Executive Development Programme in Prioritizing Options with MCDA Techniques

This course is designed for senior executives and decision-makers in business, government, and non-profit sectors who need to prioritize complex, multi-criteria options. Participants will learn to apply Multi-Criteria Decision Analysis (MCDA) techniques to evaluate and rank alternatives systematically, ensuring informed and effective decision-making processes.

Attendees will gain practical skills in using tools like Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Analytical Network Process (ANP) to handle real-world challenges. They will also develop the ability to communicate and justify their choices to stakeholders, enhancing their strategic leadership capabilities.

1. 1. Introduction to Multiple Criteria Decision Analysis (MCDA): Learners will understand the foundational concepts of MCDA, its applications in decision-making processes, and the key principles that underpin the technique. By the end of this module, learners will be able to identify situations where MCDA can be effectively applied.
2. 2. Decision-Making Frameworks and Models in MCDA: This module covers various frameworks and models used in MCDA, including criteria weighting, benefit function construction, and aggregation methods. Learners will gain the ability to select appropriate models based on specific decision contexts.
3. 3. Structuring Decision Problems with MCDA: Focuses on how to structure complex decision problems using MCDA techniques. Learners will master the art of defining criteria, alternatives, and objectives in a structured manner, ensuring that the decision-making process is both comprehensive and efficient.
4. 4. Data Collection and Analysis in MCDA: This module teaches learners how to collect and analyze data relevant to decision-making problems, including qualitative and quantitative data, and how to integrate this data into MCDA models.
5. 5. Weighting Criteria in MCDA: Explains the process of weighting criteria in MCDA, including the use of expert judgment, statistical methods, and multi-criteria weighting schemes. Learners will be able to assign weights that reflect the relative importance of different criteria in the decision-making process.
6. 6. Evaluating Alternatives with MCDA Techniques: Covers various methods for evaluating alternatives in MCDA, including direct scoring, weighted sum models, and outranking methods. By the end of this module, learners will be proficient in evaluating alternatives using multiple criteria.
7. 7. Sensitivity Analysis in MCDA: Introduces learners to sensitivity analysis in MCDA, helping them understand how changes in criteria weights or other parameters can affect the final decision. Practical skills in conducting and interpreting sensitivity analysis will be developed.
8. 8. Multi-Criteria Decision-Making under Uncertainty: Focuses on dealing with uncertainty in MCDA, including the use of probabilistic models and robust decision-making techniques. Learners will learn how to incorporate uncertainty into MCDA frameworks to make more resilient decisions.
9. 9. Integrating MCDA with Other Decision-Making Techniques: This module explores how MCDA can be integrated with other decision-making techniques, such as linear programming and game theory. Learners will understand how to combine these techniques to enhance their decision-making capabilities.
10. 10. Case Studies and Practical Application of MCDA: Concludes the programme with real-world case studies and practical applications of MCDA techniques. Learners will apply their knowledge to solve complex decision-making problems and present their findings, emphasizing the practical relevance of MCDA in executive decision-making.