Applying Metrics for Predictability

Language:
English
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Feb 23
1:00 pm
5:30 pm
TIMEZONE
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Feb 24
1:00 pm
5:30 pm
TIMEZONE
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Feb 25
1:00 pm
5:30 pm
TIMEZONE
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TIMEZONE
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TIMEZONE
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Virtual
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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 your customers will ask you once you start working for them.


This hands-on workshop will give you the tools to answer those questions predictably. In this tutorial, attendees will learn what metrics are necessary for accurate forecasting, how to visualise 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.


Course details

Make meaningful data-driven decisions, improve your ability to deliver value, and be more effective. After taking the course, you will have an opportunity to validate your understanding of Metrics for Predictability with our online assessment that evaluates your knowledge and provides guidance on areas to improve. Upon passing, you will receive the “Professional Applied Metrics” (PAM) certification and badge through Credly.


Topics

  • Flow Metrics: a deep dive into WIP, Cycle Time, and Throughput
  • Flow Analytics: Cumulative Flow Diagrams (CFDs), Scatterplots, and Monte Carlo
  • Quantifying risk and risk management: how to quantify risk and develop an overall risk profile
  • How to get started: what data to collect, how to mine your data, and how much data you need to begin


What's included in the price

  • Interactive, fun and engaging training
  • One hour of free additional coaching/assessment readiness 
  • Exam token to take the Professional Applied Metrics (PAM) certification by ProKanban.org. This includes a free retake if you're unsuccessful on the first attempt when the token is used within 14 days after the class
  • Digital copy of course materials and copies of relevant books.


Register

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