# Presentation: 293099

## Introduction to Structured Decision Making

- Michael C. Runge
- USGS Patuxent Wildlife Research Center
- SDM Workshop, 28 January – 1 February 2008, NCTC

## Choosing a Mortgage

- Your bank offers you two possible 30-yr fixed rate mortgages:  51⁄4 %, or 41⁄4 % with 2 points.  Which do you choose?

## Financial Example

- _Pr_oblem:  Choose a mortgage
- _O_bjectives:  Maximize proceeds less costs
- _A_ctions:  Choice between two 30-yr fixed rate mortgages
- _C_onsequences:  Use financial formulas (model) to calculate costs and proceeds at time of sale
- _T_rade-offs:  Directly compare consequences (only 1 objective here)

- _[Spreadsheet](file:///C:/Documents%20and%20Settings/donnabrewer/Local%20Settings/Temp/notesE1EF34/Mortgage.xls)_

## OK, that was easy

- Why?
- Simple set of actions
- Single, clear objective
- System dynamics known with certainty
- Choice of best action transparent
- But what if
- One of the choices is a 1-yr ARM?  Or, in fact, there is a bewildering array of choices from many lenders?
- You don’t know how long you’ll be in the house?
- You have other objectives or constraints (e.g., monthly payments needs to be less than $1000)?

## What makes decisions hard?

- Sometimes you don’t know all the possible actions
- The objectives may be complex or contradictory, or in dispute
- The system dynamics may be poorly known
- Even knowing all the other components, the solution (optimization) may be difficult to figure out

## Structured Decision Making

- Is a formal method for analyzing a decision, by breaking it into components
- Helps identify where the impediments to a decision are, to focus effort on the right piece
- Provides a wide array of analytical tools for dealing with particular impediments

## Structured Decision Making

- Integrate
- Management _objectives_
- Alternative management _actions_
- Predictive _models_ of system response
- To identify optimal actions
- Optimal control theory provides methods

## Alternative Actions

- Objectives

## Objectives

- Explicit statement allows focused discussion, negotiation, and evaluation
- Should capture implied trade-offs
- The objective drives everything else
- Ultimately, a societal question

## Potential Actions

- Considerations
- Political
- Technological
- Scientific
- Economic
- Development of alternatives requires creative integration of these

## System Model

- Represents the state of knowledge
- But, detail should be specified by context
- Is used for prediction
- Predictions may be distributions, over which expectations may be taken
- Should capture the  scientific uncertainty about how the system responds

## Decision Trees

- The classic technique, but only one of many

## Slide 13

## Management improves persistence

- p = 0.65

- p = 0.5

- p = 0.35

- p = 0.5

## Management has no effect

- p = 0.5

- p = 0.5

- p = 0.5

- p = 0.5

## Structural Uncertainty

- Include uncertainty in the state transitions associated with each management action
- Which of the previous models is “right”: conservation increases P(persistence) or not?
- Now focus on model-averaged mean utility, with equal weights for each model

## 70

*H*2

*X*1 = 1

*X*1 = 0

*X*1 = 1

*X*1 = 0

- 20

- 20

*P* = 0.50

*P* = 0.50

*P* = 0.65

*P* = 0.35

*R*1(action) = 45

*R*2(action) = 52.5

*Action*

*H*1

*H*2

*X*1 = 1

*X*1 = 0

*X*1 = 1

*X*1 = 0

- 100

- 0

- 100

- 0

*P* = 0.50

*P* = 0.50

*P* = 0.50

*P*= 0.50

*R*1(no action) = 50

*R*2(no action) = 50

*No *
*Action*

*X*0 = 1

*E*[*R*(no action)] = 50

*E*[*R*(action)] = 48.7

## Deriving Decision Rules

- p = x

- p = 0.5

- p = 1-x

- p = 0.5

- Rule:  Take action if x > 0.6

## Multiple Objective Problems

## Impoundment Repair

| Expected Return | Actions |  |  |  |
| --- | --- | --- | --- | --- |
| Objectives | Status quo | Minor repair | Major repair | Re-build |
| Cost ($M) | 0 | 5 | 12 | 20 |
| Environmental Benefit (0-10) | 1 | 3 | 10 | 10 |
| Disturbance (0-10) | 0 | 1 | 7 | 10 |
| Silt runoff (k ft3) | 3 | 1 | 5 | 5 |
| Water Retention (MG) | 41 | 42 | 40 | 41 |

## Impoundment Repair

| Expected Return | Actions |  |  |  |
| --- | --- | --- | --- | --- |
| Objectives | Status quo | Minor repair | Major repair | Re-build |
| Cost ($M) | 0 | 5 | 12 | 20 |
| Environmental Benefit (0-10) | 1 | 3 | 10 | 10 |
| Disturbance (0-10) | 0 | 1 | 7 | 10 |
| Silt runoff (k ft3) | 3 | 1 | 5 | 5 |
| Water Retention (MG) | 41 | 42 | 40 | 41 |

- Dominated Alternative

## Impoundment Repair

| Expected Return | Actions |  |  |  |
| --- | --- | --- | --- | --- |
| Objectives | Status quo | Minor repair | Major repair | Re-build |
| Cost ($M) | 0 | 5 | 12 | 20 |
| Environmental Benefit (0-10) | 1 | 3 | 10 | 10 |
| Disturbance (0-10) | 0 | 1 | 7 | 10 |
| Silt runoff (k ft3) | 3 | 1 | 5 | 5 |
| Water Retention (MG) | 41 | 42 | 40 | 41 |

- Irrelevant Objective

## Impoundment Repair

| Expected Return | Actions |  |  |  |
| --- | --- | --- | --- | --- |
| Objectives | Status quo | Minor repair | Major repair | Re-build |
| Cost ($M) | 0 + 1 = 1 | 5 | 12 + 2 = 14 | 20 |
| Environmental Benefit (0-10) | 1 | 3 | 10 | 10 |
| Disturbance (0-10) | 0 | 1 | 7 | 10 |
| Silt runoff (k ft3) | 3 – 2 = 1 | 1 | 5 – 4 = 1 | 5 |
| Water Retention (MG) | 41 | 42 | 40 | 41 |

- Even Swap

## Multiple Objective Decision Analysis

- In this way, complex sets of objectives can be reduced
- There are a variety of approaches to finding a solution based on the remaining objectives
- We can explore some of these later if necessary

## Uncertainty

- Influence diagrams and Bayes Nets

## Manatee Threats Analysis

- Fate of Power Plants

- Carrying Capacity (over time)

- Population Size

- Mortality rates

- Electricity demand

- Watercraft
- Threat

- Oil supply

- Aerial surveys

- Detectability studies

## Articulate Uncertainty

- -0.04

- 0

- 0.04

- 0.08

- 0.12

- 0.16

- 0.20

- Increase in p(quasiextinction) due to threat

## Understanding Uncertainty

- Risk assessment
- The analytical side
- How does uncertainty propagate through our predictions?
- Risk management
- The policy side
- What is the decision-maker’s attitude toward uncertainty?

## Objectives under Uncertainty

- The decision maker’s attitude toward uncertainty is actually part of the objective function
- Thus, there is considerable nuance to specifying objectives
- A few brief comments from a vast subject:
- Formal approaches: expected utility, VOI, robustness
- Informal approaches:  sensitivity analysis
- Iterative development

## Linked Decisions & Adaptive Management

## Linked Decisions

- Often, we have a series of dependent decisions to make
- A decision early on can affect the options available later, as well as the state of the system at a later time
- Analyzing such decisions separately can lead to suboptimal decisions

## ARM:  Motivation

- All management decisions are made without perfect knowledge
- This uncertainty is what makes decisions difficult
- Any management decision can potentially provide the chance to learn
- Iterated decisions can be adaptive

## System Model

- Optimization

## Adaptive Decision Making

- System Model

- (Includes Uncertainty)

## Some Concluding Comments

## Constructed Preferences

- In many important and complex decisions, preferences may not be fully formed
- Elicitation and decision analysis processes may be the means by which decision-makers’ preferences become fully formed
- The constructed preferences can be influenced by the methods of development

## “Soft” Approaches

- May be more qualitative in nature
- But nevertheless use the same approach for analysis:
- Enumerate actions
- Articulate objectives
- Predict consequences of actions in terms of objectives
- Examine trade-offs
- Perform sensitivity analysis to understand effects of uncertainty

- “A formal application of common sense for situations too complex for the informal use of common sense.”
- R. Keeney

## Our Goal

- Use the concepts of structured decision making to develop first prototype frameworks for the applied problems you’ve brought
- A framework includes the elements of a structured decision, spelled out enough so that you can see how they fit together
- It’s the consultants’ job to bring in the theory of SDM as needed for your work
- Different groups may emphasize different elements and different approaches, but the core ideas should be recognizable in all
- It’s likely that future work will be needed to flesh out the details
- Part of your task will be to specify what the next steps are