15 Topics
4 Days
Programme Overview
Training Description
Who Should Attend
This course is designed for;
- Scrum Masters
- Agile Coaches
- Team Leads
- Product Owners
- Business Analysts
- Project Managers
- Software Developers
- Quality Assurance Professionals
- Organizational Leaders
- Anyone interested in measuring and improving team performance
Session Objectives
- Understand the purpose and principles of Agile metrics
- Differentiate between good and bad metrics
- Learn to collect and interpret key metrics for flow
- Use data to improve team predictability and forecasting
- Understand how to measure business value in an Agile context
- Master techniques for visualizing data for stakeholders
- Learn to use metrics to identify and address bottlenecks
- Create a data-driven culture of continuous improvement
- Understand the importance of qualitative feedback alongside metrics
- Use metrics to justify and demonstrate the value of Agile
About the Course
In the fast-paced world of Agile, data-driven decisions are the key to unlocking true success. This "Unlocking Value: Agile Metrics for Success Training Course" is a comprehensive program designed to equip you with the knowledge and skills to move beyond simple velocity charts and leverage meaningful metrics to improve team performance, stakeholder communication, and business outcomes. You will learn to identify the right metrics for your context, understand what they truly represent, and use them to tell a compelling story about your team's progress and value delivery.
Over this intensive 10-day course, you will gain hands-on experience in collecting, visualizing, and interpreting a wide range of Agile metrics. From flow efficiency and cycle time to customer satisfaction and business value, you will discover how to use data to foster a culture of continuous improvement and transparency. By the end of this program, you will be able to not only track your team's performance but also use metrics as a powerful tool for strategic decision-making and continuous value creation
Curriculum & Topics
15 Topics | 4 Days
-
Subtopic 1.1:
Why metrics matter in an Agile environment
-
Subtopic 1.2:
The difference between vanity metrics and actionable metrics
-
Subtopic 1.3:
The importance of context and purpose
-
Subtopic 1.4:
Establishing a baseline for measurement
-
Subtopic 1.5:
The role of metrics in fostering transparency
-
Subtopic 2.1:
Introduction to flow and its importance
-
Subtopic 2.2:
Measuring Cycle Time and Lead Time
-
Subtopic 2.3:
Understanding Work in Progress (WIP)
-
Subtopic 2.4:
The role of Cumulative Flow Diagrams (CFDs)
-
Subtopic 2.5:
Using metrics to optimize your team's workflow
-
Subtopic 3.1:
The purpose and limitations of Velocity
-
Subtopic 3.2:
Forecasting with Velocity and other metrics
-
Subtopic 3.3:
Understanding team predictability
-
Subtopic 3.4:
Using historical data to inform future planning
-
Subtopic 3.5:
The importance of stable teams for accurate metrics
-
Subtopic 4.1:
Moving beyond output to measure outcomes
-
Subtopic 4.2:
Defining and measuring business value
-
Subtopic 4.3:
Techniques for quantifying value
-
Subtopic 4.4:
The role of the Product Owner in defining value metrics
-
Subtopic 4.5:
Communicating value to stakeholders
-
Subtopic 5.1:
The importance of quality in Agile
-
Subtopic 5.2:
Measuring quality through defect density and escaped defects
-
Subtopic 5.3:
Techniques for tracking technical debt
-
Subtopic 5.4:
The role of automated testing in improving quality
-
Subtopic 5.5:
Using metrics to drive quality improvements
-
Subtopic 6.1:
The power of visual data
-
Subtopic 6.2:
Creating effective dashboards and charts
-
Subtopic 6.3:
Using burndown and burnup charts
-
Subtopic 6.4:
Presenting complex data in a simple way
-
Subtopic 6.5:
Tailoring reports for different audiences
-
Subtopic 7.1:
An overview of popular metrics and their uses
-
Subtopic 7.2:
Understanding metrics for team health and morale
-
Subtopic 7.3:
Using data to manage dependencies
-
Subtopic 7.4:
The role of metrics in managing risk
-
Subtopic 7.5:
Selecting the right tools for your metrics
-
Subtopic 8.1:
Using flow metrics to find bottlenecks
-
Subtopic 8.2:
The theory of constraints in an Agile context
-
Subtopic 8.3:
Facilitating a team discussion on bottlenecks
-
Subtopic 8.4:
Creating an action plan to resolve issues
-
Subtopic 8.5:
The importance of continuous monitoring
-
Subtopic 9.1:
Avoiding the use of metrics to punish teams
-
Subtopic 9.2:
Fostering a culture of trust and transparency
-
Subtopic 9.3:
The importance of team input in metric selection
-
Subtopic 9.4:
Using metrics as a tool for coaching
-
Subtopic 9.5:
The role of storytelling with data
-
Subtopic 10.1:
Analyzing real-world examples of successful metric implementation
-
Subtopic 10.2:
Discussing lessons learned from failures
-
Subtopic 10.3:
Role-playing exercises with a focus on metrics-based conversations
-
Subtopic 10.4:
Peer-to-peer feedback on metric dashboards
-
Subtopic 10.5:
Applying learned concepts to real-world scenarios
-
Subtopic 11.1:
The importance of customer-centric metrics
-
Subtopic 11.2:
Measuring customer satisfaction and Net Promoter Score (NPS)
-
Subtopic 11.3:
Techniques for gathering customer feedback
-
Subtopic 11.4:
The role of stakeholder engagement in metrics
-
Subtopic 11.5:
Using metrics to build credibility with the business
-
Subtopic 12.1:
The challenges of measuring at scale
-
Subtopic 12.2:
An overview of metrics in SAFe, LeSS, and Nexus
-
Subtopic 12.3:
Aligning team metrics with program and portfolio goals
-
Subtopic 12.4:
Using metrics to manage dependencies across teams
-
Subtopic 12.5:
The importance of a unified data strategy
-
Subtopic 13.1:
Using metrics in Sprint Retrospectives
-
Subtopic 13.2:
Creating a feedback loop with data
-
Subtopic 13.3:
The role of experimentation and A/B testing
-
Subtopic 13.4:
The importance of inspecting and adapting your metrics
-
Subtopic 13.5:
Building a culture of learning
-
Subtopic 14.1:
The role of tools like Jira, Azure DevOps, and others
-
Subtopic 14.2:
Setting up dashboards and reports
-
Subtopic 14.3:
Automating data collection
-
Subtopic 14.4:
Best practices for tool usage
-
Subtopic 14.5:
Troubleshooting common data issues
-
Subtopic 15.1:
Emerging trends in Agile measurement
-
Subtopic 15.2:
The role of AI and machine learning
-
Subtopic 15.3:
Measuring the impact of cultural changes
-
Subtopic 15.4:
The importance of emotional intelligence in data analysis
-
Subtopic 15.5:
The evolving role of the Agile professional
