Transforming Washington DC’s Parking Meter Program
Using Lean Six Sigma Based Asset Management
by
Soumya S. Dey, P.E., PMP
Director of Research and Technology Transfer
District Department of Transportation
Washington, DC 20003
E-mail: [email protected]
Phone; (202) 671-1369
Submitted: October 29, 2013
Word Count
4997
Figures (7)
1750
Tables (3)
750
Total
7497
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ABSTRACT
The District Department of Transportation (DDOT) is responsible for maintaining and operating over
18,000 metered on-street spaces in Washington, DC. The program went through significant changes in
2009 and 2010 including two rate adjustments, reintroduction of meter enforcement on Saturdays and
extending hours of meter operation to 10 PM in some areas. These changes caused operational
problems for the Department and frustration for the customers. This paper describes how DDOT
applied lean six sigma (LSS) processes and techniques to dramatically transform its on-street parking
meter program. The paper introduces the concept of LSS and discusses how some of the analytical
techniques and concepts were applied. Techniques such as root cause analysis, process capability, mean
testing, pareto analysis and process mapping were used to identify fundamental problems with the
program and assets. Once the problems were identified, DDOT quickly developed a strategic vision for
the future and aggressively implemented the vision. Applying lean six sigma techniques has reaped
significant rewards for DDOT within a very short period of time. These benefits include higher customer
satisfaction through enhanced payment options, lower number of service requests, better system
uptime, more proactive management of assets, better executive visibility and increased revenue.
Washington DC’s parking program is now recognized as one of the most innovative, forward thinking
programs in the country. The success of applying LSS in parking has encouraged DDOT to apply this
concept in other program areas as well.
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TRB 2014 Annual Meeting
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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BACKGROUND
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The District Department of Transportation (DDOT) is responsible for developing and maintaining a
cohesive, sustainable transportation system that delivers safe, affordable, and convenient ways to move
people and goods—while protecting and enhancing the natural, environmental and cultural resources of
the nation’s capital. As an agency, DDOT is very unique – it has attributes of both a state and municipal
department of transportation (DOT). As part of this mission, DDOT manages and operates all the
transportation assets in Washington, DC. These assets are valued at $44 billion [1]. Over the past few
years, DDOT has gone through a paradigm shift in how it manages its assets. These techniques include
performance based contracting (with incentive/disincentive and liquidated damages), application of
data mining and process enhancement techniques such as lean six sigma (LSS) and participating in
constructive partnering forums with the private sector for more cost effective service delivery.
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The District Department of Transportation (DDOT) is responsible for maintaining and operating over
18,000 metered on-street spaces in Washington, DC. Until late 2010, these spaces were controlled by
two basic asset types; (a) traditional single space meters (SSM) that each cover one space, and (b) multi
space meters (MSM) that cover approximately an average of eight metered spaces. The MSMs are
networked, while the SSMs are mechanical, non-networked assets. Moreover, the SSM are more than
10 years old and at the end of their useful life. From a customers’ perspective, credit cards were
accepted as a payment option (in addition to coins) only at the MSMs. For the rest of the assets, only
coins were accepted. Up until late 2010 customers could pay by credit cards at only 23% of the metered
spaces.
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Between March of 2009 and January 2010, the program underwent significant changes including two
rate adjustments, lifting of the Saturday moratorium on parking meter fees and extending the duration
during which meters are operational [2, Error! Reference source not found., 4]. These operational
changes put significant stress on a system that had assets that were beyond their useful life.
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The changes caused significant frustration amongst customers. Due to the rate adjustments, the
number of coin transactions on the system increased. This increased failure rates for the meters.
Consequently, customers were frequently encountered with broken meters [5]. The rate increase also
necessitated customers to carry more change. This caused additional frustration [6]. Parking related
service requests through Washington, DC’s centralized 311 system became the highest service request
in DC. In 2010, the agency received approximately 200,000 parking meter related service requests [7].
Just to put things in perspective, in 2009 DDOT received more parking meter related service requests
than the Department of Public Works (DPW) received as an entire agency [8]. Also, the perception gap
(the difference between percentage on-time service delivery and customer’s perception about the level
of service delivery measured through a sample survey), for parking meters was at 55% [9]. This was the
highest amongst all DDOT service categories. The press picked-up on the negative customer sentiment
as well [10,11]. The program became a burning issue for the Department and the District of Columbia.
Consequently, there was significant pressure on the agency to enhance the program.
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TRB 2014 Annual Meeting
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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This paper discusses how DDOT adopted a lean six sigma (LSS) based approach to identify fundamental
problems with its assets and the program, developed a strategic approach to enhance the program,
implemented the recommendations and achieved significant enhancements. It discusses some of the
analytical tools that were used in the process.
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WHAT IS LEAN SIX SIGMA
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Lean and six sigma are process improvement methodologies. Lean is a set of tools that is geared to
improve process flow. Lean primarily focuses on the elimination of waste or non-value added activities
from all business processes. Lean arose as a method to optimize auto manufacturing (initially at Ford
and Toyota). Lean focuses on eliminating seven sources of waste [12]:
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Overproduction (manufacturing items ahead of demand)
Inventory (excess material and information)
Defects (production of off-specification products)
Transport (excess transport of work-in-process or products)
Motion (human movements that are unnecessary or straining)
Over-processing (process steps that are not required)
Waiting (idle time and delays)
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Six sigma specifically focuses on process variation. It is a methodology driven by understanding of
customer needs, and the disciplined use of data, facts and statistical analysis to improve and reinvent
organizational processes by reducing variation. Six sigma evolved as a quality initiative to reduce
variance in the semi-conductor industry (initially Motorola). From a purely statistical standpoint a six
sigma process has 3.4 defects per one million opportunities [13]. The statistical roots of the term six
sigma have become less important as six sigma has evolved into a comprehensive management system.
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Lean six sigma (LSS) is a combination of lean and six sigma approaches. Despite their disparate roots,
lean and six sigma share several fundamental commonalities including a focus on customer satisfaction,
continuous improvement, identification of root causes, and comprehensive employee involvement [14].
LSS uses a data-based approach to enhance workflow and business processes.
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Though used primarily in the manufacturing sector, the concept of LSS has been applied successfully in
the service sector as well. LSS for services is a business improvement methodology that maximizes value
by achieving the fastest rate of improvement in customer satisfaction, cost, quality, process speed and
invested capital.
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Lean six sigma is a five step process as shown in Figure 1 [15]. Each of these processes has sample tools
and procedures as shown in Table 1 [16].
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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FIGURE 1. Lean Six Sigma Process
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TABLE 1. Sample Tools in Lean Six Sigma Approach
Define
Measure
Analyze
Improve
Control
Project Definition
Basic Statistics
(Measure of central
tendencies,
Measure of
variation,
Distributions, etc.)
Hypothesis testing
Design of
experiments (DOE)
Control plan
Process Mapping
Cause and Effect
Matrix
Means testing
Project closure
2k factorial design
Power & sample size
Regression analysis
Failure Modes and
Effects Analysis
(FMEA)
Graphical
techniques
Analysis of variance
(ANOVA)
Confidence intervals
Measurement
systems analysis
(MSA)
Capability analysis
Statistical process
control (SPC)
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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LITERATURE REVIEW
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Lean six sigma has been used extensively in the private sector. There are several documented uses of
LSS across different levels of government as well. Federal agencies such as the as the Department of
Defense (DOD), Environmental Protection Agency (EPA), Department of Energy (DOE); state agencies
such as Florida Department of Revenue; and municipal agencies such as City of Fort Wayne (Indiana),
City of Hartford (Connecticut) and City of Irving (Texas) have applied six sigma techniques to various
components of their programs [17,18,19]. Most of the documented applications of lean six sigma in the
transportation industry have been in the area of logistics and supply chain for humanitarian relief,
airlines, rental car and rail operations [20,21]. Lean techniques have been used for delivery and
construction of infrastructure projects [22,23]. However, as a concept, LSS has not made significant
inroads into the mainstream transportation engineering profession.
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APPLICATION OF LEAN SIX SIGMA TOOLS TO DC PARKING PROGRAM
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This section discusses how some of the tools in the LSS framework were applied to gain valuable
information and knowledge about DDOT‘s parking meter assets.
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Root Cause Analysis
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There are several techniques that can be used for root cause analysis such as fishbone diagram, cause
and effect mapping, failure modes and effects analysis (FMEA), etc. DDOT utilized cause mapping to
identify the “root causes” of the problems associated with the program. During this process, it was
important to distinguish between symptoms and causes. During the analysis it became apparent that
symptoms such as increase in number of broken meters, broken meter call volumes and customer
dissatisfaction were driven by four fundamental causes - aged assets, non-communicating meters,
increase coin transactions (because of the rate increases) and limited payment options for customers
(shown in Figure 2). Identifying the root causes was fundamental in carting a future course for program
enhancements.
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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FIGURE 2. Results of Root Cause Analysis
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Establishment of High Level Program Goals
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Based on the root cause analysis, DDOT developed three high level goals for the parking meter program.
Each goal was sub-divided into more detailed sub-goals. These included [24]:
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Improved customer service
o Multiple payment options
o Maximize convenience
o Real-time parking availability
o Fewer broken meters
Enhanced operational efficiency
o Dynamic pricing
o Real-time operational status
o Better uptime
o Lower operating cost
Better revenue management
o Minimize coin transaction
o Real-time auditing
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Parking Pilots
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In the summer of 2010, DDOT evaluated the state-of-the-art in meter hardware, payment options and
real time occupancy sensing through a series of pilots. The pilots were conducted using a competitive
procurement process. DDOT tested two different configurations of multi space meters (pay by space
and pay by license plate), credit card accepting single space meters, occupancy sensors and new
payment options such as pay by cell. The pilots were evaluated against the program goals as shown in
Table 2 below [25].
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TABLE 2. Assessment of Pilots Against Program Goals
Program Goals
Improved Customer Service
Multiple payment options
Customer convenience
Real time parking availability
Fewer broken meters
Enhanced Operational Efficiency
Dynamic Pricing
Real-time operational status
Better uptime
Lower operation cost
Better Revenue Management
Minimize coin transaction
Real-time auditing
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Pay –by-Cell
Smart SSM
Smart MSM
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Space
Occupancy
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Control Chart for Call Volumes
Control chart is a tool that helps detect any extraordinary variation in the process — variation that may
indicate a problem or fundamental change in the process. Figure 3 shows a control chart for the
number of broken meter 311 calls received between February 2007 and April 2011. The control chart
shows the overall process mean (xˉ) as well as the upper control limit (UCL) and lower control limit (LCL).
The UCL and LCL are three standard deviations from the mean. The chart also annotates policy changes
that likely impacted call volumes – the rate changes in April 2009 and January 2010 and installation of
networked single space meters in November 2010. It appears that the process has 4 distinct means:
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Between February 2007 and March 2009, the mean appeared to be between the overall mean
(xˉ) and the LCL.
Between March 2009 and January 2010, the mean jumped to between the overall mean (xˉ) and
the UCL.
Between January 2010 and November 2010, the mean jumped to above the UCL.
After new assets were introduced in November 2010 the mean dropped again to between the
UCL and the overall process mean (xˉ).
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TRB 2014 Annual Meeting
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Individual mean testing was conducted for each of the four time slices and indicated that the means
during the four periods were statistically different. This shows that external influences such as policy
changes and asset refresh affected the process.
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FIGURE 3. Control Chart for Call Volumes
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Pareto Analysis/Bad Actor Report
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All service request calls to DC’s 311 system are fielded by the Office of Unified Communications (OUC),
entered into a service request system and routed to appropriate agencies. DDOT analyzed parking
meter related service request calls from the 311 system and performed a pareto analysis. The analysis
(referred to within DDOT as the bad actor report) revealed that the worst1 1,500 meters (8% of assets)
accounted for 40% of the call volumes. The 1,500 worst performing assets averaged 25 calls per year.
This implies technicians were dispatched to investigate these meters an average of 25 times during the
course of one year. The worst performing meter was “called-in” 95 times. Ninety five percent (1,425 of
the 1,500) of the assets in the bad actor report were the oldest asset types (SSM). Figure 4 shows the
distribution of call volumes for the 1,500 worst performing meters [26].
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From a business and customer service standpoint it made more sense to systematically replace these
aged assets with newer assets.
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FIGURE 4. Call Distribution for 1500 Worst Performing Meters
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Worst meter is defined as the meter that had the maximum number of 311 calls/service requests
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Mean Testing
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Based on the Pareto analysis and the findings of the pilots, DDOT started replacing its worst performing
assets with newer networked assets. Figure 5 shows how the call volumes on the routes dropped after
new assets were installed. Mean testing of the call volumes was conducted before and after the
installation and the means were found to be statistically different.
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Similar before and after mean testing was conducted on revenues for routes where new assets were
installed. The analysis revealed that asset refresh resulted in higher revenues as well [27]. This was
most likely driven by two factors; (a) newer meters had better uptimes and were less likely to break
down, and (b) the newer networked assets accepted credit cards, hence customers had two options to
pay at these meters – coin or credit/debit card.
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FIGURE 5. Mean Testing for Routes with New Assets
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Process Capability
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DDOT manages and operates the parking meter program using a performance based asset management
contract. The contract requires the contractor to fix SSM within 72 hours and MSM within 24 hours. It
also requires an operability rate of 99% for MSM and 97% for SSM. The contract allows incentives for
exceeding the performance metrics and liquidated damages for failing to meet the performance
measures.
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A capability analysis was conducted to ascertain whether the process was capable of meeting the 72
hours requirement. As shown in Figure 6, the contractor’s mean repair time was significantly below the
upper specification limit (USL) for the contract (72 hours). The contractor was also meeting the 97%
operability requirement. Yet the program had a negative perception.
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TRB 2014 Annual Meeting
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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FIGURE 6. Capability Analysis for Meter Repair Process
Meter Repair Response Time
80
60
Upper Specification
Limit
50
40
30
20
Average Monthly Response Time (Hrs.)
70
10
FY 08
FY 11
FY 10
FY 09
0
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4
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43
Month
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In examining the issue more closely, the team realized that there was a “measurement error” built into
how performance was being measured.
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Measurement Error
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Given that most of the assets are non-networked, operability and repair time was based on a work
order/service request system. This is largely a reactive system in that broken meters factor into the
operability equation only if it is “called in”. A broken meter that is not reported does not factor into the
operability calculation.
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DDOT conducted some field observations based on a statistical sampling. The 95% confidence interval
for meter operability was between 82% and 90% with a mean of 86%. This is significantly lower than the
97% operability calculated through the work order system. Two independent “touch a meter program”,
where DDOT staff assesses operability of its entire meter inventory, estimated operability at
approximately 80% to 85%. The measurement error helps explain the difference between the “ground
truth” and work order based operability and helps explain the public frustration.
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Process Flow Charts
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DDOT also spent a considerable amount of time mapping out the various processes related to parking
and curbside management. The parking function in DDOT is very fragmented with individual groups
responsible for policy, operations, signage, permitting and enforcement. Process mapping techniques
revealed inefficiencies such as hidden factories, bottlenecks and non-value added activities. It was also
apparent that there were delays whenever there was a hand-off of responsibilities between different
groups in DDOT. Process mapping allowed DDOT to get a common understanding of the process and
responsibilities and identify inefficiencies [28].
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IMPLEMENTATION
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Based on the LSS analysis and the findings of the parking pilots in 2010, DDOT implemented a series of
changes to its parking meter program with dramatic results. These included:
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WASHINGTON, DC’S MIGRATION PATH
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Non-Communicating Assets to Networked “Smart Assets”
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DDOT started a systematic process of phasing out non-communicating meters with networked assets.
The change out was done in a systematic manner based on the findings of the bad actor report. MSM
meters were written into the standard specifications and incorporated as part of capital improvements
such as streetscape projects. Table 3 shows how the asset mix has changed over the last three years.
The number of spaces that are covered by credit card accepting, networked meters jumped from 23% in
2009 to 45% in 2013.
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TABLE 3. Washington, DC’s Changing Asset Mix for Parking Meters (2009 and 2013)
•
•
Significantly increased the number of networked assets by implementing new networked, credit
card accepting single space meters and increased the coverage provided by MSMs.
Launched a citywide pay by cell program – Following two very successful pilots, DDOT launched
a citywide pay by cell program in July 2011. The program turned out to be the most successful
pay by cell program in the country. In less than two years since launch, the program has
600,000 customers and has resulted in over 7 million transactions accounting for over 40% of
the annual parking revenue [29].
Issued a new RFP for the next generation parking asset management – DDOT issued a new RFP
for maintaining and managing its parking meter assets for the next five years. The contract is
structured as a performance based contract with liquidated damages and incentive/disincentive
clauses. It is also structured to make sure that the City is not locked into paying for services that
it does not require. Recognizing that the asset mix and revenue mix would change substantially
over the next five years, the contract has fixed price elements, fixed unit prices by asset type for
maintenance, and percentage fee for items such as coin collection and credit card processing. It
also requires use of LSS techniques for program management and an integrated back-end
system for asset monitoring and management [30].
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Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
Asset Type
Non-Networked Single
Space Meters
Networked MultiSpace Meters
Networked Single
Space Meters
TOTAL
Meter/Space Ratio
% Spaces covered by
networked, credit
card accepting assets
Networked
Payment
Options
No
Coin
Yes
Coin
Credit
Coin
Credit
Yes
2009 Asset Mix
# of
# of
%
Meters Spaces
Spaces
13,234
13,234
77%
# of
Meters
10,238
514
638
5,104
28%
NONE
3,197
3,197
17%
17,157
0.80
23%
14,073
13,748
3,923
23%
2013 Asset Mix
# of
%
Spaces Spaces
10,238 55%
18,539
0.75
45%
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Coin Transactions to Virtual Transactions
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With the introduction of credit card accepting, networked meters and the launch of pay by cell, DC’s
revenue mix has undergone a significant transformation. In 2009, 80% of DC’s parking meter revenue
was in the form of coins. Currently that percentage stands at only 30%. Therefore, a majority of DC’s
revenues are through virtual transactions, which have a lower cost structure than coin revenues [31].
Virtual revenues also provides an easier audit trail and provides real-time visibility into revenue streams
and meter usage.
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Reactive to Proactive Maintenance
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Operability of networked meters can be monitored in real-time through a back office system (as
opposed to network assets where meter malfunctions have to be reported). Hence, with the increase in
networked assets, the meter maintenance strategy can be shifted from reactive to proactive. This
increases system uptime, revenue potential and customer satisfaction. It also enables real-time
assessment of asset condition and a more realistic assessment of operability, repair time, etc. making it
easier to manage and monitor a pure performance based contract. Proactive maintenance also reduces
the cost associated with fielding parking meter related 311 calls.
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“Asset lite” Solutions
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As pay by cell adoption rates increase, DC can start considering removing meters from a block face in
areas with high pay by cell usage. These meter-less blocks would be available to customers using pay by
cell only. This can result in significant cost savings for DC, since an asset lite solution such as pay by cell
costs significantly lower than meter-based payment methods (such as coins or credit cards). DDOT will
be testing some of these asset lite strategies in a Federally funded pilot project in the Chinatown area
[32].
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RESULTS
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Program performance can be measured across various dimensions. The parking meter program has
gone through a transformation as a result of LSS analysis and follow-through. The following section
discusses some of the accomplishments.
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Increased payment options for customers – In 2009, people had one mode of payment (coin) at
70% of the metered spaces. Now people have at least two options (coin and pay by cell) to pay
at all locations. At 50% of the locations people have three payment options (coin, credit/debit
and pay by cell).
Increased revenues – In 2009 DC’s parking meter revenue was $20 million. The last set of rate
adjustments occurred in January 2010. DC’s revenue in 2010 was $25 million. DC’s 2012 and
2013 parking revenues were $38 million and $40 million, respectively. This represents a 60%
revenue increase with the same set of parameters or policy framework. This is a function of
better management of the assets, more options to pay for metered parking and better system
uptime.
Drop in call volumes – Parking meter related call volumes can be considers as a surrogate for
customer satisfaction. Call volumes have dropped significantly since an all-time high in 2009
and 2010. 2013 call volumes were 13% lower than 2010 levels.
Public perception about the program has increased – If the sentiment in the press is a reflection
of public perception, the program has undergone a sea-change over the last four years. From
heading such as “Parking Meters a Bane to Mankind” the press sentiment has turned to
“Government at its Best” after the launch of the successful pay by cell program [33,34].
Enhanced Executive visibility - Recognizing the success of the program and the full potential, the
Executive Office of the Mayor allocated $25 million in capital funds for asset refresh and
modernization over next three fiscal year budget cycles.
National Recognition - DC’s parking meter program is now widely acknowledged in the industry
as a forward thinking program. In a recent survey conducted by the International Parking
Institute, DC was ranked fourth amongst innovative parking programs in the country [35].
Figure 7 summarizes some of the performance trends in the parking meter program.
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FIGURE 7. Program Performance Metrics (2009 to 2013)
Payment Options for Parking
Customers
% of Metered Spaces
100%
80%
60%
2009
40%
2013
20%
0%
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2
3
Number of Payment Options
2
Annual Revenue in $million
Annual Parking Revenue
(in $ million)
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2008
2009
2010
2011
2012
2013
Year
3
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Parking Meter Related 311 Calls
Annual 311 Calls (Parking)
250000
200000
150000
100000
50000
0
2010
2011
2012
2013
Year
1
Revenue Mix
100
% Revenue
80
60
40
20
0
2009
2010
2011
2012
2013
Year
Pay by Cell
Credit Card
Coin
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TRB 2014 Annual Meeting
Paper revised from original submittal.
Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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LESSONS LEARNED
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This section lists some of the key success factors/lessons learned for LSS applications.
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Get Executive Buy-In – For a program such as LSS to work, there needs to be a commitment and buy-in
at the executive level. At DDOT all key executives (the Director, Deputy Director, Associate Directors
and Chief-of-Staff) went through six sigma black belt training. This “signaled” the agency staff about the
importance of LSS and set the tone for the program within the agency. The executives in turn have deep
appreciation of the process and its potential.
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Develop a Core Group of Champions – Build a core group of LSS champions throughout the agency. This
core group needs to comprise of individuals that can adapt to change, believe in the benefits of databased decision making, are enthusiastic about applying the concept to their program areas and can
mentor other people in the organization. At DDOT, this core group got subsequent training in a six
sigma train-the-trainer course.
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Institutionalize LSS – Develop training program(s) and provide infrastructure support for the concept to
promulgate throughout the agency. LSS is now part of DDOT’s standard curriculum through the training
office.
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Apply LSS to “Right Projects” - It helps if LSS is applied to a project of critical interest. This ensures
executive support, continuing momentum and sense of urgency. For DDOT, the parking meter program
was one of the highest priority problems that needed to be fixed. In addition, black belt certification
requires participants to work on a real-life project. Having executive leadership trained ensured that LSS
was being applied to projects of critical interest to the agency.
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Share Success Stories – Ensure that success stories are shared throughout the organization. DDOT (and
the DC government) has a performance/data-based culture. Sharing tangible benefits achieved through
application of LSS is part of the natural performance reporting process.
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Be Patient, Maintain Momentum – Agency transformation through LSS is a marathon, not a sprint.
Success requires patience, discipline and sustained focus over a period of time.
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CONCLUSION
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Application of LSS helped transform the parking meter program which used to be a source of frustration
for DDOT and its customers. LSS helped identify fundamental issues with the program and helped DDOT
to aggressively chart a path forward using a fact-based decision making process. Following the success
of the parking program, LSS has been applied to other asset classes and programs at DDOT as well. The
principles and tools from LSS have been successfully applied to streetlights, urban forestry, traffic
control officers and safety service patrols.
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The current trends in public sector transportation agencies towards increased use of performance
management/measurement, higher level of citizen engagement and operating in a financially
constrained environment can serve as a catalyst to adopt process improvement efforts such as LSS.
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TRB 2014 Annual Meeting
Paper revised from original submittal.
Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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Applied correctly, it has the potential to provide the framework for achieving sustainable improvements
to business processes and service delivery.
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TRB 2014 Annual Meeting
Paper revised from original submittal.
Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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REFERENCES
1. District Department of Transportation. Action Agenda – DDOT Delivers. 2010.
http://www.dc.gov/DC/DDOT/About+DDOT/Who+We+Are/Action+Agenda/Action+Agenda++2010. Accessed October 23, 2013.
2. DDOT Press Release. DDOT Announces DC Parking Meter Rate Increase. February 26, 2009.
http://newsroom.dc.gov/show.aspx/agency/ddot/section/2/release/16237. Accessed October
23, 2013.
3. Council of the District of Columbia. Fiscal Year 2010 Budget Support Act of 2009. May 2009.
4. DCMR. Title 18. Chapter 18-24. Section 18-2404. ” Parking Meter and Parking Meter Zones”.
Effective 12/26/2011.
5. Michael Neibauer. More Money, More Problems for District Parking Meters. Examiner. March
1, 2009.
6. Tom Bridge. The Difficulty with Parking Meters. September 23, 2010.
http://www.welovedc.com/2010/09/23/the-difficulty-with-parking-meters/. Accessed October
25, 2013.
7. Dey, S.S. and J. Thommana. “Agency Performance Management in the Digital Age”. October
2013. Unpublished.
8. DC CapStat Session. 911, 311 and Customer Service. October 29, 2009.
9. DC Office of Unified Communications. 2009 Customer Service Survey Data. 2009.
10. Michael Neibauer. Area Drivers File a Record Number of DC Parking Meter Complaints. The
Examiner. November 26, 2008. http://washingtonexaminer.com/area-drivers-file-recordnumber-of-d.c.-parking-meter-complaints/article/104732. Accessed July 28, 2013.
11. Jim Newell. Parking Meters Out to Destroy the Human Race. NBC4 News. February 24, 2009.
http://www.nbcwashington.com/news/local/Local-Parking-Meters-Develop-ArtificialIntelligence-Will-Destroy-Humans.html. Accessed July 28, 2013.
12. EPA, The Environmental Professional’s Guide to Lean and Six Sigma, EPA-100-K-09-006, August
2009.
13. Snyder, Kent and Peters, Newton. White Paper – Lean Six Sigma in the Public Sector, Xerox
Corporation, September 2004.
14. American Strategic Management Institute. Six Sigma Excellence Summit - Course Materials. July
2010.
15. The Performance Institute. Lean Six Sigma Train-the-Trainer Course Materials. May 2011.
16. The Performance Institute, Lean Six Sigma Black Belt Certification Course Materials, 2010.
17. Maleyeff, John. Improving Service Delivery in Government with Lean Six Sigma. IBM Center for
the Business of Government, 2007.
18. City of Fort Wayne, Indiana. Mayor to be Keynote Speaker at Six Sigma Event in California. 2006.
http://www.cityoffortwayne.org/news-archive/974-mayor-to-be-keynote-speaker-at-six-sigmaevent-in-california.html. Accessed October 25, 2013.
19. City of Irving Innovates Services with Lean Six Sigma. http://www.tmac.org/node/102. Accessed
October 25, 2013.
20. Lean Six Sigma Success Stories in Transportation and Travel Industries.
http://www.goleansixsigma.com/lean-six-sigma-success-stories-in-transportation-and-travelindustries/. Accessed October 25, 2013.
21. Helferich, K. Application of Six Sigma to Humanitarian Relief Logistics. 2013 TRB Annual
Meeting, Session 383, Paper P13-5944.
22. Hanna, Awad et. al. Applying Lean Techniques in the Delivery of Transportation Infrastructure
Projects. 2011 TRB Annual Meeting, Session 388, Paper 11-1405.
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TRB 2014 Annual Meeting
Paper revised from original submittal.
Dey, S.S., Transforming Washington DC’s Parking Meter Program Using Lean Six Sigma Based Asset Management
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23. Han, Seung Heon et. al. Six Sigma-Based Approach to Improve Performance in Construction
Operations. Journal of Management in Engineering, pp21-31, 2008-1.
24. DDOT. Pre-Bid Conference - Asset Management Services for Parking Meter Assets Citywide.
December 2, 2011.
http://app.ocp.dc.gov/RUI/information/scf/solicitation_detail.asp?solicitation=DCKA-2012-R0018. Accessed October 24, 2013.
25. Dey, S.S. and T. Viteri. “Washington, DC Pilots New Meter Programs to Enhance Its Parking
System.” The Parking Professional, July 2011.
26. SAIC, Parking Meter Performance Audit Report, Task 1 – Program Assessment Report. Prepared
for DDOT. December 2009.
27. Dey, S.S., S.Dock and E. Patterson. “Economic Implications of Changing Dynamics for Metered
On-Street Parking”. Unpublished.
28. SAIC, Strategic Parking Plan. Prepared for DDOT, September 2010.
29. Dey, S.S. and A. Rao. “Dialing and Thriving” The Parking Professional, August 2013.
30. Office of Contract & Procurement, DDOT. Asset Management Services for Parking Meter Assets
Citywide, DCKA-2012-R-0018, November 2011.
31. Dey, S.S., “Asset Lite Solutions to Metered Curbside Parking”, ITE Annual Meeting, August 4-7,
2013, Boston, MA.
32. DDOT, Multimodal Value Pricing for Metered Curbside Parking, 2012 Discretionary Grant
Program – Value Pricing Pilot Grant Application, January 2012.
http://s3.documentcloud.org/documents/407820/ddot-value-pricing-pilot-program-grantproposal.pdf. Accessed July 31, 2013.
33. David Alpert. An Example of Government at Its Best. The Washington Post. October 18, 2011.
http://www.washingtonpost.com/blogs/all-opinions-are-local/post/an-example-of-governmentat-its-best/2011/03/22/gIQA332RuL_blog.html. Accessed July 29, 2013.
34. Justin Jouvenal. DC Rolls Out Pay by Phone Parking Meter System. Washington Post. April 20,
2011. http://www.washingtonpost.com/local/dc-rolls-out-pay-by-phone-parking-metersystem/2011/04/20/AFg9pSEE_story.html Accessed July 29, 2013.
35. International Parking Institute. 2013 Emerging Trends in Parking. May 2013.
http://www.parking.org/media/emerging-trends-in-parking.aspx. Accessed July 28, 2013.
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TRB 2014 Annual Meeting
Paper revised from original submittal.