Helsinki University of Technology
Systems Analysis Laboratory
RPM-Explorer - A Web-based Tool
for Interactive Portfolio Decision Analysis
Erkka Jalonen and Ahti Salo
Systems Analysis Laboratory
Helsinki University of Technology
P.O. Box 1100, 02015 TKK, Finland
http://www.sal.tkk.fi
firstname.lastname@tkk.fi
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Helsinki University of Technology
Systems Analysis Laboratory
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).
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Helsinki University of Technology
Systems Analysis Laboratory
Impact of Additional Information (1/2)

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 (
narrower score intervals ( Sv  Sv )
Sw  Sw ) and/or
– Several preference elicitation methods can be employed
– No new portfolio can become non-dominated PN ( S )  PN ( S )

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
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Helsinki University of Technology
Systems Analysis Laboratory
Impact of Additional Information (2/2)



No information
S w0   w | wi  0,  wi  1 
542 NDPs
104 borderline projects
 A rank-ordering

S wrank  w  S w0 | w1  w2  w3
 109 NDPs
 64 borderline projects

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Helsinki University of Technology
Systems Analysis Laboratory
Decision Support in RPM
Large set of
projects
Loose statements
on weights and
scores
Multiple criteria
Compute non-dom.
portfolios
Add. core
Borderline
projects
Borderline
 focus on
Add. exter.
Update ND
portfolios
Exterior proj.
 discard
Decision
rules,
heuristics
Negotiation,
iteration
Not selected
Resource and
portfolio
constraints
Additional
information
Preceding
core proj.
Selected
Core projects
 choose
Preceding
exterior
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Helsinki University of Technology
Systems Analysis Laboratory
RPM-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)
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Helsinki University of Technology
Systems Analysis Laboratory
Decision Support Tools for RPM
Large set of
projects
Loose statements
on weights and
scores
Multiple criteria
Compute non-dom.
portfolios
projects
Borderline
 focus on
Add. exter.
Update ND
portfolios
Exterior proj.
 discard
E.g
Opinions-Online©
(voting tool)
RPM-Solver©
Add. core
Borderline
Decision
rules,
heuristics
Negotiation,
iteration
Not selected
Resource and
portfolio
constraints
Additional
information
Preeding
core proj.
Selected
Core projects
 choose
Preceding
exterior
RPM-Explorer©
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Helsinki University of Technology
Systems Analysis Laboratory
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’
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Helsinki University of Technology
Systems Analysis Laboratory
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
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Helsinki University of Technology
Systems Analysis Laboratory
Application of RPM-Explorer - Case Study (3/4)
Theme
Producers
Decision
Makers
Theme
Evaluators
Internet
RPM-Explorer
analysis applet
Opinions-Online ©
questionnaire software
OpinionsOnline©
Database
RPMSolver
analysis
software
RPM-Explorer
configuration
files
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Helsinki University of Technology
Systems Analysis Laboratory
Application of RPM-Explorer - Case Study (4/4)

An Example: Theme Group 4: Packaging Materials
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Helsinki University of Technology
Systems Analysis Laboratory
RPM-Explorer in Use (1/2)
Specifications of
preferences results
in corresponding
adjustments in realtime
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Helsinki University of Technology
Systems Analysis Laboratory
RPM-Explorer in Use (2/2)
Several
visualization tools
Explicit support for
project selection
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Helsinki University of Technology
Systems Analysis Laboratory
RPM-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
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Helsinki University of Technology
Systems Analysis Laboratory
RPM-Decisions© (1/2)

RPM-Decisions©
– Combines RPM-Solver and RPMExplorer
– Under intensive development
– Demo available

New Features
– Web-interface to analysis (RPMExplorer)
– Criteria hierarchies
– Project interdependencies
– Soft budget constraints

www.rpm.tkk.fi
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Helsinki University of Technology
Systems Analysis Laboratory
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
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Helsinki University of Technology
Systems Analysis Laboratory
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
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