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Management
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Homework 5 Management Case Study Research Paper Essay

Case Study Instructions:

Don't write too professionally. Instead of using complex clauses, use simple sentences.

 

INFS5872 C-L Tseng Homework 5 (Due by 30 March 2020) Read the case “Deutsche Allgemeinversicherung”. You can find the link to download this case from Moodle. What are your views for solving the five measurement challenges facing Annette Kluck that are described on pages 8-9 of the case? Use the following style in your answer: 1. Better teams do more sampling < your view > 2. When is a mistake not a mistake? When it’s not important. < your view> … 5. On the prowl < your view > Overall, limit your answer to two pages in total and submit it to Turnitin.

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Homework 5
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Better teams do more sampling
In any organization, better teams usually have clear goals and pursue those goals through open communication, collaboration, and trust among its members. As a result, DAV teams should prove their worth by doing more sampling because the larger the sample size, the higher the rate of accuracy they will achieve. The uncertainty of DAV is related to its weaknesses that competitors may explore. If the teams fail to spot that uncertainty in the sample size, then the SPC program will not be of much help because it operates on the basis of garbage in, garbage out.
When is a mistake not a mistake? When its not important
It is true that a mistake is not a mistake if it is not important. During sampling, non-important errors are considered insignificant because they occur frequently but offset each other. However, non-sampling errors are only insignificant if they are influenced by external factors rather than an issue within a research or study (Phung et al. 2015). Therefore, the error caused by wrongfully entering a customer’s phone number is important because it was influenced by internal factors. As a result, the error caused by the wrong phone number is as important as providing wrong address information of a customer. In this regard, the DAV teams should mark all wrong phone numbers as “bad” because the higher the number of mistakes in the sample, the less reliable it will be.
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