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Overview/Description Six Sigma teams must possess specific qualities to succeed throughout the development stages of their life cycles. Leaders who know how to facilitate teams will greatly enhance their chances for project success, which in turn will benefit their organizations. Motivation is one essential component that can optimize a team's focus on accomplishing its assigned goals. By making the teamwork enriching and satisfying to members, leaders can motivate a Six Sigma team with dramatic effects on overall success. Modern motivational theory informs today's motivational techniques,...
Overview/Description In the Analyze phase of the DMAIC methodology, a Six Sigma team begins to analyze the root causes of the problems that it identified in the earlier stages. This analysis may require churning out huge volumes of data of different types. Sometimes this data is of a multivariate nature, meaning that many dependent and independent variables need to be considered simultaneously. As such, Six Sigma teams often use advanced multivariate tools to manage this type of data. Data can also be of an attribute nature, for which Six Sigma teams use a different set of data analysis tools...
Overview/Description Hypothesis testing is a process of assuming an initial claim about the population characteristics and then statistically testing this claim using sample data. Testing hypotheses is a very important activity in Six Sigma projects in the areas of analysis, decision making, and change implementation. In conventional hypothesis tests – called parametric tests – a sample statistic is obtained to estimate a population parameter and hence requires a number of assumptions to be made about the underlying population; such as the normality of data. However, another category of...
Overview/Description Getting to the source of why something has gone wrong in a system or process is critical to identifying the changes necessary for resolving the problem. During the Analyze phase of a Six Sigma project, a Black Belt practitioner utilizes a variety of statistical and nonstatistical tools and methods for analyzing systems and processes to identify variation and defects, reduce costs, eliminate waste, and reduce cycle time. While many of the tools used in the Analyze phase are statistical and quantitative in nature, there are many useful nonstatistical methods. Nonstatistical...
Overview/Description In the final stages of the Six Sigma DMAIC methodology, once process improvement opportunities are identified and implemented, teams need to control the improved processes in order to sustain improvement gains. Process control includes applying tools to continuously monitor and maintain each improved process, and to prevent it from reverting to its previous state. This course introduces basic nonstatistical control tools as well as tools for maintaining control so that process improvement initiatives continue as they were intended. Specifically, it explores how total...
Overview/Description Probability distributions are an essential part of descriptive statistics that Six Sigma teams can use to assist in fitting collected data into various types of distributions. Probability distributions help to ascertain specific probability values in the distribution and lead the Six Sigma teams down the hypothesis testing roadmap to the next stage of the Six Sigma DMAIC process. Of course, all this is meaningless if the data you have gathered and used is not accurate or precise, which is where measurement systems analysis (MSA) comes into play. MSA is a task in the...
Overview/Description Organizations need to make inferences about a population from sample data, and understanding how to calculate the probability that an event will occur is crucial to making those inferences. In a Six Sigma context, it is often important to calculate the likelihood that a combination of events or that an ordered combination of events will occur. Understanding probabilities can provide Black Belts with the tools to make predictions about events or event combinations. To make accurate inferences about a population from the sample data collected in the Measure stage, Black...
Overview/Description Albert Einstein is reputed to have said, "The significant problems we face cannot be solved at the same level of thinking we were at when we created them." To solve quality and process-related problems, managers should continuously enhance their knowledge of organizational processes and quality management tools. These tools help managers find root causes of problems, an important step toward removing them. Success in ensuring quality and organizational excellence depends on how effectively managers apply these tools to solve quality and process-related problems. This...
Overview/Description In any improvement initiative, organizations must determine whether their existing processes meet the targets and specifications demanded by the business, or by the customer. Measuring and analyzing the capability and performance of a process under review enables organizations to numerically represent and interpret its current state, and to report its sigma level. When done correctly, process capability analyses enable Black Belts to precisely assess current performance in light of future goals, and ultimately, to determine the need and targets of process improvement....
Overview/Description To improve the processes behind an organization's products and services, a Six Sigma Black Belt must measure them. But first, they must identify those processes. Among the many Six Sigma tools, several are designed specifically to isolate relevant process variables, determine their relationships to each other, prioritize their importance relative to customer or business requirements, and assess their efficiency. Using SIPOC and cause-and-effect matrices, Black Belts can determine which process inputs to target first – those with the most significant impact on important...

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