Definition: Sigma symbolizes standard variation, which can be a source of defect and poor quality, as it can lead to unexpected results. Six Sigma is a Quality standard or a management philosophy, which is used as a process management tool to continuously, improve quality and minimize defects through measurement of variation, defects and quality (Hartung, 2010). By reducing the amount of variation in a process, this data-driven approach leads to consistent and predictable output. Therefore, by enhancing the predictability of the business processes, business performance is improved (Carreira et. al., 2006).
Six Sigma employs a variety of tools, ranging from simple to highly complex, to decrease variation in the process and improve quality. It utilizes data supported by statistical analysis to apply standardized step-by-step process with specific tools leading toward logical improvements. The method focuses on improving customer satisfaction, reducing time cycle, and improving productivity to result in bottom line profitability (Pande et. al., 2002). It can be adjusted based on the company requirements. Six Sigma is analyzed based on its performance, efficiency and quality outcome (Carreira et. al., 2006).
Ehrlich (2002), states that Six Sigma is a statistical term which characterizes your quality having <3.4 defects per million for a given product or process specification.
Bandyopadhyay et. al. (2007) concluded that, the Six Sigma approach to program design and process improvement can be used, to implement continuous quality and productivity improvement schemes, by institutions of higher learning globally. However, they did not provide any empirical data and just voiced their opinion.
Marjorie Hook said, Today I think people sometimes try to make Six Sigma seem complicated and overly technical. My father’s approach was, If you want to improve something, involve the people who are doing the job.’ He always wanted to make it simple so people would use it. (Sehmus, 2011)
3.4.1 Six Sigma tools
Six Sigma uses data and statistical tools in order to evaluate the quality of a process and measure any defects caused by variation. According to Hartung (2010), 80% of the defects and problems are caused by processes and not by people. For this reason, Six Sigma tools endeavor to deliver a stable outcome with better quality, independent from people as much as possible. The basic tools used in Six Sigma include Pareto charts, Control charts, Run charts, Failure Modes and Effects Analysis (FMEA) and DMAIC (as shown in figure 5).
Figure 5- Six Sigma tools
One of the most important tools of Six Sigma is Pareto chart, shown in appendix A, figure 16. It is a form of bar chart, which states that approximately 20 percent of root cause of problems (or the inputs) account for approximately 80 percent of all problems encountered (or the outputs) (Basu, 2009). Pareto chart is applied to analyze the problems in order of priority; from highest to lowest priority, represented by bars on the chart.
This helps to identify the most frequent problems and also focus improvement efforts on areas that will have the greatest impact (loss of efficiency or profit) (George, 2003). Focusing on the critical 20 percent of causes rather than 80 percent of the problems can increase waste elimination, instead of wasting time and other resources trying to eliminate the remaining small percentage of the problems (Ramasmy, 2005).
Another Six Sigma tool, the Control Chart, uses graphical technique to examine historical and current set of data (as shown in appendix A, figure 17). It plots (on the vertical axis) measured values of a certain process characteristic against time (on the horizontal axis) (Basu, 2009). Control chart divides variations in any process into random variation and assignable variation. If a process is in statistical control, only random variation will exist, whereas if the process involves a departure or deviation from statistical control, then assignable variation will occur (Sehmus, 2011)
The aim of control chart is to determine whether the process remains in statistical control i.e. remains stable, and distinguish usual or common variability from unusual (special assignable) causes, which will need remedial action. The graph presents three control limits; the central line (CL), which indicates the mean output, and the upper and lower control limits, UCL and LCL, respectively, which present the boundaries of the allowed outputs (Basu, 2009).
Run Chart is another graphical tool of Six Sigma that plots process characteristic, usually against time (as shown in appendix A, figure 18). It is part of the control chart methodology and has a wide range of applications, including identification of non-random patterns, such as seasonality process jumps and trends (Basu, 2009).
Run Chart identifies the maximum and minimum values, and the average of the measured characteristic, in order to allow comparison of the performance of a process, before and after implementation of the solution (Sehmus, 2011).
Another tool of Six Sigma is Failure Modes and Effects Analysis (FMEA), shown in appendix A, figure 19. This is associated with prioritizing customer requirements (Brue, 2003). It is used to evaluate the potential failure of a product or process, identify actions that could eliminate or reduce the likelihood of the potential failure occurring, and document the entire process as stated by George (2003).
DMAIC is an essential data-driven tool of Six Sigma. It includes five phases of Define, Measure, Improve and Control. Products and processes are measured against metrics and improvement activities are determined through DMAIC. This tool will be described in more detail in the Lean Six Sigma section (Basu, 2009).
3.4.2 Advantages and Disadvantages of Six Sigma
Many advantages result from the implementation of Six Sigma; some of these are highlighted below:
¢ Even though Six Sigma methodologies are considered to be complex by many people or organizations, it can be applied in a simple or complex manner, or somewhere in between. One of the benefits of Six Sigma is that by applying the basic tools, without using complex statistical analysis, significant improvements can be made in the organization.
¢ Six Sigma is a data-driven improvement process; it drives metrics from the available data, to track progress. It sorts and displays data in charts in order to highlight the points that can be improved in an organization (Carreira et. al., 2006).
On the other hand, there are some disadvantages to using Six Sigma:
¢ Application of Six Sigma methodologies are complex compared to Lean principles, which are fairly simple and easy to understand. For this reason, many people or organizations avoid implementing Six Sigma principles (Carreira et. al., 2006).
¢ Using Six Sigma in some organizations, such as academic accounting department to improve the CPA pass rate, may require very long data collection.
¢ Finding the critical processes and causes of defects in Six Sigma, means the project will take a long time to complete (Sehmus, 2011).
3.5 Lean Six Sigma
Definition: Carreira et. al. (2006), the Lean Six Sigma approach is a combination of Six Sigma basic tools and Lean Manufacturing. This combination is necessary because Six Sigma on its own cannot dramatically improve process speed, or reduce invested capital, and Lean cannot bring a process under statistical control (George, 2002).
Lean principles reduce cycle time so products move through processes more quickly, and eliminate waste, while Six Sigma is used to improve quality and reduce variation by measuring defects (per million output/opportunities) (George, 2003). The result is optimal shareholder value due to rapid improvement in customer satisfaction, process speed, and invested capital (George, 2002).
Taghizadegan (2006) defines Lean Six Sigma as a data-driven approach and methodology to analyze the root causes of manufacturing and business problems/processes by eliminating defects (driving toward six standard deviations between the mean and the nearest specification limit), and dramatically improving the product.
Lean Six Sigma is a continuous analysis involving measuring, charting, and comparing. It results in significant improvement in cost and quality, through identifying areas that need improvement, prioritizing projects, keeping track of the progress, and assessing the success of the initiatives (George, 2002).
Lean Six Sigma also identifies and eliminates unnecessary and non-valued added process steps and activities. Moreover, it enables employees to have a better knowledge of the process in order to make adjustments that optimize desired outcomes (Environmental Protection Agency, 2006).
In Lean Six Sigma, the DMAIC tool of Six Sigma is not just a process improvement technique, but a management strategy to manage the project’s financial goals (Carreira et. al. 2006).