Case Study: Deutsche Allgemeinversicherung
Case Study: Deutsche Allgemeinversicherung
Executive Summary:
This case study involved the analysis of the Statistical Process Control of documents for DAU, a company looking to stay ahead of the rest in today’s competitive market. Specifically, the company is looking to improve their process of documenting customer information in forms both filled by customers, as well as by representatives. What is important to note here, is that documents can have errors (as they often do), however, these errors aren’t necessarily all of the same importance to the company. The challenge here was to implement a relevant method which would actually yield improvements in the long run, which is why the company chose to establish P-charts. In essence these p-charts lay out whether a document is correct or has errors, and displays them on a graph. Through the involvement of all departments of the company, these errors can be analyzed, and information can be acquired on specific sectors of the company in need of help. Throughout the case study we made recommendations addressing the potential challenges which a P-charting process brings to the table. We also made specific suggestions addressing the gray area of what constitutes a mistake in a document.
1. DAV is using SPC because it’s a mathematical method which is easily analyzable as a hard science method. This method is usually easily implemented in the manufacturing industry since one is usually looking at parts which have precise measurement requirements. In our case, however, we run in to the issue that DAV is looking at forms which are filled out by the customers themselves. For starters, these forms have varying errors, from wrong addresses, as an example, to wrong telephone numbers. Also, each form could have multiple errors, therefore this poses the question of what exactly constitutes and error. All of these “variables” need to be defined clearly beforehand so that error counts are accurate, and mistakes such as
Executive Summary:
This case study involved the analysis of the Statistical Process Control of documents for DAU, a company looking to stay ahead of the rest in today’s competitive market. Specifically, the company is looking to improve their process of documenting customer information in forms both filled by customers, as well as by representatives. What is important to note here, is that documents can have errors (as they often do), however, these errors aren’t necessarily all of the same importance to the company. The challenge here was to implement a relevant method which would actually yield improvements in the long run, which is why the company chose to establish P-charts. In essence these p-charts lay out whether a document is correct or has errors, and displays them on a graph. Through the involvement of all departments of the company, these errors can be analyzed, and information can be acquired on specific sectors of the company in need of help. Throughout the case study we made recommendations addressing the potential challenges which a P-charting process brings to the table. We also made specific suggestions addressing the gray area of what constitutes a mistake in a document.
1. DAV is using SPC because it’s a mathematical method which is easily analyzable as a hard science method. This method is usually easily implemented in the manufacturing industry since one is usually looking at parts which have precise measurement requirements. In our case, however, we run in to the issue that DAV is looking at forms which are filled out by the customers themselves. For starters, these forms have varying errors, from wrong addresses, as an example, to wrong telephone numbers. Also, each form could have multiple errors, therefore this poses the question of what exactly constitutes and error. All of these “variables” need to be defined clearly beforehand so that error counts are accurate, and mistakes such as