Describe the quantitative analysis approach, to include a high level overview of the importance of identifying the problem, developing a model, acquiring input data, developing a solution, testing the solution, analyzing results, and implementation.
2. Select any organization of interest and discuss how decision analysis could be used to solve a business problem. Describe a decision tree and discuss how such a tool can be utilized to improve decision making.
3. Discuss the different types of forecasts to include time-series, causal, and qualitative models. When might a researcher or project manager utilize exponential smoothing? What benefit does a Delphi technique provide when working with qualitative-based decision making?
4. Discuss the requirements of a linear programming (LP) model. Provide an example of an LP model and define each variable used. What are the key steps that need to be considered when formulating an LP problem?
5. Discuss the benefits provided by network modeling. Describe how the shortest-route and maximal-flow techniques can be utilized. Please provide an example of one of these techniques.
6. Discuss the significance of waiting line costs. Here, ensure to address the importance of satisfied customers, arrival points, and service characteristics.
7. Discuss the many costs that businesses face today. Is it always practical to test new ideas via a ‘real life’ study – with participants, facilities, etc? If not, how can a simulation be utilized to test ideas while keeping costs manageable? If a simulation is used, what steps are needed in order to have a successful model?
8. What is the most practical and easily applied lesson you learned by answering the previous questions? What was the hardest to grasp? Why? What else do you need to know about Quantitative Analysis?