Date: This webinar is now available On-Demand.
Duration: 90 Minutes
In order to address long-standing problems in a process and to ensure solutions are of value, we need to identify the root causes driving process problems. We need to analyze the impact of each potential input (X) on the output (Y), both graphically and statistically. If we can’t create a graph to show the impact, or non-impact, it will be very difficult to convince the stakeholders to take action or discard the myths. Statistical analysis then validates the graphical analysis.
In this 90-minute online session, we will introduce you to a fundamental concept of process data analysis and a structured approach. This will enable you to identify and qualify the impact of your inputs on your process output.
Y=f(x) is the basis of process knowledge. We may be unhappy with the performance of our process in terms of the output but until we understand the relationship between the inputs and the outputs, we cannot make purposeful changes to gain improvement. Exploring the relationship between the inputs and outputs is fundamental to our ability to conduct graphical and statistical analysis.
Identifying the “vital few” inputs. In the Analyze phase we begin the process of identifying the vital few inputs from the trivial many. We can use graphical techniques to visually assess an input’s effect on the response, and communicate these preliminary results with others. We will introduce the following to begin this journey:
- How to select the appropriate chart for your inputs.
- How to use control charts.
- Other charts useful for analyzing variable output.
Applying statistical techniques. A fundamental piece of analysis is to discern your data from a desired target. The tests we introduce will provide backup to the indications that we obtained from our graphical analysis. We will use:
- Hypothesis tests to determine significance for means and variance.
- Regression analysis to explore relationships between X and Y variables.
- ANOVA to distinguish sources of variation and how they can affect your primary metric.
Who should attend
- Process improvement specialists
- Lean and Lean Six Sigma practitioners
- Operations and quality leaders
- Data analysts and other data analysis professionals
- Process owners
About the series
This four-part series explores the data and analysis tools that enable today’s process excellence practitioner to achieve a deep understanding of their processes, leading to opportunities for sustained improvement within their organization. From Measure, where we explore our baseline process through to Analyze, where we uncover the root causes driving our performance, attendees will take a journey on how to capture validated data to investigate and improve their processes. Discounts available when you register for the entire series.
- Session 1: To Fix it, I Must Be Able to Measure It
Date: Sept. 24, 2015
- Session 2: Analyze Clues to Discover the Root Cause of Process Problems
Date: Oct. 15, 2015
- Session 3: How to Become an Attribute Data Detective
Date: Nov. 12, 2015
- Session 4: Quality Data Leads to Quality Conclusions
Date: Dec. 10, 2015
Included with all registrations
- A login for the live training course
- Downloadable slides for note-taking
- 1 year access to an on-demand version of the course
Continuing education credits
Each registration entitles you to receive continuing education credits through our partnership with the International Association for Continuing Education & Training (IACET). During the training session, you'll receive instructions on how to claim your credits.
IACET continuing education credits are accepted by the American Society for Quality (ASQ) and hundreds of other organizations and companies.
Choose your registration type:
- Individual -- for those who want to attend the training alone. $199.
- Group* -- if you want to train multiple people at your location. $349.
- Series Registration -- Extra discounts available when you register for the entire series
* Rules for groups:
A "group" consists of multiple people within a single room at a single location, viewing the training session on a single screen. If you want to train people in multiple locations, or if each person requires their own screen to view, they must register separately.
- A CD-ROM of the training course can be added to any registration for an additional $99.
This training session, presented in partnership with IndustryWeek, will be conducted using a slides-and-audio format. You will also have the ability to ask the instructor questions, and you can participate in polls the instructor pushes to the audience during the session.
After you complete your registration, you will receive a confirmation email with details for joining the training course, as well as your unique password. On the day of the training, use the instructions in this email to log in.
A few days after the live training session is over, you'll receive an email informing you that the on-demand version is available.
Sign up for this online training course
Joanne Sauvey is an experienced Lean Six Sigma practitioner and trainer who is credited with developing BMGI's online Green Belt and Black Belt curricula. In her capacity as an eInstructor, Sauvey trains and mentors practitioners across North America, New Zealand, Europe and Asia in a wide variety of industries, including healthcare, manufacturing, utilities, financial services and technology. Sauvey also manages the Master Black Belt development program at BMGI, working with practitioners to expand their mastery of Lean Six Sigma. She holds a Bachelor's in Industrial and Systems Engineering from Ohio University, and is a certified Lean Six Sigma Master Black Belt.
Renee Snell has more than 20 years of experience in developing and teaching continuous improvement techniques. A Lean Six Sigma Master Black Belt and statistical expert, she has mentored more than 1,000 practitioners in Lean and Six Sigma. In addition to her role as an instructor, Snell develops customized curriculum for organizations in both transactional and manufacturing industries. Snell holds a Master's degree in statistics and has completed post-graduate work in management science/statistics at the University of Tennessee, Knoxville.