll learn how to facilitate a prioritization discussion as a Product Owner, Product Manager, Scrum Master, or Agile Coach. We'll cover transparency, decision-making, mandate, and handling conflicting interests.