The article below provides approaches to business process management and improvement. Described is how to effectively integrated lean Six Sigma process improvement techniques with BPM through an Integrated Enterprises Excellence (IEE) BPM deployment, so that the big-picture benefits.
Approaches to Business Process Management and Improvement Read More »
Quality Digest website response to inquiry: To compute a sigma number, what would be the lowest and highest number of data points that one should uses to calculate a dpm’s – too little will result in a highly reactive number & too many will result in a highly unreactive number.
Sigma Level Metric: Confusion and Resolution Read More »
Six Sigma in small businesses have similar issues to those that occur in larger organizations; e.g., making improvements so the big picture benefits.
Six Sigma in Small Businesses Read More »
Multiple regression analysis example in the PDF link below addresses how to validate a multiple regression analysis.
Multiple Regression Analysis Example: Process Validation Read More »
These enhanced predictive analytics examples illustrate the power of providing futuristic statements in business management system scorecards and how to create this form of enhanced performance measurement reporting.
As an introduction to a lean Six Sigma deployment, organizations need to address the article-described issues (provided in a PDF below) so there will be big-picture will benefits.
Introduction to Lean Six Sigma: Important Implementation Aspects Read More »
The importance of an XmR control charts and data normality consideration is that if data are not normally distributed false special-cause signals may occur in a control chart without a data transformation.
XmR Control Charts and Data Normality Read More »
Quality quote: To survive and prosper, an organization must create quality products and services that delight customers and create cash. Organizations need to transition from harboring an environment that firefights the problems of the day to a system that encourages and rewards fire prevention and long-term success. To move to the next level, organizations need
Faces of Quality: Forrest Breyfogle Read More »
Six Sigma infrastructure needs. Measurements of Six Sigma. Beyond Six Sigma: E=MC**2. Satellite-level metrics, 30,000-foot-level metrics. The following IEE (Integrated Enterprise Excellence) process to select projects aligned with the business trategic plans is called an enterprise business planning methodology
Six Sigma and Beyond: A Subject Matter Expert’s Persepctive Read More »
This paper addresses x-bar and R control charting issues. For a given process, do you believe that everyone would make the same statement relative to: 1. process control/predictability from a created control chart? 2. process capability to meet its specifications? Not necessarily! Process statements such as these are not only a function of process characteristics but can also be very dependent upon sampling approach. The limits for the x-bar chart are derived from within-subgroup variability, while sampling standard deviation for XmR charts are calculated from between-subgroup variability. Statistical Process Control (SPC) has a primary purpose, which is to identify when special cause conditions occur for timely corrective actions. SPC textbooks and training state that an x-bar and R control chart is appropriate for situations where there are multiple continuous responses in a subgroup. Described in this paper are technical issues with the x-bar and R chart which can lead to falsely identifying common cause process variation as though it were special cause. The reason for these issues is discussed along with an alternative 30,000-foot-level reporting system that addresses these issues. Traditional x-bar and R control charts can lead to much firefighting, since the underlying assumptions for these charts are often not valid in the real world. In the 30,000-foot-level metric reporting methodology, which centers on use of the individuals control chart, process response is evaluated for regions of stability. Within identified stable regions, a process capability non-conformance estimate can then be reported. If there is a recent region of stability, one can consider the data in this region to be a random sample of the future; hence, a prediction statement can be made. Within identified stable regions, a process capability non-conformance estimate can then be reported if a specification exists. If there is a recent region of stability, one can consider the data in this region to be a random sample of the future; hence, a prediction statement can be made. An enterprise can assess its value-chain metrics collectively – where each has 30,000-foot-level reporting – to determine where improvements can be made that positively impact the enterprise financials as a whole. Goals to these metrics would pull for a process improvement or design project creation that positively impacts these 30,000-foot-level metrics.
Enhanced Control Charts for Variable Data with Predictive Process Capability Statement Read More »
