- Short Summary
Achieving predictable Agile delivery is a challenge—traditional planning methods relying on velocity and gut-feel estimates often fall short.

This hands-on, interactive workshop introduces three powerful, data-driven forecasting techniques:

* Evidence-Based Management (EBM) – Aligning Agile delivery with business outcomes.
* Monte Carlo Forecasting – Replacing unreliable estimates with probabilistic forecasting that stakeholders can trust.
* Flow Metrics – Using Work In Progress (WIP), Cycle Time, and Throughput to optimize team efficiency and eliminate bottlenecks.

Through custom dice-based simulations and real-world scenarios, participants will shift from deterministic deadlines to probabilistic decision-making, gaining practical techniques to improve forecasting, stakeholder alignment, and delivery confidence.

- Full Session Description / Abstract
Why do so many Agile teams struggle with predictability?
Because they rely on outdated planning techniques that don’t reflect real-world variability. Velocity-based forecasts fail under uncertainty, leading to missed expectations, reactive decision-making, and frustrated stakeholders.

In this workshop, participants will learn and apply modern forecasting and flow techniques that turn uncertainty into actionable, data-driven insights. Through interactive simulations and hands-on exercises, attendees will discover how to use Monte Carlo Forecasting, EBM, and Flow Metrics to improve delivery planning and optimize team performance.

What You’ll Experience
Introduction – Why Traditional Agile Planning Fails
* Common challenges in Agile forecasting and planning.
* The Triforce of Predictable Delivery: Monte Carlo Forecasting, EBM, and Flow Metrics.

Monte Carlo Forecasting: Simulating Reality for Smarter Decisions
* Hands-on Dice-Based Forecasting Exercise – Participants simulate delivery variability using digital dice tools (or physical dice at home), recording results in a shared worksheet.
* Shifting Mindsets – Moving from deterministic deadlines to probabilistic, confidence-based delivery conversations.
* Visualizing Forecasts – Using sticky notes, participants compare deterministic vs. probabilistic predictions.

Evidence-Based Management (EBM) & The Hidden Impact of Defects
* Defect Simulation – Participants use digital dice to model how emergent work and production incidents disrupt delivery.
* Key Value Areas (KVAs) – Understanding Technical Debt, Production Incidents, and Innovation Rate to drive better decisions.

Flow Metrics & Aging WIP: Improving Team Efficiency
* Understanding Work In Progress (WIP), Cycle Time, and Throughput – and how they impact flow.
* Interactive Bottleneck Mapping – Participants visualize aging WIP and simulate queueing theory principles.
* “Stop Starting, Start Finishing” – How to apply WIP limits and optimize flow for faster, more predictable delivery.

Wrap-Up & Action Planning
* Creating Personalized Action Plans – How to apply these techniques with real stakeholders and teams.
* Live Group Discussion & Q&A – Ensuring participants leave with confidence and actionable insights.

Key Takeaways
* Replace unreliable velocity-based planning with probabilistic forecasting that stakeholders can trust.
* Simulate real-world unpredictability using Monte Carlo techniques—developing confidence intervals for delivery.
* Understand how escape defects and emergent work disrupt delivery—and how to mitigate their impact.
* Use Flow Metrics to identify bottlenecks and optimize efficiency, reducing time spent on in-progress work.
* Shift the conversation with leadership—move from gut-feel estimates to data-driven decision-making.