Model-based decision processes for agenda building and project funding

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Essentially all organizations need to recognize relevant future developments in their operational environment as a backdrop for building strategic priorities which are typically implemented by choosing corresponding actions (such as R&D projects). These interlinked processes – most notably horizon scanning, strategic priority-setting and project selection – can all be framed as decision problems in which a subset or portfolio of alternatives is to be selected subject to limited resources and other relevant constraints. They can therefore be approached with methods of portfolio decision analysis (PDA) in order to maximize the value that the selected portfolio can be expected to yield and also to improve the transparency and quality of decision processes. This Dissertation develops PDA methods to support the above decision processes, particularly in contexts where there are significant uncertainties. These methods capture uncertainties through set inclusion of feasible parameters and probability distributions. The methods accommodate the possibly conflicting preferences of multiple decision-makers, and they help identify portfolios that are resilient across a range of scenarios about the future. They also help mitigate so-called post-decision disappointment, which results from the fact that those projects whose values have been overestimated are more likely to be selected. The methods in this Dissertation can also be used to develop optimal project funding policies which maximize the average value of the selected project portfolio or the number of those projects whose values are exceptionally high. They also guide the reduction of uncertainties by indicating about which projects it is optimal to acquire additional value estimates such that the resulting increase in the value of the portfolio exceeds the costs of acquiring such estimates.
Translated title of the contributionMalliperusteisia päätösprosesseja agendan rakentamiseen ja hankerahoitukseen
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Salo, Ahti, Supervising Professor
  • Salo, Ahti, Thesis Advisor
  • Liesiö, Juuso, Thesis Advisor
Publisher
Print ISBNs978-952-60-5677-7
Electronic ISBNs978-952-60-5678-4
Publication statusPublished - 2014
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • portfolio decision analysis
  • project selection
  • multi-attribute value theory
  • group decision making
  • incomplete information
  • robustness
  • scenarios
  • Bayesian modeling
  • value of information

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