Training course

Overview

Agile Estimation and Planning Poker is the study and practical application of the principles, techniques, tools, and collaborative practices used to estimate Agile work, forecast delivery, and develop realistic plans in iterative and adaptive project environments. The course covers essential areas such as Agile estimation principles, relative estimation, story points, team-based estimation, Planning Poker, user stories, acceptance criteria, product backlogs, velocity, throughput, capacity, release planning, sprint planning, forecasting, and estimation accuracy. Participants will develop the practical skills required to estimate work collaboratively while recognizing uncertainty, complexity, dependencies, technical risk, and changing requirements.

The primary purpose of effective Agile estimation and planning is to enable teams and stakeholders to make informed decisions about scope, priorities, capacity, delivery expectations, and product outcomes without creating false precision. Agile teams use estimation to support conversations and forecasting rather than to create rigid commitments based on uncertain information. The course incorporates Scrum and Agile principles, Planning Poker, Fibonacci and modified Fibonacci scales, T-shirt sizing, affinity estimation, bucket estimation, relative sizing, velocity analysis, throughput measurement, capacity planning, backlog refinement, release planning, and Monte Carlo forecasting. Participants will learn how to combine quantitative information with team expertise and collaborative judgment to produce useful delivery forecasts.

In today's rapidly changing digital and business environment, Agile teams must continuously respond to evolving customer needs, emerging technologies, market conditions, technical uncertainty, and changing organizational priorities. Traditional detailed upfront estimates can quickly become outdated when requirements change or new information emerges. Agile estimation and planning therefore require flexible approaches that allow teams to progressively refine their understanding of work, use empirical evidence, and adapt plans as delivery data becomes available. This course combines Agile planning practices with practical estimation techniques, uncertainty management, dependency analysis, risk-based estimation, capacity considerations, and data-driven forecasting to improve planning decisions in Scrum, Kanban, and hybrid environments.

Agile Estimation and Planning Poker is therefore essential for Scrum Masters, Product Owners, Agile project managers, product managers, business analysts, software development teams, delivery managers, project coordinators, Agile coaches, PMO professionals, and other professionals responsible for planning and forecasting Agile work. The course combines established Agile frameworks, practical estimation tools, interactive Planning Poker exercises, backlog workshops, case studies, simulations, forecasting activities, and real-world delivery scenarios. Participants progressively develop the ability to prepare estimation-ready user stories, facilitate collaborative estimation sessions, apply appropriate estimation scales, analyze velocity and throughput, forecast releases, manage uncertainty, communicate estimates effectively, and improve estimation practices through empirical learning and continuous improvement.

Course Duration

5 Days (40 Hours)

Target Participants

This course is suitable for:

• Project Managers

• Agile Project Managers

• Scrum Masters

• Product Owners

• Product Managers

• Agile Coaches

• Business Analysts

• Requirements Analysts

• Software Developers

• Software Engineers

• Quality Assurance and Testing Professionals

• UX and UI Professionals

• Technical Leads and Engineering Managers

• Delivery Managers

• Programme Managers

• Project Management Office (PMO) Professionals

• Project Coordinators

• Product Development Teams

• Digital Transformation Professionals

• IT Managers

• Operations Managers

• Change Management Professionals

• Management Consultants

• Business Owners and Entrepreneurs

• Professionals Responsible for Agile Planning, Estimation, Forecasting, and Delivery

Course Objectives

By the end of the training, participants will be able to:

• Understand the principles, purpose, and limitations of Agile estimation and planning.

• Understand the difference between estimation, forecasting, planning, and commitment.

• Apply Agile principles and Scrum practices to iterative estimation and planning.

• Understand relative estimation and why Agile teams estimate size rather than exact duration.

• Apply story points, T-shirt sizing, affinity estimation, and other relative estimation techniques.

• Facilitate effective Planning Poker sessions using structured team discussion and consensus.

• Select appropriate reference stories and establish meaningful estimation baselines.

• Apply Fibonacci and modified Fibonacci estimation scales.

• Prepare user stories and acceptance criteria for effective estimation.

• Identify ambiguity, dependencies, assumptions, technical complexity, and risks that affect estimates.

• Apply team-based estimation and collaborative decision-making techniques.

• Understand velocity, throughput, cycle time, capacity, and other Agile delivery measures.

• Calculate and interpret team capacity for Sprint and iteration planning.

• Use historical delivery data to improve Agile forecasting.

• Develop realistic Sprint plans based on capacity, priorities, dependencies, and team availability.

• Apply backlog refinement techniques to maintain estimation readiness.

• Estimate epics, features, user stories, tasks, and technical work at appropriate levels.

• Apply release planning and roadmap forecasting techniques.

• Use velocity ranges and probabilistic forecasting rather than relying solely on single-point estimates.

• Understand Monte Carlo forecasting and its application to Agile delivery prediction.

• Identify and manage estimation bias, anchoring, optimism bias, groupthink, and false precision.

• Manage disagreement and facilitate constructive conversations during estimation sessions.

• Integrate risk, uncertainty, technical complexity, and dependencies into Agile planning decisions.

• Apply estimation practices in Scrum, Kanban, and hybrid delivery environments.

• Use digital Agile tools to facilitate Planning Poker, backlog estimation, capacity planning, and forecasting.

• Communicate Agile estimates and forecasts effectively to stakeholders and decision-makers.

• Avoid common estimation anti-patterns, including estimating hours unnecessarily, forcing consensus, and converting story points directly into fixed deadlines.

• Improve estimation practices through retrospectives, empirical data, and continuous improvement.

• Develop practical strategies for improving estimation quality, forecasting reliability, and delivery predictability.

• Apply Agile estimation and planning techniques to realistic workplace scenarios and complex delivery environments.

Course Content

Day 1: Foundations of Agile Estimation and Relative Sizing

Module 1: Agile Estimation Principles, User Stories, and Collaborative Sizing Fundamentals

Topics

1. Overview of Agile Estimation and Planning Principles
2. Agile Planning, Estimation, Forecasting, and Commitment
3. Agile Manifesto Principles and Empirical Planning Practices
4. Scrum Framework, Product Backlog, Sprint Planning, and Backlog Refinement
5. Relative Estimation Versus Traditional Time-Based Estimation
6. Story Points, Complexity, Effort, Risk, and Relative Size
7. Estimation Scales: Fibonacci, Modified Fibonacci, and T-Shirt Sizing
8. Preparing Estimation-Ready User Stories and Acceptance Criteria
9. Practical Exercise: Establishing Reference Stories and Estimating a Product Backlog
10. Case Study: Correcting Poor Agile Estimates Caused by Ambiguous Requirements and False Precision

Day 2: Planning Poker and Collaborative Agile Estimation

Module 1: Planning Poker Facilitation, Consensus Building, and Estimation Techniques

Topics

1. Principles, Purpose, and Benefits of Planning Poker
2. Planning Poker Roles, Rules, Preparation, and Facilitation
3. Presenting User Stories and Clarifying Acceptance Criteria
4. Selecting Reference Stories and Establishing Estimation Anchors
5. Fibonacci-Based Planning Poker and Relative Sizing Techniques
6. Handling Estimation Differences, Outliers, and Disagreement
7. Identifying Complexity, Uncertainty, Dependencies, and Technical Risk During Estimation
8. Planning Poker Anti-Patterns, Estimation Bias, Anchoring, and Groupthink
9. Practical Exercise: Facilitating a Complete Planning Poker Estimation Workshop
10. Simulation Exercise: Estimating a Complex Product Backlog With Conflicting Team Perspectives

Day 3: Capacity, Velocity, Throughput, and Sprint Planning

Module 1: Agile Capacity Planning, Delivery Metrics, and Iteration Forecasting

Topics

1. Agile Capacity Planning Principles and Team Availability
2. Velocity: Calculation, Interpretation, Limitations, and Appropriate Use
3. Throughput, Cycle Time, Work Item Aging, and Flow Metrics
4. Historical Delivery Data and Empirical Forecasting
5. Sprint Capacity, Team Availability, Holidays, Leave, and Operational Commitments
6. Sprint Planning Using Prioritized Backlogs, Estimates, and Capacity
7. Managing Dependencies, Technical Work, Defects, Spikes, and Unplanned Work
8. Forecasting With Velocity Ranges and Delivery Trends
9. Practical Exercise: Calculating Capacity and Developing a Realistic Sprint Plan
10. Case Study: Replanning an Agile Release After Significant Changes in Team Capacity and Velocity

Day 4: Release Planning, Forecasting, and Managing Uncertainty

Module 1: Advanced Agile Forecasting, Probabilistic Planning, and Delivery Prediction

Topics

1. Agile Release Planning and Product Roadmap Alignment
2. Feature, Epic, and Release-Level Estimation
3. Forecasting Release Scope, Timing, and Delivery Outcomes
4. Managing Uncertainty, Variability, Risks, and Estimation Ranges
5. Dependency Mapping and Cross-Team Estimation
6. Probabilistic Forecasting and Monte Carlo Simulation Fundamentals
7. Throughput-Based and Velocity-Based Forecasting Approaches
8. Communicating Forecasts, Confidence Levels, Scenarios, and Assumptions to Stakeholders
9. Practical Exercise: Developing a Probabilistic Agile Release Forecast
10. Case Study: Forecasting a High-Visibility Product Release With Uncertain Scope and Multiple Dependencies

Day 5: Advanced Estimation, Forecast Improvement, and Integrated Application

Module 1: Strategic Agile Estimation, Continuous Improvement, and Workplace Implementation

Topics

1. Advanced Agile Estimation and Planning Strategies
2. Estimation Across Scrum, Kanban, Scaled Agile, and Hybrid Environments
3. Improving Estimation Accuracy Through Historical Data and Empirical Learning
4. Managing Estimation Bias, Cognitive Biases, and Stakeholder Pressure
5. Integrating Estimation With Risk Management, Prioritization, Capacity, and Value Delivery
6. Digital Planning Poker Tools, Agile Boards, Backlog Management, and Forecasting Platforms
7. Advanced Forecasting, Scenario Analysis, and Confidence-Based Delivery Planning
8. Practical Workshop: Developing an Integrated Agile Estimation, Planning, and Forecasting Framework
9. Integrated Case Study: Replanning a Complex Agile Product With Changing Priorities, Limited Capacity, Technical Debt, and Delivery Uncertainty
10. Final Assessment, Course Review, Personal Action Plan, and Workplace Implementation Strategy