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Improve the success of your DMAIC or Six Sigma projects with these practical tips

What you will learn

Identify good Six Sigma project ideas

Recognize the difference between traditional Project Management and Six Sigma

Ways to get buy-in for projects from management and workers

Appreciate the importance of milestones and celebrating benefits

Description

This course will provide you with an overview of the most frequent challenges new Green Belt facilitators face. This will be particularly helpful if you are just starting your DMAIC or Six Sigma Project.

Most Green Belt courses today focus on Statistics. These skills are needed, however the majority of students struggle not with Data Analysis and Statistics but with the people and organizational culture they encounter when leading improvement projects.

People are resistant to change. This makes it essential for you to have both Project and Change management skills to successfully execute your project.


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These five tips covered in this course are the common roadblocks you will encounter when executing Lean Six Sigma projects. Including some recommendations to improve the likeliness improvements will be sustained in the long-term. These support your Six Sigma journey while giving you the Project and Change management support to meet your goals.

Lean Six Sigma or DMAICΒ is applicable regardless of your industry or location. If you’ve struggled to apply these tools you will find these tips helpful both in getting started on your project and throughout project execution. This course is intended for those that have some background in Lean Six Sigma and are looking to apply the structured problem solving tool of DMAIC.

English
language

Content

Introduction

Welcome and Introduction

5 Quick Tips

Identifying the right project
Project Management vs Lean Six Sigma Projects
Managing Change to Get Buy-in
Seeing the Real Process or Work
How to Use the Control Phase to Make Changes Stick

Wrap-Up

Wrap-Up and Thank You
Extra: The 3 Questions You Need to Answer with Data