Use of Data to Reduce Variation in Process

Assignment Help Experts New Blog Post - Data used in the process is quite important to the statisticians, quality managers, Six Sigma Green and Black belts and other improvement professionals that have participated in the process. Organizations might use data within internal environment for reducing variation in the process. It might use data with fundamental concept of algorithm that is helpful to reduce variation through step by step procedure. Algorithm increases knowledge about how a process acts and behaves as a cost effective change that is significant to reduce variation (Scholtes, Joiner & Streibel, 2003). The collected data is used by the organization to define new system. An effective data sharing is useful to share data within the organization that reduces variations in different organizational processes.

At the same time, the organization might use data for statistical thinking with the help of statistical process control that reduces process variability. The data can be used for making chart for the organizational system and quality parameters. Reduction in process variation is quite important for the organization to improve quality system and performance and to meet customers’ expectation (Kaira, 2011). Six Sigma approach is a statistical technique that measures variation through using data for a process. Statistical thinking is significant due to its three key elements that include process variation, source of variation and use of data etc.

From the reduction in process variation, the result will not be in terms of yield. It is because; yield is the amount that returns the security of owners. In addition, Yield does not contain the price variation, if there is difference between total returns. It is the return of investment such as interest and dividend, but does not reduce the variation in the process (Bhunia & Mukhopadhyay, 2010). Generally, it is carried on the basis of percentages on cost of investment. By reducing the process, the results are not considered as yield, but results affect the yield.

References
Bhunia, S. & Mukhopadhyay, S. (2010). Low-Power Variation-Tolerant Design in Nanometer Silicon. USA: Springer.
Kaira, J. (2011). Medical Errors and Patient Safety: Strategies to Reduce and Disclose Medical Errors and Improve Patient Safety. Germany: Walter de Gruyter.
Scholtes, P.R., Joiner, B.L. & Streibel, B.J. (2003). The Team Handbook. (3rd ed.). Oriel Incorporated.