MG456 Half Unit
Analytics for Strategic Decisions
This information is for the 2017/18 session.
Dr Valentina Ferretti NAB 3.04
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), MSc in Marketing and MSc in Operations Research & Analytics. 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.
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, marketing management, resource allocation, operations management, and investment. Moreover, important decisions are not only made by managers and entrepreneurs, but also by the consumers of their goods and services, and by their business rivals, partners and employees. 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. The ability to make better decisions is an invaluable part of everyone’s toolbox. 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 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.
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).
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:
- Group project plan presentation (i.e. decision context selected) during week 7.
- Individual revision of an anonymous technical report from one of the previous editions of the course during week 8.
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 5 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.
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 on the group project is due in Week 1 of Summer Term.
Total students 2016/17: 71
Average class size 2016/17: 24
Controlled access 2016/17: No
Value: Half Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Specialist skills