Making Better Decisions

The argument for

Structured Decision Making

Mike Larson, Forest Wildlife Research Supervisor

• What is SDM & why use it?

• Concepts/tools to remember…

• PrOACT

• Objectives hierarchy

• Consequences table

• Example

• Questions/discussion

Outline

“…we are not so much rational

creatures as we are creatures

capable of rationalizing.”David Orr (2004, Conservation Biolology 18:1459)

4

How Decisions Are Usually ResolvedA

ll D

ecis

ion

s

Worthy of thought

Procrastination30%

Too Little Time Spent

20%

No Brainers

Thought About 50%

Gets Systematic Thought 4%

Small Consequences

(SDM steps)Not Clear

30%

Informal16%

Adapted from Keeney (2004)

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“...if you are a resource manager,

all paths lead to a decision.”

Better to “set it up that way from the start.”

– Gregory et al. 2012

Can the problem, issue, challenge, or controversybe reframed as a decision?

Framing Problems as Decisions

Decisions = Choices = Selecting an action

Structured Decision Making

• Established theory, tools & techniques

for complex decisions

• Deconstruct, analyze, synthesize

decision components

6

7

What’s Different

SDM ApproachFamiliar Approaches

• Acknowledges Subjectivity

• Structure Decisions

• Emphasize Objectivity

• Simplify Decisions

8

Common Decision Components

• PrOACT (Hammond et al. 1999. Smart Choices)

• Problem

• Objectives ( Values)

• Alternatives

• Consequences

• Trade-offs

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All

Dec

isio

ns

Worthy of thought

No Brainers

Small Consequences

Get Systematic Thought

“Clear Thinking”75%

Full Decision Analysis

5%Partial Decision

Analysis20%

How Decisions Should Be Resolved

Adapted from Keeney (2004)

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Common Decision Components• PrOACT (Hammond et al. 1999. Smart Choices)

• Problem• Asking the right question, framing, scoping

• Objectives (• What “you” care about (Values) Values)

• Alternatives• Be creative!

• Consequences• Need to predict (Science & Uncertainty)

• Trade-offs• Weighing apples & oranges

Consequence Table

Objectives

Alternatives 1 2 3

A

B

C

Problem:

Consequence Table

Objectives

Alternatives 1 2 3

A

B

C

Problem:

Consequence Table

Objectives

Alternatives 1 2 3

A

B

C

Problem:

Consequence Table

Objectives

Alternatives 1 2 3

A

B

C

Problem:

Consequence Table

Objectives

Alternatives 1 2 3

A

B Consequences

C

Problem:

Decision Making Resources

16Adapted from Rowland et al. (2014)

TriggerImplement

decision

Framework (SDM)

Methods(scenario planning)

Tools(models, Zonation)

Boundaries of SDM Use

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Good Decisions

What makes a decision good

is the process by which it was generated,

not necessarily the ultimate outcome

because we can’t eliminate uncertainty or fully control the system.

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SDM yields decisions that are…

• More likely to achieve objectives

• Deliberative, thorough

• Values-based

• Relies on science, Robust to uncertainty

• More likely to be accepted by others

• Incorporates competing values

• Clarifies roles of science & values

• Transparent, Explicit, Documentable, Replicable

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• Little

• 1 person at their desk, in the field

• 5 min – 1 hour

• Urgent, relatively small scope

• Medium

• Committee, work group

• Days – weeks

• Seasonal, regional scope

• Big

• Committee with leadership, stakeholders involved

• Weeks – years

• State-wide importance

What decisions is SDM good for?

Full SDM Example

Sharp-tailed grouse harvest regulations in EC Minnesota

• Trigger: Concern about population

status

• Scope:

• EC population, maybe

just southern part

• Harvest regulations only,

not habitat management

Problem

Objectives

Additive mortality from

hunting(-)

Me

ans

Hunting opportunities

(+)

Regulatory burden

(-)

Abundance of STGR

(+)

Open brushland systems(+)

Perception that hunting is

limiting the STGR population (-)

Changes to rules, statutes

(-)

Probability of STGR persistence

(+)

Ease of enforcing

regs. (+)

DNR & hunter credibility as conservationists

(+)

Support for habitat

mgt.(+)

Annual admin. of the hunt

(-)

Stra

tegi

c

Brushland-dependent wildlife(+)

MN’s hunting heritage

(+)

Public knowledge of lek locations

(-)

Disturbance to breeding activity

(-)

Public awareness of

STGR & brushlands

(+)

Fun

dam

enta

l

• Strategies based on varying

components of harvest season

structure

• Length of season

• Bag limits

• Who gets to hunt & where

Alternatives

Influence Diagram – STGR Population in EC MN

Blue hexagons = Objectives

Green rectangles = Alternative Actions

Abundance of STGR during spring (+)

Fall-to-spring survival

Nest, chick, & adult survival

during summer

Weather

STGR abundanceduring fall

Regulatory burden (-)

Hunting regulations

Harvest of STGR

Habitat

Hunter-days per year (+)

November 1, 2016

Toxicants, disease,

pheasants

Succession, land use

conversion

Habitat conservation & management

Confidence hunting is justified

(+)

Support for management

Climate change

Consequences

Objectives:STGR

abundance in 20 years Hunting heritage

DNR credibility as conservationists

Regulatory burden

Alterna-tive Metric: (males at leks) (hunter-days) (0-10 index)

(Index of DNR costs)

Status quo 384 (0-1000) 4,882 (1,000-12,400) 3.5 (0-8) 0

Shorter season 399 (0-1000) 4,123 (775-8,600) 5.5 (0-8) 0

Lottery 444 (0-1000) 2,105 (550-5,000) 6.5 (4-10) 20

WMAs as refuges 441 (0-1,100) 4,109 (675-11,400) 5.2 (0-8) 2

Partial closure 1 495 (15-1,475) 3,423 (725-8,500) 6.3 (2-10) 1

Full closure 558 (10-1,650) 0 (0-0) 9.1 (5-10) 1

Consequences

• Status quo, Lottery, & Full closure

ruled out

• Partial closure – also no

• Unspecified objective

• Selected Shorter season

• Would have had highest

weighted sum

Trade-offs

• SDM helps us make better decisions

• Framework for clear thinking

• More likely to achieve objectives

• More likely to be accepted by

• others

• Remember…

• PrOACT

• Objectives hierarchy

• Consequences table

Presentation Summary