This is the accessible text file for GAO report number GAO-13-603 
entitled 'U.S.-Mexico Border: CBP Action Needed to Improve Wait Time 
Data and Measure Outcomes of Trade Facilitation Efforts' which was 
released on July 24, 2013. 

This text file was formatted by the U.S. Government Accountability 
Office (GAO) to be accessible to users with visual impairments, as 
part of a longer term project to improve GAO products' accessibility. 
Every attempt has been made to maintain the structural and data 
integrity of the original printed product. Accessibility features, 
such as text descriptions of tables, consecutively numbered footnotes 
placed at the end of the file, and the text of agency comment letters, 
are provided but may not exactly duplicate the presentation or format 
of the printed version. The portable document format (PDF) file is an 
exact electronic replica of the printed version. We welcome your 
feedback. Please E-mail your comments regarding the contents or 
accessibility features of this document to Webmaster@gao.gov. 

This is a work of the U.S. government and is not subject to copyright 
protection in the United States. It may be reproduced and distributed 
in its entirety without further permission from GAO. Because this work 
may contain copyrighted images or other material, permission from the 
copyright holder may be necessary if you wish to reproduce this 
material separately. 

United States Government Accountability Office: 
GAO: 

Report to the Ranking Member, Subcommittee on Immigration, Refugees 
and Border Security, Committee on the Judiciary, U.S. Senate: 

July 2013: 

U.S.-Mexico Border: 

CBP Action Needed to Improve Wait Time Data and Measure Outcomes of 
Trade Facilitation Efforts: 

GAO-13-603: 

GAO Highlights: 

Highlights of GAO-13-603, a report to Ranking Member, Subcommittee on
Immigration, Refugees and Border Security, Committee on the Judiciary, 
U.S. Senate. 

Why GAO Did This Study: 

Trade with Mexico is important to the United States’ economy. Most of 
this trade crosses the border by truck, and studies have shown that 
long waits at border crossings can negatively affect the U.S. economy. 
CBP is responsible for securing U.S. borders at ports of entry to 
prevent illegal entry of persons and contraband while also facilitating
legitimate trade and travel. GAO was asked to examine CBP data on and
actions taken to address wait times at southwest border crossings. This
report addresses the extent to which (1) CBP wait time data are 
reliable for public reporting and informing CBP decisions, (2) CBP has 
identified infrastructure and staffing needed to process current 
commercial traffic volumes, and (3) CBP performance measures assess 
progress toward its trade facilitation goal. GAO assessed the 
reliability of CBP’s wait time data; visited six land border crossings 
(not generalizable, but selected largely for high traffic volume); 
analyzed CBP documentation, including needs assessments; and interviewed
stakeholders and CBP officials. 

What GAO Found: 

Within the Department of Homeland Security (DHS), U.S. Customs and 
Border Protection’s (CBP) data on commercial vehicle wait times—-the 
time it takes to travel from the end of the queue to the CBP primary 
inspection point at land border crossings—-are unreliable for public 
reporting and CBP management decisions across border crossings. These 
data-—which are collected manually by CBP officers-—are unreliable 
because CBP officers inconsistently implement an approved data 
collection methodology, and the methodologies used vary by crossing. 
For example, five of the six crossings GAO visited require observation
of the end of the queue to estimate wait times, but officials at these 
crossings reported the lines extended beyond their view at times. As a 
result, these data are generally not used by the private sector and 
are of limited usefulness for CBP management decisions on staffing and 
infrastructure investments. Determining and taking steps to help CBP 
officials overcome challenges to consistent implementation of existing 
methodologies could improve the reliability and usefulness of CBP’s 
current wait time data. CBP officials have identified automated wait 
time data collection technology as the best way to improve data
reliability. The Department of Transportation (DOT), in coordination 
with state DOTs and CBP, has ongoing pilot projects to use technology 
to gather more reliable wait time data at some border crossings. 
However, CBP has not assessed the feasibility of replacing current 
methods with automated data collection. Doing so, consistent with 
program management standards, could help CBP determine how to best 
improve data reliability. 

CBP officials report and analyses indicate infrastructure and staff 
needs, but documenting CBP’s staff allocation process could improve 
transparency and facilitate review and validation by CBP and others. 
CBP officials and analyses identify needs for additional 
infrastructure-—such as more lanes—-at some crossings, and GAO 
analysis of CBP data on lane use generally supported agency views on 
the extent to which CBP opens lanes at the six crossings GAO visited. 
Further, GAO analysis of lane use and traffic volume data generally
supported CBP officials’ statements that they open and close primary 
inspection lanes in response to fluctuations in commercial traffic 
volume. CBP analyses identified a need for 3,811 additional officers, 
and CBP headquarters officials told GAO all southwest border ports 
require additional staff, but CBP field and port managers at three of 
six crossings GAO visited reported having sufficient staff. CBP human 
capital officials reported that they adjust staff allocations across
locations to better ensure that staff levels match areas of greatest 
need, but CBP has not documented this process, and there is no 
guidance defining the methodology used or factors considered when 
allocating staff across ports. Documenting this process, consistent 
with internal control standards, could improve transparency, helping 
CBP and others to better ensure that scarce staff resources are 
effectively allocated to fulfill mission needs across ports. 

CBP does not have outcome-oriented performance measures to determine the
extent to which the agency is facilitating trade. The Office of 
Management and Budget and GAO guidance recommend using outcome-
oriented measures to promote accountability for results. In the 
absence of such measures, it is difficult for the agency or others to 
gauge CBP’s progress in meeting its stated goal of facilitating trade. 

What GAO Recommends: 

GAO recommends that CBP (1) determine and take steps to help ensure 
consistent implementation of existing wait time data collection 
methodologies, (2) assess the feasibility of replacing current 
methodologies with automated methods, (3) document its staff 
allocation process and rationale, and (4) develop outcome-oriented
performance measures. DHS agreed with these four recommendations and
identified steps to address them, although the planned actions will not
address the intent of one. 

View [hyperlink, http://www.gao.gov/products/GAO-13-603]. For more 
information, contact Rebecca Gambler at (202) 512-8777 or 
gamblerr@gao.gov. 

[End of section] 

Contents: 

Letter: 

Background: 

CBP's Wait Time Data Are Unreliable for Informing the Public and CBP 
Management Decisions, and CBP Has Not Assessed the Feasibility of 
Automated Data Collection Options: 

CBP Analyses and Officials Identified Some Infrastructure and Staff 
Needs, but the Methodology Used to Allocate Staff across Ports of 
Entry Has Not Been Documented: 

CBP Performance Measures Do Not Reflect Progress in Achieving Trade 
Facilitation Goals: 

Conclusions: 

Recommendations for Executive Action: 

Agency Comments and Our Evaluation: 

Appendix I: Results of Studies on the Economic Impact of Wait Times on 
Cross-Border Commerce: 

Appendix II: Objectives, Scope, and Methodology: 

Appendix III: U.S. Customs and Border Protection's Capital Investment 
Planning Process: 

Appendix IV: Ongoing, Planned, or Completed Land Port of Entry 
Renovation Projects, Fiscal Years 2008 through 2012: 

Appendix V: Average Hourly Traffic Volume and Average Hourly 
Percentage of Lanes Open Per Month, Fiscal Years 2008-2012: 

Appendix VI: Performance Measures for U.S. Customs and Border 
Protection Activities, Fiscal Year 2013: 

Appendix VII: Comments from the Department of Homeland Security: 

Appendix VIII: GAO Contact and Staff Acknowledgments: 

Tables: 

Table 1: Infrastructure Needs as Identified in Customs and Border 
Protection (CBP) and General Services Administration Assessments (GSA) 
and by CBP Officials at the Six Crossings We Visited: 

Table 2: Studies of the Economic Impact of Commercial Vehicle Wait 
Times on the Southwest Border: 

Table 3: Categories of Criteria Customs and Border Protection Uses to 
Prioritize Land Port of Entry Projects: 

Table 4: Prioritization Rank of Infrastructure Needs at Commercial 
Southwest Border Crossings: 

Table 5: Completed Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic, 
Fiscal Years 2008 through 2012: 

Table 6: Ongoing Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic as 
of May 2013: 

Table 7: Planned Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic, as 
of May 2013: 

Table 8: Descriptions of Six Selected Crossings including Year Built 
and Renovated, and the Number of Available Commercial Lanes, Fiscal 
Years 2008 through 2012: 

Table 9: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Otay Mesa Crossing near San Diego, 
California, Fiscal Years 2008 through 2012: 

Table 10: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Mariposa Crossing in Nogales, Arizona, 
Fiscal Years 2008 through 2012: 

Table 11: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Bridge of the Americas Crossing in El Paso, 
Texas, Fiscal Years 2008 through 2012: 

Table 12: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Ysleta Crossing in El Paso, Texas, Fiscal 
Years 2008 through 2012: 

Table 13: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Columbia Solidarity Bridge Crossing in 
Laredo, Texas, Fiscal Years 2008 through 2012: 

Table 14: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at World Trade Bridge Crossing in Laredo, 
Texas, Fiscal Years 2008 through 2012: 

Table 15: U.S. Customs and Border Protection-Focused Performance 
Measures, Fiscal Year 2013: 

Figures: 

Figure 1: Commercial Vehicles in Line to Enter the United States at 
Otay Mesa near San Diego, California: 

Figure 2: Commercial Vehicle Inspection Process at a Land Port of 
Entry: 

Figure 3: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Selected Southwest Border Crossings, Fiscal 
Years 2008-2012: 

Figure 4: The Otay Mesa Crossing near San Diego, California: 

Figure 5: Commercial Vehicle Primary Inspection Lanes at the Mariposa 
Crossing in Nogales, Arizona: 

Figure 6: The Bridge of the Americas Crossing in El Paso, Texas: 

Figure 7: The Ysleta Crossing in El Paso, Texas: 

Figure 8: The Columbia Solidarity Bridge Crossing in Laredo, Texas: 

Figure 9: The World Trade Bridge Crossing in Laredo, Texas: 

Figure 10: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Otay Mesa Crossing near San Diego, 
California, Fiscal Year 2008 through 2012: 

Figure 11: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at the Mariposa Crossing in Nogales, Arizona, 
Fiscal Year 2008 through 2012: 

Figure 12: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at the Bridge of the Americas Crossing in El 
Paso, Texas, Fiscal Year 2008 through 2012: 

Figure 13: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Ysleta Crossing in El Paso, Texas, Fiscal 
Year 2008 through 2012: 

Figure 14: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Columbia Solidarity Bridge Crossing in 
Laredo, Texas, Fiscal Year 2008 through 2012: 

Figure 15: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at World Trade Bridge Crossing in Laredo, 
Texas, Fiscal Year 2008 through 2012: 

Abbreviations: 

ARRA: American Recovery and Reinvestment Act: 

ATU: Advance Targeting Unit: 

CBP: U.S. Customs and Border Protection: 

CIP: capital investment plan: 

C-TPAT: Customs and Trade Partnership Against Terrorism: 

DHS: Department of Homeland Security: 

DOT: Department of Transportation: 

FAST: Free and Secure Trade: 

FDA: Food and Drug Administration: 

FHWA: Federal Highway Administration: 

FOUO: for official use only: 

GDP: gross domestic product: 

GPRA: Government Performance and Results Act: 

GSA: General Services Administration: 

OA: Office of Administration: 

OFO: Office of Field Operations: 

OMB: Office of Management and Budget: 

SRA: Strategic Resource Assessment: 

WHTI: Western Hemisphere Travel Initiative: 

[End of section] 

GAO:
United States Government Accountability Office: 
441 G St. N.W. 
Washington, DC 20548: 

July 24, 2013: 

The Honorable John Cornyn: 
Ranking Member: 
Subcommittee on Immigration, Refugees and Border Security: 
Committee on the Judiciary: 
United States Senate: 

Dear Senator Cornyn: 

Trade with Mexico, the nation's third-largest trade partner behind 
Canada and China, is important to the United States' economic health, 
and timely access to Mexican goods is important to both U.S. 
manufacturers and consumers. The value of goods imported into the 
United States from Mexico has increased over 30 percent in the last 5 
years, and in 2012 imports from Mexico were valued at nearly $278 
billion. Most of this trade crosses the border by commercial truck, 
and in 2012 there were over 5 million truck crossings into the United 
States from Mexico. Industry representatives who rely on commercial 
vehicles to quickly transport goods across the U.S.-Mexico border have 
raised concerns about long waits at border crossings, and several 
studies have shown that the time that commercial vehicles spend 
waiting to cross into the United States from Mexico can have a 
negative impact on the U.S. economy in terms of lost revenue and jobs. 

The Department of Homeland Security's (DHS) U.S. Customs and Border 
Protection (CBP) is the lead federal agency charged with a dual 
mission of keeping terrorists, criminals, and inadmissible aliens out 
of the country while facilitating the flow of legitimate travel and 
commerce at the nation's borders.[Footnote 1] CBP's Office of Field 
Operations (OFO) is responsible for cargo and passenger processing 
activities related to security, trade, immigration, and agricultural 
inspection at air, land, and sea ports of entry, and CBP's Office of 
Administration (OA) is responsible for real estate management, 
including the construction, maintenance, and leasing of facilities, 
such as land ports of entry.[Footnote 2] CBP's focus has historically 
been on security; however, CBP has also undertaken specific efforts to 
facilitate legitimate travel and trade, such as launching the Free and 
Secure Trade (FAST) program in 2002 to expedite the travel of low-risk 
screened shipments across the border, and publishing border crossing 
wait times on a website to inform public and private sector border 
crossing decisions. 

We previously reported that CBP has faced challenges balancing the 
goals of security and trade facilitation, and some information 
necessary to assess its trade facilitation efforts has not been 
available.[Footnote 3] Specifically, we reported in July 2010 that 
CBP's Automated Commercial Environment collected data on freight 
processing but did not differentiate between FAST and non-FAST 
shipments--information needed to help CBP determine the extent to 
which FAST program participants experience intended benefits.[Footnote 
4] We recommended that CBP (1) develop milestones for completing 
enhancement of the database used to capture data on FAST program 
benefits, and (2) conduct a study to determine if program benefits are 
being realized that could help CBP determine what program adjustments, 
if any, are needed. CBP agreed with these recommendations; took action 
to collect the needed data; and, as of June 2013, drafted an 
evaluation of FAST lanes and commercial traffic at select crossings on 
the northern border to determine whether there is a need to expand the 
usage of FAST lanes. This study is currently under review and CBP 
expects to fully implement this recommendation by December 30, 2013. 

You asked us to review what data CBP collects and reports on wait 
times for commercial vehicles at southwest border land ports of entry 
and actions CBP has taken to reduce those wait times. This report 
addresses the following questions: 

* To what extent are CBP wait time data reliable for public reporting 
and informing CBP decisions on staffing and infrastructure investments? 

* To what extent has CBP identified infrastructure and staffing needed 
to process current commercial traffic volume at select southwest 
border crossings with high traffic volume? 

* To what extent do CBP performance measures assess progress toward 
its goal of facilitating trade? 

This report also presents information on the results of studies that 
have quantified the economic impact of commercial vehicle wait times 
on cross border commerce. This information, including the methodology 
used to identify these studies, is presented in appendix I. 

To inform our analysis of the first and second objectives, we visited 
six border crossings--Bridge of the Americas and Ysleta in El Paso, 
Texas; World Trade Bridge and Columbia Solidarity Bridge in Laredo, 
Texas; Mariposa in Nogales, Arizona; and Otay Mesa near San Diego, 
California--selected based on their commercial traffic volume, 
geographic diversity, and representation of a mix of recent or ongoing 
infrastructure modernization projects. At each location, we 
interviewed CBP management, toured the facility, and convened a 
roundtable of local industry representatives and local government 
officials. To obtain a range of perspectives on commercial vehicle 
traffic at southwest border crossings, we met with representatives of 
21 companies and associations (who were identified to us as 
knowledgeable stakeholders representing industries that rely on cross-
border commerce, including customs brokers, trucking companies, and 
distributors) as well as bridge directors and representatives of four 
local government entities (the Mayors of El Paso and San Diego, the 
Laredo City Manager, and representatives of the San Diego Association 
of Governments) at all four cities we visited or by teleconference. 
[Footnote 5] We also interviewed officials from federal agencies 
involved in securing the border and facilitating trade at land ports 
of entry. Although the results of our site visits and interviews are 
not generalizable, they provided us with perspectives on operations at 
ports of entry that accounted for a total of approximately 70 percent 
of the commercial vehicle crossings into the United States from Mexico 
for fiscal year 2008 through July 2012. Over the course of our work, 
we also interviewed other stakeholders, including officials from the 
Mexican Foreign Ministry, academics, and representatives of national 
trade associations, such as the American Trucking Associations and the 
Border Trade Alliance, to obtain a broader range of perspectives on 
commercial vehicle traffic at southwest border crossings.[Footnote 6] 

To address the first objective, we reviewed and analyzed CBP's 
policies and guidance for calculating and reporting wait times and CBP 
evaluations of its wait time data, including a fiscal year 2008 CBP 
Commercial Wait Times Analysis Report completed by CBP's Western 
Hemisphere Travel Initiative (WHTI) Office.[Footnote 7] We also 
reviewed CBP's fiscal year 2012 wait time data for the six crossings 
we visited and compared documentary and testimonial evidence of how 
wait times are currently being calculated by officials at land ports 
of entry on the southwest border against CBP policies and guidance to 
identify any discrepancies. We also compared CBP's policies and 
guidance with criteria in Standards for Internal Control in the 
Federal Government.[Footnote 8] Our assessment of the reliability of 
these data is discussed later in this report. To determine the status 
of the Department of Transportation's (DOT) pilot projects to automate 
wait time data at the southwest border, we interviewed officials at 
DOT's Federal Highway Administration (FHWA), Texas Department of 
Transportation, and Texas A&M University and reviewed documentary 
evidence they provided, such as written updates on the status of 
certain pilot projects.[Footnote 9] We compared CBP's plans to 
automate wait times with standards for program management.[Footnote 10] 

To address the second objective, we reviewed and analyzed CBP and 
General Services Administration (GSA) assessments of land port of 
entry capacity, such as CBP's Strategic Resource Assessments (SRA), 
and reviewed documentation of CBP's Workload Staffing Model, used to 
determine staff needs at land ports of entry.[Footnote 11] We also 
interviewed CBP and GSA officials about infrastructure needs at land 
border crossings and how these needs are identified and prioritized. 
We interviewed CBP officials about the agency's staff allocation 
policies and processes and compared these with criteria in our 
previous work on human capital management and Standards for Internal 
Control in the Federal Government.[Footnote 12] We also analyzed CBP 
data on traffic volume and the number of primary lanes open during 
operating hours at the six crossings from fiscal years 2008 through 
2012. We selected this time period for our data analyses to permit a 
trend analysis. Our data analyses are not generalizable to the entire 
southwest border, but represent trends at six high-volume crossings. 
To assess the reliability of these data sources, we reviewed 
documentation, interviewed agency officials, electronically tested the 
data, reviewed internal controls, and traced a selection of data to 
source files. We determined that the data were sufficiently reliable 
for the purposes of our report. 

To address the third objective, we reviewed documentation of CBP's 
fiscal year 2013 performance goals, measures, and reports. We assessed 
CBP's measures against criteria in Office of Management and Budget 
(OMB) Circular No. A-11 and useful practices GAO previously identified 
to enhance performance management and measurement processes.[Footnote 
13] We also interviewed relevant DHS and CBP officials regarding CBP's 
current performance measures and the extent to which CBP uses its wait 
time data to measure progress, among other things. 

We also identified studies that quantified the economic impact of 
commercial vehicle wait times on cross-border commerce by searching 
literature and asking relevant interviewees whether they were aware of 
any such studies. We reviewed over 100 identified studies and analyzed 
the 6 studies that determined an economic impact of commercial vehicle 
wait times on the southwest border. A more detailed description of our 
methodology and the results of these studies are presented in appendix 
I. 

We conducted this performance audit from July 2012 to July 2013 in 
accordance with generally accepted government auditing standards. 
Those standards require that we plan and perform the audit to obtain 
sufficient, appropriate evidence to provide a reasonable basis for our 
findings and conclusions based on our audit objectives. We believe 
that the evidence obtained provides a reasonable basis for our 
findings and conclusions based on our audit objectives. Additional 
details on our scope and methodology are contained in appendix II. 

Background: 

Agencies' Responsibilities at Land Ports of Entry: 

In addition to CBP, various agencies have responsibilities for 
facilitating trade at land ports of entry and conducting inspections 
of commercial vehicles. GSA oversees design, construction, and 
maintenance for all ports of entry in consultation with CBP. In 
consultation with GSA, CBP develops an investment plan to manage the 
modernization of the land ports of entry inventory. Within DOT, FHWA 
provides funding for highway and road construction. In addition, the 
Federal Motor Carrier Safety Administration and state DOTs in some 
states--Arizona, Texas, and California on the southwest border--may 
conduct commercial vehicle inspections at or adjacent to land ports of 
entry to ensure compliance with federal and state-specific safety 
standards. 

In executing its mission, CBP operates 168 land border crossings, 
which vary in size, location, and commercial traffic volume. Of these, 
46 crossings are located on the southwest border, and 24 of these 
crossings process commercial vehicle traffic. The four largest land 
border ports of entry on the southwest border by commercial vehicle 
traffic volume are Laredo, Texas; Otay Mesa, California; El Paso, 
Texas; and Calexico East, California. See figure 1 for a picture of 
commercial vehicles in line to enter the United States at the Otay 
Mesa border crossing near San Diego, California. 

Figure 1: Commercial Vehicles in Line to Enter the United States at 
Otay Mesa near San Diego, California: 

[Refer to PDF for image: photograph] 

Source: CBP. 

Note: This photo was taken on April 22, 2011. 

[End of figure] 

Inspections of Commercial Vehicles at Land Ports of Entry: 

Processing commercial vehicles into the United States at land ports of 
entry involves various steps and requirements.[Footnote 14] First, CBP 
requires carriers to submit electronic lists describing their 
shipments, known as e-Manifests, prior to a shipment's arrival at the 
border.[Footnote 15] Second, CBP reviews the e-Manifest using its 
Automated Commercial Environment database, among others, and assigns a 
risk level to the shipment.[Footnote 16] Next, the commercial vehicle 
proceeds into the United States and to a primary inspection booth at 
the U.S. port of entry, where a CBP officer reviews documentation on 
the exporter, importer, and goods being transported. If the 
documentation is consistent with CBP requirements and no further 
inspections are required, the truck is allowed to pass through the 
port. Depending on the port of entry, goods imported, or law 
enforcement requirements, CBP may direct the commercial truck to 
secondary inspection. According to CBP, trucks are referred to 
secondary inspection for numerous reasons, such as officer's 
initiative, targeted inspection, or random inspection.[Footnote 17] 
Secondary inspection involves more detailed document processing and 
examinations using other methods including gamma ray imaging systems 
and advanced radiation portal monitors or unloading and physical 
inspection.[Footnote 18] Trucks that require secondary inspection may 
be inspected by more than one federal agency, depending on their 
cargo.[Footnote 19] See figure 2 for an illustration of the steps in 
the commercial vehicle inspection process at land ports of entry. 

Figure 2: Commercial Vehicle Inspection Process at a Land Port of 
Entry: 

[Refer to PDF for image: process illustration] 

Total crossing time: 

(1) Queue for Mexican customs: U.S.-bound commercial vehicles wait for 
processing at Mexican customs. Measurement of a vehicle's "total 
crossing time" begins here. 

(2) Mexican customs: Prior to entering the U.S., commercial vehicles 
are cleared by Mexican customs again. When the vehicle is cleared, it 
crosses the border and proceeds to the Customs and Border Protection 
(CBP) primary inspection facility in the United States. 

(3) Queue for U.S. primary inspection: CBP's definition of wait time 
begins when a commercial vehicle arrives at the end of the queue for 
primary inspection. 

(4) Primary inspection: CBP's definition of wait time ends as soon as 
the vehicle arrives at the primary inspection booth. At a primary 
inspection booth, a U.S.-bound commercial vehicle makes its first 
contact with CBP officers who review documentation on the exporter, 
importer, and good being transported. If its documentation is 
consistent with CBP requirements and no further inspections are 
required, the vehicle is allowed to pass through the port without 
further inspection. However, CBP may direct the vehicle to secondary 
inspection depending upon the cargo, law enforcement requirements, or 
officer initiative. 

(5a) Secondary inspection: Secondary inspection involves more detailed 
document and physical examination, possibly including manual 
offloading and inspection by CBP or other federal agencies. For 
example, Food and Drug Administration inspectors may request 
commercial vehicles be sent to secondary inspection to ensure 
compliance with U.S. safety requirements. 

(5b) Nonintrusive inspection: CBP officers who suspect a commercial 
vehicle to hold persons or contraband can refer the vehicle to be 
scanned by gamma ray systems or advanced radiation portal monitors. 

(6) State-specific commercial vehicle safety inspection: At some 
crossings, commercial vehicles may be inspected by federal and state 
departments of transportation to ensure compliance with federal and 
state-specific safety standards. 

(7) Exit: Once the truck has been cleared by CBP, other federal 
agencies, and any state department of transportation inspectors, it is 
allowed to proceed freely into the U.S. The measurement of a vehicle's 
"Total crossing time" ends here. 

Source: GAO analysis of CBP data. 

[End of figure] 

To facilitate the travel of low-risk screened shipments across the 
border, CBP created the FAST program, which is intended to secure and 
facilitate legitimate trade by providing expedited processing of 
participants' merchandise in designated traffic lanes at select border 
crossings, fewer referrals to secondary inspections, "front-of-the-
line" processing for CBP secondary inspections, and enhanced 
security.[Footnote 20] To be eligible to receive the benefits of the 
FAST program, every link in the supply chain--the carrier, the 
importer, and the manufacturer--is required to be certified under the 
Customs and Trade Partnership Against Terrorism (C-TPAT) program and 
the driver must be preapproved for participation in the FAST program. 
[Footnote 21] 

CBP Public Reporting of Border Crossing Wait Time Data: 

CBP defines border wait time as the time it takes for a vehicle to 
travel from the end of the queue--which may be in Mexico or the United 
States, depending on the length of the line--to the CBP primary 
inspection point in the United States. See figure 2 for an 
illustration of these points in the border-crossing process. As a 
service to the traveling public and the trade community, CBP began 
publicly reporting hourly wait time data through a web page on CBP.gov 
in early 2004, and currently reports these data for 42 of 46 crossings 
on the southwest border. CBP began formally collecting commercial and 
private passenger vehicle wait times on a daily basis in late 
September 2001 in response to the delays experienced immediately after 
September 11, 2001, when heightened enforcement efforts resulted in 
significant delays at many land border ports of entry. Over time, the 
collection of wait time data evolved as additional crossings were 
added and the amount of information collected was expanded. CBP 
reported that it is important that the trade community have current 
and consistent wait times on the CBP web site, noting that the web 
site is the only source of wait time information at many locations. 

Some border stakeholders, such as those in the private sector, find 
"total crossing time" to be a more useful measure than CBP's 
definition of wait time. Unlike CBP's narrower "wait time" measure, 
which captures the time it takes for a vehicle to travel from the end 
of the queue to the CBP primary inspection point, total crossing time 
is generally defined as the total time elapsed from entering the line 
in Mexico leading to Mexican export inspection through exit from U.S. 
inspection facilities, including any U.S. state-conducted inspections. 
See figure 2 for an illustration of the differences between these two 
measurements. 

CBP Staff at Land Border Crossings: 

CBP has developed a workload staffing model to determine the optimum 
number of CBP officers that each port of entry needs to accomplish its 
mission responsibilities at its land, air, and sea ports of entry. 
This model existed in different versions, beginning in fiscal year 
2006. The conference report for the fiscal year 2007 DHS 
appropriations act, expressing concern regarding CBP's ability to 
align staffing resources to mission requirements, directed CBP to 
submit a resource allocation model for staffing requirements that 
would explain CBP's methodology for aligning staffing levels with 
threats, vulnerabilities, and workload across all mission areas. 
[Footnote 22] In April 2013, CBP submitted the most recent version of 
its workload staffing model to Congress in response to language in the 
conference and committee reports for the fiscal year 2012 DHS 
appropriations.[Footnote 23] 

DHS has received appropriations to support increased staffing levels 
for CBP officers on the southwest border over the last 5 fiscal years. 
For example, the conference report accompanying the fiscal year 2009 
supplemental appropriation indicated that it included $30 million to 
fund the hiring of up to 125 CBP officers for the southwest border, 
and the fiscal year 2010 emergency supplemental appropriation for 
border security included $29 million for hiring additional CBP 
officers for southwest border land ports of entry.[Footnote 24] 

Assessments of Port Infrastructure: 

CBP and GSA have assessed infrastructure needs at all land border 
crossings over the last 9 fiscal years. From fiscal years 2004 to 
2006, CBP assessed its complete portfolio of land port of entry 
facilities and identified infrastructure investment needs through its 
SRA process. The SRA includes architectural and analytical assessments 
of land port of entry inspection facilities' condition and operations 
as well as relevant regional planning data and studies. Appendix III 
provides more information regarding CBP's SRA process. 

GSA has also assessed land port of entry infrastructure needs when 
planning and designing land port of entry renovation projects. For 
example, before undertaking construction, GSA evaluates the design of 
projects to renovate, expand, or construct a new land port of entry 
using its BorderWizardTM program--a program used to simulate projected 
traffic flow through the proposed facility to help identify potential 
deficiencies, such as insufficient primary inspection lanes.[Footnote 
25] See appendix IV for more information on completed, ongoing, or 
planned infrastructure improvement projects at southwest border land 
ports of entry for fiscal years 2008 through 2012. 

CBP's Wait Time Data Are Unreliable for Informing the Public and CBP 
Management Decisions, and CBP Has Not Assessed the Feasibility of 
Automated Data Collection Options: 

Wait Time Data Are Unreliable and of Limited Usefulness; CBP Has Not 
Taken Steps to Improve Its Current Wait Time Estimation Methodology: 

CBP policy identifies two methodologies to be used by ports of entry 
for manually calculating wait times for commercial vehicles; however, 
challenges in implementing these methodologies contribute to CBP wait 
time data being of limited usefulness for public reporting and 
management decision making across border crossings. Specifically, CBP 
policy provides port directors two options for manually calculating 
wait times at the border crossings they oversee: (1) line-of-sight and 
(2) driver survey. Port directors for each crossing are to choose 
which methodology to use based primarily on a consideration of the 
infrastructure layout of each crossing. CBP officers at border 
crossings are to use the first methodology when the end of the line is 
visible via the naked eye or camera. In accordance with this 
methodology, the CBP supervisor at the crossing is to estimate wait 
time based on traffic volume, number of lanes open, and where the end 
of the queue occurs relative to landmarks (i.e., foot of bridge, 
building, or intersection). When the end of the line is not visible, 
CBP policy recommends that officials estimate wait times using the 
second methodology--asking at least five drivers how long they have 
been waiting in the queue, dropping the highest and lowest responses, 
and averaging the rest. 

CBP's October 2007 interim guidance, which prescribes these two 
methodologies to calculate wait times, states that "it is critically 
important that all locally posted wait times for ports or crossings 
are reasonably accurate and are uniformly reported by all 
stakeholders." In addition, CBP's May 2008 memorandum on land border 
wait time measurement states that "the importance of accurate land 
border wait time measures cannot be understated. Efficient and 
reliable land border wait time measures help to facilitate the 
movement of people and goods across our border and directly impact the 
economic health of border communities and the nation as a whole." 
Among the six crossings we visited, Mariposa used driver surveys, and 
the remaining five crossings used line of sight to estimate wait 
times. However, CBP's wait time data are of limited usefulness for 
public reporting and management decision making across border 
crossings because of three key factors: (1) CBP officers 
inconsistently implemented the line-of-sight methodology; (2) the 
other CBP-approved methodology, driver surveys, is inherently 
unreliable; and (3) CBP officials use different methodologies to 
calculate wait times across land border crossings.[Footnote 26] 

Inconsistent implementation of line-of-sight methodology: Port 
directors at the five crossings we visited that primarily used the 
line-of-sight methodology cited implementation challenges resulting in 
data that are not reliable for management decisions and informing the 
public.[Footnote 27] Specifically: 

* At all five of the crossings, the end of the queue at times extended 
beyond the landmarks used in the line-of-sight methodology and none 
had a camera system in place with the capacity to consistently view 
the end of queues. Two crossings--World Trade Bridge and Columbia 
Solidarity Bridge--had camera systems that allowed officials to view 
the queue several miles into Mexico, but CBP officers noted that it 
could not be used to see the end of the queue on hazy and dusty days. 
CBP previously reported in a fiscal year 2008 WHTI program office 
study on the reliability of CBP's methods for calculating commercial 
vehicle wait times that if officials cannot see the end of the line, 
they cannot accurately gauge the full duration of wait times. 

* At two crossings--World Trade Bridge and Columbia Solidarity Bridge--
senior field office and port officials noted that there were 
frequently gaps between groups of trucks in the queue and that at one 
of these crossings trucks co-mingled with private cars on the bridge 
leading up to the primary inspection booths for commercial traffic. 
According to these officials, these factors hinder officers' ability 
to accurately determine the full duration of wait times as gaps or 
cars between commercial vehicles may make wait times appear to be 
longer or shorter than they actually are. 

* At one crossing--Otay Mesa--CBP officers used the line-of-sight 
methodology but did not consider the number of primary inspection 
lanes open, as required by CBP policy.[Footnote 28] The number of 
lanes open to commercial vehicle traffic influences the rate at which 
traffic moves through primary inspection. CBP's fiscal year 2008 WHTI 
study on the reliability of CBP's methods for calculating commercial 
vehicle wait times notes that the number of lanes open greatly affects 
wait time, so not considering the number of lanes open limits CBP's 
ability to accurately estimate wait times using the line-of-sight 
methodology. 

Driver survey methodology is unreliable: CBP's fiscal year 2008 WHTI 
study on the reliability of CBP's methods for calculating commercial 
vehicle wait times stated that driver surveys have been shown to be 
consistently inaccurate when measuring wait time in part because they 
measure the wait time of travelers currently at the front of the 
queue, not the expected wait time of travelers currently at the end of 
the queue. As a result, if queuing conditions quickly change, the wait 
times collected using this methodology become inaccurate. In addition, 
Port officials at Mariposa used driver surveys as the crossing's 
primary method of estimating wait times, but noted that the 
methodology produced unreliable wait time data. Senior CBP officials 
at this crossing reported that officers had to use driver surveys to 
estimate wait times because a curve in the road leading up to the 
crossing obstructs officers' view of the queue, thereby preventing the 
crossing from using the line-of-sight approach. Senior CBP officials 
at this crossing stated that driver survey is an unreliable 
methodology because of survey bias--drivers may be inclined to report 
longer or shorter wait times than they actually experienced. 

Different methodologies across land border crossings: Port directors 
choose between the two CBP-approved methodologies to estimate wait 
times in accordance with CBP policy; however, OFO and OA headquarters 
officials stated that the use of different methodologies at crossings 
precludes comparison of data across locations in making management 
decisions. Although officials at each crossing determine which of the 
two methodologies to use based on the layout of each crossing and 
other local characteristics, the use of different methodologies at 
crossings makes CBP's wait time data unreliable for comparison across 
southwest border crossings, as they may produce different results. OFO 
and OA headquarters officials told us that because of the different 
methodologies used at different crossings, the wait time data are not 
comparable across crossings and therefore are of limited use in making 
resource allocation decisions. 

In light of these challenges in implementing CBP's approved 
methodologies for estimating wait times, CBP's wait time data do not 
allow for reliable trend analysis to show the extent of wait times 
within or across southwest border crossings. Industry representatives 
at two of the six crossings we visited reported that, in their view, 
the actual wait times commercial vehicle drivers experienced were 
often longer than those CBP publicly reported. For example, industry 
representatives at the roundtable we convened in Nogales reported 
their view that wait times, as defined by CBP, were at times up to 2 
hours longer than those CBP publicly reported. Industry 
representatives at two other crossings reported that CBP's wait time 
data were generally accurate.[Footnote 29] In addition, three 
organizations that commissioned studies to quantify the economic 
impact of wait times at southwest border crossings did not use CBP's 
wait time data as the basis for their studies but rather collected 
original wait time data by, for example, using cameras to photograph 
trucks' license plates at various points along the border-crossing 
routes and then matching these photographs to identify the wait time 
of each vehicle. (See appendix I for the results of these studies.) 
Because of these various limitations, we and others cannot use CBP's 
wait time data to analyze the extent of current wait times across 
border crossings on the southwest border or determine historical 
trends. 

Wait time data currently reported on CBP's public website are of 
limited usefulness to inform industry and the public because of the 
data limitations we identified and because they do not reflect the 
total border crossing time. None of the industry stakeholders 
representing 21 companies and associations we met with over the course 
of our study reported using CBP's wait time data because they 
questioned the accuracy of the data. Industry representatives at the 
roundtables we convened in Nogales, San Diego, and Laredo said that 
more reliable wait time data would be useful to, for example, help 
businesses improve the efficiency of their operations and to make 
informed decisions including where to build new facilities, how much 
inventory to maintain, when and how frequently to send shipments 
across the border, and when to schedule truckers' or manufacturing 
plant employees' shifts. In addition, industry representatives at our 
roundtables in El Paso and San Diego noted that they did not use CBP's 
wait time data because the data did not provide information on the 
duration of the complete border-crossing experience--total crossing 
time--a more comprehensive measure that would be helpful in making 
business decisions.[Footnote 30] A 2008 study commissioned by the 
Department of Commerce also found it was important to use a measure of 
total crossing time to capture the border-crossing system as a whole, 
and to account for the fact that wait time associated with U.S. 
primary inspection was not the sole driver of total wait time for 
commercial vehicles. Instead, they reported that delays were due to 
several factors, including many outside U.S. federal control. FHWA 
officials acknowledge the value of total crossing time and are 
piloting projects to automate such data collection. 

In addition, according to CBP headquarters officials, these wait time 
data are also not sufficiently reliable to inform CBP management 
decisions--more specifically, decisions on staffing and infrastructure 
investments--and officers at the six crossings we visited told us that 
they use the wait time data in limited ways. At the headquarters 
level, OFO officials stated that because of data limitations, CBP's 
wait time data are not useful for comparison across crossings and 
explained that they do not use the data as a basis for determining 
staffing needs or allocating staff across field offices but rather 
rely on CBP's traffic volume data as a proxy.[Footnote 31] A senior 
OFO human capital official explained that the wait time data are not 
systematically compared across ports but ports with known chronic wait 
time problems do get consideration in staff allocation decisions. 
Similarly, OA headquarters officials stated that they do not use wait 
time data to prioritize infrastructure improvement projects because of 
concerns about the reliability of CBP's wait time data. However, CBP 
field office and port officials reported using their existing wait 
time data to a limited extent to inform management decisions in the 
field. Specifically, senior CBP officials at the six crossings we 
visited reported using wait time data as one of various factors 
considered when, for example, allocating staff across crossings and 
shifts, overtime decisions, and as support for white papers sent to 
headquarters requesting funding for infrastructure improvement 
projects. CBP officials at the six crossings we visited reported that 
more reliable wait time data would be useful to them in making such 
decisions. For example, CBP officials at each of these crossings 
stated that more reliable wait time data would help them in making 
staffing decisions. 

CBP does not have efforts underway or planned to help port officials 
overcome challenges to consistent implementation of existing wait time 
estimation methodologies. For example, CBP has not fully implemented 
recommendations from a fiscal year 2008 CBP study that could help the 
agency implement its current wait time estimation methodologies more 
reliably. In fiscal year 2008, CBP's WHTI program office studied the 
reliability of CBP's methods for calculating commercial vehicle wait 
times and identified six recommendations, three of which could, in 
part, help address the limitations discussed above. The 
recommendations directed CBP to, among other things (1) use closed-
circuit television cameras to measure wait time in real time; (2) 
provide a standardized measurement and validation tool, such as a 
useful and well-documented benchmarking system; and (3) continue to 
monitor and evaluate applications of transportation technologies at 
the border that allow for better measurement and reporting of wait 
times.[Footnote 32] CBP headquarters officials from three offices--the 
office that sponsored the report (Land Border Integration), the office 
in charge of cargo operations (Cargo Conveyance and Security), and the 
office that maintains the agency's wait time data (Planning Program 
Analysis and Evaluation)--were all unclear as to the steps, if any, 
that had been taken to address the first two recommendations and which 
office was responsible for implementing them. With regard to the first 
recommendation, an official we met with in Cargo Conveyance and 
Security said that some crossings had access to cameras that helped 
them view the end of the line, but this official did not know how many 
crossings on the southern border had cameras for this purpose and 
further stated that there were no plans to expand camera availability 
to improve wait time data reliability. With regard to the second 
recommendation, this Cargo Conveyance and Security official stated 
that CBP had not taken steps to develop a standardized wait time 
measurement and validation tool and had no plans to do so. However, 
CBP officials with Land Border Integration and Planning, Program 
Analysis, and Evaluation stated that CBP had implemented the third 
recommendation by continuing to monitor and evaluate applications of 
transportation technologies in its work with FHWA to pilot projects 
for automating data collection. 

CBP guidance identifies the importance of reliable wait time 
measurement to facilitate the movement of people and goods across the 
border. Further, Standards for Internal Control in the Federal 
Government calls for agencies to establish controls, such as those 
provided through policies and procedures, to ensure the accuracy and 
timeliness of data. Control activities that ensure the prompt, 
complete, and accurate recording of data help to maintain their 
relevance and value to management in controlling operations and making 
decisions. In the near term, identifying and carrying out steps that 
can be taken to help CBP officials overcome challenges to consistent 
implementation of existing wait time estimation methodologies--such as 
implementing past CBP recommendations to expand the use of cameras to 
see the ends of queues and providing standardized wait time 
measurement and validation tools--could improve the reliability and 
usefulness of CBP's current wait time data. 

CBP Has Not Assessed the Feasibility of New Automation Options: 

In February 2008, FHWA, in coordination with state DOTs and CBP, 
initiated pilot projects to develop automated wait time data 
collection methods at select southwest border crossings. Automation of 
wait time data collection relies on Radio-Frequency Identification 
readers to read the unique signals from passing vehicles at several 
points along the border-crossing route. These data points are then 
automatically matched and analyzed to estimate the current wait time 
at that crossing. As of March 2013, FHWA and state DOTs in Arizona, 
California, and Texas had eight pilot projects under way or completed 
to automate and standardize calculation of both wait time and total 
crossing time at eight crossings on the southwest border, including 
projects at each of the six crossings we visited.[Footnote 33] Wait 
time data resulting from some of these pilots is currently shared on a 
publicly available website with updates every 10 minutes.[Footnote 34] 
These eight projects were initiated on a crossing-by-crossing basis 
and are in various stages of implementation--one completed and seven 
ongoing. Two additional projects are planned so senior FHWA officials 
expect automated wait time data to be available at 10 crossings by 
2015 at which point current federal funding commitments for these 
projects end.[Footnote 35] 

CBP headquarters and field officials, as well as FHWA and a Texas 
Department of Transportation official, cited a range of potential 
benefits that could result from automating border wait time 
measurement. CBP's fiscal year 2008 WHTI report found that the long-
term solution to standardize wait time measurement is to take 
advantage of automation technology. CBP headquarters, field office, 
and port officials told us that automation would reduce the burden on 
staff of manually collecting wait time data and increase staff 
availability for security efforts and other tasks. OFO headquarters 
officials also stated that automation would increase the accuracy, 
reliability, and timeliness of the wait time data that are collected 
and disseminated. Moreover, they stated that automated data would come 
from a more independent source, and thus the data may be perceived by 
industry organizations as more accurate than CBP's current data. This 
would reduce the burden on CBP officials to respond to queries about 
their wait time data, according to CBP officials. OFO headquarters 
officials and senior CBP officials at the six crossings we visited 
reported that accurate wait time data would facilitate CBP management 
decisions such as staffing needs, infrastructure investment, 
performance management (such as evaluating efforts to mitigate wait 
times), and operations planning at land ports of entry. In addition, 
CBP officials at four of the six crossings reported automation could 
provide data on CBP's definition of wait time as well as total border-
crossing time. This could provide CBP with more holistic information 
on the complete border-crossing experience, thereby improving CBP's 
ability to identify and address bottlenecks and providing industry 
stakeholders with more useful data to inform their business processes. 

At the same time, CBP officials reported limitations of the current 
automation pilot projects. In 2011, CBP commissioned a study to review 
the quality of the data resulting from the Texas-based pilot projects 
and found the automated wait time data were not yet sufficiently 
accurate for CBP's purposes. In response to these findings, CBP worked 
with pilot project officials to modify the algorithm used to calculate 
the wait times, with the intention to improve the accuracy of the 
data. Another concern raised by CBP officials is that none of the 
pilots are yet able to consistently differentiate between wait times 
for FAST and non-FAST traffic. Not capturing separate wait time data 
for FAST and non-FAST traffic could limit the usefulness for key 
industry stakeholders and limit CBP's ability to measure whether FAST 
participants are experiencing reduced wait times, as set forth in FAST 
program goals. FHWA officials reported that the technology solutions 
used in the current pilot projects are flexible enough to enable 
adding more readers to differentiate results for FAST and non-FAST 
traffic, but none of the current pilot projects are gathering data for 
this purpose, and FHWA officials reported that they have no plans to 
conduct additional research on solutions that differentiate between 
FAST and non-FAST traffic. In addition, CBP officials note that there 
are no pilot programs to automate wait time data collection at 34 of 
the 42 southwest border crossings where CBP currently reports hourly 
wait times. 

CBP, as the lead agency in collecting and reporting wait time data and 
the sole source of wait time data across the southwest border, does 
not have plans to oversee or manage these automation projects, 
although FHWA and others are anticipating an expanded CBP role once 
the pilot phases conclude. FHWA officials have led the research phase 
of these projects but expect their role to decline as the pilot phases 
end, and they are looking to others to manage these efforts in the 
longer term. FHWA has taken a lead role in the research, testing, and 
evaluation of wait time automation technology including fully funding 
the pilot projects at the Bridge of the Americas and Otay Mesa and 
providing limited financial support for others. However, FHWA 
officials stated that they do not plan to fund these projects after 
the pilot phases end. CBP has coordinated with FHWA by, for example, 
consulting on the algorithms used to project wait times, but CBP has 
not provided funding for the projects on the southwest border. CBP 
officials reported that they do not intend to fund, adopt, or 
otherwise oversee these wait time automation projects once the pilot 
phases supported by FHWA and state DOTs conclude because CBP officials 
stated that they want another entity, such as FHWA or state DOTs, to 
do so. Texas Department of Transportation officials report that they 
are committed to continuing the Texas-based pilot projects in the 
short term, but are looking for another source of funding, possibly 
CBP or others to support the projects in the future. There are no 
other such commitments for the pilots in other states. CBP officials 
report that they are in discussion with FHWA about collaborative 
approaches to continuing these efforts, such as public-private 
partnerships. 

CBP officials stated that the agency has not taken action to improve 
or modify its current methods for collecting and reporting wait time 
data in the short-term because officials believe that automated 
collection of wait time data is the most effective way to obtain 
reliable, standardized data, and the current automation projects are 
still in development. However, CBP has not assessed the feasibility of 
replacing or supplementing current methods of manually calculating 
wait times with the automated methods piloted by DOT or other means. 
Assessing the feasibility could include assessing all of the 
associated costs and benefits, options for how the agency will use and 
publicly report the results of automated data collection, the 
potential trade-offs associated with moving to this new system, and 
other factors such as those influencing the possible expansion of 
automation efforts to the 34 other locations that currently report 
wait times but have no automation project under way. OFO officials 
stated that CBP has not considered assessing the feasibility of 
automating wait time data collection and does not have estimates of 
potential costs or time frames because the pilot projects are still in 
development and CBP management has not committed to automating wait 
time data collection. However, standards for program management call 
for the feasibility of programs to be assessed early on.[Footnote 36] 
Given that CBP officials have stated that automated data collection is 
the most effective method for obtaining standardized and reliable wait 
time data, conducting an assessment of the feasibility of the methods 
piloted by FHWA or other automation methods, in consultation with FHWA 
and state DOTs, could help CBP determine how to best achieve its goal 
of improving the reliability of its publicly reported wait time data. 

CBP Analyses and Officials Identified Some Infrastructure and Staff 
Needs, but the Methodology Used to Allocate Staff across Ports of 
Entry Has Not Been Documented: 

CBP Analyses and Officials Indicated Need for Additional 
Infrastructure at Some Crossings, and Our Analysis of Data on Primary 
Lane Use Generally Supported These Assessments: 

CBP analyses and port officials identified needs for additional 
infrastructure--such as more lanes--at some border crossings, and our 
analysis of CBP data on lane use generally supported agency views on 
the extent to which CBP opens lanes at the six crossings we visited. 
Further, our analysis supports CBP officials' statements that they 
generally open and close primary inspection lanes in response to 
fluctuations in commercial traffic volume, but some port officials 
cited constraints to opening more lanes during times of peak traffic. 

CBP and GSA assessments and officials identified current 
infrastructure limitations affecting commercial vehicle processing at 
three of the six crossings we visited. Specifically, CBP and GSA 
assessments and CBP officials cited infrastructure limitations related 
to an insufficient number of primary lanes at Otay Mesa, insufficient 
space for secondary inspections at Otay Mesa and World Trade Bridge, 
and poor facility layout as well as an insufficient number of exit 
gates at Bridge of the Americas.[Footnote 37] CBP port of entry 
officials for two of the three remaining crossings we visited stated 
that current infrastructure was sufficient to process commercial 
traffic at Columbia Solidarity Bridge and Ysleta. At the last 
crossing, Mariposa, CBP port officials reported that infrastructure 
would be sufficient once GSA's ongoing project to replace and expand 
the port is completed in the fall of 2014. Table 1 summarizes the 
infrastructure needs identified in CBP or GSA assessments as well as 
those identified by CBP port officials at the six crossings we visited. 

Table 1: Infrastructure Needs as Identified in Customs and Border 
Protection (CBP) and General Services Administration Assessments (GSA) 
and by CBP Officials at the Six Crossings We Visited: 

Name and location of border crossings: Otay Mesa: San Diego, CA; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: GSA assessments conducted in 
2008 and 2010 predicted that commercial vehicle wait times would 
increase because of deficiencies including inadequate primary lanes 
and space to conduct secondary and nonintrusive inspections.[A] These 
most recent assessments found that eight additional primary lanes were 
needed to meet the demands of projected commercial traffic volume at 
the crossing; 
Infrastructure needs identified by CBP port officials: CBP port 
officials reported there is an insufficient number of primary lanes 
and there is insufficient secondary inspection space. 

Name and location of border crossings: Mariposa: Nogales, AZ; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: CBP's 2005 Strategic Resource 
Assessment (SRA) identified the need for additional secondary 
inspection space, and a 2009 GSA assessment identified the need for 
additional primary inspection lanes, among other deficiencies 
identified. Four primary lanes were added in April 2012; 
Infrastructure needs identified by CBP port officials: CBP port 
officials told us that once the ongoing renovation and expansion 
project is complete in fall 2014, Mariposa will have no further 
infrastructure needs for commercial vehicle processing. 

Name and location of border crossings: Bridge of the Americas: El 
Paso, TX; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: CBP's 2006 SRA found that the 
crossing was poorly configured and that the configuration and 
placement of primary inspection lanes and exit gates created backups 
and bottlenecks that prevented the effective flow of both regular 
commercial traffic and Free and Secure Trade traffic.[B] Two new exit 
booths were added in 2012 to partially address these issues.c CBP and 
GSA officials have not conducted an assessment to determine the extent 
of reconfiguration needed, stating that they conduct such assessments 
when funds become available to do so; 
Infrastructure needs identified by CBP port officials: CBP port 
officials reported the Bridge of the Americas currently has sufficient 
capacity at its primary and secondary inspection facilities, but that 
the crossing's layout and number of exit gates adversely affect the 
flow of traffic. They also stated that the crossing is at maximum 
capacity and if commercial traffic increases, as CBP officials expect, 
the crossing will have an insufficient number of primary inspection 
lanes and insufficient infrastructure for secondary inspections. 

Name and location of border crossings: Ysleta: El Paso, TX; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: CBP's 2006 SRA identified an 
inadequate number of primary inspection lanes to process commercial 
traffic during peak times and reported that the placement of exit 
gates contributes to congestion within the facility. These 
deficiencies were addressed when GSA completed a renovation that 
included adding two primary inspection lanes in October 2008 and 
reconfiguring the site; 
Infrastructure needs identified by CBP port officials: CBP port 
officials stated that the port had a sufficient number of primary 
lanes and sufficient infrastructure for secondary inspections to 
process commercial traffic. 

Name and location of border crossings: Columbia Solidarity Bridge: 
Laredo, TX; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: CBP's 2006 SRA did not identify 
any infrastructure deficiencies that would limit the crossing's 
ability to process commercial traffic; 
Infrastructure needs identified by CBP port officials: CBP port 
officials stated that the crossing had a sufficient primary and 
secondary capacity to process commercial traffic. 

Name and location of border crossings: World Trade Bridge: Laredo, TX; 
Infrastructure needs identified in CBP or GSA assessments and reported 
actions taken to address these needs: CBP's 2006 SRA reported a need 
to expand primary and secondary inspection infrastructure. Seven 
primary inspection lanes were added in 2011; 
CBP and GSA officials have not conducted an assessment to determine 
the extent to which secondary facilities need to be expanded. CBP and 
GSA officials stated that they conduct such assessments when funds 
become available to do so; 
Infrastructure needs identified by CBP port officials: CBP port 
officials stated that seven primary lanes were added in 2011, but 
insufficient space to conduct secondary and nonintrusive inspections 
results in congestion. 

Source: GAO analysis of CBP and GSA documents and CBP officials' 
statements. 

Notes: Primary inspections are conducted by a CBP officer at a primary 
inspection booth. Secondary inspections occur when a vehicle is 
referred for further inspection, including gamma ray scans, paperwork, 
and physical examinations. 

[A] Nonintrusive inspection includes the use of gamma ray technologies 
to detect contraband in commercial trucks. 

[B] CBP initiated the Free and Secure Trade (FAST) program in 2002 to 
expedite the travel of known low-risk screened shipments across the 
border. Seventeen out of the 24 land border crossings on the southwest 
border have dedicated FAST lanes to expedite FAST traffic. 

[C] According to CBP officials, this infrastructure improvement 
project at the Bridge of the Americas was funded out of the Office of 
Field Operations' operating budget at a cost of approximately $264,500. 

[End of table] 

Further, our analysis of CBP data on lane use generally supported CBP 
officials' statements regarding the extent to which CBP officials open 
existing primary inspection lanes at the six crossings we visited. The 
number of primary inspection lanes available and open at each crossing 
was frequently cited by CBP and industry officials as a critical 
variable affecting wait times for commercial vehicles and, further, as 
evidence of whether a crossing's primary lane infrastructure was 
sufficient to process current traffic volumes. For example, at all the 
locations we visited, industry representatives expressed concern that 
CBP had an insufficient number of primary inspection lanes to process 
current traffic volumes or was not fully utilizing existing lanes. 
[Footnote 38] To determine the extent to which CBP was opening its 
existing primary inspection lanes, we analyzed CBP data on the average 
hourly percentage of primary inspection lanes open per month during 
operating hours over the last 5 fiscal years (October 2007-September 
2012). This analysis showed the following: 

* In fiscal year 2012, lane use data for two of the six crossings we 
visited suggest that these crossings--Otay Mesa and Mariposa--were at 
times operating at or near full capacity, as reported by agency 
officials. In fiscal year 2012, Otay Mesa opened an hourly average of 
82 to 89 percent of its primary inspection lanes per month. At 
Mariposa, our analysis of lane use data for the first half of fiscal 
year 2012, prior to the addition of four new primary inspection lanes 
in April 2012, showed that during months of peak traffic, port 
officials opened an hourly average of between 80 and 84 percent of 
Mariposa's primary lanes per month.[Footnote 39] 

* The average hourly percentage of primary lanes open per month at the 
remaining four crossings we visited--Bridge of the Americas, Ysleta, 
Columbia Solidarity Bridge, and World Trade Bridge--were all lower. 
[Footnote 40] This generally supported CBP officials' statements that 
they have the capacity to open more primary inspection lanes at these 
crossings. 

Our analysis also supports CBP officials' statements that they 
generally open and close primary inspection lanes in response to 
fluctuations in commercial traffic volume--a practice CBP calls active 
lane management; however, some port officials cited constraints in 
opening more lanes during times of peak traffic. Port officials at all 
six crossings we visited reported that they consider commercial 
traffic volume, among other factors, when deciding to open and close 
primary inspection lanes. We compared trends in CBP's data on lane use 
and commercial traffic volume and found that the two were generally 
consistent at five of the six crossings we visited, supporting CBP 
officers' statements that they generally open more lanes when traffic 
volume rises and close lanes when traffic decreases.[Footnote 41] 
However, CBP officials at one of these five crossings--World Trade 
Bridge--explained that other factors kept them from opening all 
primary inspection lanes during periods of high traffic. Specifically, 
these officials said that bottlenecks would form if all primary lanes 
were opened, causing congestion throughout the facility because of 
limited space at secondary inspection.[Footnote 42] The one crossing 
where the lane use and commercial traffic volume did not appear to 
track as closely was Columbia Solidarity Bridge. However, CBP 
officials at Columbia Solidarity Bridge explained that traffic volumes 
and wait times there were so low that they generally did not need to 
open or close lanes in response. Figure 3, an interactive graphic, 
summarizes our analysis and includes additional information for each 
of the six crossings we selected. 

Figure 3: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Selected Southwest Border Crossings, Fiscal 
Years 2008-2012: 

[Refer to PDF for image: interactive graphic] 

Click on the highlighted border crossings for more information. Click 
on the X to close. For a printer friendly version please see appendix 
V. 

Source: GAO analysis of CBP data; CBP (photos). 

[End of figure] 

CBP officials at headquarters and in the field cited various ways they 
are working to address infrastructure limitations given challenges 
caused by budgetary and geographic constraints, among others. In 
regard to budgetary constraints, CBP and GSA officials stated that GSA 
has not received funding to conduct additional expansion projects in 
the last 2 fiscal years, and as a result, they have not been able to 
execute new projects to address infrastructure needs at land ports of 
entry on the southwest border. GSA officials reported that the agency 
has used alternative funding sources to pay for prioritized 
infrastructure projects.[Footnote 43] For example, GSA and CBP 
officials reported using funds from the city of Laredo to support the 
expansion of primary inspection lanes at the World Trade Bridge 
crossing in 2011.[Footnote 44] In regard to geographic constraints, 
port officials at the Bridge of the Americas stated that the urban 
area around that crossing limits opportunities to expand the 
crossing's footprint. Officials with the city of El Paso told us that 
they are promoting a plan to divert all commercial traffic to the 
nearby Ysleta crossing because it has greater capacity to process 
commercial traffic and a larger footprint that can accommodate future 
expansion. CBP field office and port officials stated that they 
support this plan. In another example, CBP officials at headquarters 
and in the field reported participating in binational working groups 
in an effort to address the infrastructure limitations of ports of 
entry along the southwest border. For example, senior CBP officials 
reported participating in the U.S.-Mexico Joint Working Committee to 
develop regional master plans to better ensure the development of a 
well-coordinated land transportation and infrastructure planning 
process along the border.[Footnote 45] 

CBP Cites Need for Additional CBP Officers to Process Commercial 
Traffic at Some Crossings but Documentation Could Increase 
Transparency of Staff Allocations across Locations: 

CBP's workload staffing model--CBP's primary tool for determining the 
number of CBP officers needed at the nation's air, land, and sea 
ports--found that additional CBP officers are needed to meet CBP's 
mission requirements. CBP submitted the most recent version of its 
workload staffing model to Congress in response to language in the 
conference and committee reports for the fiscal year 2012 DHS 
appropriations.[Footnote 46] According to CBP documents submitted to 
Congress, the workload staffing model found that 3,811 additional CBP 
officers are needed to meet CBP's mission requirements in fiscal year 
2014.[Footnote 47] 

In addition, CBP field and port officials at three of the six 
crossings we visited reported having insufficient staff to process 
commercial traffic. Specifically, CBP field office and port officials 
reported insufficient staff at the World Trade Bridge, Columbia 
Solidarity Bridge, and Mariposa crossings and noted that insufficient 
staff at these crossings contributed to commercial vehicle wait times 
and reduced their ability to conduct secondary inspections, among 
other effects.[Footnote 48] Officials at the remaining three 
crossings--Otay Mesa, Bridge of the Americas, and Ysleta--reported 
having a sufficient number of staff to process commercial traffic. 
However, senior OFO headquarters officials reported that all southwest 
border land ports of entry require additional staff to perform at 
optimal levels. 

CBP headquarters and field office officials cited efforts to mitigate 
the effect of reported staffing shortages on ports' ability to process 
commercial vehicle traffic. CBP officials reported that these staffing 
shortages, caused in part by budget constraints and the time needed to 
train and assign new CBP officers, challenged their ability to 
increase the numbers of officers at the ports of entry. Specifically, 
CBP officials reported that since fiscal year 2009, CBP has not 
received sufficient funding to hire the number of CBP officers that it 
requires at land ports of entry. In response to budgetary constraints, 
CBP headquarters officials reported working to identify alternative 
funding strategies as well as reviewing user fees to ensure they 
effectively support operations. For example, DHS's fiscal year 2014 
congressional budget request included a proposed increase for 1,877 
fee-funded full-time-equivalent positions in addition to a funding 
increase of approximately $210 million for 1,600 additional CBP 
officers. In response to staffing shortages related to the length of 
time it takes for new CBP officers to complete required training and 
to be available for duty at their assigned ports of entry, CBP 
headquarters officials reported considering the extent that new CBP 
officers have completed their training and are available for duty when 
allocating staff. They further reported actively working to adjust 
staff allocations across locations to better ensure that staffing 
levels are matched to areas of greatest need. For example, a senior 
OFO official reported prioritizing allocations to field offices with 
the highest discrepancy between current staffing levels and workload 
staffing model results when developing fiscal year 2012 annual 
staffing allocation. Finally, port officials at all six crossings we 
visited reported using overtime to mitigate the effect of any staffing 
shortages on ports' capacity to process commercial traffic. For 
example, port officials in El Paso said that using overtime pay was an 
effective and efficient solution to provide increased coverage to 
process commercial traffic during peak times on weekdays and on 
weekends.[Footnote 49] However, officials at the Otay Mesa port of 
entry noted that the availability of overtime funds has decreased 
because of budget constraints in recent years.[Footnote 50] 

In fiscal year 2013, CBP revised its process to allocate available CBP 
officers to its field offices, ports of entry and border crossings. 
However, CBP has not yet documented this process or its methodology, 
including the factors and underlying rationale considered in making 
staff allocation decisions. A senior official in CBP's Human Capital 
Division reported that CBP's most recent staff allocation process 
consisted of the following six steps: (1) OFO's Human Capital Division 
obtained the workload staffing model's findings to determine the 
number of officers ideally needed to meet the expected workload; (2) 
Human Capital Division staff conducted a "gap analysis" by comparing 
the model's findings to current staff levels to identify the locations 
with the greatest gap between current and the staff levels identified 
by the workload staffing model; (3) Human Capital Division staff 
drafted a proposed staff allocation that realigned staff to those 
field offices with the greatest gap; (4) OFO leadership made 
adjustments to the proposal based on institutional priorities 
including mission, priorities, and threats before approving the 
allocation; (5) on receiving approval from leadership, OFO staff 
communicated the authorized staffing levels to each field office; and 
(6) the field offices then allocated their authorized staff to the 
individual ports of entry under their purview. However, this official 
explained that this process is not documented and there is no guidance 
clearly defining this methodology, the factors considered, or the 
rationale for making staff allocation decisions. 

OFO Human Capital officials acknowledged the need to document this 
process and stated that they had not yet done so because, 
historically, such decisions were made informally and the current, 
more formalized process is still evolving. In addition, these 
officials noted that the last fiscal year was the first time OFO used 
the process described above and they planned to make further changes 
to the process within the next 2 fiscal years. 

Best practices for strategic workforce planning identified by GAO 
emphasize the importance of ensuring that the methodology underlying 
staffing decisions is well documented.[Footnote 51] Standards for 
Internal Control in the Federal Government also calls for clear 
documentation of policies and procedures that are readily available 
for examination.[Footnote 52] These standards state that such control 
activities are an integral part of an entity's accountability for 
stewardship of government resources and achieving effective results. 
Without documented policies and procedures including its rationale and 
factors considered in allocating staff, OFO's staff allocation process 
lacks transparency and is therefore difficult for CBP officials or 
others to review and validate. As a result, CBP and its stakeholders 
do not have reasonable assurance that its staffing processes most 
effectively and efficiently allocate scarce resources to fulfill 
mission needs across ports. 

CBP Performance Measures Do Not Reflect Progress in Achieving Trade 
Facilitation Goals: 

In fiscal year 2013, CBP identified 28 performance measures to assess 
and report on progress toward CBP's security and trade facilitation 
goals.[Footnote 53] Nine measures were selected by DHS as Government 
Performance and Results Act (GPRA) measures (these are also called 
strategic measures within the department); 15 management measures are 
used to inform agency decisions on program priorities and resource 
allocation, and to monitor progress and performance; and 4 operational 
measures are maintained by OFO to capture former GPRA measures that 
OFO continues to use internally.[Footnote 54] (See appendix IV for a 
list of CBP's fiscal year 2013 performance measures.) 

Two of these 28 performance measures address the level of 
participation in CBP's trade facilitation programs but none gauge the 
impact of CBP's trade facilitation efforts. Of the 28 measures, 26 are 
focused on security, enforcement, and compliance with trade laws, and 
2 are focused on the agency's trade facilitation goals. These 2 
measures include (1) the percent of cargo by value imported to the 
United States by participants in CBP trade partnership programs, and 
(2) the percent increase in travelers to the United States enrolled in 
a Trusted Traveler program.[Footnote 55] These 2 measures can serve as 
indicators of the level of participation in CBP trade facilitation 
programs, such as FAST, and thus are important for CBP to track, but 
they do not provide information on whether these programs are 
facilitating trade because they do not measure desired outcomes for 
the programs.[Footnote 56] OMB defines outcome as an event or 
condition that is of direct importance to the intended beneficiaries 
or the public, such as facilitated trade.[Footnote 57] DHS's 
Quadrennial Homeland Security Review Report stated that DHS would 
improve measurement of desired mission outcomes and the contribution 
of programs, activities, and resources to them. OFO and OA officials 
stated that CBP's existing performance measures imply that trade will 
be facilitated through increased participation in trade partnership 
programs rather than by directly measuring the desired outcomes. More 
specifically, OFO and OA officials stated that the measure percent of 
cargo by value imported to the United States by participants in CBP 
trade partnership programs implies that trade will be facilitated 
through participation in the programs, rather than directly measuring 
the desired outcomes of shorter wait times, for example. Similarly, 
OFO and OA officials told us that the measure percent increase in 
travelers to the United States enrolled in a Trusted Traveler program 
is not intended to capture the benefits to the program participants or 
trade facilitation, but, rather, is primarily an internal program 
measure that captures progress toward CBP's goal of growing enrollment 
in Trusted Traveler programs, including FAST. 

DHS and CBP officials stated that they have not developed more 
performance measures for trade facilitation primarily because key 
stakeholders, including DHS leadership and Congress, have not pushed 
for this, and trade facilitation measures are difficult to develop. 
DHS and CBP officials reported that they have more performance 
measures focused on security and enforcement because these have been 
more of a focus for stakeholders than trade facilitation. In addition, 
CBP officials report that they have not created outcome-oriented 
measures for trade facilitation because the results of their trade 
facilitation efforts are difficult to capture in one or two measures. 
OFO and OA officials told us that it can be hard to articulate trade 
facilitation to external stakeholders because trade facilitation means 
different things to different stakeholders, each with its own 
interests. However, these same concerns could apply to outcome-
oriented measures for CBP's security and enforcement efforts, and CBP 
has developed an outcome-oriented measure in that area--the land 
border interdiction rate for major violations. OFO and OA officials 
told us that this measure is the single best outcome measure for 
security, though they note that it is limited to passenger vehicles. 
[Footnote 58] In addition, OMB guidance states that proxy measures 
that are closely tied to the desired outcome can be used to indirectly 
measure program outcomes when programs are difficult to measure 
because data are not available.[Footnote 59] Potential outcome-
oriented measures or proxy measures for trade facilitation could 
include, for example, measures to determine the extent to which CBP 
trusted shipper programs have met their goal, such as the percentage 
of time FAST traffic waits a certain percentage less time than regular 
commercial traffic or the ratio of FAST to non-FAST referrals to 
secondary inspection. 

In the absence of outcome-oriented or proxy measures, CBP's ability to 
identify and publicly report the impact of the agency's trade 
facilitation programs is limited. OFO and OA officials reported that 
as a result of not having more outcome-oriented measures for trade 
facilitation, the agency is less prepared to identify and report the 
positive impact of its trade facilitation efforts to the public, and 
industry representatives we met with noted a lack of information on 
the impact of CBP's trade facilitation efforts. CBP officials at 
headquarters and in the field have stated that participation in the 
FAST program has resulted in shorter wait times for program 
participants, but Border Trade Alliance officials and industry 
representatives at two of the roundtables we held raised concerns that 
FAST program participants were not receiving these benefits and were 
unclear about the impact of this particular trade facilitation program. 

OMB and our guidance recommend the use of outcome-oriented performance 
measures to promote accountability for results. Our guidance states 
that leading organizations promote accountability by establishing 
results-oriented outcome goals and corresponding measures by which to 
gauge progress.[Footnote 60] This guidance further states that 
measuring performance allows organizations to track the progress they 
are making toward their goals and gives managers critical information 
on which to base decisions for improving their progress. More 
specifically, we identified establishing performance goals and 
measures to better translate activities into results as a useful 
practice to enhance performance management and measurement processes, 
and we have previously issued guidance that agencies should identify 
and use outcome goals wherever possible to reflect the results of 
their activities.[Footnote 61] In addition, OMB guidance encourages 
the use of outcome measures because they are much more meaningful to 
the public.[Footnote 62] In the absence of meaningful outcome-oriented 
performance measures, or proxy measures, for trade facilitation--such 
as measures capturing whether FAST participants are receiving their 
intended benefits of quicker processing time and fewer inspections--it 
is difficult for CBP, decision makers, and other stakeholders to gauge 
CBP progress in achieving the agency's stated trade facilitation goals. 

Conclusions: 

Trade between Mexico and the United States is important to the United 
States' economic health, and the value of goods imported into the U.S. 
from Mexico is on the rise. The length of time commercial vehicles 
wait in line at the border affects this trade activity. However, CBP's 
current wait time data are unreliable, limiting the extent to which 
CBP can use wait time data across border crossings to inform 
management decisions about infrastructure investment and staffing 
allocation and industry stakeholders can rely on publicly reported 
data. Taking steps to help CBP port officials implement CBP's existing 
mechanisms for collecting wait time data, consistent with agency 
guidance, could improve data reliability and usefulness for these 
purposes. Moreover, assessing the feasibility of options for 
automating wait time data consistent with program management standards 
could help CBP consider ways to reduce port officials' current burden 
in manually collecting the data and provide CBP with more reliable and 
comprehensive data it can use to identify and address challenges to 
trade facilitation. 

CBP's ability to meet its mission goals--including both security and 
trade facilitation--are affected by its allocation of staff across the 
southwest border, among other things. In the absence of transparency 
about the methodology and process by which CBP allocates staff 
resources across ports of entry, it is difficult for CBP and others to 
evaluate whether existing staff have been allocated to most 
effectively address CBP's mission needs. Documenting CBP's staff 
allocation methodology in accordance with best practices for strategic 
workforce planning could help better position CBP to ensure that it is 
allocating its staff efficiently and effectively across ports of entry 
and border crossings. 

In addition, it is difficult for CBP or others to gauge the agency's 
progress in meeting its trade facilitation goal because CBP does not 
have outcome-oriented measures for its trade facilitation efforts. 
Developing outcome-oriented, or proxy, performance measures that 
capture the impact of CBP's trade facilitation efforts, consistent 
with OMB and our guidance, could help CBP officials, Congress, and 
other stakeholders better assess the effectiveness of CBP's trade 
facilitation programs in supporting the agency's overall mission and 
goals. 

Recommendations for Executive Action: 

We recommend that the Commissioner of CBP take four actions. 

To improve the usefulness of southwest border crossing wait time data 
for informing public and management decisions, the Commissioner of CBP 
should take the following two actions: 

* Identify and carry out steps that can be taken to help CBP port 
officials overcome challenges to consistent implementation of existing 
wait time estimation methodologies. Steps for ensuring consistent 
implementation of these methodologies could include, for example, 
implementing the fiscal year 2008 WHTI report recommendations to use 
closed-circuit television cameras to measure wait time in real time 
and provide a standardized measurement and validation tool. 

* In consultation with FHWA and state DOTs, assess the feasibility of 
replacing current methods of manually calculating wait times with 
automated methods, which could include assessing all of the associated 
costs and benefits, options for how the agency will use and publicly 
report the results of automated data collection, the potential trade-
offs associated with moving to this new system, and other factors such 
as those influencing the possible expansion of existing automation 
efforts to the 34 other locations that currently report wait times but 
have no automation projects under way. 

To better ensure that CBP's OFO's staffing processes are transparent 
and to help ensure CBP can demonstrate that these resource decisions 
have effectively addressed CBP's mission needs, we recommend that the 
Commissioner of CBP document the methodology and process OFO uses to 
allocate staff to land ports of entry on the southwest border, 
including the rationales and factors considered in making these 
decisions. 

To facilitate transparency and performance accountability for its 
trade facilitation programs and meeting CBP's goal of balancing its 
trade and security missions, we recommend that the Commissioner of CBP 
develop outcome-oriented performance measures or proxy measures to 
capture the impact of CBP's trade facilitation efforts, such as 
measures to determine the extent to which CBP trusted shipper programs 
have met their goals. 

Agency Comments and Our Evaluation: 

We provided a draft of this report to DHS, GSA, DOT, the Department of 
Commerce, and the Department of Health and Human Services for their 
review and comment. GSA, DOT, the Department of Commerce, and 
Department of Health and Human Services did not have any comments on 
the draft of the report. DHS provided written comments, which are 
summarized below and reproduced in full in appendix VII. In the 
written comments, DHS concurred with our four recommendations and 
discussed actions to address them. However, the actions DHS identified 
will not address the intent of one of these recommendations. DHS also 
provided technical comments, which we incorporated, as appropriate. 

DHS agreed with our first recommendation that CBP identify and carry 
out steps to help CBP port officials overcome challenges to consistent 
implementation of existing wait time estimation methodologies. In 
written comments, DHS officials explained that if funding is 
available, CBP has a goal to automate the estimation and reporting of 
border wait times. To this end, they plan to establish an internal and 
external stakeholder group and identify the best candidate 
technologies to pilot. These steps will help further CBP's longer-term 
plans to automate wait time data collection, but do not address the 
intent of our recommendation that CBP take steps to help port 
officials more consistently implement existing manual wait time 
estimation methodologies. 

DHS agreed with our second recommendation that CBP assess the 
feasibility of replacing current methods of manually calculating wait 
times with automated methods. In commenting on a draft of this report, 
DHS officials noted that CBP has taken some steps to assess options 
for automating wait time data collection at northern and southern land 
border crossings and provided us with supplemental documents that 
included rough cost estimates for piloting, deploying, and maintaining 
automation technology. Based on this information, DHS requested that 
we consider this recommendation closed. While DHS has taken positive 
initial steps to address this recommendation, DHS should complete 
additional feasibility analysis to fully address the intent of our 
recommendation and better position the agency to decide whether and 
how to automate data collection. For example, DHS written comments 
stated that the feasibility of financing, funding, and operating 
automation technology is "reduced." More detailed and comprehensive 
cost analysis--such as estimating and comparing the costs of different 
technology solutions and analyzing potential funding sources--could 
help CBP assess the feasibility of wait time automation. In addition, 
DHS officials noted in their written comments that CBP has not yet 
identified the best technologies to pilot. Determining the best 
technology, if any, for use at each border crossing could influence 
the overall feasibility of planned automation across southwest border 
land ports of entry. 

With regard to our third recommendation that CBP document the 
methodology and process OFO uses to allocate staff to land ports of 
entry, DHS agreed and stated that CBP will develop and document a 
standardized process for allocating CBP officers that includes 
assumptions, factors, and concerns to guide the decision-making 
process. If implemented effectively, these actions should meet the 
intent of our recommendation. 

With regard to our fourth recommendation that CBP develop outcome-
oriented performance measures or proxy measures to capture the impact 
of CBP's trade facilitation efforts, DHS concurred and stated that 
they plan to create a team of subject matter experts from OFO trade-
related programs to identify at least two outcome measures or 
acceptable proxy measures for trade facilitation. They also noted 
plans to collaborate with private sector entities in order to identify 
metrics of greatest concern. If implemented effectively, these actions 
should meet the intent of our recommendation. 

We are sending copies of this report to the Departments of Homeland 
Security, Commerce, Transportation, and Health and Human Services; and 
the General Services Administration. The report is also available at 
no charge on the GAO website at [hyperlink, http://www.gao.gov]. 

If you or your staff have any questions about this report, please 
contact me at (202) 512-8777, or at GamblerR@gao.gov. Contact points 
for our Office of Congressional Relations and Public Affairs may be 
found on the last page of this report. GAO staff who made major 
contributions to this report are listed in appendix VIII. 

Sincerely yours, 

Signed by: 

Rebecca Gambler: 
Director: 
Homeland Security and Justice Issues: 

[End of section] 

Appendix I: Results of Studies on the Economic Impact of Wait Times on 
Cross-Border Commerce: 

To determine what is known about the economic impact of wait time on 
cross-border commerce, we identified and analyzed relevant studies. 
[Footnote 63] We searched academic, government, and other literature 
published from January 1, 2000, to June 30, 2012, to capture a wide 
array of recently published literature, and asked all relevant 
interviewees--including officials with the Department of Homeland 
Security's (DHS) U.S. Customs and Border Protection (CBP), Department 
of Commerce, trade associations, private industry, and academics--
whether they were aware of any such studies.[Footnote 64] We reviewed 
over 100 identified studies and narrowed our focus to the 6 studies 
that determined an economic impact of commercial vehicle wait times on 
the southwest border. We interviewed officials at the organizations 
that sponsored each of the qualifying studies to better understand the 
methodologies and limitations. We then analyzed the studies by 
comparing their methodologies with best practices for economic impact 
studies, including cost-benefit criteria in Office of Management and 
the Budget (OMB) Circular A-94 and comparing and contrasting the 
studies' scopes, methodologies, and findings.[Footnote 65] 

CBP Study Estimated the Effect of Additional Staff at Ports of Entry 
on Wait Times and the U.S. Economy: 

An April 2013 CBP-commissioned study found that reduced waits at 
select border crossings would result in benefits to the U.S. economy 
in terms of increased gross domestic product (GDP) and jobs.[Footnote 
66] This study, conducted by the National Center for Risk and Economic 
Analysis of Terrorism, estimates the benefit of adding one CBP officer 
to select border land and air border crossings--assuming these added 
staff would each open one additional primary inspection lane--in terms 
of reduced waits and resulting benefits to the U.S. economy. The study 
found, for example, that at seven of the biggest southwest border 
commercial vehicle crossings, having one additional staff member open 
one additional primary inspection lane during the 8 most congested 
hours of the day would result in wait time reductions ranging from 1.5 
minutes to 7.2 minutes for commercial vehicle traffic during those 
hours. The study then estimated that over the course of a year, these 
wait time reductions for commercial vehicles at these seven crossings 
would lead to direct economic benefits of $915,000 in GDP (in 2011 
dollars) and 9.3 additional jobs.[Footnote 67] CBP officials report 
that they plan to use the results of this study to demonstrate the 
benefit of adding CBP officers. These officials report that CBP has 
typically demonstrated its benefit in terms of number of seizures and 
arrests, for example, but this study will permit CBP to show an 
officer's trickledown effect on the U.S. economy. 

However, we identified three limitations to consider regarding the 
reported economic benefits. First, this study estimated the benefits 
of this change but not the costs. CBP officials state that the study 
was not intended to be a cost-benefit analysis and noted that the 
types of costs that would have to be considered in a cost-benefit 
analysis include staff salaries, inspection booth and lane 
maintenance, and equipment. Second, the study assumes that one 
additional primary processing lane is available to be opened during 
the busiest 8 hours of the day. However, CBP officials report that at 
some crossings they already open all primary inspection lanes during 
peak hours. Therefore, this assumption is unrealistic or would require 
CBP investment in additional primary inspection lanes. Third, the 
study used CBP's reported wait time data for fiscal year 2012, which, 
as described earlier in this report, we determined are not 
sufficiently reliable for analysis across crossings, among other 
things.[Footnote 68] Officials who conducted this study told us that 
they did not test the reliability of CBP's wait time data but found 
the basic data pattern plausible and therefore determined that the 
data were sufficiently reliable for their analysis. 

Other Commissioned Studies Reported That Wait Times Directly Affect 
the U.S. Economy, Resulting in Lost Revenue and Jobs: 

Five other studies, one of which was commissioned by DHS, have 
quantified the effects of commercial vehicle wait times on cross-
border commerce and also found evidence of lost revenue and jobs. The 
studies' findings are not comparable because of their differing scopes 
and methodologies, but they estimate direct impacts ranging from $452 
million in the San Diego area to $1.9 billion across five cities with 
major border crossings. All five studies have limitations that may 
have led to an overstatement of the economic impacts of wait times. In 
particular, four of these studies used economic multipliers to 
quantify the effect of wait time delays on the U.S. economy. As stated 
in OMB Circular A-94, these secondary effects should not be used when 
measuring social benefits or costs. Rather, the reported effects 
should be limited to direct effects only. Therefore, we included only 
the direct impacts in our summary of these studies. The five studies' 
findings and limitations are summarized in table 2. 

Table 2: Studies of the Economic Impact of Commercial Vehicle Wait 
Times on the Southwest Border: 

Study name: Economic Impacts of Wait Times at the San Diego-Baja 
California Border, Final Report[A]; 
Date published; January 19, 2006; 
Commissioned by: San Diego Association of Governments; California 
Department of Transportation, District 11; 
Commercial vehicle border crossings included in study: Otay Mesa and 
Tecate crossings at the border of San Diego County and the Mexican 
state of Baja California; 
Period studied: 2005; 
Wait time data used: A sample of Otay Mesa wait time data collected by 
Batelle for the Department of Transportation's Federal Highway 
Administration in July 2001[F]; 
Findings of direct effects: In 2005, delays in freight movement 
resulted in a total direct loss of $452 million in output, $99 million 
in labor income losses, and 2,117 jobs lost; 
Study limitations: Model included multiplier effects which, per the 
Office of Management and Budget’s Circular A-94, should not be 
included in the cost-benefit analysis. Therefore, we included only the 
direct effects in our summary. Model calculates the economic impact of 
the full length of the wait time, implying that the alternative is a 
wait of zero minutes. This alternative is an implausible scenario 
since some wait time and associated economic loss will always exist. 
It is not clear what the optimal level of wait time is, but if the 
optimal wait time were 20 minutes, for example, then economic losses 
should be estimated based on the difference between the estimated wait 
time and 20 minutes rather than on the full wait time. 

Study name: Improving Economic Outcomes by Reducing Border Delays: 
Facilitating the Vital Flow of Commercial Traffic Across the U.S.-
Mexico Border[B]; 
Date published; Never officially published, but March 2008 version 
released; 
Commissioned by: Department of Commerce’s International Trade 
Administration; 
Commercial vehicle border crossings included in study: Crossings at: 
* Laredo, Texas (World Trade Bridge and Columbia Solidarity Bridge); 
* El Paso, Texas (Bridge of the Americas and Ysleta); 
* San Diego, California (Otay Mesa); 
* Hidalgo, Texas (Pharr Reynosa International Bridge); 
* Nogales, Arizona (Mariposa); 
Period studied: 2008; 
Wait time data used: Original wait time data collected using high-
resolution cameras.[G] CBP’s historical wait time data were used to
annualize and extrapolate the observed wait times.[H] Total wait time 
was defined as the time elapsed from entering the line in Mexico 
leading to Mexican inspection through exit from U.S. inspection 
facilities, including any U.S. state-conducted inspections. The 
authors note that this represents an expanded definition of wait time; 
Findings of direct effects: In 2008, commercial vehicle wait times at 
these five crossings resulted in $1.9 billion in direct economic loss, 
4,939 jobs, and a labor income loss of $322 million; 
Study limitations: Model included multiplier effects which, per the 
Office of Management and Budget’s Circular A-94, should not be 
included in the cost-benefit analysis. Therefore, we included only the 
direct effects in our summary. Model calculates the economic impact of 
the full length of the wait time, implying that the alternative is a 
wait of zero minutes. This alternative is an implausible scenario 
since some wait time and associated economic loss will always exist. 
It is not clear what the optimal level of wait time is, but if the 
optimal wait time were 20 minutes, for example, then economic losses 
should be estimated based on the difference between the estimated wait 
time and 20 minutes rather than on the full wait time. 

Study name: Goods Movement Border Crossing Study and Analysis[C]; 
Date published: June 6, 2012; 
Commissioned by: Southern California Association of Governments; 
Commercial vehicle border crossings included in study: Calexico East in
Imperial County, California; 
Period studied: 2011; 
Wait time data used: Original wait time data collected using high-
resolution cameras[G]; 
Findings of direct effects: In 2011, delays in both northbound and
southbound commercial vehicle traffic at the Calexico East border 
crossing resulted in economic losses of $49 million and 334 jobs in 
Imperial County, California, and losses of $98 million and 1,000 jobs 
in the state of California; 
Study limitations: Model included multiplier effects which, per the 
Office of Management and Budget’s Circular A-94, should not be 
included in the cost-benefit analysis. Therefore, we included only the 
direct effects in our summary. Model calculates the economic impact of 
the full length of the wait time, implying that the alternative is a 
wait of zero minutes. This alternative is an implausible scenario 
since some wait time and associated economic loss will always exist. 
It is not clear what the optimal level of wait time is, but if the 
optimal wait time were 20 minutes, for example, then economic losses 
should be estimated based on the difference between the estimated wait 
time and 20 minutes rather than on the full wait time. 

Study name: Economic Benefits of Expanding the Border-Crossing for 
Commercial Vehicles at the Mariposa Crossing in Nogales, Arizona[D]: 
Date published: June 2007; 
Commissioned by: U.S. Department of Homeland Security, Private Sector 
Office; 
Commercial vehicle border crossings included in study: Mariposa 
Crossing in Nogales, Arizona; 
Period studied: 2003-2006; 
Wait time data used: CBP’s historical wait time data[H] supplemented 
with interviews with local businesses and a field study of wait times 
and traffic flows at Mariposa; 
Findings of direct effects: A 50 percent reduction in wait time for 
commercial vehicles is expected to result in a direct increase in 
output of $2.9 million and create 25 jobs per year; 
Study limitations: Model included multiplier effects that, per the 
Office of Management and Budget’s Circular A-94, should not be 
included in the cost-benefit analysis. Therefore, we included only the
direct effects in our summary; 

Study name: El Paso Regional Ports of Entry Operations Plan[E]; 
Date published: June 2011; 
Commissioned by: Texas Department of Transportation; 
Commercial vehicle border crossings included in study: Bridge of the
Americas and Ysleta in El Paso, Texas and Santa Teresa in Santa 
Teresa, New Mexico;
Period studied: 2010-2035 (period forecast); 
Wait time data used: CBP wait time data for April 24, 2010, was 
modeled and forecast through 2035; 
Findings of direct effects: In 2010 the regional economy lost $90 
million and 2,551 jobs. Assuming no changes in current infrastructure or
operations (no-build scenario), by 2035, waits are estimated to reach
11 hours, which would contract the regional economy by $54 billion and
cause a net loss of 857,000 jobs; 
Study limitations: For 2010, the model calculates the economic impact 
of the full length of the wait time, implying that the alternative is a
wait of zero minutes. This alternative is an implausible scenario since
some wait time and associated economic loss will always exist. It is 
not clear what the optimal level of wait time is, but if the optimal 
wait time were 20 minutes, for example, then economic losses should be
estimated based on the difference between the estimated wait time and 20
minutes rather than on the full wait time. The economic impact for the 
period 2011 through 2035 is calculated using the 2010 wait time as a 
baseline. Study uses CBP data that we found not reliable for the 
purposes of this study.[H] Study calibrates wait time data based on 1 
day of high traffic volume. Forecast 11-hour wait in 2035 does not 
take into account travelers’ sensitivity to wait time with respect
to the value or purpose of their trip. 

Source: GAO analysis of published studies. 

[A] HDR/HLB Decision Economics Inc., Economic Impacts of Wait Times at 
the San Diego-Baja California Border, Final Report, a report prepared 
at the request of the San Diego Association of Governments and 
California Department of Transportation, District 11, January 19, 2006. 

[B] Accenture, Improving Economic Outcomes by Reducing Border Delays: 
Facilitating the Vital Flow of Commercial Traffic across the U.S.-
Mexico Border (Draft), a study prepared for the Department of 
Commerce's International Trade, March 2008. Department of Commerce 
officials told us that the study was not given interagency clearance 
so was not published but, rather, was made public in response to a 
subsequent Freedom of Information Act request. 

[C] HDR Decision Economics, Goods Movement Border Crossing Study and 
Analysis (Final Report), a report prepared for the Southern California 
Association of Government, June 6, 2012. 

[D] RTI International, Economic Benefits of Expanding the Border-
Crossing for Commercial Vehicles at the Mariposa Crossing in Nogales, 
Arizona (Final Report), a report prepared for the U.S. Department of 
Homeland Security, Private Sector Office, June 2007. 

[E] Cambridge Systematics, Inc., El Paso Regional Ports of Entry 
Operations Plan (Final Report), a report prepared for the Texas 
Department of Transportation, June 2011. 

[F] Battelle is a nonprofit research and development organization that 
focuses on science and technology research for the national security, 
health and life sciences, and energy and environmental industries. The 
wait time data it collected for the Department of Transportation's 
Federal Highway Administration are referenced in Evaluation of Travel 
Time Methods to Support Mobility Performance Monitoring -Otay Mesa, 
Office of Freight Management and Operations, Federal Highway 
Administration, April 2002. 

[G] High-resolution cameras were used to record photographs of the 
trucks' license plates at various points along the crossing route. 
These photographs were then matched to identify crossing times per 
vehicle. 

[H] As described previously in this report, we reviewed CBP's wait 
time data and determined that the data were not reliable for some 
purposes such as comparison across border crossings. 

[End of table] 

[End of section] 

Appendix II: Objectives, Scope, and Methodology: 

This report addresses the following questions: 

* To what extent are CBP wait time data reliable for public reporting 
and informing CBP decisions on staffing and infrastructure investments? 

* To what extent has CBP identified infrastructure and staffing needed 
to process current commercial traffic volume at southwest border 
crossings with high traffic volume? 

* To what extent do CBP performance measures address progress toward 
its goal of facilitating trade? 

This report also presents information on the results of studies that 
have quantified the economic impact of commercial vehicle wait times 
on cross-border commerce. This information, including the methodology 
used to identify these studies, is presented in appendix I. 

To inform our analysis of the first and second objectives, we visited 
six crossings at four land ports of entry: Bridge of the Americas and 
Ysleta at El Paso, Texas; World Trade Bridge and Columbia Solidarity 
Bridge at Laredo, Texas; Mariposa at Nogales, Arizona; and Otay Mesa 
near San Diego, California. We selected these crossings based on their 
commercial traffic volume, and geographic diversity, and to include 
representation of crossings with a mix of recent or ongoing 
infrastructure modernization projects. At each location, we 
interviewed CBP management, toured the facility, and convened a 
roundtable of local industry representatives and local government 
officials. To obtain a range of perspectives on commercial vehicle 
traffic at southwest border crossings, we met with representatives of 
21 companies and associations (who were identified to us as 
knowledgeable stakeholders) representing industries that rely on cross-
border commerce including customs brokers, trucking companies, and 
distributors), as well as bridge directors and representatives of four 
local government entities (the Mayors of El Paso and San Diego, the 
Laredo City Manager, and representatives of the San Diego Association 
of Governments) at all four cities we visited or by teleconference. 
[Footnote 69] Because we focused on four land ports of entry with six 
commercial vehicle crossings, our findings are not generalizable to 
the entire southwest border. However, the ports we visited accounted 
for, in total, approximately 70 percent of the commercial vehicle 
crossings into the United States from Mexico in fiscal years 2008 
through July 2012. Over the course of our work, we also interviewed 
officials from agencies involved in securing the border and 
facilitating trade at land ports of entry, including officials from 
CBP's Office of Administration and Office of Field Operations, the 
General Services Administration (GSA), the Department of 
Transportation's (DOT) Federal Highway Administration and Federal 
Motor Carrier Safety Administration, the Department of Commerce 
(Commerce), the Department of Health and Human Service's Food and Drug 
Administration, and the Department of State. We also interviewed other 
stakeholders, including officials from the Mexican Foreign Ministry, 
academics, and representatives of national trade associations, 
including the American Trucking Associations and the Border Trade 
Alliance, to obtain a broader range of perspectives on commercial 
vehicle traffic at southwest border crossings.[Footnote 70] 

To address the first objective, we reviewed and analyzed CBP's 
policies and guidance for calculating and reporting wait times to 
determine the source of these data and the agency's control over these 
data. We interviewed CBP headquarters officials about the wait time 
data, including data quality, data entry protocols, quality assurance 
procedures, and any steps taken to improve the reliability of these 
data. We also interviewed officials at the six crossings we visited 
about how they collect and report wait time data. We reviewed CBP 
documents evaluating the quality of CBP's wait time data on the 
southwest border, including a fiscal year 2008 CBP Commercial Wait 
Times Analysis Report.[Footnote 71] We compared documentary and 
testimonial evidence of how wait times are currently being calculated 
by officials at land ports of entry on the southwest border against 
CBP policies and guidance to identify any discrepancies. We reviewed 
CBP's data and reports on wait times for the six crossings for fiscal 
year 2012. In addition, to obtain non-CBP perspectives on CBP's 
methods for calculating wait times and the quality and usefulness of 
CBP's wait time data, we interviewed DOT officials, local officials, 
industry groups, and a Mexican official.[Footnote 72] We compared 
CBP's policies and procedures for collecting and maintaining wait 
times data with criteria in Standards for Internal Control in the 
Federal Government.[Footnote 73] According to the assessment, the 
usefulness of the wait time data is limited and the reliability of the 
data is not insufficient for certain purposes, such as for comparisons 
across ports. To determine how CBP officials use the agency's wait 
time data to inform management decisions, we analyzed CBP guidance, 
policy, and other documents as well as interviewed CBP officials from 
headquarters and the six crossings to determine the extent to which 
wait times are a factor in CBP staff allocation decisions and 
infrastructure investment requests and decisions. To determine the 
status of DOT's pilot projects to automate wait time data at the 
southwest border, we interviewed officials at DOT's Federal Highway 
Administration, Texas Department of Transportation, and Texas A&M 
University and reviewed documentary evidence they provided. We 
compared evidence of CBP's stated plans to automate wait times with 
criteria on standards for program management.[Footnote 74] 

To address the second objective, we reviewed and analyzed CBP and GSA 
assessments of land port of entry condition and capacity, such as 
CBP's Strategic Resource Assessments and GSA's BorderWizardTM reports. 
[Footnote 75] We also interviewed CBP and GSA officials about 
infrastructure needs at land border crossings and how these needs are 
identified and prioritized. We reviewed documentation of CBP's 
workload staffing model, which is used to determine staff needs at 
land ports of entry, and interviewed CBP officials about the agency's 
staff allocation policies and processes and compared these with 
criteria in our previous work on human capital management and 
Standards for Internal Control in the Federal Government.[Footnote 76] 
In addition, we conducted an analysis of CBP's hourly data on traffic 
volume and number of primary lanes open at the six selected crossings 
to determine the extent to which CBP has utilized primary lanes for 
commercial vehicle traffic from fiscal years 2008 through 2012. We 
selected this 5-year period to provide a sufficiently long time period 
for trend analysis. As our analysis focused on identifying trends in 
routine commercial vehicle traffic by crossing, we included both Free 
and Secure Trade (FAST) and non-FAST traffic volume and lanes, but 
excluded hazardous materials traffic.[Footnote 77] To ensure data 
reliability, we did not include any records on traffic volume or lanes 
open that fell outside CBP's reported hours of operation. In addition, 
within the reported hours of operation, we included the data in our 
analysis for any given hour if CBP provided records for both traffic 
volume and lanes open. We conducted this analysis for the six 
crossings we visited; thus our findings are not generalizable to the 
entire southwest border. However, these six crossings processed 
approximately 70 percent of commercial vehicle traffic coming into the 
United States from Mexico for fiscal year 2008 through July 2012. To 
assess the reliability of these data, we reviewed relevant 
documentation; interviewed knowledgeable agency officials; and 
electronically tested for missing data during hours of operation, 
outlier records outside of hours of operation, and obvious errors 
(such as data records showing traffic being processed when no lanes 
were reportedly open). We also reviewed related internal controls and 
traced a selection of data to source files. We determined that the 
data were sufficiently reliable for the purposes of our report. 

In addition, to address the second objective, we asked CBP officials 
at headquarters, field offices, and ports of entry about (1) the 
sufficiency of staffing levels and infrastructure capacity to process 
the current volume of commercial traffic at the six crossings we 
visited, (2) CBP assessment and consideration of any staffing or 
infrastructure gaps when making resource allocation decisions, (3) CBP 
actions and plans to address any of these gaps, and (4) any challenges 
to effectively responding to any gaps that CBP identified. We also 
discussed CBP processes for determining staff needs at land ports of 
entry and allocating staff to the ports of entry. We then compared 
CBP's staffing policies and processes with criteria in our previous 
work on human capital management and Standards for Internal Control in 
the Federal Government.[Footnote 78] In addition, we discussed CBP's 
workload staffing model and how it has been used to inform staffing 
processes with CBP officials responsible for the model. In addition, 
we interviewed relevant GSA, state, and local officials, as well as 
nongovernmental stakeholders regarding any coordinated efforts to 
identify, prioritize, and implement infrastructure improvements at 
land ports of entry on the southwest border. 

To address the third objective, we reviewed documentation of CBP's 
fiscal year 2013 performance goals, measures, and reports. We then 
assessed CBP's measures against criteria in OMB Circular No. A-11 and 
useful practices GAO previously identified to enhance performance 
management and measurement processes to determine the extent to which 
CBP's existing performance measures capture progress toward goals and 
incorporate successful practices.[Footnote 79] We also interviewed 
relevant DHS and CBP officials about CBP's current performance 
measures, the adequacy of these measures, their perspectives on the 
balance between the agency's security and trade facilitation goals, 
and the extent to which CBP uses its wait time data to measure 
progress. 

We also identified studies that quantified the economic impact of 
commercial vehicle wait times on cross-border commerce by searching 
literature and asking relevant interviewees whether they were aware of 
any such studies. We reviewed over 100 identified studies and analyzed 
the six studies that determined an economic impact of commercial 
vehicle wait times on the southwest border. A more detailed 
description of our methodology and the results of these studies are 
presented in appendix I. 

We conducted this performance audit from July 2012 to July 2013 in 
accordance with generally accepted government auditing standards. 
Those standards require that we plan and perform the audit to obtain 
sufficient, appropriate evidence to provide a reasonable basis for our 
findings and conclusions based on our audit objectives. We believe 
that the evidence obtained provides a reasonable basis for our 
findings and conclusions based on our audit objectives. 

[End of section] 

Appendix III: U.S. Customs and Border Protection's Capital Investment 
Planning Process: 

This appendix describes CBP's reported process for identifying and 
prioritizing its infrastructure investment needs at land ports of 
entry on the northern and southwestern land borders. 

According to CBP documents, CBP identifies and prioritizes the 
infrastructure needs of land ports of entry through a six-part process 
that culminates in a 5-year-plan.[Footnote 80] The Department of 
Homeland Security Appropriations Act for fiscal year 2009 required 
beginning in fiscal year 2010 and every year thereafter, that CBP's 
annual budget submission for construction include, in consultation 
with GSA, a detailed 5-year plan for all federal land port of entry 
projects with a yearly update of total projected future funding needs. 
[Footnote 81] This process, known as the capital investment plan 
(CIP), includes gathering data through Strategic Resource Assessments 
(SRA), scoring identified needs at each land port of entry using data 
and information gathered from the SRA, conducting a sensitivity 
analysis on the initial ranking of needs, assessing projects' 
feasibility and risk, using the information gathered from the previous 
steps in the process to develop and issue CBP's 5-year capital 
investment plan, and assessing the CIP process. Each step is described 
in further detail below. 

1. Strategic Resource Assessments: 

According to CBP, the first stage in the CIP is to conduct SRAs, which 
are infrastructure needs assessments intended to gather and present 
data to support the prioritization of CBP's facility projects on a 
national level. The SRA includes internal and external stakeholder 
input, workload and personnel forecasts, space capacity analyses, 
architectural evaluation of port facilities, and recommended options 
to meet current and future space needs. 

2. Capital Project Scoring: 

Once CBP has completed the SRAs, the agency scores the infrastructure 
needs of each land port of entry by the criticality of its need for 
modernization using the data collected by the SRA. This score is 
calculated by combining the data collected in the SRA with 60 distinct 
criteria within the predefined four categories (see table 3), adjusted 
to reflect the relative weight of each category. For example, factors 
CBP considers under the Personnel and Workload Growth category include 
current and projected commercial vehicle traffic volume as well as the 
current peak and projected number of inspections personnel over the 
next 10-year period. 

Table 3: Categories of Criteria Customs and Border Protection Uses to 
Prioritize Land Port of Entry Projects: 

Category: Mission and Operations; 
Weight (by percent): 35. 

Category: Security and Life Safety; 
Weight (by percent): 25. 

Category: Space and Site Deficiencies; 
Weight (by percent): 25. 

Category: Personnel and Workload Growth; 
Weight (by percent): 15. 

Source: U.S. Customs and Border Protection. 

[End of table] 

Table 4 summarizes the priority rank assigned to the SRA-identified 
infrastructure needs at land ports of entry on the southwest border 
that process commercial vehicle traffic. The crossings are listed 
below in order of their ranking relative to CBP's entire portfolio of 
land ports of entry on northern and southwestern borders, including 
facilities that process bus, commercial, passenger, pedestrian, and 
rail traffic. 

Table 4: Prioritization Rank of Infrastructure Needs at Commercial 
Southwest Border Crossings: 

Crossing and location: Tornillo: Fabens, Texas[A]; 
Overall rank: 14. 

Crossing and location: Bridge of the Americas: El Paso, Texas[B]; 
Overall rank: 15. 

Crossing and location: Roma, Texas; 
Overall rank: 22. 

Crossing and location: Douglas, Arizona; 
Overall rank: 31. 

Crossing and location: Mariposa: Nogales, Arizona[A, B]; 
Overall rank: 34. 

Crossing and location: Progreso, Texas; 
Overall rank: 35. 

Crossing and location: San Luis, Arizona[C]; 
Overall rank: 48. 

Crossing and location: Ysleta: El Paso, Texas[B, C]; 
Overall rank: 53. 

Crossing and location: Del Rio, Texas[C]; 
Overall rank: 61. 

Crossing and location: Los Tomates: Brownsville, Texas; 
Overall rank: 65. 

Crossing and location: Columbus, New Mexico; 
Overall rank: 66. 

Crossing and location: Otay Mesa, California[B, C]; 
Overall rank: 96. 

Crossing and location: Presidio, Texas; 
Overall rank: 102. 

Crossing and location: World Trade Bridge: Laredo, Texas[B, C]; 
Overall rank: 106. 

Crossing and location: Naco, Arizona; 
Overall rank: 109. 

Crossing and location: Santa Teresa, New Mexico[A]; 
Overall rank: 112. 

Crossing and location: Lukeville, Arizona; 
Overall rank: 116. 

Crossing and location: Sasabe, Arizona; 
Overall rank: 117. 

Crossing and location: Eagle Pass Bridge II: Eagle Pass, Texas[D]; 
Overall rank: 126. 

Crossing and location: Pharr, Texas; 
Overall rank: 129. 

Crossing and location: Colombia Solidarity Bridge: Laredo, Texas[B]; 
Overall rank: 132. 

Crossing and location: Los Indios, Texas; 
Overall rank: 134. 

Crossing and location: Starr-Camargo Bridge: Rio Grande City, Texas; 
Overall rank: 144. 

Crossing and location: Tecate, California; 
Overall rank: 150. 

Crossing and location: Calexico East, California; 
Overall rank: 151. 

Source: GAO analysis of CBP documents. 

Notes: Each crossing's rank is relative to all crossings on both 
borders regardless of the type of traffic processed at the facility. 

This list includes only ports of entry on the southwest border in 
existence at the time of CBP's completion of the SRA process: December 
5, 2005. As a result, crossings built to address needs identified in 
the SRA, such as constructing San Luis II to address needs identified 
at San Luis, are not included on this list. 

[A] Crossing where the General Services Administration (GSA) has an 
ongoing infrastructure project as of May 2013. 

[B] Crossing we selected for site visit. 

[C] Crossing where GSA completed an infrastructure project(s) in 
fiscal years 2008-2012. 

[D] GSA plans to undertake an infrastructure project at Eagle Pass II 
in fiscal year 2013. 

[End of table] 

3. Sensitivity Analysis: 

CBP applies a sensitivity analysis of the initial ranking to determine 
if the results should consider factors unaccounted for through the 
standard SRA process, such as any unique regional conditions; 
bilateral planning and international partner interests; or interests 
of other U.S. federal, state, or local agencies. According to CBP 
officials, recent examples of factors CBP has considered include the 
identification of new manufacturing developments immediately adjacent 
to an existing land port of entry facility that would increase the 
demand for commercial processing capacities, facility damage resulting 
from floods that occurred after the SRA was completed in 2006, and the 
development of new land port of entry facility proposals in the same 
transportation region as an existing facility. CBP officials report 
that this information helps CBP identify additional drivers, 
constraints, and legislative mandates that may change the critical 
needs ranking. 

4. Risk and Feasibility Assessments: 

In this phase, CBP coordinates with key project stakeholders such as 
GSA to evaluate the feasibility and risk associated with project 
implementation including environmental, cultural, and historic 
preservation requirements as well as land acquisition requirements. 
Additionally, according to senior CBP officials, CBP considers the 
likelihood of obtaining the necessary resources to fund the proposed 
project. 

5. 5-Year Capital Investment Plan: 

Once CBP has taken the previous steps, it uses the information and 
analyses to develop its capital investment plan, in coordination with 
GSA. CBP and GSA update the capital investment plan annually, taking 
into account any changes in DHS's mission and strategy, the changing 
conditions at land ports of entry, and any other factors discovered in 
the course of projects already under way. With each update, CBP 
identifies which projects are of highest priority. GSA then works with 
CBP to identify which projects may be considered for near-term design 
and construction funding, which require an initial or updated 
feasibility study, or which require further evaluation to account for 
issues such as environmental and local community concerns. 

6. Assessment of the CIP Methodology: 

In response to expected budget constraints and as a general 
revalidation of its existing planning cycle, according to CBP Office 
of Administration officials and CBP documents, CBP is revisiting the 
process it uses to develop the 5-year plan. Although the assessment is 
in development, CBP aims to better incorporate up-front stakeholder 
involvement, place additional emphasis on state and local government-
driven master planning fed by regional trend analyses, adopt a 
consistent and comprehensive communications approach, evaluate 
alternative funding mechanisms, assess broader programmatic needs, and 
target high-impact and lower-cost investments. 

[End of section] 

Appendix IV: Ongoing, Planned, or Completed Land Port of Entry 
Renovation Projects, Fiscal Years 2008 through 2012: 

The tables in this appendix summarize infrastructure improvement 
projects that CBP and GSA officials reported were completed from 
fiscal year 2008 through 2012 at southwest border land ports of entry 
that process commercial traffic as well as infrastructure improvement 
projects GSA and CBP reported to be ongoing or in planning or design 
phases as of May 2013.[Footnote 82] GSA's Federal Buildings Fund 
included $564 million for land port of entry infrastructure 
improvement projects in fiscal years 2008 through 2010 and none in 
fiscal years 2011 and 2012. In addition, the American Recovery and 
Reinvestment Act (ARRA) of 2009 allocated $300 million for the GSA-
owned land ports of entry that is being used to provide design or 
construction funds to seven new or ongoing capital projects.[Footnote 
83] CBP officials reported that the completed projects presented in 
table 4 cost a total of approximately $115 million and estimates that 
ongoing and planned projects to renovate these land ports of entry, 
presented in table 5, will cost approximately $370 million. 

Table 5 summarizes the five infrastructure improvement projects GSA 
completed at southwest border land ports of entry that process 
commercial traffic in the period of fiscal years 2008 through 2012. 
Three of these projects were at crossings we visited--World Trade 
Bridge in Laredo, Texas; Ysleta in El Paso, Texas; and Otay Mesa near 
San Diego, California. 

Table 5: Completed Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic, 
Fiscal Years 2008 through 2012: 

Project title: Del Rio; Land Port of Entry Modernization Project; 
Infrastructure improvement project description: This project was a 
complete port replacement and expansion; 
Location: Del Rio, Texas; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: GSA Federal Buildings Fund--$24 million; CBP 
Appropriations--$4.3 million; Total project cost: $28.3 million; 
Date of completion: June 2009. 

Project title: San Luis II Land Port of Entry Construction Project; 
Infrastructure improvement project description: This project 
constructed a new port, San Luis II. The project redirected commercial 
traffic from the San Luis I crossing to the new San Luis II crossing 
to improve commercial traffic flow and processing capacity; 
Location: San Luis II, Arizona; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: GSA Federal Buildings Fund--$42 million; CBP 
Appropriations--$7.6 million; 
Total project cost: $49.6 million; 
Date of completion: October 2010. 

Project title: Laredo III: World Trade Bridge Land Port of Entry 
Commercial Lane Expansion Project; 
Infrastructure improvement project description: The project added 
seven new commercial primary inspection lanes and a bypass lane to 
facilitate traffic flow and increase commercial processing capacity; 
Location: Laredo Bridge III: World Trade Bridge, Texas; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: City of Laredo funding--$7.5 million; GSA Repairs & 
Alterations Appropriations--$1.3 million, CBP Appropriations-$1.6 
million; 
Total project cost: $10.4 million; 
Date of completion: April 2011. 

Project title: Ysleta Commercial Lane Expansion Project; 
Infrastructure improvement project description: The project added two 
commercial primary inspection lanes to increase processing capacity 
and reconfigured the site to create direct access to the Texas 
Department of Transportation safety inspection facility; 
Location: Ysleta, Texas; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: GSA Federal Buildings Fund--$20.2 million; CBP 
Appropriations--$3.6 million; 
Total project cost: $23.8 million; 
Date of completion: May 2009. 

Project title: Otay Mesa Land Port of Entry Commercial Lane 
Realignment Projects; 
Infrastructure improvement project description: The project improved 
the curvature of the existing commercial lanes and added Free and 
Secure Trade (FAST) technology to booths to facilitate traffic flow 
and increase commercial processing capacity, improved commercial 
traffic flow, and increased processing capacity; 
Location: Otay Mesa, California; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: California Department of Transportation--$2.6 million; 
CBP Appropriations--$0.5 million; 
Total project cost: $3.1 million; 
Date of completion: December 2009. 

Project title: Total all projects fiscal years 2008 through 2012; 
Sources (both federal and nonfederal) and amounts of funding provided 
for the project: GSA appropriations: $87.5 million; CBP 
appropriations: $17.6 million; Non-federal sources: $10.1 million; 
Total project cost: $115.2 million. 

Source: GAO analysis of GSA and CBP documents and officials' 
statements. 

[End of table] 

Table 6 summarizes the three ongoing GSA infrastructure improvement 
projects at southwest border land ports of entry that process 
commercial traffic as of May 2013. 

Table 6: Ongoing Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic as 
of May 2013: 

Project title: Tornillo-Guadalupe Land Port of Entry Modernization 
Project; 
Infrastructure improvement project description: The project is to 
replace and expand the existing facility including adding two 
commercial lanes capacity to the currently passenger-only port; 
Location (specific border crossing affected): Tornillo: Guadalupe, 
Texas; 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: GSA Federal Buildings Fund--$95.9 million; 
CBP Appropriations--$14.3 million; 
Estimated total project cost: $79.6 million[A]; 
Expected date of completion: Summer 2013. 

Project title: Nogales West--Mariposa Land Port of Entry Modernization 
Project; 
Infrastructure improvement project description: This project is to 
replace and expand the existing facility, including major outbound 
infrastructure improvements and adding four commercial inspection 
lanes; 
Location (specific border crossing affected): Nogales West: Mariposa, 
Arizona; 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: GSA Federal Buildings Fund--$9.8 million 
(design), GSA ARRA--$182.7 million, CBP ARRA Savings--$10.5 
million,[B]; 
CBP Appropriations--$36.5 million; 
Estimated total project cost: $239.5 million; 
Expected date of completion: Fall 2014. 

Project title: Santa Teresa Land Port of Entry Lane Expansion Project; 
Infrastructure improvement project description: This project is to 
expand the facility, including an additional commercial processing 
lane; 
Location (specific border crossing affected): Santa Teresa, New Mexico; 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: ARRA Savings--$10 million; CBP Reimbursable 
Work Authorization--$1.3 million[C]; 
Estimated total project cost: $11.3 million; 
Expected date of completion: February 2013. 

Project total: 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: GSA appropriations: $105.7 million; ARRA: 
$203.2 million CBP appropriations: $50.8 million; CBP Reimbursable 
Work Authorization: $1.3 million; 
Estimated total project cost: $330.4 million. 

Source: GAO analysis of GSA and CBP documents and officials' 
statements. 

[A] According to GSA officials, Congress appropriated about $95.9 
million for the Tornillo-Guadalupe project, and the total project cost 
is expected to be $79.6 million or less. 

[B] These funds were derived from unused ARRA funds that were 
reprogrammed to other projects because of savings or changes to the 
original projects. 

[C] Reimbursable Work Authorizations are established to capture and 
bill the costs of altering, repairing, renovating, or providing 
services in space managed by GSA, over and above the basic operations 
financed through rent. 

[End of table] 

Table 7 summarizes the one planned infrastructure improvement project 
at a southwest border land port of entry that processes commercial 
traffic. 

Table 7: Planned Infrastructure Improvement Projects at Southwest 
Border Land Ports of Entry That Process Commercial Vehicle Traffic, as 
of May 2013: 

Project title: Eagle Pass II Commercial Lane Realignment Project; 
Infrastructure improvement project description: The project is to 
improve the curvature of the two existing commercial lanes to 
facilitate traffic flow and increase commercial processing capacity; 
Location (specific border crossing affected): Eagle Pass II, Texas; 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: City of Eagle Pass--$6.6 million, CBP 
Repairs & Alterations budget--$0.4 million; 
Estimated total project cost: $7 million; 
Expected start date: Summer to fall 2013. 

Project total: 
Sources (both federal and nonfederal) and amounts of funding to be 
provided for the project: $7 million; 
Estimated total project cost: $7 million. 

Source: GAO analysis of GSA and CBP documents and officials' 
statements. 

[End of table] 

[End of section] 

Appendix V: Average Hourly Traffic Volume and Average Hourly 
Percentage of Lanes Open Per Month, Fiscal Years 2008-2012: 

This appendix provides additional information on the average hourly 
traffic volume and average hourly percentage of lanes open per month 
at selected crossings, for fiscal years 2008 through 2012. Table 8 
describes, for each of six selected land border crossings on the 
southwest border that process commercial vehicle traffic, (1) the year 
the crossing was built and last renovated, and (2) the number of 
primary inspection lanes for commercial vehicles in fiscal years 2008 
through 2012. Figures 4 to 9 illustrate the layout of five of the six 
selected crossings and the primary inspection lanes of the remaining 
crossing for which CBP was not able to provide an aerial photo. Tables 
8 through 13 provide the average hourly traffic volume, per month and 
the average hourly percentage of lanes opened, per month, at each of 
six selected crossings that process commercial vehicle traffic on the 
southwest border for the period fiscal years 2008 through 
2012.[Footnote 84] Figures 10 through 15 graphically depict the 
average hourly traffic volume and average hourly percentage of lanes 
open per month for each of the six selected crossings. 

Table 8: Descriptions of Six Selected Crossings including Year Built 
and Renovated, and the Number of Available Commercial Lanes, Fiscal 
Years 2008 through 2012: 

Crossing name: Otay Mesa: San Diego, California; 
Year built/last renovation: 1984/2009; 
Number of lanes available: 
* 10 commercial lanes available from October 1, 2007, to September 30, 
2012. 

Crossing name: Mariposa: Nogales, Arizona; 
Year built/last renovation: 1976/2014[A]; 
Number of lanes available: 
* 4 commercial lanes available from October 1, 2007, to April 29, 2012; 
* 8 commercial lanes available from April 30, 2012, to September 30, 
2012. 

Crossing name: Bridge of the Americas: El Paso, Texas; 
Year built/last renovation: 1967/2003; 
Number of lanes available: 
* 6 commercial lanes available from October 1, 2007, to September 30, 
2012. 

Crossing name: Ysleta: El Paso, Texas; 
Year built/last renovation: 1991/2009; 
Number of lanes available: 
* 6 commercial lanes available from October 1, 2007, to October 20, 
2008; 
* 8 commercial lanes available from October 21, 2008, to September 30, 
2012. 

Crossing name: Columbia Solidarity: Laredo, Texas; 
Year built/last renovation: 1991/NA; 
Number of lanes available: 
* 8 commercial lanes available from October 1, 2007, to September 30, 
2012. 

Crossing name: World Trade Bridge: Laredo, Texas; 
Year built/last renovation: 2000/2011; 
Number of lanes available: 
* 8 commercial lanes available from October 1, 2007, to April 14, 2011; 
* 15 commercial lanes available from April 15, 2011, to September 30, 
2012. 

Source: GAO analysis of CBP data. 

[A] Mariposa is currently undergoing renovation. CBP officials report 
that these renovations are expected to be complete in fiscal year 2014. 

[End of table] 

Figure 4: The Otay Mesa Crossing near San Diego, California: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Figure 5: Commercial Vehicle Primary Inspection Lanes at the Mariposa 
Crossing in Nogales, Arizona: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Figure 6: The Bridge of the Americas Crossing in El Paso, Texas: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Figure 7: The Ysleta Crossing in El Paso, Texas: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Figure 8: The Columbia Solidarity Bridge Crossing in Laredo, Texas: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Figure 9: The World Trade Bridge Crossing in Laredo, Texas: 

[Refer to PDF for image: photograph] 

Source: CBP. 

[End of figure] 

Table 9: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Otay Mesa Crossing near San Diego, 
California, Fiscal Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 227; 
Average hourly lane utilization per month (in percent): 70. 

Month and year: November 2007; 
Average hourly traffic volume per month: 229; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: December 2007; 
Average hourly traffic volume per month: 209; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: January 2008; 
Average hourly traffic volume per month: 190; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: February 2008; 
Average hourly traffic volume per month: 214; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: March 2008; 
Average hourly traffic volume per month: 229; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: April 2008; 
Average hourly traffic volume per month: 237; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: May 2008; 
Average hourly traffic volume per month: 246; 
Average hourly lane utilization per month (in percent): 74. 

Month and year: June 2008; 
Average hourly traffic volume per month: 241; 
Average hourly lane utilization per month (in percent): 72. 

Month and year: July, 2008; 
Average hourly traffic volume per month: 242; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: August 2008; 
Average hourly traffic volume per month: 233; 
Average hourly lane utilization per month (in percent): 73. 

Month and year: September 2008; 
Average hourly traffic volume per month: 234; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: October 2008; 
Average hourly traffic volume per month: 229; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: November 2008; 
Average hourly traffic volume per month: 194; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: December 2008; 
Average hourly traffic volume per month: 178; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: January 2009; 
Average hourly traffic volume per month: 165; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: February 2009; 
Average hourly traffic volume per month: 168; 
Average hourly lane utilization per month (in percent): 67. 

Month and year: March 2009; 
Average hourly traffic volume per month: 171; 
Average hourly lane utilization per month (in percent): 67. 

Month and year: April 2009; 
Average hourly traffic volume per month: 187; 
Average hourly lane utilization per month (in percent): 72. 

Month and year: May 2009; 
Average hourly traffic volume per month: 191; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: June,2009; 
Average hourly traffic volume per month: 202; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: July 2009; 
Average hourly traffic volume per month: 197; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: August 2009; 
Average hourly traffic volume per month: 197; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: September 2009; 
Average hourly traffic volume per month: 209; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: October 2009; 
Average hourly traffic volume per month: 221; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: November 2009; 
Average hourly traffic volume per month: 214; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: December 2009; 
Average hourly traffic volume per month: 194; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: January 2010; 
Average hourly traffic volume per month: 174; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: February 2010; 
Average hourly traffic volume per month: 195; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: March 2010; 
Average hourly traffic volume per month: 213; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: April 2010; 
Average hourly traffic volume per month: 219; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: May 2010; 
Average hourly traffic volume per month: 217; 
Average hourly lane utilization per month (in percent): 82. 

Month and year: June 2010; 
Average hourly traffic volume per month: 223; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: July 2010; 
Average hourly traffic volume per month: 213; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: August 2010; 
Average hourly traffic volume per month: 212; 
Average hourly lane utilization per month (in percent): 82. 

Month and year: September 2010; 
Average hourly traffic volume per month: 219; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: October 2010; 
Average hourly traffic volume per month: 215; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: November 2010; 
Average hourly traffic volume per month: 220; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: December 2010; 
Average hourly traffic volume per month: 188; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: January 2011; 
Average hourly traffic volume per month: 185; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: February 2011; 
Average hourly traffic volume per month: 202; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: March 2011; 
Average hourly traffic volume per month: 210; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: April 2011; 
Average hourly traffic volume per month: 212; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: May 2011; 
Average hourly traffic volume per month: 208; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: June 2011; 
Average hourly traffic volume per month: 227; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: July 2011; 
Average hourly traffic volume per month: 216; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: August 2011; 
Average hourly traffic volume per month: 216; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: September 2011; 
Average hourly traffic volume per month: 220; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: October 2011; 
Average hourly traffic volume per month: 226; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: November 2011; 
Average hourly traffic volume per month: 224; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: December 2011; 
Average hourly traffic volume per month: 189; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: January 2012; 
Average hourly traffic volume per month: 197; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: February 2012; 
Average hourly traffic volume per month: 206; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: March 2012; 
Average hourly traffic volume per month: 224; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: April 2012; 
Average hourly traffic volume per month: 223; 
Average hourly lane utilization per month (in percent): 82. 

Month and year: May 2012; 
Average hourly traffic volume per month: 234; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: June 2012; 
Average hourly traffic volume per month: 232; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: July 2012; 
Average hourly traffic volume per month: 223; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: August 2012; 
Average hourly traffic volume per month: 230; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: September 2012; 
Average hourly traffic volume per month: 230; 
Average hourly lane utilization per month (in percent): 89. 

Source: GAO analysis of CBP data. 

[End of table] 

Table 10: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Mariposa Crossing in Nogales, Arizona, 
Fiscal Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 87; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: November 2007; 
Average hourly traffic volume per month: 114; 
Average hourly lane utilization per month (in percent): 64. 

Month and year: December 2007; 
Average hourly traffic volume per month: 123; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: January 2008; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: February 2008; 
Average hourly traffic volume per month: 146; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: March 2008; 
Average hourly traffic volume per month: 150; 
Average hourly lane utilization per month (in percent): 70. 

Month and year: April 2008; 
Average hourly traffic volume per month: 156; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: May 2008; 
Average hourly traffic volume per month: 166; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: June 2008; 
Average hourly traffic volume per month: 128; 
Average hourly lane utilization per month (in percent): 95. 

Month and year: July 2008; 
Average hourly traffic volume per month: 102; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: August 2008; 
Average hourly traffic volume per month: 102; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: September 2008; 
Average hourly traffic volume per month: 96; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: October 2008; 
Average hourly traffic volume per month: 119; 
Average hourly lane utilization per month (in percent): 48. 

Month and year: November 2008; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 56. 

Month and year: December 2008; 
Average hourly traffic volume per month: 123; 
Average hourly lane utilization per month (in percent): 59. 

Month and year: January 2009; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 73. 

Month and year: February 2009; 
Average hourly traffic volume per month: 133; 
Average hourly lane utilization per month (in percent): 67. 

Month and year: March 2009; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: April 2009; 
Average hourly traffic volume per month: 136; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: May 2009; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 70. 

Month and year: June 2009; 
Average hourly traffic volume per month: 128; 
Average hourly lane utilization per month (in percent): 66. 

Month and year: July 2009; 
Average hourly traffic volume per month: 91; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: August 2009; 
Average hourly traffic volume per month: 89; 
Average hourly lane utilization per month (in percent): 49. 

Month and year: September 2009; 
Average hourly traffic volume per month: 93; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: October 2009; 
Average hourly traffic volume per month: 119; 
Average hourly lane utilization per month (in percent): 52. 

Month and year: November 2009; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 60. 

Month and year: December 2009; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 73. 

Month and year: January 2010; 
Average hourly traffic volume per month: 151; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: February 2010; 
Average hourly traffic volume per month: 157; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: March 2010; 
Average hourly traffic volume per month: 161; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: April 2010; 
Average hourly traffic volume per month: 166; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: May 2010; 
Average hourly traffic volume per month: 174; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: June 2010; 
Average hourly traffic volume per month: 146; 
Average hourly lane utilization per month (in percent): 95. 

Month and year: July 2010; 
Average hourly traffic volume per month: 102; 
Average hourly lane utilization per month (in percent): 87. 

Month and year: August 2010; 
Average hourly traffic volume per month: 101; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: September 2010; 
Average hourly traffic volume per month: 100; 
Average hourly lane utilization per month (in percent): 65. 

Month and year: October 2010; 
Average hourly traffic volume per month: 118; 
Average hourly lane utilization per month (in percent): 66. 

Month and year: November 2010; 
Average hourly traffic volume per month: 135; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: December 2010; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: January 2011; 
Average hourly traffic volume per month: 150; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: February 2011; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: March 2011; 
Average hourly traffic volume per month: 134; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: April 2011; 
Average hourly traffic volume per month: 145; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: May 2011; 
Average hourly traffic volume per month: 168; 
Average hourly lane utilization per month (in percent): 92. 

Month and year: June 2011; 
Average hourly traffic volume per month: 139; 
Average hourly lane utilization per month (in percent): 82. 

Month and year: July 2011; 
Average hourly traffic volume per month: 103; 
Average hourly lane utilization per month (in percent): 57. 

Month and year: August, 2011; 
Average hourly traffic volume per month: 103; 
Average hourly lane utilization per month (in percent): 57. 

Month and year: September 2011; 
Average hourly traffic volume per month: 104; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: October 2011; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 61. 

Month and year: November 2011; 
Average hourly traffic volume per month: 134; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: December 2011; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 72. 

Month and year: January 2012; 
Average hourly traffic volume per month: 147; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: February 2012; 
Average hourly traffic volume per month: 151; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: March 2012; 
Average hourly traffic volume per month: 155; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: April 2012; 
Average hourly traffic volume per month: 159; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: May 2012; 
Average hourly traffic volume per month: 178; 
Average hourly lane utilization per month (in percent): 47. 

Month and year: June 2012; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 48. 

Month and year: July 2012; 
Average hourly traffic volume per month: 101; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: August 2012; 
Average hourly traffic volume per month: 103; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: September 2012; 
Average hourly traffic volume per month: 104; 
Average hourly lane utilization per month (in percent): 42. 

Source: GAO analysis of CBP data. 

[End of table] 

Table 11: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Bridge of the Americas Crossing in El Paso, 
Texas, Fiscal Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 164; 
Average hourly lane utilization per month (in percent): 87. 

Month and year: November 2007; 
Average hourly traffic volume per month: 164; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: December 2007; 
Average hourly traffic volume per month: 143; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: January 2008; 
Average hourly traffic volume per month: 153; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: February 2008; 
Average hourly traffic volume per month: 164; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: March 2008; 
Average hourly traffic volume per month: 161; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: April 2008; 
Average hourly traffic volume per month: 168; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: May 2008; 
Average hourly traffic volume per month: 168; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: June 2008; 
Average hourly traffic volume per month: 175; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: July 2008; 
Average hourly traffic volume per month: 163; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: August 2008; 
Average hourly traffic volume per month: 168; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: September 2008; 
Average hourly traffic volume per month: 154; 
Average hourly lane utilization per month (in percent): 92. 

Month and year: October 2008; 
Average hourly traffic volume per month: 154; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: November 2008; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: December 2008; 
Average hourly traffic volume per month: 120; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: January 2009; 
Average hourly traffic volume per month: 134; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: February 2009; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: March 2009; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: April 2009; 
Average hourly traffic volume per month: 118; 
Average hourly lane utilization per month (in percent): 75. 

Month and year: May 2009; 
Average hourly traffic volume per month: 114; 
Average hourly lane utilization per month (in percent): 73. 

Month and year: June 2009; 
Average hourly traffic volume per month: 117; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: July 2009; 
Average hourly traffic volume per month: 118; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: August 2009; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: September 2009; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: October 2009; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: November 2009; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: December 2009; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 82. 

Month and year: January 2010; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: February 2010; 
Average hourly traffic volume per month: 144; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: March 2010; 
Average hourly traffic volume per month: 139; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: April 2010; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: May 2010; 
Average hourly traffic volume per month: 66; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: June 2010; 
Average hourly traffic volume per month: 126; 
Average hourly lane utilization per month (in percent): 70. 

Month and year: July 2010; 
Average hourly traffic volume per month: 125; 
Average hourly lane utilization per month (in percent): 49. 

Month and year: August 2010; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 48. 

Month and year: September 2010; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 53. 

Month and year: October 2010; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: November 2010; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: December 2010; 
Average hourly traffic volume per month: 111; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: January 2011; 
Average hourly traffic volume per month: 120; 
Average hourly lane utilization per month (in percent): 60. 

Month and year: February 2011; 
Average hourly traffic volume per month: 117; 
Average hourly lane utilization per month (in percent): 65. 

Month and year: March 2011; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 66. 

Month and year: April 2011; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 68. 

Month and year: May 2011; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 72. 

Month and year: June 2011; 
Average hourly traffic volume per month: 133; 
Average hourly lane utilization per month (in percent): 72. 

Month and year: July 2011; 
Average hourly traffic volume per month: 125; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: August 2011; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: September 2011; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 75. 

Month and year: October 2011; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: November 2011; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 67. 

Month and year: December 2011; 
Average hourly traffic volume per month: 109; 
Average hourly lane utilization per month (in percent): 49. 

Month and year: January 2012; 
Average hourly traffic volume per month: 121; 
Average hourly lane utilization per month (in percent): 63. 

Month and year: February 2012; 
Average hourly traffic volume per month: 118; 
Average hourly lane utilization per month (in percent): 54. 

Month and year: March 2012; 
Average hourly traffic volume per month: 117; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: April 2012; 
Average hourly traffic volume per month: 117; 
Average hourly lane utilization per month (in percent): 52. 

Month and year: May 2012; 
Average hourly traffic volume per month: 116; 
Average hourly lane utilization per month (in percent): 52. 

Month and year: June 2012; 
Average hourly traffic volume per month: 116; 
Average hourly lane utilization per month (in percent): 74. 

Month and year: July 2012; 
Average hourly traffic volume per month: 113; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: August 2012; 
Average hourly traffic volume per month: 114; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: September 2012; 
Average hourly traffic volume per month: 111; 
Average hourly lane utilization per month (in percent): 72. 

Source: GAO analysis of CBP data. 

[End of table] 

Table 12: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Ysleta Crossing in El Paso, Texas, Fiscal 
Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 92. 

Month and year: November 2007; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: December 2007; 
Average hourly traffic volume per month: 119; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: January 2008; 
Average hourly traffic volume per month: 121; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: February 2008; 
Average hourly traffic volume per month: 135; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: March 2008; 
Average hourly traffic volume per month: 144; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: April 2008; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: May 2008; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 92. 

Month and year: June 2008; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 95. 

Month and year: July 2008; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 94. 

Month and year: August 2008; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 88. 

Month and year: September 2008; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: October 2008; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 81. 

Month and year: November 2008; 
Average hourly traffic volume per month: 84; 
Average hourly lane utilization per month (in percent): 50. 

Month and year: December 2008; 
Average hourly traffic volume per month: 71; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: January 2009; 
Average hourly traffic volume per month: 73; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: February 2009; 
Average hourly traffic volume per month: 73; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: March 2009; 
Average hourly traffic volume per month: 79; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: April, 2009; 
Average hourly traffic volume per month: 82; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: May 2009; 
Average hourly traffic volume per month: 83; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: June 2009; 
Average hourly traffic volume per month: 105; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: July 2009; 
Average hourly traffic volume per month: 102; 
Average hourly lane utilization per month (in percent): 54. 

Month and year: August 2009; 
Average hourly traffic volume per month: 110; 
Average hourly lane utilization per month (in percent): 56. 

Month and year: September 2009; 
Average hourly traffic volume per month: 118; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: October 2009; 
Average hourly traffic volume per month: 116; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: November 2009; 
Average hourly traffic volume per month: 115; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: December 2009; 
Average hourly traffic volume per month: 101; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: January 2010; 
Average hourly traffic volume per month: 103; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: February 2010; 
Average hourly traffic volume per month: 112; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: March 2010; 
Average hourly traffic volume per month: 117; 
Average hourly lane utilization per month (in percent): 57. 

Month and year: April 2010; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: May 2010; 
Average hourly traffic volume per month: 179; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: June 2010; 
Average hourly traffic volume per month: 141; 
Average hourly lane utilization per month (in percent): 59. 

Month and year: July 2010; 
Average hourly traffic volume per month: 121; 
Average hourly lane utilization per month (in percent): 33. 

Month and year: August 2010; 
Average hourly traffic volume per month: 124; 
Average hourly lane utilization per month (in percent): 35. 

Month and year: September 2010; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: October 2010; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: November 2010; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: December 2010; 
Average hourly traffic volume per month: 112; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: January 2011; 
Average hourly traffic volume per month: 120; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: February 2011; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: March 2011; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: April 2011; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: May 2011; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 43. 

Month and year: June 2011; 
Average hourly traffic volume per month: 131; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: July 2011; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 42. 

Month and year: August 2011; 
Average hourly traffic volume per month: 126; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: September 2011; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: October 2011; 
Average hourly traffic volume per month: 128; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: November 2011; 
Average hourly traffic volume per month: 123; 
Average hourly lane utilization per month (in percent): 35. 

Month and year: December 2011; 
Average hourly traffic volume per month: 104; 
Average hourly lane utilization per month (in percent): 29. 

Month and year: January 2012; 
Average hourly traffic volume per month: 123; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: February 2012; 
Average hourly traffic volume per month: 135; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: March 2012; 
Average hourly traffic volume per month: 135; 
Average hourly lane utilization per month (in percent): 27. 

Month and year: April 2012; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 35. 

Month and year: May 2012; 
Average hourly traffic volume per month: 141; 
Average hourly lane utilization per month (in percent): 35. 

Month and year: June 2012; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: July 2012; 
Average hourly traffic volume per month: 127; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: August 2012; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 48. 

Month and year: September 2012; 
Average hourly traffic volume per month: 139; 
Average hourly lane utilization per month (in percent): 46. 

Source: GAO analysis of CBP data. 

[End of table] 

Table 13: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Columbia Solidarity Bridge Crossing in 
Laredo, Texas, Fiscal Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 143; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: November 2007; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: December 2007; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 42. 

Month and year: January 2008; 
Average hourly traffic volume per month: 133; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: February 2008; 
Average hourly traffic volume per month: 148; 
Average hourly lane utilization per month (in percent): 44. 

Month and year: March 2008; 
Average hourly traffic volume per month: 143; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: April 2008; 
Average hourly traffic volume per month: 157; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: May 2008; 
Average hourly traffic volume per month: 145; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: June 2008; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 47. 

Month and year: July 2008; 
Average hourly traffic volume per month: 123; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: August 2008; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 47. 

Month and year: September 2008; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: October 2008; 
Average hourly traffic volume per month: 129; 
Average hourly lane utilization per month (in percent): 47. 

Month and year: November 2008; 
Average hourly traffic volume per month: 122; 
Average hourly lane utilization per month (in percent): 45. 

Month and year: December 2008; 
Average hourly traffic volume per month: 109; 
Average hourly lane utilization per month (in percent): 47. 

Month and year: January 2009; 
Average hourly traffic volume per month: 105; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: February 2009; 
Average hourly traffic volume per month: 110; 
Average hourly lane utilization per month (in percent): 46. 

Month and year: March 2009; 
Average hourly traffic volume per month: 102; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: April 2009; 
Average hourly traffic volume per month: 107; 
Average hourly lane utilization per month (in percent): 42. 

Month and year: May 2009; 
Average hourly traffic volume per month: 96; 
Average hourly lane utilization per month (in percent): 43. 

Month and year: June 2009; 
Average hourly traffic volume per month: 99; 
Average hourly lane utilization per month (in percent): 42. 

Month and year: July 2009; 
Average hourly traffic volume per month: 96; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: August 2009; 
Average hourly traffic volume per month: 98; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: September 2009; 
Average hourly traffic volume per month: 108; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: October 2009; 
Average hourly traffic volume per month: 108; 
Average hourly lane utilization per month (in percent): 41. 

Month and year: November 2009; 
Average hourly traffic volume per month: 114; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: December 2009; 
Average hourly traffic volume per month: 110; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: January 2010; 
Average hourly traffic volume per month: 119; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: February 2010; 
Average hourly traffic volume per month: 125; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: March 2010; 
Average hourly traffic volume per month: 134; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: April 2010; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: May 2010; 
Average hourly traffic volume per month: 126; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: June 2010; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 40. 

Month and year: July 2010; 
Average hourly traffic volume per month: 115; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: August 2010; 
Average hourly traffic volume per month: 137; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: September 2010; 
Average hourly traffic volume per month: 132; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: October 2010; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: November 2010; 
Average hourly traffic volume per month: 146; 
Average hourly lane utilization per month (in percent): 39. 

Month and year: December 2010; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: January 2011; 
Average hourly traffic volume per month: 138; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: February 2011; 
Average hourly traffic volume per month: 151; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: March 2011; 
Average hourly traffic volume per month: 155; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: April 2011; 
Average hourly traffic volume per month: 148; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: May 2011; 
Average hourly traffic volume per month: 139; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: June 2011; 
Average hourly traffic volume per month: 139; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: July 2011; 
Average hourly traffic volume per month: 130; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: August 2011; 
Average hourly traffic volume per month: 134; 
Average hourly lane utilization per month (in percent): 35. 

Month and year: September 2011; 
Average hourly traffic volume per month: 144; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: October 2011; 
Average hourly traffic volume per month: 144; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: November 2011; 
Average hourly traffic volume per month: 145; 
Average hourly lane utilization per month (in percent): 36. 

Month and year: December 2011; 
Average hourly traffic volume per month: 141; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: January 2012; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: February 2012; 
Average hourly traffic volume per month: 156; 
Average hourly lane utilization per month (in percent): 38. 

Month and year: March 2012; 
Average hourly traffic volume per month: 158; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: April 2012; 
Average hourly traffic volume per month: 166; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: May 2012; 
Average hourly traffic volume per month: 151; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: June 2012; 
Average hourly traffic volume per month: 148; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: July 2012; 
Average hourly traffic volume per month: 141; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: August 2012; 
Average hourly traffic volume per month: 142; 
Average hourly lane utilization per month (in percent): 37. 

Month and year: September 2012; 
Average hourly traffic volume per month: 140; 
Average hourly lane utilization per month (in percent): 36. 

Source: GAO analysis of CBP data. 

[End of table] 

Table 14: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at World Trade Bridge Crossing in Laredo, 
Texas, Fiscal Years 2008 through 2012: 

Month and year: October 2007; 
Average hourly traffic volume per month: 327; 
Average hourly lane utilization per month (in percent): 87. 

Month and year: November 2007; 
Average hourly traffic volume per month: 369; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: December 2007; 
Average hourly traffic volume per month: 349; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: January 2008; 
Average hourly traffic volume per month: 333; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: February 2008; 
Average hourly traffic volume per month: 363; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: March 2008; 
Average hourly traffic volume per month: 358; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: April 2008; 
Average hourly traffic volume per month: 373; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: May 2008; 
Average hourly traffic volume per month: 374; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: June 2008; 
Average hourly traffic volume per month: 374; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: July 2008; 
Average hourly traffic volume per month: 361; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: August 2008; 
Average hourly traffic volume per month: 367; 
Average hourly lane utilization per month (in percent): 89. 

Month and year: September 2008; 
Average hourly traffic volume per month: 336; 
Average hourly lane utilization per month (in percent): 90. 

Month and year: October 2008; 
Average hourly traffic volume per month: 361; 
Average hourly lane utilization per month (in percent): 93. 

Month and year: November 2008; 
Average hourly traffic volume per month: 335; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: December 2008; 
Average hourly traffic volume per month: 306; 
Average hourly lane utilization per month (in percent): 91. 

Month and year: January 2009; 
Average hourly traffic volume per month: 240; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: February 2009; 
Average hourly traffic volume per month: 247; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: March 2009; 
Average hourly traffic volume per month: 253; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: April 2009; 
Average hourly traffic volume per month: 255; 
Average hourly lane utilization per month (in percent): 73. 

Month and year: May 2009; 
Average hourly traffic volume per month: 242; 
Average hourly lane utilization per month (in percent): 74. 

Month and year: June 2009; 
Average hourly traffic volume per month: 307; 
Average hourly lane utilization per month (in percent): 80. 

Month and year: July 2009; 
Average hourly traffic volume per month: 344; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: August 2009; 
Average hourly traffic volume per month: 369; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: September 2009; 
Average hourly traffic volume per month: 386; 
Average hourly lane utilization per month (in percent): 86. 

Month and year: October 2009; 
Average hourly traffic volume per month: 384; 
Average hourly lane utilization per month (in percent): 85. 

Month and year: November 2009; 
Average hourly traffic volume per month: 382; 
Average hourly lane utilization per month (in percent): 83. 

Month and year: December 2009; 
Average hourly traffic volume per month: 386; 
Average hourly lane utilization per month (in percent): 84. 

Month and year: January 2010; 
Average hourly traffic volume per month: 371; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: February 2010; 
Average hourly traffic volume per month: 397; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: March 2010; 
Average hourly traffic volume per month: 398; 
Average hourly lane utilization per month (in percent): 75. 

Month and year: April 2010; 
Average hourly traffic volume per month: 418; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: May 2010; 
Average hourly traffic volume per month: 405; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: June 2010; 
Average hourly traffic volume per month: 414; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: July 2010; 
Average hourly traffic volume per month: 372; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: August 2010; 
Average hourly traffic volume per month: 418; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: September 2010; 
Average hourly traffic volume per month: 412; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: October 2010; 
Average hourly traffic volume per month: 405; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: November 2010; 
Average hourly traffic volume per month: 403; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: December 2010; 
Average hourly traffic volume per month: 391; 
Average hourly lane utilization per month (in percent): 77. 

Month and year: January 2011; 
Average hourly traffic volume per month: 396; 
Average hourly lane utilization per month (in percent): 78. 

Month and year: February 2011; 
Average hourly traffic volume per month: 419; 
Average hourly lane utilization per month (in percent): 76. 

Month and year: March 2011; 
Average hourly traffic volume per month: 431; 
Average hourly lane utilization per month (in percent): 79. 

Month and year: April 2011; 
Average hourly traffic volume per month: 443; 
Average hourly lane utilization per month (in percent): 71. 

Month and year: May 2011; 
Average hourly traffic volume per month: 435; 
Average hourly lane utilization per month (in percent): 53. 

Month and year: June 2011; 
Average hourly traffic volume per month: 432; 
Average hourly lane utilization per month (in percent): 51. 

Month and year: July 2011; 
Average hourly traffic volume per month: 414; 
Average hourly lane utilization per month (in percent): 49. 

Month and year: August 2011; 
Average hourly traffic volume per month: 431; 
Average hourly lane utilization per month (in percent): 52. 

Month and year: September 2011; 
Average hourly traffic volume per month: 440; 
Average hourly lane utilization per month (in percent): 52. 

Month and year: October 2011; 
Average hourly traffic volume per month: 435; 
Average hourly lane utilization per month (in percent): 48. 

Month and year: November 2011; 
Average hourly traffic volume per month: 429; 
Average hourly lane utilization per month (in percent): 51. 

Month and year: December 2011; 
Average hourly traffic volume per month: 403; 
Average hourly lane utilization per month (in percent): 50. 

Month and year: January 2012; 
Average hourly traffic volume per month: 421; 
Average hourly lane utilization per month (in percent): 49. 

Month and year: February 2012; 
Average hourly traffic volume per month: 470; 
Average hourly lane utilization per month (in percent): 54. 

Month and year: March 2012; 
Average hourly traffic volume per month: 490; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: April 2012; 
Average hourly traffic volume per month: 480; 
Average hourly lane utilization per month (in percent): 57. 

Month and year: May 2012; 
Average hourly traffic volume per month: 486; 
Average hourly lane utilization per month (in percent): 58. 

Month and year: June 2012; 
Average hourly traffic volume per month: 488; 
Average hourly lane utilization per month (in percent): 57. 

Month and year: July 2012; 
Average hourly traffic volume per month: 462; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: August 2012; 
Average hourly traffic volume per month: 481; 
Average hourly lane utilization per month (in percent): 55. 

Month and year: September 2012; 
Average hourly traffic volume per month: 462; 
Average hourly lane utilization per month (in percent): 54. 

Source: GAO analysis of CBP data. 

[End of table] 

Figure 10: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Otay Mesa Crossing near San Diego, 
California, Fiscal Year 2008 through 2012: 

[Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 227; 
Average hourly percentage of lanes open: 70. 

Date: January 2008; 
Average hourly traffic volume: 190; 
Average hourly percentage of lanes open: 83. 

Date: April 2008; 
Average hourly traffic volume: 237; 
Average hourly percentage of lanes open: 77. 

Date: July 2008; 
Average hourly traffic volume: 242;
Average hourly percentage of lanes open: 76. 

Date: October 2008; 
Average hourly traffic volume: 229; 
Average hourly percentage of lanes open: 71. 

Date: January 2009; 
Average hourly traffic volume: 165; 
Average hourly percentage of lanes open: 71. 

Date: April 2009; 
Average hourly traffic volume: 187; 
Average hourly percentage of lanes open: 72. 

Date: July 2009; 
Average hourly traffic volume: 197; 
Average hourly percentage of lanes open: 79. 

Date: October 2009; 
Average hourly traffic volume: 221; 
Average hourly percentage of lanes open: 81. 

Date: January 2010; 
Average hourly traffic volume: 174; 
Average hourly percentage of lanes open: 77. 

Date: April 2010; 
Average hourly traffic volume: 219; 
Average hourly percentage of lanes open: 84. 

Date: July 2010; 
Average hourly traffic volume: 213; 
Average hourly percentage of lanes open: 83. 

Date: October 2010; 
Average hourly traffic volume: 215; 
Average hourly percentage of lanes open: 81. 

Date: January 2011; 
Average hourly traffic volume: 185; 
Average hourly percentage of lanes open: 78. 

Date: April 2011; 
Average hourly traffic volume: 212; 
Average hourly percentage of lanes open: 84. 

Date: July 2011; 
Average hourly traffic volume: 216; 
Average hourly percentage of lanes open: 88. 

Date: October 2011; 
Average hourly traffic volume: 226; 
Average hourly percentage of lanes open: 86. 

Date: January 2012; 
Average hourly traffic volume: 197; 
Average hourly percentage of lanes open: 85. 

Date: April 2012; 
Average hourly traffic volume: 223; 
Average hourly percentage of lanes open: 82. 

Date: July 2012; 
Average hourly traffic volume: 223; 
Average hourly percentage of lanes open: 88. 

Source: GAO analysis of CBP data. 

[End of figure] 

Figure 11: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at the Mariposa Crossing in Nogales, Arizona, 
Fiscal Year 2008 through 2012: 

[Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 887; 
Average hourly percentage of lanes open: 45. 

Date: January 2008; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 71. 

Date: April 2008; 
Average hourly traffic volume: 156; 
Average hourly percentage of lanes open: 77. 

Date: July 2008; 
Average hourly traffic volume: 102;
Average hourly percentage of lanes open: 46. 

Date: October 2008; 
Average hourly traffic volume: 119; 
Average hourly percentage of lanes open: 48. 

Date: January 2009; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 73. 

Date: April 2009; 
Average hourly traffic volume: 136; 
Average hourly percentage of lanes open: 63. 

Date: July 2009; 
Average hourly traffic volume: 91; 
Average hourly percentage of lanes open: 55. 

Date: October 2009; 
Average hourly traffic volume: 119; 
Average hourly percentage of lanes open: 52. 

Date: January 2010; 
Average hourly traffic volume: 151; 
Average hourly percentage of lanes open: 80. 

Date: April 2010; 
Average hourly traffic volume: 166; 
Average hourly percentage of lanes open: 90. 

Date: July 2010; 
Average hourly traffic volume: 102; 
Average hourly percentage of lanes open: 87. 

Date: October 2010; 
Average hourly traffic volume: 118; 
Average hourly percentage of lanes open: 66. 

Date: January 2011; 
Average hourly traffic volume: 150; 
Average hourly percentage of lanes open: 89. 

Date: April 2011; 
Average hourly traffic volume: 145; 
Average hourly percentage of lanes open: 76. 

Date: July 2011; 
Average hourly traffic volume: 103; 
Average hourly percentage of lanes open: 57. 

Date: October 2011; 
Average hourly traffic volume: 122; 
Average hourly percentage of lanes open: 61. 

Date: January 2012; 
Average hourly traffic volume: 147; 
Average hourly percentage of lanes open: 80. 

Date: April 2012; 
Average hourly traffic volume: 159; 
Average hourly percentage of lanes open: 83. 

Date: July 2012; 
Average hourly traffic volume: 101; 
Average hourly percentage of lanes open: 44. 

Source: GAO analysis of CBP data. 

[End of figure] 

Figure 12: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at the Bridge of the Americas Crossing in El 
Paso, Texas, Fiscal Year 2008 through 2012: 

[Refer to PDF for image][Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 164; 
Average hourly percentage of lanes open: 87. 

Date: January 2008; 
Average hourly traffic volume: 153; 
Average hourly percentage of lanes open: 93. 

Date: April 2008; 
Average hourly traffic volume: 168; 
Average hourly percentage of lanes open: 94. 

Date: July 2008; 
Average hourly traffic volume: 163;
Average hourly percentage of lanes open: 94. 

Date: October 2008; 
Average hourly traffic volume: 154; 
Average hourly percentage of lanes open: 91. 

Date: January 2009; 
Average hourly traffic volume: 134; 
Average hourly percentage of lanes open: 88. 

Date: April 2009; 
Average hourly traffic volume: 118; 
Average hourly percentage of lanes open: 75. 

Date: July 2009; 
Average hourly traffic volume: 118; 
Average hourly percentage of lanes open: 76. 

Date: October 2009; 
Average hourly traffic volume: 129; 
Average hourly percentage of lanes open: 81. 

Date: January 2010; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 86. 

Date: April 2010; 
Average hourly traffic volume: 140; 
Average hourly percentage of lanes open: 90. 

From May 10, 2010 through June 5, 2010 all commercial traffic was 
diverted from the Bridge of the Americas to Ysleta to minimize the 
effect of roadwork on commercial traffic. 

Date: July 2010; 
Average hourly traffic volume: 125; 
Average hourly percentage of lanes open: 49. 

Date: October 2010; 
Average hourly traffic volume: 130; 
Average hourly percentage of lanes open: 63. 

Date: January 2011; 
Average hourly traffic volume: 120; 
Average hourly percentage of lanes open: 60. 

Date: April 2011; 
Average hourly traffic volume: 132; 
Average hourly percentage of lanes open: 68. 

Date: July 2011; 
Average hourly traffic volume: 125; 
Average hourly percentage of lanes open: 77. 

Date: October 2011; 
Average hourly traffic volume: 127; 
Average hourly percentage of lanes open: 71. 

Date: January 2012; 
Average hourly traffic volume: 121; 
Average hourly percentage of lanes open: 63. 

Date: April 2012; 
Average hourly traffic volume: 117; 
Average hourly percentage of lanes open: 52. 

Date: July 2012; 
Average hourly traffic volume: 113; 
Average hourly percentage of lanes open: 77. 

Source: GAO analysis of CBP data. 

[End of figure] 

Figure 13: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Ysleta Crossing in El Paso, Texas, Fiscal 
Year 2008 through 2012: 

[Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 131; 
Average hourly percentage of lanes open: 92. 

Date: January 2008; 
Average hourly traffic volume: 121; 
Average hourly percentage of lanes open: 91. 

Date: April 2008; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 94. 

Date: July 2008; 
Average hourly traffic volume: 127;
Average hourly percentage of lanes open: 94. 

October 2008: New lanes opened. 

Date: October 2008; 
Average hourly traffic volume: 131; 
Average hourly percentage of lanes open: 81. 

Date: January 2009; 
Average hourly traffic volume: 73; 
Average hourly percentage of lanes open: 44. 

Date: April 2009; 
Average hourly traffic volume: 82; 
Average hourly percentage of lanes open: 44. 

Date: July 2009; 
Average hourly traffic volume: 102; 
Average hourly percentage of lanes open: 54. 

Date: October 2009; 
Average hourly traffic volume: 116; 
Average hourly percentage of lanes open: 58. 

Date: January 2010; 
Average hourly traffic volume: 103; 
Average hourly percentage of lanes open: 55. 

Date: April 2010; 
Average hourly traffic volume: 127; 
Average hourly percentage of lanes open: 58. 

From May 10, 2010 through June 5, 2010 all commercial traffic was 
diverted from the Bridge of the Americas to Ysleta to minimize the 
effect of roadwork on commercial traffic. 

Date: July 2010; 
Average hourly traffic volume: 121; 
Average hourly percentage of lanes open: 33. 

Date: October 2010; 
Average hourly traffic volume: 129; 
Average hourly percentage of lanes open: 39. 

Date: January 2011; 
Average hourly traffic volume: 120; 
Average hourly percentage of lanes open: 36. 

Date: April 2011; 
Average hourly traffic volume: 142; 
Average hourly percentage of lanes open: 44. 

Date: July 2011; 
Average hourly traffic volume: 122; 
Average hourly percentage of lanes open: 42. 

Date: October 2011; 
Average hourly traffic volume: 128; 
Average hourly percentage of lanes open: 37. 

Date: January 2012; 
Average hourly traffic volume: 123; 
Average hourly percentage of lanes open: 38. 

Date: April 2012; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 35. 

Date: July 2012; 
Average hourly traffic volume: 127; 
Average hourly percentage of lanes open: 44. 

Source: GAO analysis of CBP data. 

[End of figure] 

Figure 14: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at Columbia Solidarity Bridge Crossing in 
Laredo, Texas, Fiscal Year 2008 through 2012: 

[Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 143; 
Average hourly percentage of lanes open: 87. 

Date: January 2008; 
Average hourly traffic volume: 133; 
Average hourly percentage of lanes open: 90. 

Date: April 2008; 
Average hourly traffic volume: 157; 
Average hourly percentage of lanes open: 90. 

Date: July 2008; 
Average hourly traffic volume: 123;
Average hourly percentage of lanes open: 86. 

Date: October 2008; 
Average hourly traffic volume: 129; 
Average hourly percentage of lanes open: 93. 

Date: January 2009; 
Average hourly traffic volume: 105; 
Average hourly percentage of lanes open: 85. 

Date: April 2009; 
Average hourly traffic volume: 107; 
Average hourly percentage of lanes open: 73. 

Date: July 2009; 
Average hourly traffic volume: 96; 
Average hourly percentage of lanes open: 85. 

Date: October 2009; 
Average hourly traffic volume: 108; 
Average hourly percentage of lanes open: 85. 

Date: January 2010; 
Average hourly traffic volume: 119; 
Average hourly percentage of lanes open: 79. 

Date: April 2010; 
Average hourly traffic volume: 137; 
Average hourly percentage of lanes open: 79. 

Date: July 2010; 
Average hourly traffic volume: 115; 
Average hourly percentage of lanes open: 79. 

Date: October 2010; 
Average hourly traffic volume: 142; 
Average hourly percentage of lanes open: 79. 

Date: January 2011; 
Average hourly traffic volume: 138; 
Average hourly percentage of lanes open: 78. 

Date: April 2011; 
Average hourly traffic volume: 148; 
Average hourly percentage of lanes open: 71. 

Date: July 2011; 
Average hourly traffic volume: 130; 
Average hourly percentage of lanes open: 49. 

Date: October 2011; 
Average hourly traffic volume: 144; 
Average hourly percentage of lanes open: 48. 

Date: January 2012; 
Average hourly traffic volume: 142; 
Average hourly percentage of lanes open: 49. 

Date: April 2012; 
Average hourly traffic volume: 166; 
Average hourly percentage of lanes open: 57. 

Date: July 2012; 
Average hourly traffic volume: 141; 
Average hourly percentage of lanes open: 55. 

Source: GAO analysis of CBP data. 

[End of figure] 

Figure 15: Average Hourly Traffic Volume and Average Hourly Percentage 
of Lanes Open Per Month at World Trade Bridge Crossing in Laredo, 
Texas, Fiscal Year 2008 through 2012: 

[Refer to PDF for image: multiple line graph] 

Date: October 2007; 
Average hourly traffic volume: 327; 
Average hourly percentage of lanes open: 36. 

Date: January 2008; 
Average hourly traffic volume: 333; 
Average hourly percentage of lanes open: 45. 

Date: April 2008; 
Average hourly traffic volume: 373; 
Average hourly percentage of lanes open: 45. 

Date: July 2008; 
Average hourly traffic volume: 361;
Average hourly percentage of lanes open: 45. 

Date: October 2008; 
Average hourly traffic volume: 361; 
Average hourly percentage of lanes open: 47. 

Date: January 2009; 
Average hourly traffic volume: 240; 
Average hourly percentage of lanes open: 46. 

Date: April 2009; 
Average hourly traffic volume: 255; 
Average hourly percentage of lanes open: 42. 

Date: July 2009; 
Average hourly traffic volume: 344; 
Average hourly percentage of lanes open: 39. 

Date: October 2009; 
Average hourly traffic volume: 384; 
Average hourly percentage of lanes open: 41. 

Date: January 2010; 
Average hourly traffic volume: 371; 
Average hourly percentage of lanes open: 38. 

Date: April 2010; 
Average hourly traffic volume: 418; 
Average hourly percentage of lanes open: 37. 

Date: July 2010; 
Average hourly traffic volume: 372; 
Average hourly percentage of lanes open: 38. 

Date: October 2010; 
Average hourly traffic volume: 405; 
Average hourly percentage of lanes open: 38. 

Date: January 2011; 
Average hourly traffic volume: 396; 
Average hourly percentage of lanes open: 37. 

April 2011: New lanes opened. 

Date: April 2011; 
Average hourly traffic volume: 443; 
Average hourly percentage of lanes open: 37. 

Date: July 2011; 
Average hourly traffic volume: 414; 
Average hourly percentage of lanes open: 37. 

Date: October 2011; 
Average hourly traffic volume: 435; 
Average hourly percentage of lanes open: 37. 

Date: January 2012; 
Average hourly traffic volume: 421; 
Average hourly percentage of lanes open: 37. 

Date: April 2012; 
Average hourly traffic volume: 480; 
Average hourly percentage of lanes open: 37. 

Date: July 2012; 
Average hourly traffic volume: 462; 
Average hourly percentage of lanes open: 37. 

Source: GAO analysis of CBP data. 

[End of figure] 

[End of section] 

Appendix VI: Performance Measures for U.S. Customs and Border 
Protection Activities, Fiscal Year 2013: 

Table 15 lists the 28 performance measures DHS and CBP are using in 
fiscal year 2013 to assess and report on CBP progress toward the 
agency's security and trade facilitation goals. These CBP-focused 
performance measures include the following: 

* Nine measures selected by DHS as Government Performance and Results 
Act (GPRA) measures.[Footnote 85] (These are also called strategic 
measures within the department.) These measures are aligned with the 
goals and objectives in DHS's Quadrennial Homeland Security Review 
Report and publicly reported to communicate achievement of these 
strategic goals and objectives.[Footnote 86] 

* Fifteen management measures that are not reported publicly but 
rather inform internal CBP decisions on program priorities and 
resource allocation, and to monitor progress and performance. CBP 
officials report, for example, that these measures are used in 
crafting the department's budget justification. 

* Four CBP Office of Field Operations (OFO) operational measures that 
capture former GPRA measures that OFO uses internally to evaluate 
senior officials' performance, for example.[Footnote 87] 

Table 15: U.S. Customs and Border Protection-Focused Performance 
Measures, Fiscal Year 2013: 

Type of performance measure: Government Performance and Results Act/ 
strategic performance measures; 
Performance measure name: 
1: Number of apprehensions on the southwest border between the ports 
of entry; 
Fiscal year 2013 target: less than 391,000. 

Performance measure name: 
2: Percent of people apprehended multiple times along the southwest 
border; 
Fiscal year 2013 target: 18%. 

Performance measure name: 
3: Percent of detected conventional aircraft incursions resolved along 
all borders of the United States; 
Fiscal year 2013 target: 100%. 

Performance measure name: 
4: Percent of cargo by value imported into the U.S. by participants in 
CBP trade partnership programs; 
Fiscal year 2013 target: 57%. 

Performance measure name: 
5: Percent of import revenue successfully collected; 
Fiscal year 2013 target: 100%. 

Performance measure name: 
6: Percent of imports compliant with U.S. trade laws; 
Fiscal year 2013 target: 97.5%. 

Performance measure name: 
7: Amount of smuggled outbound currency seized at ports of entry; 
Fiscal year 2013 target: 30 million. 

Performance measure name: 
8: Number of smuggled outbound weapons seized at ports of entry; 
Fiscal year 2013 target: 400. 

Performance measure name: 
9: Percent of inbound cargo identified by CBP as potentially high risk 
that is assessed or scanned prior to departure or at arrival at a U.S. 
port of entry; 
Fiscal year 2013 target: FOUO[A]. 

Type of performance measure: Management performance measures; 

Performance measure name: 
1: Average number of apprehensions for persons with multiple 
apprehensions along the southwest border; 
Fiscal year 2013 target: 2.48. 

Performance measure name: 
2: Number of joint operations conducted along the southwest border by 
Border Patrol agents and Mexican law enforcement partners; 
Fiscal year 2013 target: 11. 

Performance measure name: 
3: Number of joint operations conducted along the northern border by 
Border Patrol agents and Canadian law enforcement partners; 
Fiscal year 2013 target: 18. 

Performance measure name: 
4: Percent of apprehensions at Border Patrol checkpoints; 
Fiscal year 2013 target: less than 5%. 

Performance measure name: 
5: Percent of air support launches accomplished to support Homeland 
Security missions; 
Fiscal year 2013 target: more than 95%. 

Performance measure name: 
6: Percent of pharmaceutical, health, and chemical industry imports 
compliant with U.S. trade laws; 
Fiscal year 2013 target: 98%. 

Performance measure name: 
7: Percent of petroleum industry imports compliant with U.S. trade 
laws; 
Fiscal year 2013 target: 95%. 

Performance measure name: 
8: Value of shipments seized as a result of intellectual property 
rights violations; 
Fiscal year 2013 target: $136 million. 

Performance measure name: 
9: Number of shipments seized as a result of intellectual property 
rights violations; 
Fiscal year 2013 target: 24,000. 

Performance measure name: 
10: Compliance rate for Customs-Trade Partnership Against Terrorism (C-
TPAT) members with established C-TPAT security criteria[B]; 
Fiscal year 2013 target: 94%. 

Performance measure name: 
11: Percent of land border passengers compliant with laws, rules, and 
regulations; 
Fiscal year 2013 target: 99.5%. 

Performance measure name: 
12: Percent of air passengers compliant with laws, rules, and 
regulations; 
Fiscal year 2013 target: 98%. 

Performance measure name: 
13: Percent of border vehicle passengers in compliance with 
agricultural quarantine regulations; 
Fiscal year 2013 target: 95.5%. 

Performance measure name: 
14: Percent of international air passengers in compliance with 
agricultural quarantine regulations; 
Fiscal year 2013 target: 95.5%. 

Performance measure name: 
15: Percent of time TECS is available to end users[C]; 
Fiscal year 2013 target: 99%. 

Type of performance measure: Office of Field Operations' operational 
performance measures[D]; 

Performance measure name: 
1: Percent increase in travelers to the U.S. enrolled in a Trusted 
Traveler program (cumulative); 
Fiscal year 2013 target: 16%. 

Performance measure name: 
2: Percent of individuals screened against law enforcement databases 
for entry into the United States; 
Fiscal year 2013 target: FOUO[A]. 

Performance measure name: 
3: Air passenger interdiction rate for major violations; 
Fiscal year 2013 target: FOUO[A]. 

Performance measure name: 
4: Land border interdiction rate for major violations; 
Fiscal year 2013 target: FOUO[A]. 

Source: GAO analysis of CBP performance measurement documents. 

[A] The specific performance target is designated by CBP as for 
official use only (FOUO). 

[B] C-TPAT is a customs-to-business partnership program that provides 
benefits to supply chain companies that agree to comply with 
predetermined security measures: 

[C] TECS is the principal system used by CBP officers at the border to 
assist with screening and determinations regarding admissibility of 
arriving persons. 

[D] According to CBP officials, OFO is the only office within CBP that 
maintains such operational measures. 

[End of table] 

[End of section] 

Appendix VII: Comments from the Department of Homeland Security: 

U.S. Department of Homeland Security: 
Washington, DC 20528: 

July 5, 2013: 

Rebecca Gambler: 
Director, Homeland Security and Justice Issues: 
U.S. Government Accountability Office: 
441 G Street, NW: 
Washington, DC 20548: 

Re: Draft Report GAO-13-603, "U.S.-Mexico Border: CBP Action Needed to 
Improve Wait Time Data and Measure Outcomes of Trade Facilitation 
Efforts" 

Dear Ms. Gambler: 

Thank you for the opportunity to review and comment on this draft 
report. The U.S. Department of Homeland Security (DHS) appreciates the 
U.S. Government Accountability Office's (GAO's) work in planning and 
conducting its review and issuing this report. 

As the report highlights, trade between Mexico and the United States 
is important to U.S. economic health, and the number of commercial 
vehicles carrying goods across the U.S.-Mexico border is on the rise. 
U.S . Customs and Border Protection (CBP) recognizes that the length of
time commercial vehicles wait in line at the border affects trade 
activity between the United States and Mexico. CBP is taking action to 
develop a high-level trade facilitation goal to support a strong 
economy by expediting legitimate trade. 

The draft report contained four recommendations with which the 
Department concurs. Specifically, GAO recommended that the 
Commissioner of CBP: 

Recommendation 1: Identify and carry-out steps that can be taken to 
help CBP port officials overcome challenges to consistent 
implementation of existing wait time estimation methodologies. Steps 
for ensuring consistent implementation of these methodologies could
include, for example, implementing the fiscal year 2008 WHTI report 
recommendations to use closed-circuit television cameras to measure 
wait time in real time and provide a standardized measurement and 
validation tool. 

Response: Concur. CBP's Office of Field Operations (OFO) will continue 
to work cooperatively with the bi-national Border Wait Time work group 
(Canada Border Security Agency, Transport Canada, and Federal Highway 
Administration [FHWA]) and regional transportation stakeholders to 
leverage existing technologies (such as radio frequency 
identification, inductive loops, Bluetooth, etc.) and to identify 
emerging technologies for automating the measurement of vehicle wait 
times at the land border. 

The resulting automated land border wait time management solution will 
enable CBP/OFO to: 

1) eliminate manual reporting of wait times; 

2) obtain standard, reliable, and consistent wait time and delay 
information in real time; 

3) improve customer service by increasing availability of staff for 
enforcement operations; 

4) improve agency transparency by enabling land border wait times to 
be easily shared with participating agencies and regional traffic 
management centers; 

5) reduce delays in freight movement and loss of business income at 
the regional, state, and national level; and; 

6) reduce environmental costs by decreasing pollution and carbon 
emissions associated with heavy congestion. 

If funding is available, CBP/OFO has a goal to automate the estimation 
and reporting of border wait times. CBP/OFO has researched available 
and emerging wait time methodologies, conducted pilots in automated 
wait time measurement, and met with various stakeholders as they have 
begun to conduct separate pilots. 

CBP/OFO will work proactively to validate the accuracy and usefulness 
of the wait time estimates produced by these solutions. If credible, 
CBP/OFO will adopt these estimates for use in its Border Wait Time 
(BWT) Web site; replacing existing manual estimates and processes. CBP 
has already developed (in concert with FHW A) a data schema for 
accepting external wait time estimates into the BWT site. The BWT site 
is currently used to report border crossing wait time estimates to 
trade, stakeholders, and the traveling public. Corrective actions toward
meeting this recommendation include: establishing the internal/ 
external stakeholder group; and identifying the best candidate 
technologies to pilot. Estimated Completion Date (ECD): June 30, 2014. 

Recommendation 2: In consultation with FHW A and state DOTs, assess 
the feasibility of replacing current methods of manually calculating 
wait times with automated methods, which could include assessing all 
of the associated costs and benefits, options for how the agency will
use and publicly report the results of automated data collection, the 
potential trade-offs associated with moving to this new system, and 
other factors such as those influencing the possible expansion of 
existing automation efforts to the 34 other locations that currently 
report wait times but have no automation projects under way. 

Response: Concur. Various wait time measurement technologies are 
currently in production in the Cascade Corridor, Niagara Region, and 
at several crossings on the southern border. These solutions continue 
to mature and show great promise for measuring vehicle wait times that 
can be used by border agencies to manage delays. It should be noted 
that calculating vehicle wait times, at the surface, appears to be a 
simple process; however, in reality, calibrating an effective, 
reliable, and accurate measurement system is a complicated endeavor 
with many variables encompassing local, regional, and international 
stakeholders. 

CBP has consulted with FHW A and multiple state Departments of 
Transportation (DOTs) to assess automated wait time feasibility. 
Further, CBP has conducted a pilot automated wait time solution in 
concert with FHW A and other stakeholders. Whereas the pilot did not 
yield a truly effective automated solution, it did improve upon wait 
time estimates when compared to manual estimation; and CBP 
successfully integrated the solution's data into its BWT Web site. CBP 
has also consulted with several of its DHS Centers of Excellence, most 
notably the BORDERs Center of Excellence (University of Arizona). 
Emerging and refined technologies, in conjunction with lessons learned 
during the pilot, indicate that from a technology standpoint 
automating wait time estimation is extremely feasible. Feasibility is 
reduced from a financing, funding, and operating standpoint. We 
request that this recommendation be considered resolved and closed. 

Recommendation 3: Document the methodology and process OFO uses to 
allocate staff to land ports of entry on the southwest border, 
including the rationales and factors considered in making these 
decisions. 

Response: Concur. CBP/OFO will develop a standardized process for 
allocating CBP Officers that uses Workload Staffing Model results; 
current and future operational priorities and threats; and historical 
staffing levels and patterns. The process will document both phases of 
the allocation: 

I) allocations to each field office, and; 

2) further allocation down to the port level. 

The process also will document assumptions, factors and concerns to be 
used at all levels to guide the decision-making and allocation 
process. ECD: December 31, 2013. 

Recommendation 4: Develop outcome-oriented performance measures or 
proxy measures to capture the impact of CBP's trade facilitation 
efforts, such as measures to determine the extent to which CBP trusted 
shipper programs have met their goals. 

Response: Concur. CBP/OFO recognizes the need to maintain a strong 
economy by expediting legitimate trade and understands that meeting 
its high-level trade facilitation goal is critical to making this 
happen. Although past CBP measurement efforts have focused largely on 
the more immediate concerns of security, enforcement, and compliance; 
OFO concurs with the importance of outcome-based measurement in 
support of CBP's trade facilitation efforts. CBP is currently engaged 
in two studies that address both the security and facilitation aspects 
of trade. The first is the DHS QHSR Trade Flows Study. The second is 
the National Security Staff Trans-border Directorate's Trusted Trader 
efforts in support of the National Strategy for Global Supply Chain
Security. Participating in these high-level initiatives within the 
Department and the Administration will help provide additional clarity 
in defining the specific goals going forward for trusted trader 
programs. 

OFO will create a team of subject matter experts from OFO trade-
related programs to identify several outcome measures and/or 
acceptable proxy measures for trade facilitation. OFO will also
collaborate with private-sector entities such as the Commercial 
Operations Advisory Council in order to identify metrics of greatest 
concern. OFO will work towards putting into place at least two new 
trade facilitation outcome measures and/or proxy measures as OFO 
operational measures, following the general guidance outlined in this 
report. ECD: June 30, 2014. 

Again, thank you for the opportunity to review and provide comments on 
this draft report. Technical comments were previously provided under 
separate cover. Please feel free to contact me if you have any 
questions. We look forward to working with you in the future. 

Sincerely, 

Signed by: 

Jim H. Crumpacker: 
Director: 
Departmental GAO-OIG Liaison Office: 

[End of section] 

Appendix VIII: GAO Contact and Staff Acknowledgments: 

GAO Contact: 

Rebecca Gambler, (202) 512-8777 or GamblerR@gao.gov: 

Staff Acknowledgments: 

In addition to the contact named above, Lacinda Ayers, Assistant 
Director; Claudia Becker; Sarah Kaczmarek; and Michael Lenington made 
key contributions to this report. Also contributing to this report 
were Pedro Almoguera, Frances Cook, Juan Gobel, Eric Hauswirth, Phil 
Herr, Stan Kostyla, Jessica Orr, Minette Richardson, and Loren Yager. 

[End of section] 

Footnotes: 

[1] The agency's trade facilitation goals are articulated in DHS's 
February 2010 Quadrennial Homeland Security Review Report, which 
outlined a strategic framework for homeland security. The two relevant 
mission goals are to (1) prevent the illegal flow of people and goods 
across U.S. air, land, and sea borders while expediting the safe flow 
of lawful travel and commerce, and (2) ensure security and resilience 
of global movement systems (which includes global trading and 
transportation networks). See DHS, Quadrennial Homeland Security 
Review Report: A Strategic Framework for a Secure Homeland 
(Washington, D.C.: February 2010). 

[2] The General Services Administration (GSA) also has 
responsibilities related to the construction and maintenance of GSA-
owned facilities that include land ports of entry. Ports of entry are 
the facilities that provide for the controlled entry into or departure 
from the United States for persons and materials. Specifically, a port 
of entry is any officially designated location (seaport, airport, or 
land border location) where DHS officers or employees are assigned to 
clear passengers and merchandise, collect duties, and enforce customs 
laws. A single land port of entry may be composed of one or more 
crossings. For example, the Port of Laredo, Texas, headed by a port 
director, oversees operations at four separate border crossings, one 
rail crossing, and one airport. CBP operates 168 land border 
crossings, 46 of which are located on the southwest border. 

[3] GAO, Border Security: CBP Lacks the Data Needed to Assess the FAST 
Program at U.S. Northern Border Ports, [hyperlink, 
http://www.gao.gov/products/GAO-10-694] (Washington, D.C.: July 19, 
2010). 

[4] CBP's Automated Commercial Environment is CBP's commercial trade 
processing system--one of several databases and tools used by CBP to 
screen and assign risk levels to travelers and cargo entering the 
United States. 

[5] The San Diego Association of Governments is a public planning, 
transportation, transit construction, and research agency. 

[6] These organizations and officials were identified to us as 
knowledgeable stakeholders who could provide us with a range of 
perspectives on commercial vehicle traffic at southwest border 
crossings. The American Trucking Associations is a national trade and 
safety organization representing the U.S. trucking industry. The 
Border Trade Alliance is a nonprofit organization that serves as a 
forum for participants to address key issues affecting trade, travel, 
and security in North America. 

[7] CBP reported on the reliability of wait time calculations in its 
Western Hemisphere Travel Initiative, Commercial Wait Times Analysis 
Final Report, October 2007-September 2008. The goal of WHTI is to 
facilitate entry for U.S. citizens and legitimate foreign visitors 
while strengthening U.S. border security. The WHTI Program Office 
sponsored this evaluation of commercial vehicle wait times to validate 
the current wait time reporting systems at individual crossings and to 
determine if a national standard for reporting wait times can be 
established. 

[8] GAO, Standards for Internal Control in the Federal Government, 
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00-21.3.1] 
(Washington, D.C.: November 1999). These standards, issued pursuant to 
the requirements of the Federal Managers' Financial Integrity Act of 
1982, Pub. L. No. 97-255, 96 Stat. 814, provide the overall framework 
for establishing and maintaining internal control in the federal 
government. 

[9] As described later in this report, automation of wait time data 
collection relies on Radio-Frequency Identification readers to read 
the unique signals from passing vehicles at several points along the 
border-crossing route. These data points are then automatically 
matched and analyzed to estimate the current wait time at that 
crossing. 

[10] Project Management Institute, The Standard for Program 
Management©, Second Edition, (Newton Square, Pennsylvania: 2008). 

[11] The SRA is a needs assessment process by which CBP collects and 
analyzes information about the infrastructure at each crossing along 
the northern and southwestern borders, identifies needs, and 
prioritizes infrastructure improvement projects. CBP officials 
reported conducting these assessments fiscal years 2003 through 2006. 

[12] See GAO, A Model of Strategic Human Capital Management, 
[hyperlink, http://www.gao.gov/products/GAO-02-373SP] (Washington, 
D.C.: March 2002), and [hyperlink, 
http://www.gao.gov/products/GAO/AIMD-00-21.3.1]. The first report 
describes a human capital model we developed that identifies eight 
critical success factors for managing human capital strategically. In 
developing this model, we built upon GAO's Human Capital: A Self-
Assessment Checklist for Agency Leaders, [hyperlink, 
http://www.gao.gov/products/GAO/OCG-00-14G] (Washington, D.C.: 
September 2000). Among other steps, we also considered lessons learned 
from GAO reports on public and private organizations that are viewed 
as leaders in strategic human capital management and managing for 
results. 

[13] See OMB Circular No. A-11, Preparation, Submission, and Execution 
of the Budget (Washington, D.C.: Aug. 3, 2012). See also GAO, Managing 
for Results: Strengthening Regulatory Agencies' Performance Management 
Practices, [hyperlink, http://www.gao.gov/products/GAO/GGD-00-10] 
(Washington, D.C.: Oct. 28, 1999). In this report we gathered 
information from 23 federal and state organizations that we or other 
credible sources identified as using or planning to use a variety of 
useful practices to enhance specific aspects of their performance 
management and measurement processes. The organizations, although they 
had different missions, sizes, and organizational structures, said 
they consistently recognized that these practices are important in 
their efforts to develop a stronger results orientation. 

[14] For the purpose of this report, we focused on commercial vehicle 
traffic, as opposed to private vehicle or pedestrian traffic. 

[15] The entry document (e-Manifest) contains information about a 
shipment, including the shipment type, conveyance, passenger/crew, and 
equipment. E-Manifests for FAST shipments must be submitted 30 minutes 
before arrival, and e-Manifests for non-FAST shipments must be 
submitted at least 1 hour before arrival. See 19 C.F.R. § 123.92(a). 

[16] CBP uses various databases and tools, including the Automated 
Targeting System, Automated Commercial Environment, and local Advance 
Targeting Units (ATU) to screen and assign risk levels to travelers 
and cargo entering the United States. 

[17] According to CBP, officers select shipments for targeted 
inspection based on several factors. Specifically, shipments may be 
selected for targeted inspection based on information provided by the 
ATUs, Manifest Review Units, Document Analysis Units, and other 
specialized enforcement units. The ATUs use information from the 
Automated Targeting System or Automated Commercial Environment to 
review manifest data prior to the shipments crossing into the United 
States. The Manifest Review Units are responsible for analyzing 
manifests, which list in detail the total cargo of shipments. Examples 
of data elements on a manifest include shipper, point and country of 
origin of goods, export carrier, and description of packages and 
goods. The Document Analysis Units are responsible for analyzing 
fraudulent documents. 

[18] Prior to the primary inspection booths, CBP also screens 
commercial traffic using radiation portal monitors to detect nuclear 
and radiological materials. Radiation portals are capable of detecting 
various types of radiation emanating from nuclear devices, dirty 
bombs, special nuclear materials, natural sources, and isotopes 
commonly used in medicine and industry. Unlike gamma ray imaging 
systems--such as CBP's Vehicle and Cargo Inspection System--these 
devices do not produce images, but are passive systems that alert when 
energy emitted by radioactive sources is detected. 

[19] For example, according to officials with the U.S. Department of 
Health and Human Services' Food and Drug Administration (FDA), FDA 
personnel conduct public health inspections on incoming commercial 
vehicles on the southwest border in an effort to ensure that food and 
food products from abroad meet U.S. standards. 

[20] Front-of-the-line processing refers to opportunities at some 
crossings for FAST vehicles to begin their secondary inspection before 
non-FAST vehicles when there is a backup of traffic waiting for 
secondary inspection. 

[21] C-TPAT is a customs-to-business partnership program that provides 
benefits to supply chain companies that agree to comply with 
predetermined security measures. 

[22] H.R. Rep. No. 109-699, at 126 (2006) (Conf. Rep.). The 
explanatory statement for the fiscal year 2008 consolidated 
appropriations act noted that CBP had submitted the resource 
allocation model and had developed a workload staffing model to 
generate estimates of staffing needed to meet workload and mission 
requirements. 

[23] H.R. Rep. No. 112-331, at 958 (2011) (Conf. Rep.); H.R. Rep. No. 
112-91, at 27-28 (2011); S. Rep. No. 112-74, at 31 (2011). 

[24] H.R. Rep. No. 111-151, at 110 (2009) (Conf. Rep.); Pub. L. No. 
111-230, 124 Stat. 2485, 2485 (2010). 

[25] BorderWizardTM analyses include factors such as projected traffic 
volume, workload processing time, and the proposed infrastructure 
improvements. The analysis does not take into account staffing levels 
at the port of entry. 

[26] CBP officials responsible for maintaining CBP's wait time data 
and others noted that they do not maintain information on the wait 
time calculation methodologies used at each crossing. They reported 
that they would have to ask officials at each crossing to develop such 
a list. 

[27] CBP officials at three of the five crossings that reported 
primarily using the line-of-sight methodology also reported using the 
driver survey methodology at times, such as during construction or to 
routinely check their line-of-sight methodology. 

[28] CBP officials at Otay Mesa did not respond to our question about 
why the number of primary inspection lanes was not considered. 

[29] Officials at these two crossings noted that CBP's wait time data 
are of limited usefulness because they do not capture total crossing 
time. Industry representatives we met with at the remaining two of six 
crossings indicated the need for a standardized system for wait time 
measurement but did not specifically indicate whether CBP's wait time 
data were longer or shorter than actual waits they experienced. 

[30] CBP officials report that industry's interest in total crossing 
time may present an opportunity for CBP to engage in a public-private 
partnership. 

[31] According to CBP officials and documents, CBP's workload staffing 
model does not (1) consider CBP's current wait time data as an input, 
or (2) assume a certain wait time goal because the model is not 
designed to calculate different results depending on performance-
related goals, such as meeting wait time service goals. 

[32] In making the first recommendation, the report notes that for 
various geographical reasons it is often difficult for cameras 
positioned on the U.S. side to provide adequate views of queues. 
Therefore, the report recommends that, where possible, CBP work to 
leverage use of cameras in use by stakeholders on or near land border 
crossings. With regard to the second recommendation to provide a 
standardized measurement and validation tool, the report further 
specifies that such a tool could include a spreadsheet with formulas 
taking into account the local benchmarks used to identify the end of 
the line, the number of inbound lanes, the average processing time, 
and the number of open primary booths, among other variables, in order 
to determine wait time. The report also included three other 
recommendations including the following: (1) provide administrative 
support to ensure accurate wait time reporting and reduce CBP officer 
workload, (2) increase the timeliness and frequency of wait time 
updates on CBP's website to a minimum of 30 minutes or less, and (3) 
provide video feeds to the CBP website. 

[33] The completed pilot project was at Otay Mesa (Otay Mesa, 
California) and the ongoing projects are at Pharr (Pharr, Texas), 
Bridge of the Americas (El Paso, Texas), Ysleta (El Paso, Texas), 
World Trade Bridge (Laredo, Texas), Columbia Solidarity Bridge 
(Laredo, Texas), Veterans (Brownsville, Texas), and Mariposa (Nogales, 
Arizona). 

[34] The website is [hyperlink, http://bcis.tamu.edu]. 

[35] Automation projects are planned at Santa Teresa (Santa Teresa, 
New Mexico) and Camino Real International Bridge (Eagle Pass, Texas). 

[36] Project Management Institute, The Standard for Program 
Management©, Second Edition. 

[37] Upon arriving at the border crossing, traffic waiting to enter 
the United States queues up in primary inspection lanes that lead to 
primary inspection booths where a CBP officer reviews documentation on 
the exporter, importer, and goods being transported. If no further 
inspections are required, the vehicle is allowed to enter the United 
States. Secondary inspections occur when a vehicle is referred by the 
primary line officer for further inspection, including gamma ray 
scans, paperwork, and physical examinations. 

[38] For example, industry representatives and Mexican officials in 
Laredo, Texas told us that seven new primary inspection lanes were 
added at the World Trade Bridge in 2011 to reduce wait times for 
commercial vehicles, but the new lanes were often not opened. 

[39] Mariposa is a major crossing for agricultural products and 
therefore has high seasonal variability in commercial traffic volume. 
Prior to the addition of new primary inspection lanes, the peak months 
in fiscal year 2012 were January, February, March, and April, when 
average monthly commercial vehicle traffic volume exceeded that of 
nonpeak months by approximately 20 percent. The monthly average 
percentage of lanes opened on average per hour for the nonpeak months 
in fiscal year 2012, prior to the opening of new lanes on April, 30 
2012--October 2011 to December 2011--ranged from 61 to 79 percent. 
Following the addition of new lanes in April 2012, this rate dropped 
to a monthly average of between 41 and 48 percent. However, it is 
important to note that this period (May-September 2012) is generally a 
period of low traffic volume, which, together with the availability of 
four new lanes, may account for this decrease. 

[40] In fiscal year 2012, the average monthly percentage of primary 
lanes open on average per hour at these crossings was 39-79 percent at 
Bridge of the Americas, 27-48 percent at Ysleta, 36-38 percent at 
Columbia Solidarity Bridge, and 48-58 percent at World Trade Bridge. 

[41] Our analysis does not indicate whether CBP is maximizing use of 
its lanes, but rather allows us to observe how closely the average 
hourly traffic volume per month corresponds to the average number of 
hourly lanes open per month. 

[42] In addition, CBP officials at the World Trade Bridge said they 
previously had insufficient staff to open all primary lanes during the 
midday rush but they have since added 20 new staff, which allowed them 
to add a new shift in January 2013 to minimize the effect of officer 
lunch breaks on their ability to open primary lanes. Because this 
initiative is relatively new, it is too early to assess its impact on 
lane utilization. 

[43] According to GSA and CBP officials, GSA has statutory authority 
under 40 U.S.C. § 3175 to accept gifts from the private sector to fund 
expenses such as infrastructure renovation, but CBP does not have this 
authority. These officials also reported that GSA has accepted private 
sector gifts to fund the construction or renovation of land ports of 
entry. 

[44] This primary lane expansion project was primarily funded by the 
city of Laredo. The city provided $7.5 million, GSA provided $1.3 
million, and CBP provided $1.6 million. 

[45] Regional border master plans are comprehensive long-range plans 
to identify and prioritize port of entry infrastructure needs and 
projects within a defined area. These plans represent binational 
stakeholder efforts to (1) prioritize port of entry and related 
transportation projects leading to ports of entry, (2) inform decision 
making, (3) allocate limited funding sources, and (4) ensure continued 
dialogue and coordination on future infrastructure needs and projects. 
In the near future, six regional border master plans will have been 
completed in California (1), Arizona (1), New Mexico (1), and Texas 
(3). 

[46] H.R. Rep. No. 112-331, at 958 (2011) (Conf. Rep.); H.R. Rep. No. 
112-91, at 27-28 (2011); S. Rep. No. 112-74, at 31 (2011) and 
Department of Homeland Security, U.S. Customs and Border Protection, 
Resource Optimization at Ports of Entry: Fiscal Year 2012 Report to 
Congress (Washington, D.C.: April 10, 2013). 

[47] We did not evaluate CBP's workload staffing model as part of this 
review; however, we did review CBP documentation of the model. CBP 
officials and documentation indicated that the workload staffing 
model's purpose is to inform CBP budget decisions, such as the 
development of CBP budget requests, as well as its staffing allocation 
process. In addition, CBP documentation also indicated that the 
model's methodology assesses staffing needs based on workload data, 
processing times, and complexity. To arrive at the number of full-time-
equivalent officers needed to complete the work, the model assumes a 
baseline number of hours per year are available for a CBP officer to 
focus on core mission work. The model then calculates the volume of 
core mission work using transactional data for each business process 
that CBP officers carry out--e.g., number of truck primary exams, 
number of truck container nonintrusive inspection exams, and so forth. 
CBP then uses data on the level of effort in minutes or hours expended 
each time an officer performs these activities to calculate the volume 
per hour, per inspection booth, per officer, and the equivalent 
officer hours to accomplish the mission. 

[48] More specifically, CBP officials at these crossings told us that 
because of staffing shortages, they have had to reassign CBP officers 
from secondary inspection and other activities such as K-9 patrols to 
open additional primary lanes during periods of high traffic volume. 

[49] Officials with the Port of El Paso, for example, stated that 
Mexican and U.S. business practices generally result in peak times for 
commercial traffic that require increased staffing for only 2 hours or 
so in the morning and afternoon, but union requirements state that CBP 
officers must work in uninterrupted 8-hour shifts. Senior CBP 
officials also reported that the use of overtime allows coverage of 
peak times without hiring additional staff that are not needed to 
cover a full shift. 

[50] CBP's Fiscal Year 2012 Resource Optimization at Ports of Entry 
report states that OFO's overtime budget has decreased by 8.2 percent 
from fiscal year 2008 through fiscal year 2013, thereby lessening the 
agency's ability to use overtime as a means of leveraging existing 
resources. 

[51] See [hyperlink, http://www.gao.gov/products/GAO-02-373SP]. 

[52] See [hyperlink, http://www.gao.gov/products/GAO/AIMD-00-21.3.1]. 

[53] As mentioned previously, the agency's trade facilitation goals 
are articulated in DHS's February 2010 Quadrennial Homeland Security 
Review Report, which outlined a strategic framework for homeland 
security. DHS's two goals related to trade facilitation are (1) 
prevent the illegal flow of people and goods across U.S. air, land, 
and sea borders while expediting the safe flow of lawful travel and 
commerce, and (2) ensure security and resilience of global movement 
systems. See DHS, Quadrennial Homeland Security Review Report: A 
Strategic Framework for a Secure Homeland. 

[54] Pub. L. No. 103-62, 107 Stat. 285 (1993). GPRA seeks to improve 
the management of federal programs, as well as their effectiveness and 
efficiency, by establishing a system under which agencies set goals 
for program performance and measure their results. Specifically, GPRA 
requires executive agencies to prepare multiyear strategic plans, 
annual performance plans, and annual performance reports. The GPRA 
Modernization Act of 2010, Pub. L. No. 111-352, 124 Stat. 3866 (2011), 
amended GPRA to establish a framework aimed at taking a more 
crosscutting and integrated approach to focusing on results and 
improving government performance. Under this framework, organizational 
components of agencies, such as CBP, are not treated separately; 
rather, agencies are to work with their components to identify 
priorities, goals, and performance indicators relative to the mission 
and strategic objectives of the agency. See OMB Circular No. A-11, 
Section 200.1 (2012). In fiscal year 2013, DHS has designated 84 GPRA 
performance measures--9 of which focus on CBP efforts. 

[55] The percent of cargo by value imported to the United States by 
participants in CBP trade partnership programs is a GPRA or strategic 
measure, and the percent increase in travelers to the United States 
enrolled in a Trusted Traveler program is a CBP operational measure. 
CBP's Trusted Traveler programs provide expedited travel for 
preapproved, low-risk travelers through dedicated lanes and kiosks. 
FAST is one of several such programs. 

[56] According to CBP, the intended benefits to participants in the 
FAST trade partnership program include (1) access to dedicated lanes 
for greater speed and efficiency in processing transborder shipments; 
(2) reduced number of inspections resulting in reduced delays at the 
border; (3) priority, front-of-the-line processing for CBP 
inspections; and (4) enhanced supply chain security while promoting 
the economic prosperity of the United States, Canada, and Mexico. 

[57] This definition of outcome comes from OMB Circular No. A-11, 
Preparation, Submission, and Execution of the Budget (Washington, 
D.C.: June 26, 2008). 

[58] OFO and OA officials explained that there is no such measure for 
commercial vehicles because the commercial environment is much more 
complex with more layers of review and the threshold that triggers an 
examination is much lower in the commercial setting. 

[59] Office of Management and Budget, Performance Measurement 
Challenges and Strategies, (Washington, D.C.: June 18, 2003). 

[60] See, for example, GAO, Executive Guide: Effectively Implementing 
the Government Performance and Results Act, [hyperlink, 
http://www.gao.gov/products/GAO/GGD-96-118] (Washington, D.C.: June 
1996). 

[61] See GAO, Managing for Results: Strengthening Regulatory Agencies' 
Performance Management Practices, [hyperlink, 
http://www.gao.gov/products/GAO/GGD-00-10] (Washington, D.C.: Oct. 28, 
1999). In this report we gathered information from 23 federal and 
state organizations that we or other credible sources identified as 
using or planning to use a variety of useful practices to enhance 
specific aspects of their performance management and measurement 
processes. The organizations, although they had different missions, 
sizes, and organizational structures, said they consistently 
recognized that these practices are important in their efforts to 
develop a stronger results orientation. See also The Results Act: An 
Evaluator's Guide to Assessing Agency Annual Performance Plans, (GAO, 
GGD.10.1.20 (Washington, D.C.: April 1998). 

[62] See OMB Circular No. A-11, Preparation, Submission, and Execution 
of the Budget (Washington, D.C.: Aug. 3, 2012). See also OMB, 
Performance Measurement Challenges and Strategies (Washington, D.C.: 
June 18, 2003). 

[63] Throughout this report, we use Customs and Border Protection's 
definition of wait time--the time it takes for a vehicle to travel 
from the end of the queue to the primary inspection point in the 
United States. 

[64] We conducted both subject and key word literature searches 
utilizing more than 20 subject-specific bibliographic databases to 
systematically scan and identify academic, government, and other 
sources. Other sources scanned include gray literature--informally 
published written material--and government sources. We searched all 
sources for scholarly and peer-reviewed material, government reports, 
trade and industry articles, association and think tank publications, 
and working papers. As with any such literature search, there are a 
number of limitations to consider. This scan is a sample and does not 
attempt to review all published or gray literature on this topic. 
Attempting to scan all published and gray literature would be an 
immense task, and searching bibliographic databases represents a 
transparent and well-documented proxy for what is being expressed 
across the broader subject community. We recognize that there is a lag 
time in ideas and research findings making their way into the indexing 
of bibliographic databases as well as a growing amount of peer-
reviewed material being retracted. 

[65] OMB Circular A-94 Revised, Guidelines and Discount Rates for 
Benefit-Cost Analysis of Federal Programs (Washington, D.C.: Oct. 29, 
1992). 

[66] National Center for Risk and Economic Analysis of Terrorism 
Events, The Impact on the U.S. Economy of Changes in Wait Times at 
Port of Entry, April 4, 2013, a report prepared for DHS. The National 
Center for Risk and Economic Analysis of Terrorism Events is a 
university-based center of excellence funded by the Office of 
University Programs of the Science and Technology Directorate of DHS. 
The Center's mission is to improve U.S. security through research and 
development of models and tools to evaluate risks, costs, and 
consequences of terrorism and natural and manmade hazards, and to 
guide economically viable investments in homeland security. 

[67] For the six commercial vehicle crossings we visited in the course 
of our study--Bridge of the Americas and Ysleta in El Paso, Texas; 
World Trade Bridge and Columbia Solidarity Bridge in Laredo, Texas; 
Mariposa in Nogales, Arizona; and Otay Mesa near San Diego, California-
-CBP's study found that having one additional staff member open one 
additional primary inspection lane during the 8 most congested hours 
of the day would result in wait time reductions ranging from 1.5 
minutes to 6.3 minutes and would lead to direct economic benefits of 
$645,000 in GDP (in 2011 dollars) and 6.5 additional jobs. The 
estimated number of jobs created does not include the CBP officers 
added. 

[68] CBP staff at each crossing manually collect and report hourly 
wait time data into CBP's Border Wait Time Administrative Tool. 

[69] The San Diego Association of Governments is a public planning, 
transportation, transit construction, and research agency. 

[70] These organizations and officials were identified to us as 
knowledgeable stakeholders who could provide us with a range of 
perspectives on commercial vehicle traffic at southwest border 
crossings. The American Trucking Associations is a national trade and 
safety organization representing the U.S. trucking industry. The 
Border Trade Alliance is a nonprofit organization that serves as a 
forum for participants to address key issues affecting trade, travel, 
and security in North America. 

[71] CBP reported on the reliability of wait time calculations in its 
Western Hemisphere Travel Initiative (WHTI), Commercial Wait Times 
Analysis Final Report, October 2007 - September 2008. The goal of WHTI 
is to facilitate entry for U.S. citizens and legitimate foreign 
visitors while strengthening U.S. border security. The WHTI Program 
Office sponsored this evaluation of commercial vehicle wait times to 
validate the current wait time reporting systems at individual 
crossings and to determine if a national standard for reporting wait 
times can be established. 

[72] We selected these non-CBP stakeholders to provide us with a range 
of perspectives on commercial vehicle traffic at southwest border 
crossings. The results of these interviews are not generalizable but 
rather provide context for CBP officials' perspectives on these issues. 

[73] GAO, Standards for Internal Control in the Federal Government, 
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00-21.3.1] 
(Washington, D.C.: November 1999). These standards, issued pursuant to 
the requirements of the Federal Managers' Financial Integrity Act of 
1982, Pub. L. No. 97-255, 96 Stat. 814, provide the overall framework 
for establishing and maintaining internal control in the federal 
government. 

[74] Project Management Institute, The Standard for Program 
Management©, Second Edition, (Newton Square, Pennsylvania: 2008). 

[75] The strategic resource assessment is a needs assessment process 
by which CBP collects and analyzes information about the 
infrastructure at each crossing, identifies needs, and prioritizes 
infrastructure improvement projects along the northern and southern 
borders. CBP officials reported conducting these assessments fiscal 
years 2003 through 2006. BorderWizardTM analyses serve as a decision-
making resource/reference for GSA and assist GSA in planning and 
designing land ports of entry. 

[76] For prior work on human capital management see GAO, A Model of 
Strategic Human Capital Management, [hyperlink, 
http://www.gao.gov/products/GAO-02-373SP] (Washington, D.C.: March 
2002), and [hyperlink, 
http://www.gao.gov/products/GAO/AIMD-00-21.3.1]. This report describes 
a human capital model we developed that identifies eight critical 
success factors for managing human capital strategically. In 
developing this model, we built upon GAO's Human Capital: A Self-
Assessment Checklist for Agency Leaders ([hyperlink, 
http://www.gao.gov/products/GAO/OCG-00-14G], September 2000). Among 
other steps, we also considered lessons learned from GAO reports on 
public and private organizations that are viewed as leaders in 
strategic human capital management and managing for results. See also 
GAO, Standards for Internal Control in the Federal Government, 
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00-21.3.1] 

[77] CBP initiated the FAST program in 2002 to expedite the travel of 
low-risk screened shipments across the border. Many land border 
crossings have dedicated FAST lanes to expedite FAST traffic. 

[78] See [hyperlink, http://www.gao.gov/products/GAO-02-373SP] and 
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00-21.3.1]. 

[79] See OMB Circular No. A-11, Preparation, Submission, and Execution 
of the Budget (Washington, D.C.: Aug. 3, 2012). See also GAO, Managing 
for Results: Strengthening Regulatory Agencies' Performance Management 
Practices, [hyperlink, http://www.gao.gov/products/GAO/GGD-00-10] 
(Washington, D.C.: Oct. 28, 1999). In this report we gathered 
information from 23 federal and state organizations that we or other 
credible sources identified as using or planning to use a variety of 
useful practices to enhance specific aspects of their performance 
management and measurement processes. The organizations, although they 
had different missions, sizes, and organizational structures, said 
they consistently recognized that these practices are important in 
their efforts to develop a stronger results orientation. 

[80] Department of Homeland Security, U.S. Customs and Border 
Protection, Land Port of Entry Modernization: Promoting Security, 
Travel and Trade Fiscal Year 2012 Report to Congress, (Washington, 
D.C.: June 2012). 

[81] Pub. L. No. 110-329, div. D, 122 Stat. 3652, 3658 (2008). The 
fiscal year 2010 DHS appropriation included the same language. See 
Pub. L. No. 111-83, 123 Stat. 2142, 2148 (2009). In fiscal year 2012, 
the DHS appropriation included similar language but also required that 
the projected future funding needs be delineated by land port of 
entry. See Pub. L. No. 112-74, div. D., 125 Stat. 943, 949 (2011). The 
fiscal year 2011 continuing resolution and the fiscal year 2013 DHS 
appropriation did not include this language. See Pub. L. No. 112-10, 
125 Stat. 38, 140; Pub. L. No. 113-6, div. D, 127 Stat. 342, 346. 

[82] We included projects completed or in development over the last 5 
fiscal years to provide a perspective on the most recent projects 
completed or under way. We excluded small-scale projects, such as the 
addition of two exit booths at the Bridge of Americas in El Paso, 
Texas, in 2012, because these projects are primarily funded out of 
CBP's Office of Field Operation's operation budget--not GSA's Federal 
Building Fund or American Reconstruction and Recovery Act. 

[83] Pub. L. No. 111-5, 123 Stat. 115, 149. Two of the seven GSA-owned 
land port of entry ARRA-funded projects were for crossings that 
process commercial traffic on the southwest border: Mariposa in 
Arizona, and Santa Teresa in New Mexico. The remainder of the funds 
were for crossings that are located on the northern border or do not 
process commercial traffic. In addition, ARRA also allocated another 
$420 million to modernize 31 existing land crossings owned by CBP. See 
123 Stat. at 162. However, all but three of these projects were for 
crossings on the northern border, and none of the projects were for 
crossings on the southwest border that process commercial traffic. 

[84] We selected these six crossings based on their commercial traffic 
volume, geographic diversity, and representation of a mix of recent or 
ongoing infrastructure modernization projects. 

[85] In fiscal year 2013, DHS has designated 84 GPRA performance 
measures--9 of which focus on CBP efforts. 

[86] The agency's security and trade facilitation goals are 
articulated in DHS's February 2010 Quadrennial Homeland Security 
Review Report, which outlined a strategic framework for homeland 
security. See DHS, Quadrennial Homeland Security Review Report: A 
Strategic Framework for a Secure Homeland (Washington, D.C.: February 
2010). 

[87] According to CBP officials, OFO is the only office within CBP 
that maintains such operational measures. 

[End of section] 

GAO’s Mission: 

The Government Accountability Office, the audit, evaluation, and 
investigative arm of Congress, exists to support Congress in meeting 
its constitutional responsibilities and to help improve the 
performance and accountability of the federal government for the 
American people. GAO examines the use of public funds; evaluates 
federal programs and policies; and provides analyses, recommendations, 
and other assistance to help Congress make informed oversight, policy, 
and funding decisions. GAO’s commitment to good government is 
reflected in its core values of accountability, integrity, and 
reliability. 

Obtaining Copies of GAO Reports and Testimony: 

The fastest and easiest way to obtain copies of GAO documents at no 
cost is through GAO’s website [hyperlink, http://www.gao.gov]. Each 
weekday afternoon, GAO posts on its website newly released reports, 
testimony, and correspondence. To have GAO e-mail you a list of newly 
posted products, go to [hyperlink, http://www.gao.gov] and select 
“E-mail Updates.” 

Order by Phone: 

The price of each GAO publication reflects GAO’s actual cost of 
production and distribution and depends on the number of pages in the 
publication and whether the publication is printed in color or black 
and white. Pricing and ordering information is posted on GAO’s 
website, [hyperlink, http://www.gao.gov/ordering.htm]. 

Place orders by calling (202) 512-6000, toll free (866) 801-7077, or 
TDD (202) 512-2537. 

Orders may be paid for using American Express, Discover Card, 
MasterCard, Visa, check, or money order. Call for additional 
information. 

Connect with GAO: 

Connect with GAO on facebook, flickr, twitter, and YouTube.
Subscribe to our RSS Feeds or E mail Updates. Listen to our Podcasts.
Visit GAO on the web at [hyperlink, http://www.gao.gov]. 

To Report Fraud, Waste, and Abuse in Federal Programs: 

Contact: 
Website: [hyperlink, http://www.gao.gov/fraudnet/fraudnet.htm]; 
E-mail: fraudnet@gao.gov; 
Automated answering system: (800) 424-5454 or (202) 512-7470. 

Congressional Relations: 

Katherine Siggerud, Managing Director, siggerudk@gao.gov: 
(202) 512-4400: 
U.S. Government Accountability Office: 
441 G Street NW, Room 7125: 
Washington, DC 20548. 

Public Affairs: 

Chuck Young, Managing Director, youngc1@gao.gov: 
(202) 512-4800: 
U.S. Government Accountability Office: 
441 G Street NW, Room 7149: 
Washington, DC 20548. 

[End of document]