杏吧论坛

Prof Valentina Ferretti NAB 3.04

This course is compulsory on the MSc in Management Science (Decision Sciences). This course is available on the CEMS Exchange, Global MSc in Management, Global MSc in Management (CEMS MiM), Global MSc in Management (MBA Exchange), MBA Exchange, MSc in Management (1 Year Programme) and MSc in Marketing. This course is available as an outside option to students on other programmes where regulations permit.

This course is complementary to any behavioural course offered at 杏吧论坛.

Elementary statistical and mathematical concepts.

How to choose in tough situations where stakes are high, and there are multiple conflicting objectives? How do we perceive risk, and how to act when there are risks and uncertainties involved in a decision? How can we create options that are better than the ones originally available? Decision making is a central aspect of virtually every management and business activity, including marketing, strategic planning, project management, resource allocation, operations management, and investment. The ability to make better decisions is thus an invaluable part of everyone’s toolbox, particularly for rising stars that will be in positions of leadership in the future. It is this ability that will be developed in this course, which introduces students to the use of Risk and Decision Analysis as a form of analytics that integrates hard data and judgments to develop winning strategies. Through this course students will learn how to better understand, represent, communicate and take decisions across many different contexts, both private and public. They will discover what are the key behavioural traps that prevent smart decisions to be made and what are the corresponding cutting edge analytical solutions.

The course uses real-world Risk and Decision Analysis applications in organisations and public policy making, and employs several case-studies to build students' skills in decision modelling and analysis. It covers structuring and modelling decisions involving multiple stakeholders and conflicting objectives (multi-criteria decision analysis) as well as uncertainty (decision trees, influence diagrams, and risk analysis). This course is open to anyone with a keen interest towards discovering the vital ingredients to smart decision-making processes.

20 hours of lectures and 13 hours and 30 minutes of seminars in the LT.

A reading week will take place in Week 6. There will be no teaching during this week.

Students will be expected to produce 1 presentation and 1 essay in the LT.

There are two pieces of formative assignments:

1. Group project plan presentation (i.e. personal decision context selected, due in week 7)

2. Individual review of an anonymous technical report developed from students who took this course last year. Students will have to review the report by following specific criteria and by completing a set of both descriptive and evaluative tasks (e.g. indicating the strongest part of the report, indicating sentences or paragraphs that seem out of order, incompletely explained or in need of revision, etc.). This review assignment will help students to improve their reading, writing and collaborative skills.

The topic of the project (i.e. a decision making problem to be modelled and analysed by means of Multicriteria Analysis) can be a personal decision (i.e. which job offer to accept when confronted with multiple ones, which master to apply for, etc.) or a real world case. Students will have to collect data, develop and apply a quantitative model, interpret the results and refer to the key scientific literature for the main steps in the development of the model. Students are allowed to work in groups of maximum 4/5 people. In the individual technical report of the group project, students will have to report on the developed process. This assignment will help students develop their operational problem solving skills by demonstrating their ability to apply a quantitative model to solve a strategic problem, interpret its results, and develop sound recommendations.

Belton, V. and Stewart, T. (2002) Multiple Criteria Decision Analysis. London, Kluwer.

Bouyssou, D., Marchant, T., Pirlot, M., Tsoukias, A., and Vincke, P. (2006) Evaluation and Decision Models with Multiple Criteria. Stepping stones for the analyst. Springer, International Series in Operations Research & Management Science, Vol. 86.

Bouyssou, D., Marchant, T., Pirlot, M., Tsoukias, A., and Vincke, P. (2007) Evaluation and Decision Models with Multiple Criteria. A critical perspective. Springer, International Series in Operations Research & Management Science, Vol. 32.

Clemen, R.T. and Reilly, T. (2014)  Making Hard Decisions. Pacific Grove: Duxbury.

Edwards W., Miles Jr R.F. and von Winterfeldt D. (eds). Advances in Decision Analysis: From Foundations to Applications. Cambridge University Press: New York.

Eisenführ, F., Weber, M. and Langer, T. (2010) Rational Decision Making, 1st ed. Berlin: Springer.

Goodwin, P. and G. Wright (2014). Decision analysis for management judgement. Chichester, Wiley.

Ishizaka, A. and Nemery, P. (2013) Multi-criteria Decision Analysis: Methods and Software. Wiley

Keeney, R.L. (1992) Value-Focused Thinking: A Path to Creative Decision-making. Cambridge: Harvard Univ. Press. HD30.23 K21 (Course Collection).

Keeney, R. L. and Raiffa, H. (1993) Decisions with Multiple Objectives: Preferences and Value Trade-offs. Cambridge: Cambridge University Press, 2nd ed.

Mcnamee, P. and Celona, J. (2007) Decision Analysis for the Professional. Menlo Park: Smart Org, 4th ed (e-book available in the library).

G.S. Parnell et al. (2013) Handbook of Decision Analysis. Hoboke, Wiley.

von Winterfeldt, D. & Edwards, W. (1986) Decision Analysis and Behavioral Research. Cambridge: Cambridge University Press.

Project (25%) in the LT.
Essay (75%) in the ST.

Presentation of the group project (25%) and an individual technical report on the group project (75%).

The presentation is of the group project is due in Week 11 of Lent Term.

The individual technical report for the group project is due in Week 1 of Summer Term.

In May 2017 Dr Valentina Ferretti was awarded an 杏吧论坛 Student-led Teaching Excellence Award in the category of Inspirational Teaching for this course