Full course description
Learn how to derive meaning from data; Introduce statistical thinking, concepts, basic methods, and language essential to practical problem solving, process design, analysis, improvement, and management. Lay the foundation for statistically-based methods in Six Sigma Green and Black Belt.
One old process improvement professional’s refrain is that you can’t improve something that you can’t define. Another is that you can’t improve something until you can measure it. Quantifying the gap between your ideal state – where you want to go – and the current state of things is essential to being to do so and necessary to enable you to communicate your project background and goals to others. But it’s not only about measuring effects. You can’t improve something and achieve the full potential until you can measure the causes – i.e., the factors that determine the results that you are interested in. This is the very essence of the Six Sigma side of things. Quantitative methods are what make Six Sigma and other applications of the primary scientific method to discover and solve problems so robust – and sustainable.
Why Take This Course
This introductory course to quantitative methods forms the basis for everything else you do in Six Sigma and generally for process improvement. It introduces concepts for measuring and visualizing data and treating it to extract meaning – confirm what you already might know about something and expose truths you may never have imagined.
The course is intended to get you warmed-up to quantitative methods by taking you through the fundamental definitions, concepts, and techniques. You will be able to discover some pretty amazing things about things relevant to your problem solving or opportuning realizing quest.
What You Will Learn
- Learn common, unique and assignable cause variation and signal and noise concepts
- Practice normal distribution and area under the curve
- Implement histograms, distributions, the measures of a distribution - parameters, and statistics.
- Review normality testing, causes of non-normality and the importance
- Discuss interpretation and reaction to particular cause variation
- Review run charts
You will leave this course with:
- How to describe data visually and quantitatively.
- What are statistics, why it’s your best friend, why it can be fun, and how it unlocks the secrets to your process or product improvement initiatives?
- How to interpret what you describe with methods such as histograms, box and whisker plots, run charts, and basic statistical control charts.
- How and where to apply the methods in your problem solving or process or product improvement project.
Who Should Attend
- Anyone who aspires to continue their training and certification in LSS.
- Anyone who wants to become skilled in and more effective in solving problems or realizing improvement opportunities.
- Those will want to support large and small problem-solving initiatives that others lead.
- It is required for LSS Yellow Belt, Green, and Black certification candidates.
Course ScheduleDay 1: 8:00 a.m.- 4:30 p.m. Tuesday, September 1, 2020
Course Location: OSU Portland Center, 555 SW Morrison Street, Portland, OR 97204
Managing Partner and Co-Founder NWCPE
Steve Zagarola is a Six Sigma Executive Master Black Belt certified by Mikel Harry – a co-founder of the Six Sigma methodology. Steve has more than 25 years’ experience in the application of statistical and modern structured approaches to the optimization of manufacturing and transactional processes, quality systems, and R&D. He has worked with and provided training and consulting for industries ranging from apparel manufacturing, advanced semiconductors, food and beverage, plastics molding, and wind energy in both the manufacturing and service and administration sectors. He has worked to improve manufacturing operations for global organizations on six continents and in English, Spanish, and German. Steve also served Six Sigma Program and Quality Manager at Vestas Wind Systems and as Director of Quality for Cascade Microtech and as a Senior Manufacturing Manager at The Coca-Cola Company. He provided technical editing for the 2012 edition of Six Sigma for Dummies for John Wiley & Sons. Steve is fluent in English, Spanish, Italian, and German. He earned a BS in Mechanical Engineering from Georgia Tech and completed post-graduate studies in Psychology and Statistics at Georgia Tech and Georgia State University and with Dr. Douglas Montgomery.
Principal and Co-Founder NWCPE
Tom has been teaching leadership, kaizen, and Lean Systems for over thirty years in a wide range of industries, including health care, automotive, aerospace, and food processing. He is the President and founder of Lean Manufacturing Tools, co-founder of the Northwest Center for Performance Excellence. He received his original Lean training from first-generation experts including Dr. Shigeo Shingo (co-architect of The Toyota Production System), Hiroyuki Hirano (author and noted JIT expert), Dr. Ryuji Fukuda (member of The Sigma Project in Japan and winner of the Deming Prize), and TPM experts from Japan Institute of Plant Maintenance. Tom has authored several books on Lean, including Lean Tooling, The Five Keys to Lean in Healthcare, 5S for the Office, The Lean Primer, and Value Stream Management. Current and former clients include Multnomah County Clinics, Capsa Solutions, Gerber Blades, Cascade Microtech, Eaton Corporation, Ford Motor Company, Wells Fargo, Lee Blake Precision Tooling, Oregon Department of Corrections, Oregon Department of Transformation, Stanley Tools, Regence Blue Cross Blue Shield, Oregon Primary Care Association, Dana Cancer Institute, Lane County (OR) Medical Clinics, OHSU Internal Medicine and Family Medicine Clinics, Saint Luke’s Medical Center, Hexcel Corporation 7-Up Bottling Company, Gleason Cutting Tools, and Komet America. Tom holds an undergraduate engineering degree from Tufts University, an M.Ed., and a Law Degree. That said, his greatest passion is getting out on the front line and helping people remove obstacles in their daily work life.