Why is DAV using SPC? What are the primary challenges in applying Statistical Process Control (SPC) to a service industry compared with manufacturing?
Using SPC at DAV
The Statistical Process Control is to be implemented by DAV in order to make the operations of the company efficient and flexible. The data entry process of the company is currently causing problems for the company however, if SPC is implemented, then the data entry operators of the company would be able to perform their tasks more efficiently and the chances of making an error would decrease.
The data entry operators can then work as a single team and the culture of full quality assurance would be developed throughout the organization. All the employees of the company would then take steps to reduce the number of the errors generated and an error free work environment would be created which is going to boost the productivity of the employees. However, there are many challenges that first need to be addressed before successfully implementing SPC at DAV.
SPC implementation challenges in service industry as compared to manufacturing
SPC has always been associated with the manufacturing industry and nobody has ever thought to implement SPC in a service industry however, the SPC could be changed and tailored to the needs of the service industry so that it could be implemented in a service industry. But this is going to prove challenging for the management of the company. This is because measuring the exact and accurate performance of the employees in a service industry is not easy and it is complex each time. The reason for this is that the work tasks are not repeatable in a service industry such as the back office operations. The workers interact with the customers on a daily basis and that interaction varies each time which makes the measurement of the performance a complex task.
The success of a service industry is based on the skills, knowledge and expertise of the employees and on the basis of that they create the operations of the company. Therefore, the management faces the issue related to what to measure about them employees, how to measure and when to measure. These are critical issues in any service industry. Furthermore, deciding upon the specific control limits and performance metrics is another challenge.
Explain the concept of a p-chart to a group of bank tellers without a background in SPC or statistics.
In the service industry and also in the manufacturing industry, the data is collected in the form of sub-groups most of the time. Therefore, in order to determine the effectiveness and efficiency of the employees on the basis of that data the P-charts are used. P-charts are a popular type of the statistical chart which can easily demonstrate the changes in a specific process over a period of time. A specific attribute of the process could be easily measured through a P-chart and then based on the control limits we can identify whether a decision should be made in yes or not, a process should go ahead or does not go etc. The construction of the P-charts is based on upper and lower control limits and if these limits are crossed by the process, then it means that the process if not in control.Deutsche Allgemeinversicherung Case Solution
P-charts have many advantages such as keeping proper check and track of different processes such as sustaining the operations of the company, enhancing the profitability and increasing the quality of the customer service. The process implementation teams and the project management teams make extensive uses of P-charts to increase the efficiency of the operations and keep the plan on track. Also, as the P-charts provide the management with specific control limits therefore, the management knows what to expect regarding the future performance of the company.
The first 12 weeks of the data in exhibit 4 represent the diagnostic period for the Policy Extension Group. What are the 3 sigma control limits for the process?
Exhibit 4 contains the data related to the New Policy Extension Group where the total sample size and the total number of the weeks are given. This data set has been used in order to calculate the three sigma control limits as provided in excel spreadsheet. The lower control limit for the process is 0.3756 and the upper control limit for the process is 0.4240......................
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Essay on Deutsche Allgemeinversicherung Solution
2111 WordsFeb 4th, 20139 Pages
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Process Measurement and Improvement
The case is based on an insurance service company which traced back to 1994. The company was facing problems in controlling and improving service quality and operation performance. This essay will stress on introducing the SPC (statistical process control) to DAV and providing suggestions on improving both the SPC and the company’s operation performance. The five questions required are covered and allocated…show more content…
The average of fraction defective is merely a number which cannot tell us what to do with it even when we get it. Thus SPC is more accurate and systematic to analyze the process of customer service operation.
2. Primary challenges
There are basically two challenges that implementing the SPC to a service company:
1) Difficulties of deciding and selecting what to measure and
2) Too much uncertainty because of the human behavior
3. Sample: how SPC works
Here is an example of employing SPC (P-Chart) for DAV’s PMV project.
The first 12 weeks of the data displayed in Appendix I represent the diagnostic period for the Policy Extension Group.
From the calculation (See Appendix I), we get the 3-sigma control limits for the process, i.e. UCL=0.091, LCL=0.014. These control limits indicate that if the error proportion is within the range of [0.014, 0.091], the process is under control; if not, the process is out of control.
Here is the P-Chart for the data from Week 13 to Week 30.
It is then clear that the process is out of control in Week 23 and Week 24.
In addition to process control, SPC can also help lower rank employees to better understand the different standards of the services and draw their attention to self-control of fraction