9-5

Six sigma and data analysis

The repeatability and reproducibility process are used in SIX SIGMA and other measurement system analysis. The Amazon use this analysis to pinpoint measurements within the company. The data collect for analysis should be data which aids in further defining the problem (competitive advantage). In addition, the data collected should provide information concerning causal factors which shows how, where, and when the problem occur (Tennant, 2006). The two types of data collected are quantitative and qualitative data. Quantitative data is objective and can be measured while qualitative data is subjective and cannot be measured objectively. In most case, it is necessary to get data in process performance over a certain period of time (Keller & Keller, 2010). The control chart can be used to collect data. Control chart help in identification of trends and outlying measurements.

In the quantitative data, experts need to have discrete and continuous data, data which is based on counts and on continuous scale respectively. Example of discrete data include: count of customers using Amazon; numbers of errors on bill; and numbers of calls offered in marketing. The data collected should be based on key performance indicators (KPI) (Dasgupta, 2003). Once the data is collected, the company needs to do exploratory data analysis to make an informed assumption about the data and check if the figures can be trusted. Therefore, the company using the six sigma need to use the gage repeatability and reproducibility method. If the data gotten is balanced, equal number of measurement per sample within and between operators, and measurement devices the data can be considered reliable.

Conclusion

Six Sigma can bring benefits to any business, but these benefits depends on collection and analysis of data to understand opportunities for improvement and make sustainable and significant changes. The people collecting the data or the practitioner should be highly skilled experts in various field including statistics. Some methods of checking accuracy of data include: analysis of variance, use of gage R&R, correlation, and general linear model.

References Dasgupta, T. (2003). Using the six-sigma metric to measure and improve the performance of a supply chain. Total Quality Management & Business Excellence, 14(3), 355–366. doi:10.1080/1478336032000046652 Keller, P. A., & Keller, P. (2010). Six Sigma Demystified. New York: McGraw-Hill Professional. Tennant, G. (2006). SIX SIGMA: SPC and TQM in Manufacturing and Services. SIX SIGMA: SPC and TQM in Manufacturing and Services.