Agile Metrics and Coaching using Data

Learn how to design, capture and display data for organization and team improvement.

Description

This one-day workshop teaches practical data capture and visualization techniques applied to any flavor of Agile software development. Learn easy ways to capture and use data for organizational and team improvements. 

The Agenda at a glance:

  • The Five Rules of using Metrics
  • Visualization Theory and Practice
  • The Six Performance Dimensions
  • Spotting Wrong - Anomaly Detection
  • Finding Balance and using Polarities for Coaching
  • Survey Data Theory and Practice
  • Data Stewardship

Who is this course for?

Agile metrics and coaching using data will benefit people in the following roles:

  • Managers
  • Team leads
  • Scrum masters
  • Agile coaches

More generally, it is perfect for:

  • Anyone who wants to use data for managing and improving organizations and teams.

Learning outcomes

  • To learn what data to capture and why
  • To learn how to display data to cause action
  • To learn how to coach people on balance across multiple competing metrics
  • To learn what dimensions are essential to measure and balance
  • To learn how to capture, store and manage data as an asset for future planning
  • To learn how to create and capture survey data on team and organizational health

Detailed Agenda

  • The Golden Rules of Metrics
  • The Six Performance Dimensions (and Counter-Measures)
  • Performance Measures Debrief
  • Visualization basics
  • Exploring Legacy charts
  • Outcome-Driven Metrics
  • Insight Driven Chart Alternatives
  • Debrief: Gallery Walk Examples & Alternatives
  • Survey Theory
  • Exercise: Survey data
  • Debrief: Sustainability survey
  • Anomaly Detection
  • Exercise: Anomaly Jeopardy
  • Exercise: Anomalize your performance measures from this morning
  • Debrief: Key takeaways about anomaly detection
  • Coaching using Polarities
  • Debrief: Polarity early warning signs
  • Getting reliable data from people and tools
  • Storing Data
  • Exercise: Tagging and Deleting (archiving) Data
  • Debrief: Data Policies
  • Key take-aways

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