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