Applying Metrics for Predictability (AMP)

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Applying Metrics for Predictability will give you the tools you need to answer those questions predictably. In this course, attendees will learn what metrics are necessary for accurate forecasting, how to visualize those metrics in appropriate analytics, how to use those analytics to make reliable forecasts and understand risk, and, finally, how to make meaningful interventions for overall process improvement.

Target Audience

The Applying Metrics for Predictability course is for anyone who may be asked, “When Will It Be Done?” or had to estimate when a User Story, Epic, Feature, or Project will be delivered. This includes executives, managers, product owners, or team members who want better transparency into the health and performance of their process.

Learning Objectives

After attending the course, learners will be able to:

• Define metrics required for predictability
• Create accurate forecasts for single items
• Create accurate forecasts for multiple items (features, epics, etc.)
• Know how to use flow metrics and analytics to achieve a stable process

• Flow Metrics: WIP, Cycle Time and Throughput
• Understanding Little’s Law
• Flow Analytics: Cumulative Flow Diagrams (CFDs), Scatterplots and Histograms
• Forecasting using Monte Carlo Simulation
• Quantifying Risk and Risk Management
• How to Get Started: What data to collect, how to mine your data, and how much data you need to begin