Contents Introduction of Metsähallitus Use of decision support tools Experiences

1. Experiences on the use of decisionsupporttools in participatoryforestplanning at MetsähallitusRobin Wood conference 11.10. 2013 Veikko Hiltunen, Metsähallitus, Forestry - senior adviser • Contents • Introduction of Metsähallitus • Use of decisionsupporttools • Experiences • References: - ForestPolicy and Economics 10 (2008) 117-127 - ForestPolicy and Economics 9 (2009) 1-9 - Can. J. For. Res. 37: 853-865 (2007) - Silva Fennica 46(4): 539-554 (2012)

2. Forest land in commercial forests, 3.6 million ha Poorly productive and non-productive land, 1.5 million ha (excluded from forestry) Protected areas, wilderness reserves and other areas, 4.0 million ha Water areas, 3.4 million haPublic water areas In total12.5 million ha = 1/3 of the country Ownership of forest land in Finland State (Metsähallitus)CompaniesOther Private forest owners Metsähallitus’ lands and waters

3. History of the use of desionsupport (DS) tools • Participationwasstarted in early 1990’s • Regionalstakeholdergroupsare in the keyrole • Citizenshavealsotheirsays in the planning • Use of decisionsupporttoolsstartedparallelwithparticipation • Evaluation of alternativeplansweresupportedfirst • Withnumerical, cardinalDS methods, likeaplications of AHP and SMART • Wehavenormally5 - 8 differentoptionalplans in comparison • Support for criteriaselection and preferenceelicitingstarted in early 2000’s • OrdinalDS methods, likevotingmethods, wereadapted • Combineduseof ordinal and cardinal DS methodswastaken into use in late 2000’s • In evaluation

4. Votingtechniquesapplied 1(2) • Plurality voting and approval voting (AV) • Have been used in selection of the decision criteria • objectives (= whatwewant) arediscribed in moredetails in terms of criteria • In deciding the number of the criteria • In selectionbetweencompetitavecriteriacandidates • In plurality voting every voter has one voice that she/he casts to the candidate she/he prefers. The candidate getting most votes is the winner. • In approval voting every voter gives a vote to so many candidates than she/he “approves”. The candidate getting most votes is the winner.

5. Traditionalvotingtechniquesapplied 2(2) • Borda count and cumulative voting • Have been used in eliciting preferences of stakeholders • (= howimportantaredifferentobjectives in relation to eachothers) • In Borda count method, in a case of n candidates, a voter gives points to the most preferred candidate, n-1 to the second preferred candidate, etc., until one to the least preferred one • In a common application of cumulative voting, a voter distributes 100 points to the candidates in a way she/he prefers • In bothmethods the group’spreferencesconsist of the sum of the individuals’ preferences

6. Multicriteriadecisionsupport (MCDS) methodsapplied in the evaluation of the alternativeplans • Multicriteria approval (MA) • Approval borders (thresholds)are first decided for every criterion • Plan alternatives are classified as approved or disapproved in regard of every criterion • In holistic evaluation of the alternatives importance order of the criteria is utilised • Provides the rank of the alternatives(= ordinalevaluation) • Interactive utility analysis (IUA) • Structuring the decisionhierarchy of the problem (Valuetreeanalysis) • Deciding the weights of the criteria on eachlevel (by AHP or SMART) • Providescardinal,numericalevaluation of the alternatives • Combination of MA and IUA • Ranking the alternatives by MA • Deeper cardinal analysis with IUA (for best alternatives) • Wehavetestedalsosomeothertechniques, buttheyarenotrepotedhere

7. Experiences on the use of DS methods 1(2) • Votingmethods • Plurality voting and approval voting (AV) • Both work well in criteria selection, our experiences recommend using AV • Borda count and cumulative voting • Bothwork in preferenceeliciting, ourexperiencesrecommend the use of Borda Count method • MA- method • EvaluationsolutioncanoftenbefoundbyMA-voting, • Example of Kainuu • Ifnot, deeperanalysiscanbecarried out withcardinalmethods • In thatphase, the participantsarewelleducated into the planningproblem, whichhelps in selecting an appropriatemethod and finding a common solution • Allowonlysimplesensitivityanalysis

8. Example 1. Results of cumulativevoting and Borda Count voting in the planning case of Kainuu • Preference of the criteria in the stakeholder group by different votings •  results differ by methods and by a priori / posteriori eliciting • Cumulative voting, Borda count voting, Borda count voting, • a prioria priori posterior • criterion • - CUT - ECONETWORK - JOBS • - QUAL OF ENW - SCENERY - CUT • - SCENERY - CUT - SCENERY • - JOBS - JOBS - QUAL OF ENW • - ECONETWORK - QUAL OF ENW - ECONETWORK • - TURNOVER - GAME - TURNOVER • - GAME - INCOME - GAME • - INCOME - TURNOVER - INCOME • Importanceorder of the criteria is differentbydifferentmethods and in a priori and posteriorivotings • In groupdiscussions, Borda Count posterioriwasassessed as the mostvalid and to beused in evaluation

9. Example 2. Results of MA evaluation of the alternativeplans in Kainuu region-Alternative 5 became a clearfavoriteCriteria in theirimportanceorder

10. Experiences on the use of DS methods 2(2) • Cardinal methods(like IUA) • Provide ”exact” prefenceinformationbetween the alternativeplans and allowsophisticatedsensitivityanalysis • Participantsneed to know and understand the methodswell • An outsider expert / facilitator is generallyneeded for use the method • Combineduse of ordinal and cardinalmethods • The plansarefirstanalysedbyordinalvotingmethods • Deepercardinalanalysis for bestalternativeswithcardinalmethods, like IUA • Example of Western Finland

11. Example 3. Results of MA evaluation of the alternativeplans Western Finland region • Criteria in their importance order • ECONET RECR JOBS RICH CUT BEAUT INC TURN • Alternative • BASIC - - + - + - + + • ECONO - - + - + - + + • CONS - - + + + - + - • CONS2 + + - + - + - - • REC + + - + - + - - • COMB + + - + - + - - • PROTEC + + - + - + - - • Alternatives (4) – (7) seem to doequallywell

12. Example 4. Results of IUA evaluation of alternatives in Western Finland regionGlobalpriorities of the alternatives - Alternative 5 carrieshighestutility

13. Lessons • Multi-goalapproachis the basicmatter in participatoryplanning • Use of DS toolsimproveswork of the participatorygroups and makesitmoreefficient • Mutuallyagreedconcepts pointlessarguingdecreases • Emphasis on elements to bedecided, likepriorities and criteria • The processbecomesmoretransparent and fair • Also the ”shy and silent” becomeequallyheardwith DS tools • Transparencyimprovesunderstanding of otherparticipants’ sights in the groupfacilitatesgroupnegotiations and finding the group’s common decision • However, finaldecisionshave in allourcasesbeen a matter of humanjudgement • Acceptance of the resultshasimproveddue to the applied DS methods

14. Lessons Behavioralaspectsareimportant • Easiness to use and understandappliedmethodsis especiallyimportant in participatoryapproaches • Manypeoplemoreeasilyaccept a satisfactorysolution the rationale of whichtheycanunderstandthanresults of sophisticatedmethodswhicharetoocomplex for them • Facilitators, visualisation, etc. is needed to interpretcalculations, alternatives, results • Inquiriesneeded in a DS methodshouldnotbetoodifficult • e.g. ifit is hard for stakeholders to express cardinalimportance for the criteria, forcingthem to answercorresponginginquiriesmightlead to biasedresults • Interactivity is a precondition of the effectiveness of mostdecisionsupportprocesses (withanymethod)

15. Main messages • Generally, keep a participatoryprocess as simple as possible • Usedecisionsupportmethodsadaptively • Apply ”easy” ordinalmethodsfirst, • Cardinal methodsthereafterifnecessary • Votingmethodsproviderelevantsupportalso for evaluation • Votingmethodsarefamiliar to mostparticipantsfromothercontexts (likeelections), easy in theirprinciples, and easy to use • Ifdeeperanalysisareneeded, the votingresultsserve a naturalbasis for cardinalanalysis • Directholisticevaluationseldomprovides the bestsolution

16. Thankyou !