# Deutsche Allgemeinversicherung Case Essay

Words: 1400
Pages: 6

Deutsche Allgemeinversicherung was founded in 1966 by Andreas Steininger. It was one of the world’s largest insurance companies. Around 51% of its business was in Germany with a 60% of its business in the field of retail insurance. Its keys to success were the traditional insurance management and its remarkable customer service. In DA, a typical process flow of a new policy would start by either a customer going to one of the companies branches or contacting a company agent. The customer would fill out an application – sometimes a check was attached- and the application was then sent through the company mail to the Retail Transaction Processing (VEG) division in Hamburg. Also, some customers filled out applications at home and sent them …show more content…
Calculate the control limits (in this case z=3) UCL = p + z sp = 0.05222 + 3 x 0.012844 = 0.090752
LCL = p - z sp = 0.05222 – 3 x 0.012844 = 0.013688

5. Plot the individual sample proportions, the average of the proportions, and the control limits

Once the upper and lower limits are identified it becomes easy to recognize in which (if any) of the subsequent weeks was the process out of control. This could be carried out by calculating the p for the subsequent weeks and checking whether they were within the limits or not. In this case, in week 23 and 24, the process was out of control because the p of both weeks were higher than the upper limit (0.11 and 0.1533 consecutively) Now after coming up with these results and before going on with what Annette Kluck should consider as next steps in DA’s quality efforts. We need to highlight the challenges that faced Annette when applying SPC as an insurance company or in other words the challenges that could face insurance companies in general when implementing SPC. These challenges could be as follow: • Successful companies such as DA have processes with high accuracy value (like in this case 99%). Accordingly, the company has to increase the confidence interval in the sample hence resulting in an increased sample size which at some point can be either financially unfeasible or physically unfeasible. A