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Helsinki University of Technology Systems Analysis Laboratory

RPM-Explorer - A Web-based Tool RPM-Explorer - A Web-based Tool

for Interactive Portfolio Decision Analysisfor Interactive Portfolio Decision Analysis

Erkka Jalonen and Ahti SaloSystems Analysis Laboratory

Helsinki University of TechnologyP.O. Box 1100, 02015 TKK, Finland

http://www.sal.tkk.fifirstname.lastname@tkk.fi

Helsinki University of Technology Systems Analysis Laboratory

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Robust Portfolio Modelling (RPM)Robust Portfolio Modelling (RPM)

Extends Preference Programming to portfolio problems – A subset of project proposals is selected in view of multiple evaluation criteria

– Project and portfolio value expressed as a weighted sum of criteria scores

– Admits incomplete information about criterion weights and projects’ scores

Focus on non-dominated portfolios (NDP)– A rational DM would not choose a dominated portfolio focus on NDPs

– All NDPs are computed with specialised algorithms

– Core Index value convey the share of NPDs that contain a given project

Liesiö, Mild, Salo (2006). Preference Programming for Robust

Portfolio Modeling and Project Selection, EJOR (to appear).

Helsinki University of Technology Systems Analysis Laboratory

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Dominance relations depend on the information set S– Loose statements lead to a large number of non-dominated portfolios (NDP)

– Complete information typically leads to a unique portfolio

Additional information makes the set of NDPs smaller – This information is modelled through a smaller weight set ( ) and/or

narrower score intervals ( )

– Several preference elicitation methods can be employed

– No new portfolio can become non-dominated

Elicitation efforts can be focused on borderline projects– Additional information affects the Core Index of borderline projects only

Narrower score intervals needed for borderline projects only

Impact of Additional Information (1/2)Impact of Additional Information (1/2)

w wS S

v vS S

( ) ( )N NP S P S

Helsinki University of Technology Systems Analysis Laboratory

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Impact of Additional Information (2/2)Impact of Additional Information (2/2)

No information A rank-ordering

542 NDPs 109 NDPs 104 borderline projects 64 borderline projects

0 | 0, 1w i iS w w w 01 2 3|rank

w wS w S w w w

Helsinki University of Technology Systems Analysis Laboratory

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Add. exter.

Decision Support in RPMDecision Support in RPM

Se

lec

ted

No

t se

lec

ted

Decision rules, heuristics

Additional information

Large set of

projects

Multiple criteria

Resource and

portfolio

constraints

Borderline

projects

focus on

Exterior proj. discard

Core projects choose

Borderline

Negotiation, iteration

Compute non-dom. portfolios

Update ND portfolios

Add. core

Preceding core proj.

Preceding exterior

Loose statements on weights and scores

Helsinki University of Technology Systems Analysis Laboratory

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RPM-Explorer - BackgroundRPM-Explorer - Background

Old: Analyses often suggest a single optimal solution– Recommendation often stated in written documents– Such documents provide little support for the interactive exploration of results

New: Provide an interactive interface to the analysis– Allow stakeholders to specify their preferences about the importance of criteria– Produce decision recommendations based on the stakeholders’ preferences – Visualise decision recommendations for projects based on Core Index values– Make use of widely available communication technologies (=Internet)

Helsinki University of Technology Systems Analysis Laboratory

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Add. exter.

Decision Support Tools for RPMDecision Support Tools for RPM

Se

lec

ted

No

t se

lec

ted

Decision rules, heuristics

Additional information

Large set of

projects

Multiple criteria

Resource and

portfolio

constraints

Borderline

projects

focus on

Exterior proj. discard

Core projects choose

Borderline

Negotiation, iteration

Compute non-dom. portfolios

Update ND portfolios

Add. core

Preeding core proj.

Preceding exterior

Loose statements on weights and scores

RPM-Solver©RPM-Explorer©

E.g Opinions-Online©(voting tool)

Helsinki University of Technology Systems Analysis Laboratory

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Application of RPM-Explorer - Case Study (1/4)Application of RPM-Explorer - Case Study (1/4)

Development of the strategic research

agenda for the Association of

Packaging Industry in Finland

Collaborative consultation process (i) producing research themes (70 participants)

(ii) commenting and elaboration of themes

(the same participants as in previous phase)

(iii) evaluating of themes (10 evaluators)

(iv) analysing them first personally and then

jointly in a workshop (15 decicion makers)

Research themes treated as ’projects’

Helsinki University of Technology Systems Analysis Laboratory

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Application of RPM-Explorer - Case Study (2/4)Application of RPM-Explorer - Case Study (2/4)

Themes (~80) evaluated with regard to three criteria(i) innovativeness

(ii) feasibility

(iii) relevance

– evaluated on a 1-to-7 Likert-scale

– theme-specific scores computed as the mean of evaluators’ ratings

Results communicated by RPM-Explorer and as pdf-documents

Interactive analysis of themes with DMs in two workshops – First one with the Board of the Association (14 leading industrialists)

– Second with 10 including external stakeholders

Helsinki University of Technology Systems Analysis Laboratory

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Application of RPM-Explorer - Case Study (3/4)Application of RPM-Explorer - Case Study (3/4)

Opinions-Online© Database

Internet RPM-Exploreranalysis applet

RPM-Explorer configuration

files

RPM-Solver

analysis software

Theme Producers

ThemeEvaluators

Decision Makers

Opinions-Online ©questionnaire software

Helsinki University of Technology Systems Analysis Laboratory

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Application of RPM-Explorer - Case Study (4/4)Application of RPM-Explorer - Case Study (4/4)

An Example: Theme Group 4: Packaging Materials

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RPM-Explorer in Use (1/2)RPM-Explorer in Use (1/2)

Specifications of

preferences results

in corresponding

adjustments in real-

time

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RPM-Explorer in Use (2/2)RPM-Explorer in Use (2/2)Several

visualization tools

Explicit support

for project

selection

Helsinki University of Technology Systems Analysis Laboratory

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RPM-Explorer - ConclusionsRPM-Explorer - Conclusions

Positive feedback from users – RMP-Explorer clearly stimulated workshop discussions

Generic software for many problem contexts and uses– Personal learning through Internet-mediated preference analysis

– Collaborative decision making in facilitated workshops

Software may introduce several benefits– Decision making: Personal interests, sensitivity analyses

– Communication: Increased commitment, enhanced understanding

– Information elicitation: Guidance for focusing the elicitation efforts

Helsinki University of Technology Systems Analysis Laboratory

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RPM-Decisions© (1/2)RPM-Decisions© (1/2)

RPM-Decisions©– Combines RPM-Solver and RPM-

Explorer

– Under intensive development

– Demo available

New Features– Web-interface to analysis (RPM-

Explorer)

– Criteria hierarchies

– Project interdependencies

– Soft budget constraints

www.rpm.tkk.fi

Helsinki University of Technology Systems Analysis Laboratory

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RPM-Decisions© (2/2)RPM-Decisions© (2/2)

Spread-sheet form data input– Scores, costs and constraints– Preference elicitation wizard– Constraint wizards

Computation– Approximative algorithms for large problems– Exact algorithms for up to 70 projects

Interactive analysis

– Core indexes, decision rules, robustness– Score scatter plots, additional information– Export for interactive analysis web-interface

Helsinki University of Technology Systems Analysis Laboratory

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On-going RPM Applications On-going RPM Applications

Management of infrastructure assets – Optimization of road and bridge maintenance and repair programmes

– Allocation of resources among different asset classes in view of multiple criteria

Voluntary conservation of forest reserves – Evaluation of conservation value of sites offered by forest owners

– Design of optimal decision analytic evaluation process

Innovation management – Valuation of intellectual property rights (Nokia Wireless Technologies)

– Evaluation of longitudinal data from innovation programmes (Salo et al., 2006)

– Solicitation, commenting, evaluation and selection of innovation themes