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A framework for choosing what's best for your organization
WITHIN THE AMERICAN business community a multitude of process improvement champions are vying for leadership attention.
Each champion advocates the adoption of his or her improvement methodology in your organization. Almost all plead that if you adopt their specific tools or follow a specific way of thinking, all your business problems will be solved.
After listening to multiple champions advocate their special methodology, how do you choose what will be best for your situation? What methodology fits the culture of your organization?
Many process improvement methodologies appear to conflict with each other or at least downplay the contribution of other methodologies. This montage of tools and philosophies creates the illusion of conflicting strategies.
In this article, I will discuss the basics of the three improvement methodologies and present a model to help you understand their concepts and effects and similarities and differences. Table 1 describes the essence of each methodology.
Six Sigma
Six Sigma claims that focusing on reduction of variation will solve process and business problems. By using a set of statistical tools to understand the fluctuation of a process, management can begin to predict the expected outcome of that process. If the outcome is not satisfactory associated tools can be used to further understand the elements influencing that process.
Through a rigid and structured investigation methodology, the process elements are more completely understood. The assumption is the outcome of the entire process will be improved by reducing the variation of multiple elements.
Six Sigma includes five steps: define, measure, analyze, improve and control (commonly known as DNI-AIC):
Define. Practitioners begin by defining the process. They ask who the customers are and what their problems are. They identify the key characteristics important to the customer along with the processes that support those key characteristics. They then identify existing output conditions along with the process elements.
* Measure. Next the focus is on measuring the process. Key characteristics are categorized, measurement systems are verified and data are collected.
* Analyze. Once data are collected, it is analyzed. The intent is to convert the raw data into information that provides insights into the process. These insights include identifying the fundamental and most important causes of the...