​​​Applying Metrics for Predictability - April 1-3, 2025, 10:30am-2:30pm eastern time each day - Register here!

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"When will it be done?"

“How many items will I get in the next release?” 

“When will all of the items in the backlog be completed?” 

Those are some of the first questions that your customers will ask you once you start work for them.

This hands-on workshop will provide you with the tools you need to answer those questions predictably. 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 how to make meaningful interventions for overall process improvement.

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Learning Outcomes:

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After attending the course, learners will have:

• An understanding of which Lean/Agile metrics are necessary for predictability

• An ability to make accurate forecasts for single items including how to forecast when an individual story, epic, or feature will be done

• An ability to make accurate forecasts for multiple items including how to know when all items remaining in a backlog will be done; or an ability to project how many items will be completed by a given release date and the risks associated with each

• An understanding of how to use flow metrics and analytics to achieve a stable process, including an understanding of why a stable process is necessary for accurate forecasting

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Topics:

• Flow Metrics: a deep dive into WIP, Cycle Time, and Throughput—including why you need to track them, how they are related through Little’s Law, and why they are important for forecasting

• Flow Analytics: an introduction to Cumulative Flow Diagrams (CFDs), Scatterplots, Histograms, and other supporting charts—including a detailed discussion of what they are, how to generate them correctly, and how to utilize them for better predictability

• Forecasting Using Monte Carlo Simulation: how to use flow metrics to answer “When will it be done?”—including an introduction to Monte Carlo Simulation and statistical sampling methods for forecasting (no advanced mathematics required!)

• Quantifying Risk and Risk Management: how an understanding of risk is crucial to developing accurate forecasts—including how to quantify risk in the different analytics charts and how changing forecast inputs can help to develop an overall risk profile

• How to Get Started: how to immediately apply these techniques to your current context to achieve the results you are looking for—including what data to collect, how to mine your data, and how much data you need to begin

Validated Learning:

After taking the course, attendees will have an opportunity to validate their understanding of metrics and forecasting topics via an exam for the ProKanban "Professional Applied Metrics" certification.

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Interested in a private ProKanban course for an individual or a group?  Contact Betsy to learn more!  

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