Dr Valentina Ferretti NAB 3.04

This course is compulsory on the MSc in Management Science (Decision Sciences). This course is available on the MSc in Management Science (Operational Research). 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 LSE.

Elementary statistical and mathematical concepts and experience of standard computer software is assumed.

A major characteristic of all decisions in every organisation and policy making context is that they are taken to achieve objectives, both short-term and long-term. To do this well is a fundamental skill for managers at every level in the organisation, as well as for policy makers. But decisions are often hard to make in the presence of multiple objectives, uncertainty about the future, and differences of opinion among key players. For decisions that require large amounts of resources and commitments, the weight of responsibility felt by the decision maker can be heavy, especially when the consequences require to consider judgements about trade-offs between benefits, risks and costs.

In this course students will learn how to use Risk and Decision Analysis as a form of analytics that supports decision making in private, voluntary and public organisations.  The course shows how a consistent and realistic mix of data and judgement can help decision makers to better achieve their objectives . Based on sound theory underlying normative, descriptive and prescriptive decision-making research, the course emphasises the practical application of Risk and Decision Analysis for decision-making on any topic in any organisational setting.

The course is designed to enhance the students’ decision capabilities when confronted with strategic or operational choices, when searching for decision opportunities, and when designing strategies and policies. It uses real-world Risk and Decision Analysis applications in organisations and public policy making, and employs several case-studies (supported by specialised decision software) to build students' skills in decision modelling and analysis. It covers modelling and supporting decisions involving multiple stakeholders and conflicting objectives (multi-criteria decision analysis) as well as uncertainty (decision trees, influence diagrams, and risk analysis).

The course is suitable for third-year undergraduates and postgraduate MSc students, who will attend the same lectures but different seminars. Past experience shows that both undergraduates and postgraduates benefit from asking questions and sharing their experiences in the interactive lectures.

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 project in the Week 7 and 1 essay in the Week 8.

There are two pieces of formative assignments:

• Group project plan (i.e. decision context selected, due in week 7)
• Individual technical report on classes 2, 3, 4 and 5 (due in week 8, these classes cover the additive tasks students will have to develop in their summative group project)

The topic of the project has to be a real world case study (e.g. what to recommend to a municipality analysing different options for the requalification of an abandoned subway station, what to recommend to a committee having to choose the next city for the Olympic games, which option to recommend to a company having to release a new product design, etc.). This will mean students will have to collect data, simulate a decision making process, develop critical abilities in the interpretation and discussion of the results of the model, and be able to link their process to insights coming from the latest developments in the scientific literature. Students are allowed to work in groups of maximum 4 people. In the individual technical report of the group project, students will have to report on the developed process and include a personal reflection on the operability of the tools and transferability of the developed process to other contexts. This assignment will help students develop their strategic problem solving and critical skills by demonstrating their ability to apply a quantitative model to solve a strategic decision making problem, critically evaluate its results, and develop robust 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.

Group project presentation (25%) due week 11 of Lent Term

Individual technical report on the group project (75%) due week 1 of Summer Term