Basic principles of structured decision making and ...people.oregonstate.edu/~peterjam/SDM_AFS_2011/SDM... · Structured Decision MakingProcess • Identify the decision situation

Basic principles of structured Basic principles of structured decision making and adaptive decision making and adaptive

managementmanagementContinuing EducationContinuing Education Workshop

2011 American Fisheries Society Meeting2011 American Fisheries Society Meeting

James PetersonJames Peterson Krishna Krishna PacificiPacifici

Important backgroundImportant backgroundWhat is What is ‘‘managementmanagement’’??

•• Taking an action to obtain some desired Taking an action to obtain some desired resource outcomeresource outcome

•• Requires:Requires:–– A range of alternative actions that can be takenA range of alternative actions that can be taken–– An objective weAn objective we’’re trying to achievere trying to achieve

All management is based on models!All management is based on models!•• Represents our current view of how the Represents our current view of how the

system is likely to respond to system is likely to respond to managementmanagement

•• Based on biological knowledge Based on biological knowledge (research)(research)

•• May be imperfect (WeMay be imperfect (We’’ll comell come•• back to this)back to this)

But how are decisions really made??But how are decisions really made??

Basic Elements of Natural Resource Basic Elements of Natural Resource DecisionDecision--makingmaking

CurrentCurrentspeciesspeciesstatusstatus

ManagementManagementactionaction

Actual Actual futurefuturestatusstatus

Notions ofNotions ofsystem system

dynamicsdynamics

AnticipatedAnticipatedfuture future statusstatus

Revise/updateRevise/updateideas ideas

ModelsModels PredictionsPredictions

InformationInformation

Traditional Traditional ‘‘Black BoxBlack Box’’ Approach to DecisionApproach to Decision--makingmaking

10,000 ha10,000 ha

60,000 ha60,000 ha

??????

RookieRookie

TargetTarget

Thesis

Final report

Final report

Dissertation

TAFS

JWM

Monitoring Report 2010 Monitoring Report 2010

Status and Trends

Problems with Black Box Approaches Problems with Black Box Approaches •• Generally not explicit or transparentGenerally not explicit or transparent•• Many unidentified and unstated assumptionsMany unidentified and unstated assumptions

Habitat available

Spec

ies

pers

iste

nce

•• MANYMANY uncertaintiesuncertainties

Spec

ies

pers

iste

nce

Habitat available

60,000 ha 10,000 ha

Problems with Black Box Approaches Problems with Black Box Approaches •• Not transferable or repeatableNot transferable or repeatable

•• No formal learning componentNo formal learning component

RookieRookie

VeteranVeteran

RetireeRetiree(information sink)(information sink)

Failure to use quantifiable objectives or Failure to use quantifiable objectives or feedbackfeedback

Are we Are we there there yet?yet?

Are we Are we there there yet?yet?

Good places

Environmental uncertaintyEnvironmental uncertaintydue to environmental and demographic variationdue to environmental and demographic variation

Popu

latio

n si

zePo

pula

tion

size

timetime

Wet yearWet year

Dry yearDry year

MgntMgnt. action A

. action A

Action BAction B

Uncertainty and decisionUncertainty and decision--makingmaking


Statistical uncertaintyStatistical uncertaintydue to the use of sample data to estimate parametersdue to the use of sample data to estimate parameters

Popu

latio

n si

zePo

pula

tion

size

timetime

Wet yearWet year

Dry yearDry year

Action AAction A

Action BAction B


Ecological (system) uncertaintyEcological (system) uncertaintydue to incomplete understanding of system dynamicsdue to incomplete understanding of system dynamics


Statistical uncertaintyStatistical uncertaintydue to the use of sample data to estimate parametersdue to the use of sample data to estimate parameters

Popu

latio

n si

zePo

pula

tion

size

Habitat availabilityHabitat availability


The Basis of Adaptive ManagementThe Basis of Adaptive Management

Structured Decision MakingStructured Decision Making

Management ActionsManagement Actions(habitat improvement, predator (habitat improvement, predator

control, captive breeding)control, captive breeding)

External Physical InfluencesExternal Physical Influences(weather, habitat conditions)(weather, habitat conditions)

Populations/Populations/CommunitiesCommunities

External Biological InfluencesExternal Biological Influences(competitors, predators, (competitors, predators,

exotics) exotics)

Stakeholder BenefitsStakeholder Benefits(Public satisfaction)(Public satisfaction)

Structured Decision MakingStructured Decision Making ProcessProcess•• Identify the decision situation and objectivesIdentify the decision situation and objectives

•• Identify and separate Identify and separate fundamentalfundamental and and meansmeans objectives (essential!)objectives (essential!)

Means objectives networkMeans objectives network

MinimizeMinimizeextinction riskextinction risk

MaximizeMaximizespatialspatial

distributiondistribution

IncreaseIncreasehabitathabitat

MinimizeMinimizemortalitymortality

Why is that Why is that important?important?

FundamentalFundamentalobjectivesobjectives

How could I How could I achieve this?achieve this?

MeansMeansobjectivesobjectives

ExoticExoticcontrolcontrol

EstablishEstablishcorridorscorridors

An alternative perspectiveAn alternative perspective








•• Focuses efforts things that matter most to the decisionFocuses efforts things that matter most to the decision--makermaker

Ecologist perspectiveEcologist perspective

MaximizeMaximizeharmonyharmony

MakeMakeconstituentsconstituents

happyhappy


MakeMakebossboss

happyhappy

Bureaucrat perspectiveBureaucrat perspective

Perceived asPerceived asdoing somethingdoing something

The importance of identifying and structuring objectivesThe importance of identifying and structuring objectives








TimeTime

Hab

itat a

vaila

bilit

yH

abita

t ava

ilabi

lity

Prob

abili

ty p

ersi

sten

cePr

obab

ility

per

sist

ence

Adaptive Adaptive resource resource

managementmanagementConflictConflictNoNo

Routine Routine management management

sciencescience

Negotiation, Negotiation, compromisecompromiseYesYes

YesYesNoNo

Agreement on science?Agreement on science?(how do we get there)(how do we get there)

Agreement on management objectives?Agreement on management objectives?(where do we go)(where do we go)

from Lee (1993)from Lee (1993)

PoliticsPolitics BiologyBiology

The importance of identifying and structuring objectivesThe importance of identifying and structuring objectives

Utility = species A + species BUtility = species A + species B

Structured Decision MakingStructured Decision Making ProcessProcess•• Identify the decision situation and objectivesIdentify the decision situation and objectives


-- For single objectives, it can be simple function of estimated oFor single objectives, it can be simple function of estimated output utput e.g., animal abundance, probability of persistence.e.g., animal abundance, probability of persistence.

-- When there are multiple objectives, need a means to combine valWhen there are multiple objectives, need a means to combine valuesuesin a objective function in a objective function

•• Develop utility values based on objectivesDevelop utility values based on objectivesPe

rsis

tenc

ePe

rsis

tenc

ess p

ecie

s A

peci

es A

Grassland habitatGrassland habitat

optimumoptimum

Pers

iste

nce

spec

ies

BPe

rsis

tenc

e sp

ecie

s B

•• Identify the decision situation and objectivesIdentify the decision situation and objectives


-- For single objectives, it can be simple function of estimated oFor single objectives, it can be simple function of estimated output utput e.g., animal abundance, probability of persistence.e.g., animal abundance, probability of persistence.

-- When there are multiple objectives, need a means to combine valWhen there are multiple objectives, need a means to combine valuesuesin a objective function in a objective function

•• Develop utility values based on objectivesDevelop utility values based on objectives

•• Identify decision alternativesIdentify decision alternativese.g., land management, captive breeding, regulationse.g., land management, captive breeding, regulations

Structured Decision MakingStructured Decision Making ProcessProcess

Where do we get the information?Where do we get the information?

Empirical dataEmpirical data

Published reports (metaPublished reports (meta--analysis)analysis)

•• Construct the model (need to estimate the outcome!)Construct the model (need to estimate the outcome!)-- Simple (simple is good!)Simple (simple is good!)-- Complex Complex

Structured Decision MakingStructured Decision Making ProcessProcess

““ExpertExpert”” judgmentjudgment

Making the DecisionMaking the Decision

YesYes

NoNo

Improve Improve habitathabitat

0.600.60

0.400.40PurchasePurchasereservereserve

colonizecolonizeCostCost

$270k$270k

$70k$70k

$200k$200k

Purchase reserve = 0.6*70 + 0.4*270 Purchase reserve = 0.6*70 + 0.4*270 = $150= $150

Improve habitat = $200Improve habitat = $200

““CertaintyCertainty--weightedweighted”” cost (thousands)cost (thousands)

What would I decide if the probability of colonization were 0.4?What would I decide if the probability of colonization were 0.4?

Probability weighted utilityProbability weighted utility

(reserve)(reserve)

(reserve(reserve++

habitat)habitat)

(habitat)(habitat)

Goal = minimize cost of Goal = minimize cost of conservation action whileconservation action whileincreasing persistenceincreasing persistence

Making the DecisionMaking the Decision

YesYes

NoNo

Improve Improve habitathabitat

0.400.40

0.600.60PurchasePurchasereservereserve

colonizecolonize

$270k$270k

$70k$70k

$200k$200k

““CertaintyCertainty--weightedweighted”” cost (thousands)cost (thousands)

Purchase reserve = 0.4*70 + 0.6*270 Purchase reserve = 0.4*70 + 0.6*270 = $190= $190

Improve habitat = $200Improve habitat = $200

0.350.35 0.450.45 0.550.55 0.650.65

Natural adult mortalityNatural adult mortality

Juvenile mortalityJuvenile mortality

Carrying capacityCarrying capacity

Persistence probabilityPersistence probability

0.250.25

Colonization mechanismsColonization mechanisms(system uncertainty)(system uncertainty)

Identify key uncertaintiesIdentify key uncertainties: : Sensitivity AnalysisSensitivity Analysis

PrecipPrecip. during breeding. during breeding

Model componentsModel components

Exotic densityExotic density

More sensitiveMore sensitive

Less sensitiveLess sensitive

Reducing uncertainty: Learning how a system worksReducing uncertainty: Learning how a system works

TimeTime

Popu

latio

n si

zePo

pula

tion

size

High riskHigh risk

Moderate RiskModerate Risk

Low riskLow risk

““ExperimentExperiment””

•• Conduct additional studies/experimentsConduct additional studies/experiments-- Time consuming (decisions canTime consuming (decisions can’’t wait)t wait)-- ExpensiveExpensive-- RiskyRisky

timetime

Decision Decision Decision Decision

Population Population Population Population

Sequential decisionSequential decision--making through timemaking through time

C. Moore

Learning how a system worksLearning how a system works•• Conduct additional studies/experimentsConduct additional studies/experiments

-- Time consuming (decisions canTime consuming (decisions can’’t wait)t wait)-- ExpensiveExpensive-- Potentially wastefulPotentially wasteful

•• Learn while managing (Adaptive Management)Learn while managing (Adaptive Management)-- Decisions are madeDecisions are made-- Requires Requires sequential dynamic sequential dynamic decisiondecision--making: time and/or spacemaking: time and/or space

Sequential decisionSequential decision--making through spacemaking through space

•• Conduct additional studies/experimentsConduct additional studies/experiments-- Time consuming (decisions canTime consuming (decisions can’’t wait)t wait)-- ExpensiveExpensive-- Potentially wastefulPotentially wasteful

Learning how a system worksLearning how a system works

•• Learn while managing (Adaptive Management)Learn while managing (Adaptive Management)-- Decisions are madeDecisions are made-- Requires Requires sequential dynamic sequential dynamic decisiondecision--making: time and/or spacemaking: time and/or space

timetime

Site ASite A

Site BSite B

Site CSite C

Site DSite D

Site ESite E

Site FSite F

Site GSite G

C. MooreC. Moore

An illustration: Robust An illustration: Robust redhorseredhorse

Flathead catfish abundanceFlathead catfish abundance

Red

hors

eR

edho

rse

abun

danc

eab

unda

nce

Predation by exotics?Predation by exotics?

Flow variabilityFlow variability

Red

hors

eR

edho

rse

abun

danc

eab

unda

nce

Hydropower generation?Hydropower generation?

Why are they so rare?Why are they so rare?

Decrease Decrease power generationpower generation

Control Control flatheadsflatheads

Management Management actionaction

SystemSystemdynamicsdynamics

PredictedPredictedredhorseredhorse

7070Flow variabilityFlow variability

PredationPredation

1010


PredationPredation

5050

0.50.5

0.50.5

0.50.5

0.50.5

4040

3030

00 11 22 33 44Red

hors

eR

edho

rse

abun

danc

eab

unda

nce







PredationPredation

1010


PredationPredation

5050

0.60.6

0.40.4

0.60.6

0.40.4

4646

2626

00 11 22 33 44Red

hors

eR

edho

rse

abun

danc

eab

unda

nce







PredationPredation

1010


PredationPredation

5050

0.30.3

0.70.7

0.30.3

0.70.7

2828

3838

00 11 22 33 44Red

hors

eR

edho

rse

abun

danc

eab

unda

nce

• Conduct additional studies/experiments- Time consuming (decisions can’t wait)- Expensive- Potentially wasteful

Learning how a system worksLearning how a system works

• Learn while managing (Adaptive Management)- Decisions are made- Requires sequential dynamic decision-making: time and/or space- Requires monitoring

Current state of the system (where are we?)Actual outcome of the decision (where did we end up?)

Harvest

Currentpopulation

Managementaction

Actual future

population

Model A(hypothesis)

Predicted population

Model B(hypothesis)

Predicted population

Info (monitoring data)t Info (monitoring data) t+1

Bayes’Rule

Adaptive ManagementAdaptive ManagementBasic elements:

Sequential decision-making

2 or morealternative

models

Monitoring

Basic Forms of Adaptive Basic Forms of Adaptive ManagementManagement

Relatively simpleRelatively simple

Choose decisions as if current Choose decisions as if current uncertainty will not changeuncertainty will not change

Information gained through Information gained through monitoring is incorporated, but monitoring is incorporated, but not in a planned waynot in a planned way

Computationally more complexComputationally more complex

Potential information returned by Potential information returned by each decision is given value when each decision is given value when evaluating each decisionevaluating each decision

““ProbingProbing”” is valued when: is valued when: -- uncertainty is very highuncertainty is very high

--management loss is expected management loss is expected to be high if uncertainty is to be high if uncertainty is unresolvedunresolved

PassivePassive ActiveActive

Misconception ManiaMisconception Mania

Adaptive management isAdaptive management is::

ManagementManagement

A formalA formal quantitative quantitative decision decision making process for choosing making process for choosing the best strategy and learningthe best strategy and learning

Flexible and can be used with a Flexible and can be used with a wide range of model types and wide range of model types and complexitycomplexity

Adaptive management is Adaptive management is NOTNOT::

ResearchResearch

Trying a management strategy until it Trying a management strategy until it fails, then adopting anotherfails, then adopting another

Implementing a strategy (experiment) Implementing a strategy (experiment) until an effect is detecteduntil an effect is detected

Too complex, too expensive, too hardToo complex, too expensive, too hard

•• Agricultural irrigationAgricultural irrigation

•• Increasing urbanization Increasing urbanization

•• Climate change Climate change

•• TriTri--state state ““Water WarsWater Wars””

AtlantaAtlanta

Flint River Basin

•• Endangered speciesEndangered species

Case study: Adaptively Managing Water Case study: Adaptively Managing Water Recourses in the Flint River Basin GeorgiaRecourses in the Flint River Basin Georgia

Science teamScience team StakeholdersStakeholders

Step 1: Identify decision situation and objectivesStep 1: Identify decision situation and objectives

HydrologistsHydrologistsGeomorphologistsGeomorphologists

BiologistsBiologists

Decision situationDecision situation

Decision contextDecision contextManage Manage water resourceswater resources as to maximize citizen satisfactionas to maximize citizen satisfaction

Spatial dimensionsSpatial dimensionsManagement decisions are made for individual (proposed) projectsManagement decisions are made for individual (proposed) projects(stream segment or reach(stream segment or reach--specific) over the entire basinspecific) over the entire basin

Planning horizonPlanning horizonInfinite time horizon (ensures sustainability), with decisions Infinite time horizon (ensures sustainability), with decisions potentially occurring on an annual time step.potentially occurring on an annual time step.

Decision alternativesDecision alternativesFlow regulationsFlow regulationsReservoir Reservoir sitingsiting, water withdrawal, wastewater , water withdrawal, wastewater Urban development Urban development BMPsBMPs

MaximizeMaximizepublicpublic

satisfactionsatisfaction

MaximizeMaximizeaestheticaesthetic

value value

MaximizeMaximizeBoatableBoatable//floatable floatable

daysdays

MaximizeMaximizewater water

availableavailablefor usefor use

MaximizeMaximizenonnon--consumptiveconsumptiveuser satisfactionuser satisfaction

MaximizeMaximizeconsumptiveconsumptive

user satisfactionuser satisfaction

MaximizeMaximizeanglingangling

opportunitiesopportunities

Maximize Maximize native native

biodiversitybiodiversity

Maximize Maximize water water qualityquality

LiberalizeLiberalizefishing fishing

regulationsregulations

MaximizeMaximizesportfishsportfish

populationspopulations

Partial fundamental and means objectives networksPartial fundamental and means objectives networks

gradient

Coarsewood

dissolvedsolids

Exported water(to lower basin)

bedrockcontrol

stream size(watershed size)

Boating

AestheticsLow (base) flowsExtreme low flow

Large Floods

Small floods

bedloadcharacteristics

channel geometry

riparian zone

reach postion(location)

watersource

Aquaticbiota

Riparianbiota

Shoalbass

water quality

sinuousity

confinement

reachisolation

lateralisolation

anglingmortality

exotic species

pathogens nutrients/contaminents

suspendedsediment

Temperature/dissolved oxygen

High flow pulses

Stream impoundmentStream impoundment Land use Land use BMPsBMPs Water useWater use

Step 2: Modeling the desired outcomesStep 2: Modeling the desired outcomes

Aquaticbiota

Water qual(DO, Temp)

Low (base) flows Extreme low flow

Wastewater/runoff

High flow pulses

exotic species

Water use(GW SW)

Boating

Small floods

reachisolation

stream impoundment

Aesthetics

Biological productivity

Large Floods

Nutrients

Organic matter delivery

Channel condition(type specific)

Water quality(human standards)

Land use

Spawning/seasonalmovement cues

Depth velocitydistribution

Riparian condition/ biota(type specific)

Sediment deliveryand transport

Climate

Channel/valleygeology

Step 3: Refine the modelStep 3: Refine the model

Aquaticbiota






Large Floods Small floods High flow pulses Low (base) flows Extreme low flow

reachisolation

Basic aquatic biological componentsBasic aquatic biological components

Aquaticbiota






Large Floods Small floods High flow pulses Low (base) flows Extreme low flow

reachisolation

Reality checkReality check

High flowHigh flow

Low flowLow flow

Model response as a function of channel morphologyModel response as a function of channel morphology

Final model of Flint River Basin dynamicsFinal model of Flint River Basin dynamics

Wastewater/runoff

Water use(GW SW)

Aesthetics

Extreme low flowLow (base) flowsHigh flow pulsesSmall floodsLarge Floods

stream impoundment

Land coverClimate

Channel condition

(type specific)

Riparian condition


Channel/valleygeology

Aquatic biota(fishes)

Water quality (human standards)

Boatingrecreation

Water quality(DO, Temp)Biological

productivity


reachisolation

Extreme low flowLow (base) flowsHigh flow pulsesSmall floodsLarge Floods

Channel condition

(type specific)

Riparian condition


Water use(GW SW)stream

impoundment

Land use BMPClimate

Aquatic biota

Water quality(DO, Temp)Biological

productivity


reachisolation

Wastewater/runoff

Step 4: Model parameterizationStep 4: Model parameterization

Seasonal sampling 2001Seasonal sampling 2001--20082008

Multiple Study sitesMultiple Study sites

Existing data Existing data Lower Flint River BasinLower Flint River Basin

MultiMulti--state multistate multi--season season occupancy modelsoccupancy models

DischargeDischarge

Ecological response models: Ecological response models: occupancy of stream segmentsoccupancy of stream segments

Geomorphic channel type (habitat template)Geomorphic channel type (habitat template)

P(colon/persist/reprodP(colon/persist/reprod) = ) = f(speciesf(species, geomorphic channel type, stream size,, geomorphic channel type, stream size,juxtaposition, discharge)juxtaposition, discharge)

Hydrologic modelingHydrologic modeling--Precipitation Runoff Modeling System: PRMSPrecipitation Runoff Modeling System: PRMS

Potato Creek482km2

5 12-digit HRUs

Model flows in stream segmentsModel flows in stream segments

Outputs must match ecological responseOutputs must match ecological response

Upper Flint BasinUpper Flint Basin

Colonization sourcesColonization sources

Large mainstem Large mainstem riverriver

(Mainland)(Mainland)

Small tributarySmall tributary(Island)(Island)

““Mainland islandMainland island”” metapopulationmetapopulationlarge river only source of colonists large river only source of colonists



““ClassicClassic”” metapopulationmetapopulationcolonization from nearby occupied reaches colonization from nearby occupied reaches

Example: when data are lackingExample: when data are lacking

Replication:Replication: 500 simulation runs500 simulation runs

Hydrologic model error:Hydrologic model error: spring +/spring +/-- 5.3%, summer +/5.3%, summer +/-- 14%14%

Stream classification error:Stream classification error: +/+/-- 33% commission and omission33% commission and omission

Parametric (statistical) uncertaintyParametric (statistical) uncertainty

Structural (system) uncertaintyStructural (system) uncertainty

Fish population demographics: 8 plausible alternative modelsFish population demographics: 8 plausible alternative models

-- 2 extinction models2 extinction models: : PP((extinctionextinction) = ) = ff(median(median discharge) or discharge) or ff(minimum(minimum 1010--day discharge)day discharge)XX

-- 2 reproduction models2 reproduction models: : PP((reproductionreproduction) = ) = ff(SD(SD discharge) or discharge) or ff(maximum(maximum 1010--day discharge)day discharge)

XX-- 2 colonization dynamics2 colonization dynamics: mainland: mainland--island or classicisland or classic

Step 5: Sensitivity analysis: Step 5: Sensitivity analysis: Simulating fish population dynamics in Potato CreekSimulating fish population dynamics in Potato Creek

Simulation time period:Simulation time period: 20 years, 1986 20 years, 1986 –– 2006, response: species richness2006, response: species richness

Estimating fish response to droughtEstimating fish response to droughtPotato Creek stream flowsPotato Creek stream flows

DateDate

Mea

n m

onth

ly d

isch

arge

(M

ean

mon

thly

dis

char

ge ( c

ms

cms ))

00

5050

100100

150150

200200

250250

300300

19861986 19881988 19901990 19921992 19941994 19961996 19981998 20002000 20022002 20042004 20062006

droughtdrought

LongLong--term meanterm mean

ObservedObserved

Composite estimatesComposite estimatesFish species richness 1998 (preFish species richness 1998 (pre--drought)drought)

Composite estimatesComposite estimatesFish species richness 2001 (drought)Fish species richness 2001 (drought)

Composite estimatesComposite estimatesFish species richness 2004 (postFish species richness 2004 (post-- drought)drought)

< 10< 10>10 >10 -- 1515>15 >15 -- 2020>20 >20 -- 2525>25>25

Number of speciesNumber of species

Prioritize future research: sensitivity analysisPrioritize future research: sensitivity analysis

1717 1818 1919 2020 2121 2222 2323

Flow model errorFlow model error

Channel classification errorChannel classification error

Reproduction modelReproduction model

Colonization mechanismColonization mechanism(metapopulation dynamics)(metapopulation dynamics)

Extinction modelExtinction model

Fish species richnessFish species richness

Drought effectDrought effect

Depression StorageDepression Storage Land cover changeLand cover change

Step 6: Reducing uncertaintyStep 6: Reducing uncertaintyImproving flow models with land cover dynamicsImproving flow models with land cover dynamics

Reduced flow model error by 50%Reduced flow model error by 50%

Step 6: Reducing uncertaintyStep 6: Reducing uncertainty Stream channel classificationStream channel classificationClassifying segments using highClassifying segments using high--resolution LIDARresolution LIDAR

Reduced classification by error 64%Reduced classification by error 64%

> 4> 4

1 1 -- 2 2 < 1< 1

Difference in estimatedDifference in estimatedNumber of speciesNumber of species

2 2 -- 3 3

Monitoring: Reducing uncertainty in ecological dynamicsMonitoring: Reducing uncertainty in ecological dynamicsMainland island vs. classic colonizationMainland island vs. classic colonization

High priority High priority monitoring areasmonitoring areas

Structured decisionStructured decision--making processmaking processIdentify the decision Identify the decision

situation and objectivessituation and objectives

Identify the management alternativesIdentify the management alternatives

Decompose and model the problemDecompose and model the problem

Identify the best alternativeIdentify the best alternative

Perform sensitivity analysisPerform sensitivity analysis

Is further Is further analysis needed?analysis needed?

Implement the best alternativeImplement the best alternative

NONO

YESYES

You are here You are here

Last stop Last stop

From From ClemenClemen and Reilly 2001and Reilly 2001

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Basic principles of structured decision making and ...people.oregonstate.edu/~peterjam/SDM_AFS_2011/SDM... · Structured Decision MakingProcess • Identify the decision situation