Analysis For Business Decisions

1. Apply decision analysis techniques to solve business problems.
2. Formulate and solve linear programming problems.
3. Analyze and interpret decision trees.
4. Apply game theory concepts to competitive situations.
5. Manage inventory effectively using appropriate control models.
6. Utilize project management tools and techniques for successful project completion.

13 weeks, about 28 hours in total. Yours will differ.

1. Week 1Module 1: Introduction to Decision Analysis

   • Unit 1: Elements of Decision Analysis · 2 hours

     Define and understand the concept of a decision.. Identify the role and skills of a decision maker.. Explore the components of decision making: alternatives, states of nature, and criteria.. Distinguish between states of nature and decision alternatives..

2. Week 2Module 1: Introduction to Decision Analysis

   • Unit 2: Approaches to Decision Analysis · 2 hours

     Differentiate between qualitative and quantitative approaches to decision analysis.. Identify qualitative tools like Delphi method, market research, and historical analogy.. Recognize quantitative tools including mathematics, probability, and statistics.. Understand the objectives of decision making: profit maximization and loss minimization..

3. Week 3Module 1: Introduction to Decision Analysis

   • Unit 3: Types of Decision Situations · 2 hours

     Describe decision-making under certainty, uncertainty, risk, and conflict.. Identify techniques for decision-making under each condition.. Apply appropriate techniques to solve problems under different decision situations.. Differentiate between the techniques used for certainty, uncertainty, and risk..

4. Week 4Module 1: Introduction to Decision Analysis

   • Unit 4: Decision Trees · 2 hours

     Describe a decision tree and its components.. Distinguish between decision nodes and outcome nodes.. Represent decision problems using decision trees.. Apply fold back and tracing forward analysis.. Calculate outcome values using the backward pass..

5. Week 5Module 2: Operations Research and Modeling

   • Unit 5: Operations Research (OR) · 2 hours

     Trace the history and development of Operations Research (OR).. Define Operations Research and its key characteristics.. Explain the scientific method in Operations Research.. Discuss the necessity of Operations Research in industry.. Outline the scope and areas of application of Operations Research..

6. Week 6Module 2: Operations Research and Modeling

   • Unit 6: Modelling In Operations Research · 2 hours

     Define a model and describe the modeling process.. Classify different types of models: iconic, analogue, mathematical.. Identify characteristics of good models.. Outline the advantages and limitations of using models.. Explain the steps involved in model construction..

7. Week 7Module 2: Operations Research and Modeling

   • Unit 7: Simulation · 2 hours

     Define simulation and its purpose.. Outline the advantages and limitations of simulation techniques.. Identify areas of application for simulation.. Explain Monte Carlo simulation and its steps.. Differentiate between deterministic and stochastic simulation..

8. Week 8Module 2: Operations Research and Modeling

   • Unit 8: Systems Analysis · 2 hours

     Define a system and discuss systems theory.. Identify and describe the elements of a system.. Classify different types of systems: physical, abstract, open, closed.. Explain the concept of entropy in a system.. Discuss the importance of systems analysis in decision-making..

9. Week 9Module 3: Mathematical Programming and Optimization

   • Unit 9: Mathematical Programming (Linear Programming) · 2 hours

     Explain the requirements and assumptions of linear programming problems.. Identify areas of application of linear programming.. Formulate linear programming problems from word problems.. Discuss the advantages and limitations of linear programming.. Solve linear programming problems using the graphical method..

10. Week 10Module 3: Mathematical Programming and Optimization

    • Unit 10: The Transportation Model · 2 hours

      Describe the nature of a transportation problem.. Compute initial feasible solutions using the North West Corner, Least Cost, and Vogel's Approximation methods.. Solve unbalanced transportation problems.. Formulate a linear programming model for a transportation problem.. Improve initial solutions using the Stepping Stone and Modified Distribution methods..

11. Week 11Module 3: Mathematical Programming and Optimization

    • Unit 11: Assignment Model · 2 hours

      Identify types of assignment problems.. Draw a comparison between transportation and assignment problems.. Use the Hungarian method to solve assignment problems.. Solve maximization and minimization assignment problems.. Handle assignment problems with restrictions..

12. Week 12Module 3: Mathematical Programming and Optimization

    • Unit 12: Project Management · 2 hours

      Define project management and its value.. Identify the "body of knowledge areas" in project management.. List and explain the processes involved in project management.. Discuss the concept of project planning.. Solve problems using PERT and CPM techniques..

13. Week 13Module 4: Advanced Topics and Case Analysis

    • Unit 13: Sequencing · 2 hours

      Explain what scheduling involves and the nature of scheduling.. Understand the use of Gantt charts and assignment method for loading jobs in work centers.. Discuss what sequencing involves and the use of priority rules.. Solve simple problems on scheduling and sequencing.. Apply Johnson's rule to sequence jobs in two machines..

    • Unit 14: Games Theory · 2 hours

      Define the concept of a game.. State the assumptions of game theory.. Describe the two-person zero-sum games.. Explain the concept of saddle point solution in a game.. Find pure and mixed strategies in games..