15 Topics
4 Days
Programme Overview
Training Description
Who Should Attend
- Project Coordinators and Project Officers
- Programme and Portfolio Managers
- PMO (Project Management Office) Professionals
- Product Managers
- Business Analysts
- Software Development Team Leads
- DevOps Engineers and Release Managers
- Quality Assurance (QA) and Testing Professionals
- Engineering Managers
- Digital Transformation Managers
- IT Managers and Technology Leaders
- Operations and Process Improvement Managers
- Lean Six Sigma Practitioners
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
The Unlocking Value: Agile Metrics for Success Training Course is designed to help professionals measure, analyze, and optimize the performance of Agile teams, projects, and products through meaningful metrics and data-driven decision-making. As organizations increasingly adopt Agile methodologies, selecting the right metrics is essential for improving productivity, delivering customer value, and fostering continuous improvement.
Through interactive case studies, practical exercises, and real-world scenarios, participants will learn how to build effective Agile dashboards, avoid common metric pitfalls, assess team health, improve delivery predictability, and align Agile performance with organizational objectives. The course also covers the ethical use of metrics, data visualization techniques, and strategies for fostering a culture of continuous learning and improvement.By the end of the training, participants will be able to design and implement Agile measurement frameworks that support informed decision-making, enhance collaboration, increase transparency, and drive sustainable business value across Agile projects and organizations.
Curriculum & Topics
15 Topics | 4 Days
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Subtopic 1.1:
Why metrics matter in an Agile environment
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Subtopic 1.2:
The difference between vanity metrics and actionable metrics
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Subtopic 1.3:
The importance of context and purpose
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Subtopic 1.4:
Establishing a baseline for measurement
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Subtopic 1.5:
The role of metrics in fostering transparency
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Subtopic 2.1:
Introduction to flow and its importance
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Subtopic 2.2:
Measuring Cycle Time and Lead Time
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Subtopic 2.3:
Understanding Work in Progress (WIP)
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Subtopic 2.4:
The role of Cumulative Flow Diagrams (CFDs)
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Subtopic 2.5:
Using metrics to optimize your team's workflow
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Subtopic 3.1:
The purpose and limitations of Velocity
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Subtopic 3.2:
Forecasting with Velocity and other metrics
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Subtopic 3.3:
Understanding team predictability
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Subtopic 3.4:
Using historical data to inform future planning
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Subtopic 3.5:
The importance of stable teams for accurate metrics
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Subtopic 4.1:
Moving beyond output to measure outcomes
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Subtopic 4.2:
Defining and measuring business value
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Subtopic 4.3:
Techniques for quantifying value
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Subtopic 4.4:
The role of the Product Owner in defining value metrics
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Subtopic 4.5:
Communicating value to stakeholders
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Subtopic 5.1:
The importance of quality in Agile
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Subtopic 5.2:
Measuring quality through defect density and escaped defects
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Subtopic 5.3:
Techniques for tracking technical debt
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Subtopic 5.4:
The role of automated testing in improving quality
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Subtopic 5.5:
Using metrics to drive quality improvements
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Subtopic 6.1:
The power of visual data
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Subtopic 6.2:
Creating effective dashboards and charts
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Subtopic 6.3:
Using burndown and burnup charts
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Subtopic 6.4:
Presenting complex data in a simple way
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Subtopic 6.5:
Tailoring reports for different audiences
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Subtopic 7.1:
An overview of popular metrics and their uses
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Subtopic 7.2:
Understanding metrics for team health and morale
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Subtopic 7.3:
Using data to manage dependencies
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Subtopic 7.4:
The role of metrics in managing risk
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Subtopic 7.5:
Selecting the right tools for your metrics
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Subtopic 8.1:
Using flow metrics to find bottlenecks
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Subtopic 8.2:
The theory of constraints in an Agile context
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Subtopic 8.3:
Facilitating a team discussion on bottlenecks
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Subtopic 8.4:
Creating an action plan to resolve issues
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Subtopic 8.5:
The importance of continuous monitoring
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Subtopic 9.1:
Avoiding the use of metrics to punish teams
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Subtopic 9.2:
Fostering a culture of trust and transparency
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Subtopic 9.3:
The importance of team input in metric selection
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Subtopic 9.4:
Using metrics as a tool for coaching
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Subtopic 9.5:
The role of storytelling with data
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Subtopic 10.1:
Analyzing real-world examples of successful metric implementation
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Subtopic 10.2:
Discussing lessons learned from failures
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Subtopic 10.3:
Role-playing exercises with a focus on metrics-based conversations
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Subtopic 10.4:
Peer-to-peer feedback on metric dashboards
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Subtopic 10.5:
Applying learned concepts to real-world scenarios
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Subtopic 11.1:
The importance of customer-centric metrics
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Subtopic 11.2:
Measuring customer satisfaction and Net Promoter Score (NPS)
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Subtopic 11.3:
Techniques for gathering customer feedback
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Subtopic 11.4:
The role of stakeholder engagement in metrics
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Subtopic 11.5:
Using metrics to build credibility with the business
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Subtopic 12.1:
The challenges of measuring at scale
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Subtopic 12.2:
An overview of metrics in SAFe, LeSS, and Nexus
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Subtopic 12.3:
Aligning team metrics with program and portfolio goals
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Subtopic 12.4:
Using metrics to manage dependencies across teams
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Subtopic 12.5:
The importance of a unified data strategy
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Subtopic 13.1:
Using metrics in Sprint Retrospectives
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Subtopic 13.2:
Creating a feedback loop with data
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Subtopic 13.3:
The role of experimentation and A/B testing
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Subtopic 13.4:
The importance of inspecting and adapting your metrics
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Subtopic 13.5:
Building a culture of learning
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Subtopic 14.1:
The role of tools like Jira, Azure DevOps, and others
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Subtopic 14.2:
Setting up dashboards and reports
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Subtopic 14.3:
Automating data collection
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Subtopic 14.4:
Best practices for tool usage
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Subtopic 14.5:
Troubleshooting common data issues
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Subtopic 15.1:
Emerging trends in Agile measurement
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Subtopic 15.2:
The role of AI and machine learning
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Subtopic 15.3:
Measuring the impact of cultural changes
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Subtopic 15.4:
The importance of emotional intelligence in data analysis
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Subtopic 15.5:
The evolving role of the Agile professional
