Mon, 28 December 2015
This week we are kicking off our 10 Minutes with Dr. Deming series. In this new series moderator Tripp Babbitt will cover, in 10-minute segments, a variety of topics that Dr. Deming spoke about in his seminars and speeches. In our first “10-minute” podcast, Tripp discusses innovation, mentioned prominently in Dr. Deming’s books, Out of the Crisis and The New Economics. Enjoy!
If you have comments or suggestions for future 10 Minutes with Dr. Deming topics, please contact Tripp at email@example.com or through Twitter @demingpodcast.
Thu, 3 December 2015
Lynda Finn, President of Statistical Insight, LLC and facilitator for The Deming Institute – A Picture Is Worth A Thousand Data Points.
This week's podcast features the first episode of our "Knowledge In Variation Series" with Lynda Finn, President of Statistical Insight, LLC and facilitator of The Deming Institute's 2.5 Day Seminar. Lynda discusses the importance of moving from spreadsheets to plotting data, and the common mistakes that organizations make if they aren't charting their data.
Lynda's Deming journey began when, shortly out of graduate school, she met Dr. Deming at one of his public seminars. From that point she has been helping spread his ideas through her own consulting company and her work with The Deming Institute.
She starts by sharing some of the hardest things for people to grasp about the Deming philosophy. Though it varies, Lynda finds it's most difficult when Deming's ideas don't align with the practices people feel have contributed their success.
The episode centers on why organizations should be plotting their data on charts rather than just using spreadsheets. She feels that if the number is important enough to have on a table, then it should be important enough to see it in its proper context.
Lynda outlines the mistakes people make if they aren't charting their data, starting with not caring enough to see what the data is telling them. The most important reason for charting data is so that everyone sees the same thing and can come to a common conclusion about what's happening and how to improve. How can you "see" what the data's telling you if you don't make a picture of it?