Transcript Solid Waste Facilities Master Plan

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 Utilities
May 2, 2006
Outline of Presentation
• Overview of Seattle’s 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
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)
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
The Problem
• The City’s two transfer stations are old and
outdated
• Transfer station reliability decreasing
• Transfer system inefficiencies
• Quality of customer service is decreasing
• Existing facilities lack flexibility
Many Existing Problems
•
•
•
•
Safety concerns
Old wiring
Seismic retrofit needed
High Maintenance
(floors, compactor)
• Too many “band-aid”
fixes
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
Current Waste Flow Diagram
Municipal Garbage
C
R
NRDS
SH
LT
Organics
Recyclables
C
R
SH SH R
SRDS
Private
Transfer
IM
Landfill
Organics
Processing
Recycle
Processing
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
Solid Waste
Facilities
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
Rabanco - Burlington Northern/Santa Fe Roosevelt Landfill
Waste Management Inc. - Union Pacific Columbia Ridge Landfill
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
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
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
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?
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
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
Required Elements of an
Effective Decision Framework
Develop
Value Model
and Formulate
Alternatives
•
•
•
•
•
•
•
Ensure
Leadership and
Commitment
Frame
the Problem
Organizational
Analytical
Collect
Meaningful,
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
Evaluate
Alternatives
and Make
Decision
Develop
Implementation
Plan
The Options
Key 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
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
Intermodal Site
South Recycling and Disposal
Station Option 11
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 couldn’t quantify we put into a
value model to help display the other
benefits or values of each option
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)
System Cost Model
• Costs include:
–
–
–
–
–
Property Purchase/Lease
Construction Costs
Equipment Capital
Labor and Other O&M
Contractor payments such as Disposal, Private
Transfer, Processing
– Long term competitive benefits of partnering
– Revenues from partner tons
Example Labor and Equipment Cost
Model Inputs
Capital Equipment
Scale 1
In Scale-70 ft w/Labor
In Scale-70 ft NO Labor
Waste Compaction
Track Loader (pit)
Wheel Loader (push) w/Labor
Compactor 1 Bale
Compactor 2 Bale
Yard Goat
Broom Floor Labor Existing
Hauling
G Tractor N to Argo 25t
G Tractor S to Argo 25t
Rail Loading
Reach Stacker
Gantry Crane 75 ft
Calculated
unit price
Useful life
Tons
in years Maint per
(Trips) per Operat based on operating
hour
or req't 2080 hr/yr
hour
$72,240
$72,240
90
90
1
1
63.0
63.0
$2.75
$2.75
$340,200
$251,400
$1,076,160
$750,000
$99,240
$0
100
100
100
75
200
15
1
1
1
0.5
1
1
5.0
5.0
14.0
14.0
6.0
15.0
$25.00
$22.00
$13.35
$13.35
$12.00
$0.00
$117,240
$117,240
19
28
1
1
4.0
4.0
$20.00
$20.00
$576,000
$1,800,000
660
990
2
2
14.0
29.0
$16.00
$16.00
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
2036
2034
2032
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
$-
Option 11: NPV Contributions
$700,000,000
Partner Revenue
Changes to Collection Costs
$600,000,000
Scale
$500,000,000
Private Transfer
Argo
$400,000,000
Hauling
Existing Facility
$300,000,000
Rail Loading
Waste Compaction
$200,000,000
General Facility
Recycling Construct and O&M
$100,000,000
Prop, Constr & Lease
$0
Disposal and Processing
Option 11
Cost Results
Comparison of NPV for Options 1-7
$700,000,000
$600,000,000
$500,000,000
$400,000,000
$300,000,000
$200,000,000
$100,000,000
$0
Option 0 Option 1
-$100,000,000
Option
2A
Option
2B
Option 3
Option
4A
Option
4B
Option 5 Option 6 Option 7
Quality of Service
Assessment
Primary Services Provided
• Waste reduction & recycling
• Customer service
• Work environment
• Built environment (community) impacts
• Natural environment impacts
Screening Criteria
SPU Solid Waste Facilities Masterplan
Costs
Total System
Cost
Capital
O&M
Long Run
Uncertainty
Quality of
Service
Waste
Reduction &
Recl. Goals
% Recycling
Driving and
Queue Time
Greenhouse gas
Flexibility to respond
to changes
in markets, tech
& waste streams
Wait Time
Distance to Fac.
Reuse
Opportunities
Limit Risk of
Stranded Costs
Promote
Competition
Respond to Waste/
Market Changes
Partnering
Opportunities
Room to grow
/ Modularity
Customer
Service
Customer
Convenience
Reliability
One-stop shop
Flexibility to adapt
to changes
in waste
Health &
Safety
Fall hazzards
Air Quality
Vehicle Acc
Noise
Seismic
Education
Opportunities
Service
Equity
Short Term
Impacts
Work
Environment
Facilities
Built Env.
(Community)
Impacts
Flexibility
Water
Aesthetics
Air
Quality
Consistent w/
Comp/ NH Plans
Other
Resource Imp.
Health &
Safety
Fall hazzards
Air Quality
Vehicle Acc
Noise
Mech Safety
Seismic
Flexibility
Natural
Environment
Impacts
Traffic
Noise
Dust
Odor
Community
Equity
Natural and Built Environment Impacts
are broken out by facility (NRDS,
SRDS, Intermodal).
Shaded criteria/ sub-criteria receive performance scales, weights, and option scores.
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
Quantified Evaluation Approach:
Multi-Attribute Utility Theory
Criterion
Performance
Measure
Rate
x
Value
Weight
=
Score
A
3
20
60
B
4
45
180
C
1
10
10
D
2
25
50
Total Score
300
Quality of Service
Assessment
• 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.
SPU Solid Waste Facility Masterplan
Contributions by Criteria - Total Quality of Service Score
Contributions to Quality of Se rvice from
Le ve l:
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0.0
0.0
Option 5
Option 11
Option 8
Option 0
Note: Option 5 and 11 score highest on waste reduction. This is the
differentiating for its leading score.
Used Criterium Decision Plus Software
Customer Service
Work Environment
Waste Reduction
Built Environment
Natural Environment
Overall Results
Quality of Service vs. Cost
1
Insert Cost Risk Profile Graph and
Tornado diagram
Option Score
0.8
Option 5
Option 7
Option 4B
Option 2A
0.6
Option 3
Option 6
Option 4A
Option 2B
0.4
Option 1
Option 0
0.2
0
480
516
552
Cost ($M)
588
624
660
SPU SW Facilities
Masterplan
Approach to Capture Cost Risk
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).
Growth in
City Waste
Stream
Com.
Res/ Com
Recycling
Rate
Comm
Rate
Res.
Self Haul
Net YW
Residential
Rec. Rate
KC Disposal
Participation
Total
Option
Cost
Disposal
Savings
Recycling
Revenues
Intermodal
KC Rail
Participation
Labor
Efficiency
Factor
Rail
Price
NRDS
Const.
Costs
Option
Selected
Construction
Costs
SRDS
Const.
Costs
IM
Const.
Costs
Step 2: Potential Cost Outcomes and
Probabilities Tool: Decision Tree
Example
Growth in Waste
Stream
Future Capital Costs
Forecast
No Additional Facilities
Prob = 70%
Prob = 100% C = $0 M
Facility Expansion
Above
Forecast
Prob = 20% C = $10M
Prob = 30%
New Facilities Needed
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).
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?
Tools Used
– DPL software
Interaction
– Workshop and/or
questionnaires to define
branch outcomes and
estimate probabilities and
costs
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):
Growth in Waste
Stream
Future Capital Costs
Forecast
No Additional Facilities
Prob = 70%
Prob = 100% C = $0 M
Facility Expansion
Above
Forecast
Prob = 20% C = $10M
Prob = 30%
New Facilities Needed
Prob = 80% C = $30M
No Additional Facilities = $0M
Facility Expansion = $10M
New Facilities Needed = $30M
Prob of Outcome = 0.7 * 1.0 = 0.7
Cost of Outcome = $0
Prob of Outcome = 0.3 * 0.2 = 0.06
Cost of Outcome = $10M
Prob of Outcome = 0.3 * 0.8 = 0.24
Cost of Outcome = $30M
Decision Trees: Probabilities and Cost Outcomes
Example: Rail Savings
Scenario/
Probability
S1 Merchandise Train
16.80
Without King County (Rail)
P = 20%
P = 60%
S2 - SPU waste w/ others 14.70
P = 80%
Intermodal Yes
S3 - SPU Waste w/KC
Intermodal No
Outcome
($/ton.)
13.40
With King County (Rail)
P = 70%
P = 40%
S4 SPU/KC + shared loading 12.90
P = 30%
0.00
Uncertainty Branch - Disposal Savings with Intermodal
Scenario/
Probability
Outcome
($savings/ton.)
No: P = 60%
0
Yes: P = 40%
-1
Without King County
P = 50%
Intermodal - Yes
No: P = 60%
0
Yes: P = 40%
-2
With King County
P = 50%
Interface Sheet for Decision Analysis
Inputs
Waste Stream Generation Rate
Residential
Commercial
Self-Haul Net of YW
Partner Rail Load Only
Percent Recycled
Residential
Commercial
Self-Haul net of YW DO NOT USE THIS ONE SEE EMAIL
Recycling Revenues
Rail Price
Disposal Price Change (for both IM and non-IM options)
Construction Costs (includes recycling construction)
NRDS
SRDS
Intermodal
Equipment Cost
Labor Downtime Factor
Discount Rate
Rail Load Partner Tons
Value
Units
0.03
0.07
0.07
0.07
%
%
%
%
0.70
0.70
%
%
%
1 %
13.70 $/ton
0.00 $/ton
1 %
1 %
1 %
1.2
1.21 No.
6% %
0 tons
Output
Total NPV
656,983,487
$
COST RISK PROFILE
Probabilistic Range of Option 0 Cost
1
Cumulative Probability (%)
0.9
0.8
Expected Value = $640M
0.7
90th Percentile = $742M
0.6
0.5
10th Percentile =
$553M
0.4
Base Case = $626M
0.3
0.2
0.1
0
475
500
5250
550
575
600
625
650
NPV - $M
675
700
725
750
775
800
825
“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.
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
NPV - $M
BASE CASE TORNADO DIAGRAM
Relative Impact of Uncertainties Option 1
580
600
Impact of Key Uncertainties ($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.
Option 0
Option 5
Option 8
Option 11
Waste Stream Recycling Construction
Growth
Rate
Costs
189
106
12
129
73
114
192
106
39
135
73
84
Conclusions
• Non-intermodal options (0 and 8) have the greatest cost uncertainty (high
spread between their 10th and 90th percentiles).
• Growth in the city’s 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.
What We Learned
Round 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
• Don’t need to purchase property to take
advantage of partner tons
Round 2
Revised Options
• Modifications to Recycling facilities to
increase cost effectiveness
• Less aggressive queue reduction goal
• Alternative construction that does not
require pilings at SRDS
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
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
Brief Advertisement
• It’s Not Garbage Anymore!
• New 60% City Programs include:
– ban on recyclables
– commercial collection of food waste
– residential collection of food waste with yard
waste