Practical Use of Asset Management and Structured Decision Making

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Practical Use of Asset Management and Structured
Decision Making

• Case Study Seattle Public Utilities Solid
  Waste Facilities Master Plan
• Presented by Jenny Bagby
• Principal Economist
• Seattle Public UtilitiesMay 2, 2006

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Outline of Presentation

• Overview of Seattles waste management system
• Description of problem of planning for new
  facilities
• Use of three types of analysis to help choose
  among options
• Benefit cost analysis
• Value modeling
• Decision analysis for modeling risk and
  uncertainty
• Conclusion

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What is Seattle Public Utilities?

• City Department (our director reports to Mayor)
  1200 employees including office professional
  folks as well as field staff
• Solid Waste
• Wastewater
• Drinking Water
• Surface Water (Drainage)

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Project Background

• Long-range planning (30 years)
• Involves collection, transfer, and disposal of
  municipal solid waste - Garbage, Yardwaste and
  Recyclables
• Primary customers affected are the self-haul
  customers at the recycling and disposal stations
  (RDS) and adjacent neighbors

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The Problem

• The Citys two transfer stations are old and
  outdated
• Transfer station reliability decreasing
• Transfer system inefficiencies
• Quality of customer service is decreasing
• Existing facilities lack flexibility

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Many Existing Problems

• Safety concerns
• Old wiring
• Seismic retrofit needed
• High Maintenance (floors, compactor)
• Too many band-aid fixes

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System Overview Facilities

• Two city-owned transfer stations
• Two privately-owned transfer stations
• Two intermodal rail yards
• Two private processing facilities for recyclables
  
• Private processing facility for organics
  composting
• Private landfills

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Current Waste Flow Diagram
Municipal Garbage
Organics
Recyclables
C
R
SH
LT
C
R
SH
SH
R
NRDS
SRDS
Private Transfer
IM
Organics Processing
Recycle Processing
Landfill
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System Overview Materials flow

• City-contracted collection and transfer of
  residential Garbage, Yardwaste and Recyclables
• City-contracted collection and transfer of
  commercial Garbage and organics
• Private collection of commercial recyclables
• Individual business and residential self-haul

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Solid Waste Facilities
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Rail Landfill Connection

• Two Railroad Companies Serve Seattle
• Most Large Regional Landfills are Linked by Rail
• Access to more than one rail line opens access to
  different landfills creating more competition

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Rabanco - Burlington Northern/Santa Fe -
Roosevelt Landfill
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Waste Management Inc. - Union Pacific - Columbia
Ridge Landfill
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Understanding the System

• Public private facilities work in conjunction
  with each other
• Waste flows to different facilities can change
  over time
• A flow change to one facility affects the others

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Vertical Integration of Solid Waste Business

• Industry consolidation (fewer solid waste service
  companies than before)
• Companies strive to control all aspects of the
  market (collection, transfer, long-haul, and
  disposal)
• An integrated company can reduce operation costs,
  but may also reduce competition

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Project Objectives

• Improve transfer efficiency of solid waste and
  recyclables
• Improve self-haul customer service
• Minimize neighborhood impacts from transfer
  stations
• Increase reuse and recycling opportunities
• Provide long-term system flexibility

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Primary Questions

• What is the appropriate mix of public and private
  facilities?
• Remodel or rebuild city stations?
• Do we need additional property at the city
  stations?
• Does a city-owned intermodal transfer station
  make economic sense?

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Initial Assessment

• A city-owned facility is needed in north and
  south Seattle
• Siting options are limited no substantially
  better sites were found for the City stations
• A third City-owned intermodal transfer facility
  needs to be evaluated

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Enter Asset Management

• AKA Full Employment for Economists
• C/B Analysis on all decisions (especially ones
  this large)
• Emphasis on quantifying in terms everything we
  possibly can
• Challenging!
• CH2MHill to the rescue - Value Model and Decision
  Framework

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Required Elements of an Effective Decision
Framework
Develop Value Modeland FormulateAlternatives
CollectMeaningful,Reliable Data

• Solve the right problem
• Put interests values first
• Avoid advocacy positions
• Avoid useless data
• Find lowest cost solution
• Manage risk and liability
• Track progress

Develop
Ensure Leadership andCommitment
Implementation
Plan
EvaluateAlternativesand MakeDecision
Frame the Problem
Organizational
Analytical
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The OptionsKey elements

• No action (required for EIS) - maintain operation
  and legal compliance
• Modifications to RDS - retain tipping sheds
• Total rebuild of RDS - including additional reuse
  and recycling facilities
• Add property to NRDS and/or SRDS
• Develop a City-owned transfer/intermodal facility

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Options Assessment Steps

• Develop options
• Identify Quality of Service goals criteria
• Prepare conceptual layout designs for preferred
  options
• Model Costs, Risk and Quality of Service
  performance for preferred options
• Revise options based on results

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Intermodal Site
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South Recycling and Disposal Station Option 11
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Asset Management

• We developed a cost model to quantify in dollars
  everything we could
• Goal was to compare each of the options using
  benefit-cost analysis
• What we couldnt quantify we put into a value
  model to help display the other benefits or
  values of each option

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System Cost Model

• Cost model calculates total system NET cost over
  30 years of
• Transfer
• Rail loading and hauling
• Processing
• Disposal
• Collection (IF option results in changes to
  collection costs)

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System Cost Model

• Costs include
• Property Purchase/Lease
• Construction Costs
• Equipment Capital
• Labor and Other OM
• Contractor payments such as Disposal, Private
  Transfer, Processing
• Long term competitive benefits of partnering
• Revenues from partner tons

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Example Labor and Equipment CostModel Inputs
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Cost Results
Option 4 Cost by Function
80,000,000
70,000,000
60,000,000
50,000,000
40,000,000
30,000,000
20,000,000
10,000,000
-
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
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Cost Results
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Quality of ServiceAssessment

• Primary Services Provided
• Waste reduction recycling
• Customer service
• Work environment
• Built environment (community) impacts
• Natural environment impacts

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Natural and Built Environment Impacts are broken
out by facility (NRDS, SRDS, Intermodal).
Shaded criteria/ sub-criteria receive performance
scales, weights, and option scores.
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Importance of Value Model

• Facilitated process
• Way to get all issues and concerns identified
• Moved discussion from a high level where things
  are hard to evaluate
• Began discussing what everyone really
  meant/valued when they held a certain position

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Quantified Evaluation Approach Multi-Attribute
Utility Theory
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Quality of ServiceAssessment

• Non-monetizable Quality of Service benefits were
  quantified in a variety of ways such as
• Length of time queuing
• Square feet of space available for operations
• 1-5 scale - best professional judgement
• etc.

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SPU Solid Waste Facility Masterplan Contributions
by Criteria - Total Quality of Service Score
Note Option 5 and 11 score highest on waste
reduction. This is the differentiating
for its leading score.
Used Criterium Decision Plus Software
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Overall Results Quality of Service vs. Cost
1
Insert Cost Risk Profile Graph and Tornado diagram
0.8
Option 5
Option 7
Option 4B
Option Score
Option 2A
Option 3
0.6
Option 6
Option 4A
Option 2B
0.4
Option 1
Option 0
0.2
0
480
516
552
588
624
660
Cost (M)
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SPU SW Facilities MasterplanApproach to Capture
Cost Risk
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Cost Drivers and Uncertainties Affecting NPV of
Options
The Influence Diagram below illustrates
conditional relationships between decisions
(yellow rectangles), uncertainties (green ovals),
outcomes (blue boxes).
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Step 2 Potential Cost Outcomes and Probabilities
Tool Decision Tree
Example

• For each possible outcome of a decision,
• Decision Trees show
• The Pathway - How did this happen?
• The Probability - How likely is this?
• The Cost - How much will this outcome cost?

Growth in Waste Stream
Future Capital Costs
Forecast
No Additional Facilities
Prob 70
Prob 100 C 0 M

Facility Expansion
Prob 20 C 10M
Above Forecast

• Tools Used
• DPL software
• Interaction
• Workshop and/or questionnaires to define branch
  outcomes and estimate probabilities and costs

New Facilities Needed
Prob 30
Prob 80 C 30M
The influence diagram is actually the top layer
of a mathematical model. The underlying model is
a series of interconnected decision trees. In
our simplified example only possible one tree is
shown (above).
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Calculating the Decision Tree Example Tree
The influence diagram is actually the top layer
of a mathematical model. The underlying model is
a series of interconnected decision trees. In
our simplified example only possible one tree is
shown (see below).
Costs (NVP) No Additional Facilities
0M Facility Expansion 10M New Facilities
Needed 30M
Growth in Waste Stream
Future Capital Costs
Forecast
No Additional Facilities
Prob of Outcome 0.7 1.0 0.7 Cost of Outcome
0
Prob 70
Prob 100 C 0 M

Facility Expansion
Prob of Outcome 0.3 0.2 0.06 Cost of
Outcome 10M
Prob 20 C 10M
Above Forecast
New Facilities Needed
Prob 30
Prob of Outcome 0.3 0.8 0.24 Cost of
Outcome 30M
Prob 80 C 30M
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Decision Trees Probabilities and Cost
OutcomesExample Rail Savings
Scenario/ Probability
Outcome (/ton.)
S1 Merchandise Train
16.80
P 20
Without King County (Rail)
14.70
P 60
S2 - SPU waste w/ others
P 80
Intermodal Yes

13.40
S3 - SPU Waste w/KC
With King County (Rail)
P 70
P 40
S4 SPU/KC shared loading

12.90
P 30

0.00
Intermodal No
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Uncertainty Branch - Disposal Savings with
Intermodal
Scenario/ Probability
Outcome (savings/ton.)
0
No P 60
Without King County
P 50
-1
Yes P 40
Intermodal - Yes

0
No P 60
With King County
P 50
-2
Yes P 40
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COST RISK PROFILE Probabilistic Range of Option
0 Cost
1
0.9
0.8
0.7
0.6
Cumulative Probability ()
0.5
0.4
0.3
0.2
0.1
0
475
500
5250
550
575
600
625
650
675
700
725
750
775
800
825
NPV - M
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Tornado Diagram Relative Impact of
Uncertainties Option 11
Growth in City Waste Stream
Construction Costs
Res/ Com Recycling Rate
Rail Price
KC Rail Participation
Disposal Savings
Recycling Revenues
Labor Efficiency Factor
KC Disposal Participation
620
640
660
680
700
720
740
NPV - M
A Tornado Diagram evaluates the impact of each
uncertainty by varying it from its best to worst
state, while fixing all other uncertainties to
their base (most likely) state. The width of the
bar shows the impact on total option cost.
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Risk Assessment Results
Growth in City Waste Stream

Res/ Com Recycling Rate

Construction Costs

Labor Efficiency Factor

Recycling Revenues
440
460
480
500
520
540
560
580
600
NPV - M
BASE CASE TORNADO DIAGRAM Relative Impact of
Uncertainties Option 1
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Impact of Key Uncertainties (M)
Values shown reflect the impact on total cost
when an uncertainty is varied across its range of
outcomes. All other uncertainties are held
constant at their base states.
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Conclusions

• Non-intermodal options (0 and 8) have the
  greatest cost uncertainty (high spread between
  their 10th and 90th percentiles).
• Growth in the citys waste stream and recycling
  rate changes have the greatest impact on total
  costs.
• Intermodal options are much less sensitive to
  variations in city waste and recycling growth
  rates.
• Construction cost uncertainty is lowest with
  Options 0 and 8.
• In all options, the expected value of costs is
  5-7 percent greater than our baseline cost
  estimates. This means that there is more upside
  risk than downside opportunity in the estimates.

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What We LearnedRound 1

• The cost of reuse/recycling facilities is
  relatively high compared to percent diverted
• Building costs are high at SRDS and intermodal
  due to soils
• Queue reduction goal was too aggressive resulted
  in too large a facility
• Dont need to purchase property to take advantage
  of partner tons

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Round 2Revised Options

• Modifications to Recycling facilities to increase
  cost effectiveness
• Less aggressive queue reduction goal
• Alternative construction that does not require
  pilings at SRDS

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Project Status

• Approach and results accepted by SPU Asset
  Management Committee
• AMC asked us to quantify in s some of the
  benefits from value model
• Plan supported by SPU Director and Mayor
• Site for IM announced, property purchases
  beginning or underway for all 3 site
• Decision to do a DBO for IM

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Concluding Remarks

• Decisions are likely to be supported if
• They are rational and compelling
• The underlying trade-offs have been clearly
  communicated
• Discussions and decisions have been documented
  for later reference and defensibility
• Conflicts have been anticipated, and thus
  prevented or well-managed
• Participants feel they have been listened to and
  that they have had some impact or effect on the
  final outcome
• No tool replaces human judgment

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Brief Advertisement

• Its Not Garbage Anymore!
• New 60 City Programs include
• ban on recyclables
• commercial collection of food waste
• residential collection of food waste with yard
  waste

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