Lean Six Sigma Data Analysis
Prerequisite Program Required:
Before taking this program, registrants must complete Business Process Improvement Using Lean Six Sigma and Performance Metrics.
This program provides both the theoretical background and practical skills necessary to effectively apply the Six Sigma methodology in your business. It uses the powerful and proven concepts developed in statistical process control and provides you with the knowledge, tools and guidelines to apply them quickly and effectively within the DMAIC model. The focus is less on theory and more on how to apply these influential tools to conduct projects in your business. Understanding proper data collection methods and using the proper analysis tool from the myriad of possibilities will be emphasized. Data analysis techniques to uncover the root causes for process failure will be investigated, as well as how to implement lasting controls for sustained process improvement success.
Who Should Attend
Operations managers and supervisors, business analysts, process improvement teams
Continuing Education Units
This course provides 2.1 Continuing Education Units (CEUs)
How You Will Benefit
- Differentiate between discrete and continuous data and how it affects your analysis and sample size calculations
- Use and apply Gage R&R to validate your measurement system
- Select the proper analysis tool for a specific situation: Pareto charts, histograms, scatter plots, normality tests, ANOVA, correlation, and regression analysis
- Determine and understand the effects of Cp , Cpk, and other process capability metrics
- Calculate sample size and use it in determining the scope of data collection
- Validate and measure the effect of process improvements
- Choose and apply the proper control tool: I-MR, Xbar, u-chart, p-chart
- Calculate confidence intervals based on process samples
Day 1 - Essential Statistics for Process Improvement
- Overview of variation using visual tools: descriptive statistics for central tendency and variation, types of data and sample sizes, normal distribution (empirical rule), standard scores (Z scores) visual tools (histograms, dot plot, box-whisker), testing for normality, normal probability plots
Day 2 - Software-Aided Application
- Measurement system analysis and Gage R&R
- Confidence intervals and hypothesis testing: standard error and confidence levels, confidence intervals
- Process capability metrics: steps for determining process capability; Cp, Cpk, Pp, Ppk metrics
Day 3 - Hypothesis Testing and Control Chart Creation
- Statistical process control (SPC) and control charts: common cause vs. special cause variation, run charts vs. control charts, selecting the appropriate control chart, characteristics of different control charts
- Hypothesis testing: software-aided hypothesis testing, hypothesis testing tips for interpretation, decision map for hypothesis tests
- Survey design, implementation, and analysis
For over 2 decades Scott has developed courses in his areas of expertise, which include project management, portfolio management, gathering business requirements, process improvement using Lean Six Sigma, business statistics, and decision making. He also has over a decade of applied experience in the field as a former information technology director and as a technologist for an internetworking software developer.
Scott has developed programs for a variety of audiences ranging from novices to experienced professionals to C-level executives. Clients have included Fortune 500 firms, the United States military, government, higher education, and not-for-profit agencies.
Scott is a Six Sigma black belt and received his M.B.A. from the University of Wisconsin-Madison. He holds a B.S. degree in physics from UW-Eau Claire.
Program: 8:15 a.m.-5 p.m.
Lunch and Breaks are Included with Program Registration
Program Check-In will be 7:30-8:15 a.m. on the first day of the program.