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Six Sigma has been used extensively in improving manufacturing organizations, but only relatively recently has it been used to improve processes outside the manufacturing arena. In our book Six Sigma Beyond the Factory Floor, my co-author, Dr. Ronald D. Snee, and I examine process improvement in the rest of the economy, such as financial services, e-commerce, healthcare and other transactional services. This includes non-manufacturing businesses, such as banks, law offices and nonprofits, including nonprofit hospitals, and also the non-manufacturing departments (i.e., delivery, finance and human resources) of companies that do make products.
The book explores the three major levels at which organizations must adapt Six Sigma to receive its full benefits beyond the factory floor:
The book also explains how to properly integrate Lean methods into a Six Sigma approach.
Significant parts of Six Sigma Beyond the Factory Floor offer insights into the application of Six Sigma within healthcare, in terms of overall deployment and individual projects. For example, the experiences and project results of Commonwealth Health Corporation (CHC), based in Bowling Green, Kentucky, USA, are highlighted in the chapter on deployment case studies. This case traces CHC’s experiences from its initial decision to deploy Six Sigma, to how it defined a strategy for deployment and expanded the effort, to the effect on people and roles, and finally, to the ultimate results and the impact on customers. CHC began the deployment in radiology, focused on management training and involvement in the next phase, and then moved on to billing and developing internal capability to sustain the effort.
The results are quite impressive – more than five times the investment by the fourth year. Since the organization first implemented Six Sigma in 1998, Commonwealth Health Corporation has continued to realize significant tangible and intangible benefits, improving not only financially, but raising staff and patient satisfaction as well. Commenting on CHC’s Six Sigma experiences, CEO John Desmarais said, “I only wish we had done this five years earlier…the competitive edge the organization has gained through this process is incredible.”
Key lessons learned from CHC’s Six Sigma initiative include:
The book also provides a project case study from a pharmaceutical organization. This case focuses on the batch records process – the system by which pharmaceutical companies must track all aspects of manufacturing in order to comply with government regulations. While the case involves manufacturing, the scope is actually the batch records process, not the manufacturing process itself. Typically, the inventory of pharmaceuticals had to wait for the batch records to be completed and approved, prior to shipment. Through application of Six Sigma, the project team was able to reduce the key cycle time for preparing batch records by more than 55 percent, freeing up more than $3 million in inventory for one product alone.
Two technical challenges common in healthcare, and the transactional services in general, are the prevalence of skewed (non-normal) data distributions and discrete data. The book explains when normality really matters, and when it does not. For example, contrary to some beliefs and teachings, when using regression analysis, there is no theoretical requirement for the response data (the Y) to be normally distributed. The only theoretical requirement is that the residuals from regression models be approximately normal. The book explains why exact normality will never occur in practice, hence normality hypothesis tests may give misleading answers. In practice, approximate normality is all that is needed or can be expected. The book provides options for handling severe non-normality, such as non-parametric methods and transformations.
Relative to analysis of discrete data, the book explains that there are several potential approaches that may be applicable, depending on the specific situation. Appropriate solutions could involve application of methods specifically designed for discrete data, such as logistic regression, or use of standard methods to summaries of discrete data, such as treating a sample percentage as a continuous metric. The book explains that many methods do exists for discrete data in common statistical packages, such as the capability analysis modules for discrete data in Minitab.
Healthcare professionals are likely to find much information of interest in this book – from the strategic viewpoint of overall Six Sigma deployment, to the details of application of technical tools, to everything in-between, including project selection and management.