1 School of Science and Technology Systems Analysis Laboratory Graduate school seminar presentation 28.5.2010 Current research topics in Portfolio Decision.

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1 School of Science and Technology Systems Analysis Laboratory Graduate school seminar presentation Current research topics in Portfolio Decision Analysis (PDA) Dr. Juuso Liesiö Systems Analysis Laboratory Aalto University School of Science and Technology P.O. Box 11100, Aalto, Finland

2 School of Science and Technology Systems Analysis Laboratory Multiattribute Project Portfolio Value Functions  Additive-linear value function standard in PDA-applications –Portfolio value is the sum of projects’ additive multiattribute values –Requires strong preference independence assumptions »E.g., the increase in portfolio value when adding a new project into the portfolio is constant –Evidence from applications suggests that often these assumptions do not hold  Research objectives –Relax the preference independence assumptions and derive corresponding non-additive measurable portfolio value functions –Develop techniques to elicit such value functions –Develop integer programming algorithms to maximize portfolio value subject to resource and other portfolio constraints

3 School of Science and Technology Systems Analysis Laboratory Value of Information in Portfolio Decision Analysis with Prof. Salo, Eeva Vilkkumaa, Antti Toppila  Applying PDA is often evaluation intensive –Usually dozens of projects need to be evaluated w.r.t multiple attributes –Evaluation gives only incomplete information about the project value –Careful planning of evaluation processes can reduce evaluation costs  Research questions –What is the value of additional information on project value? –How should resources be allocated between project funding and project evaluation? –Which project should be re-evaluated? –How does risk-aversion affect these results?

4 School of Science and Technology Systems Analysis Laboratory Robust portfolio models in scenario planning with Prof. Salo  Scenario building widely used to produce a structured view of the uncertain future  PDA offers a quantitative framework to evaluate actions that can be taken to prepare for the future –Scenario probabilities and actions impacts difficult to evaluate →Need to model incomplete information  Development of robust PDA models to support scenario building and strategy generation processes –Collaboration with the International Institute of Applied Systems Analysis (IIASA)