Statistics Project, Statistics service management

Statistics Project, Statistics service management
Project Overview:
The overall objective of this project is to analyze and improve a service business via the techniques covered in the class.

1. Select a service firm that you would like to focus on. The company should be a successor in its competitive environment and the reasons for selecting that particular business should be explained clearly.

2. Find one ore more contact person(s) in the company. Discuss with the individual(s) and detect/agree on a simple current problem they are encountering. Define the problem you are trying to solve in engineering terms (1-2 pages).

3. Model the problem with at least three methods we’ve covered in the classroom (Linear Programming, Data Envelopment Analysis, Histograms, Fishbone diagram, House of Quality) and suggest solutions for improvement.

4. After you complete your analysis, obtain feedback from your company contact and include his/her opinion regarding your analysis. Include your findings in the conclusions section and list the left out topics/methods in your project to provide guidance for the future research.

5. A Service Blueprint has to be prepared and explained in detail (and is not counted towards the methods you will be utilizing for the project).

Problem selection:
The topics can be selected among any real manufacturing or service industry related problems (service business is preferable). If you are working professionals, you are more than welcome to do the project in your own profession. The topics need to be decided with the group members.

Problem formulation:
You need to define your problem in detail. Students are encouraged to utilize pictures, tables, any kind of graphical representation to describe the problem.

Data collection and analysis:
You need to collect data regarding the system in focus. Visiting the problem environment is very useful in this phase. Try to obtain as much quantitative data as possible. You may change the actual numbers in order to hide the real values by multiplying them with a certain constant to provide privacy of the company.

Model development:
Develop your model using at least two methods that you have encountered during the class. Make use of animations, graphs, and statistics in this phase.

Verification and validation:
Try to verify and validate your model. If verification and/or validation is not guaranteed make the necessary changes and alter the model so that the model logic and model code will be compatible with the reality.

Output analysis:
Make changes in the prior assumptions and run your model under these conditions.

Experimentation:
Improve your results by adding/subtracting resources, altering the controllable decision variables and show a comparative analysis with the previous studies. Explain why the new arrangement functions superior compared to the initial model.

Results and Conclusions:
Summarize you work briefly and comment on the results.

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