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Advanced ScrumMaster Training Part 2 - Data Analytical Methods and Root Cause Analysis for Effective Barrier-Busting
Length:
2 Days
Description:
One of the most important parts of a ScrumMaster’s role is to remove barriers. Data analysis and root cause analysis methods, should be a powerful tools in the ScrumMaster’s arsenal. Unfortunately, with all the blogs, articles, books, lectures and tweets on Scrum best practices, there are very few on utilizing these methods for solving barriers within a Scrum deployment and even fewer practitioners, often resulting in symptoms, not the underlying root causes being attacked.
This interactive and activity-based course looks at teaching any Scrum practitioner, especially ScrumMasters an effective, new way to identify, find the root causes of and solve some of the hardest issues. Participants will be taught how to separate easy-to-solve problems from symptoms, create and prove hypotheses, employ root-cause analysis methods to find hidden root causes of the barriers, issues or gap. The course includes instructor experiences, case studies, and several in-class exercises that enable participants to build knowledge and skills through active participation instead of simply lectures.
Topics:
Introduction to data analysis
Why use data and analytical methods?
Where are analytical methods applicable in your role?
Defining the barrier, issue or problem
Understanding the problem
Process maps
Value-stream maps
Spaghetti diagrams
Y-to-x flow-down diagrams
Fishbone diagrams
Measuring and understanding the problem
Types of data
Summary statistics
Validating data collection
Distributions of data
Understanding the root causes
Generating hypotheses
5 Whys
Graphical displays
Time based analysis
Run and median charts
Introduction to control charts
Relational issues
Continuous improvement
Who should take this course?
While this course is made for ScrumMasters and change agents whose role includes breaking barriers, it is suitable for anyone who would like to or needs to solve problems and would like to do so using data and analytical methods to attack deeper, hidden root causes and not simply cover up symptoms.