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CHAPTER SEVEN
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provides a good measurement for the future health of the business. Measuring operational excellence, however, may involve several measurements, including the sales volume and the number of confirmed orders compared with the total orders placed. Similarly, a multitude of measurements can exist for the leadership: feedback by employees, the ability to inspire creativity, financial performance measurements, and planning effectiveness. The financial measurements alone are numerous and include the growth rate, profitability, cost of goods, return on net assets, return on investments, and debt/equity ratio. The Six Sigma Business Scorecard s BPIn measurements are standardized across the board. However, for internal purposes the measurements that the team selects should relate to management s ability to improve the performance. The seven categories of the Six Sigma Business Scorecard are generic enough to be the same for various companies with different measurements. One of the challenges in improving business performance is to maintain the effectiveness of improvement efforts. In many companies, thousands of Six Sigma projects have been initiated. However, only about 10 to 20 percent of those projects have been successfully completed. Many of the success stories are attributed to manipulation of the information by consultants or the assigned project leaders. The successful project reflects on the departmental processes and the rate of improvement.
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ENSURING DATA COLLECTION CAPABILITY
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Sometimes a business avoided taking measurements because doing so required excessive effort and resources. The data collected were unreliable, and no one analyzed and acted upon the data. The economy of measurements must be maintained and balanced against the available resources for data collection and analysis. How many measurements one company has is not important; instead, how many measurements a company effectively utilizes is what counts. When you are implementing the
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IMPLEMENTING THE SIX SIGMA BUSINESS SCORECARD
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Six Sigma Business Scorecard, planning for data collection is one of the more important activities. The format, methods, and tools used for data collection must be planned carefully to reduce the cost of data collection. Good data collection has several attributes. The data must be easily retrievable and usable. Their integrity must be preserved, and damage must be prevented, through proper backups and a data recovery plan. The data analysis methods must include a graphical display of the data in usable format as well as identifying action items and communication methods. Communicating with employees about performance levels and trends is a major aspect of performance improvement. Employees achieve what is expected of them. Clear communication with employees reduces the gap between the as is and the should be performance levels. To achieve dramatic improvement in performance, awareness training must be conducted with all employees to establish a common base of understanding of performance expectations. Employees have the potential to produce expected results once they understand the direction from the leadership and their roles in achieving corporate success. The main distractions in achieving corporate success are conflicting priorities and hidden agendas. Corporate leaders must clarify the importance of a corporate strategy and the role of the Six Sigma Business Scorecard in achieving results. Data integrity at all critical processes, timely interpretation, and reaction when necessary are critical to maintain and improve process performance. Performance levels, trends, and patterns and their significance are important components of data analysis. During the analysis, if one unsatisfactory incidence of performance is noted, it might be attributed to data inaccuracy, human error, or chance error. If two unacceptable data points exist, they represent a potential for change and indicate that the process needs some adjustment. However, if three data points are unacceptable, process change for one or more patterns is required. Therefore, the rule of thumb for interpreting data is this: One error is a point that can happen randomly, two errors create a line that sets a direction, and three points indicate a pattern that shows a behavior; one is a go (green), two are a caution
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