Aviation Security: TSA's Staffing Allocation Model Is Useful for Allocating Staff among Airports, but Its Assumptions Should Be Systematically Reassessed
Released: 2007-02-28T00:00:00

Letter

Background

Our Nation’s Commercial Airports

There are more than 400 airports in the United States at which TSA provides or oversees passenger and checked baggage screening. These airports, often referred to as the nation’s “commercial” airports, each contain one or more passenger screening checkpoints, and each checkpoint is composed of one or more screening lanes. In addition, airports have one or more baggage screening areas, either in airport lobbies or baggage makeup areas where baggage is sorted for loading onto aircraft. As of October 31, 2006, the nation’s commercial airports contained a total of 761 checkpoints and 2,002 screening lanes at which passengers are screened. These airports can vary dramatically, not just in terms of passenger and flight volume, but in other characteristics, including physical size and layout. Figure 1 identifies the number of commercial airports by airport security category, as of April 2006.

Federal Security Directors (FSD) are the ranking TSA authorities responsible for leading and coordinating TSA security activities at the nation’s commercial airports. TSA had 122 FSD positions at commercial airports nationwide, as of October 2006. Although an FSD is responsible for security at every commercial airport, not every airport has an FSD dedicated solely to that airport. Most category X airports have an FSD responsible for that airport alone. Other smaller airports are arranged in a “hub and spoke” configuration, in which an FSD is located at or near a hub airport but also has responsibility over one or more spoke airports of the same or smaller size.

Performance of Screening Functions at Commercial Airports

Passenger screening is a process by which authorized personnel inspect individuals and property to deter and prevent the carriage of any unauthorized explosive, incendiary, weapon, or other dangerous item aboard an aircraft or into a sterile area. Passenger screening personnel must inspect individuals for prohibited items at designated screening locations. There are four screening functions at passenger screening checkpoints. As shown in figure 2, the four passenger screening functions are: X-ray screening of property, walk-through metal detector screening of individuals, hand-wand or pat-down screening of individuals, and physical search of property and trace detection for explosives.

Typically, passengers are only subjected to X-ray screening of their carry- on items and screening by the walk through metal detector. Passengers who set off the alarm on the X-ray machine or the walk through metal detector or who are designated as selectees—that is, passengers selected by a computer-assisted passenger prescreening system or another TSA- approved process to receive additional screening—are screened by hand- wand or pat-down and have their carry-on items screened for explosives traces, or they are physically searched.

Checked baggage screening is a process by which authorized security screening personnel inspect checked baggage to deter, detect, and prevent the carriage of any unauthorized explosive, incendiary, or weapon onboard an aircraft. As shown in figure 3, checked baggage screening is accomplished through the use of explosive detection systems or explosive trace detection systems, and through the use of alternative means, such as manual searches, canine teams, and positive passenger bag match, when the explosive detection or explosive trace detection systems are unavailable.

History of TSO Staffing Levels and Staffing Models

The Aviation and Transportation Security Act mandated that TSA assume responsibility for passenger and checked baggage screening at the nation’s airports using federal employees within 1 year of enactment. By November 2002, TSA had fully deployed a federal passenger and checked baggage TSO workforce of about 55,000 full-time equivalents to the nation’s commercial airports. This level of TSOs needed to conduct passenger and checked baggage screening was identified by a consultant, relying largely on the number of private sector screeners that had been in place prior to TSA. Subsequently, TSA decided to develop a staffing model to more effectively determine the appropriate number of TSOs needed at the nation’s airports. TSA developed a demand driven model—a model based on flight schedules, connecting flight data, passenger loads, passenger arrival distribution curves, and number of passenger bags along with throughput rates for processing the passengers and bags—in an effort to make screening operations more efficient. This model identified a TSO staffing level of 49,600 full-time equivalents based, in part, on the need for 5.5 TSOs per passenger screening lane. The DHS Appropriations Act, 2004, enacted in October 2003, however, imposed a 45,000 full-time- equivalent cap specific to the number of TSOs.

In May 2003, TSA set out to develop a tool to better define aviation security staffing requirements at airports nationwide by accounting for changes in screening technology, operating conditions, and airline operations. The result of this effort is the Staffing Allocation Model—an optimization model that seeks, within certain TSA constraints, to estimate the most efficient balance of TSOs needed to ensure security and minimize wait times.

As shown in figure 4, TSA uses the staffing allocation model to generate (1) an annual full-time-equivalent total for each airport, known as an “annual allocation run,” and (2) TSO work schedules throughout the course of the year, known as a “production, or scheduling, run.” To determine the annual full-time-equivalent total for each airport, FSDs must first provide input to the model on their airports’ passenger and checked baggage screening configuration. FSDs also provide input to the model on their airports’ busiest month for screening demand based on originating passenger load factors. This “peak month” determination forms the basis of one of the model’s key operating parameters used to compute each airport’s full-time-equivalent staffing allocation. Specifically, for determination of an airport’s annual full-time equivalent level, the model assumes a screening demand based on the average demand day during the airport’s peak month. This assumption is linked to TSA’s 10-minute wait time goal for processing passengers and baggage through security. According to TSA officials, the use of the average peak demand day is intended to ensure that, on an annual basis, 85 percent or more of the total passengers screened in U.S. airports will not have to wait more than 10 minutes to be screened. Once the peak month is selected for each airport, TSA performs the annual allocation run on a representative week within the peak month.

After receiving and reviewing the inputs and assumptions for each airport, TSA runs the Staffing Allocation Model to determine each airport’s full- time equivalent level for the upcoming year. During the run, the model takes each airport’s configuration and peak month screening demand input, combines it with the assumptions regarding baggage and passenger processing, and uses these factors to simulate the flow of passengers and baggage through an airport’s screening areas to provide work force requirements. Then it calculates the total number of TSOs required (expressed in full-time equivalents) for the year based on the results of running the model for the representative week of the peak month. This representative week FTE level is used to calculate the annual FTE estimate for the airport.

After receiving their annual full-time-equivalent allocation, TSA staff at individual airports may periodically run the model throughout the year. As shown in figure 4, during these “scheduling” runs, FSD staff may use the model’s optional scheduling tool to determine work schedules for TSO staff that will satisfy screening demand on a day-to-day basis. Similar to the annual allocation runs, TSA also inputs various historic data into the model during the scheduling runs. This input includes originating passenger load factors, estimates of number of bags per passenger, and passenger arrival distribution curves.

In order to formulate TSO work schedules, the model monitors the passenger arrival patterns and recommends opening and closing lanes at passenger checkpoints to accommodate the demand. The optional scheduling software recommends a mix of full-time and part-time TSOs to satisfy the workforce requirements based on projected screening demand.

According to TSA officials responsible for the staffing allocation model, TSA first ran the Staffing Allocation Model in August 2004 for fiscal year 2005. The model, which did not yet contain complete data on each airport, identified a TSO full-time-equivalent level of 47,865 across all airports. To reach the congressionally-mandated limit of 45,000 full-time-equivalent TSOs, TSA applied a 7 percent reduction to the staffing levels identified by the model across all airport categories. TSA officials stated that they subsequently questioned this approach given that smaller (category III and IV) airports have significantly fewer TSOs and, therefore, were more significantly impacted by the 7 percent reduction in full-time equivalent positions.

According to TSA officials, because the Staffing Allocation Model was not centrally hosted and did not contain complete data, the model may have over-estimated the required FTEs for fiscal year 2005. TSA determined that in August 2005, the Staffing Allocation Model contained complete and accurate data on each airport and the agency used it to identify TSO FTE allocations for each airport, and the output reflecting the total number of FTEs required—42,303—required no adjustment to fall within the congressionally-mandated limit of 45,000 TSO FTEs. According to TSA officials, when TSA ran the model, it did so without imposing a limitation on the maximum number of full-time-equivalent TSOs, including either the 45,000 congressional limit or any budgetary limits. TSA informed FSDs of their TSO full-time-equivalent allocations in October 2005. Figure 6 shows the total TSO allocation, by airport category, for fiscal year 2004—the year prior to implementation of the staffing allocation model—through fiscal year 2007.

FSDs, air carrier representatives, and airport operators we interviewed at the 14 airports we visited stated that TSA’s efforts to allocate a sufficient number of TSOs to screen passengers and checked baggage and minimize wait times have improved over the years. These officials stated that passenger and checked baggage screening has become more efficient as TSA has matured and gained a better understanding of the airport operating environment, and frequent travelers have become more familiar with the screening process.

TSA’s Use of the National Screening Force, Reserve TSO Full-Time Equivalents, and Private Screeners for Certain Screening Needs

TSA sets aside TSO full-time equivalents for needs outside of those considered by the Staffing Allocation Model in the annual allocation run for all airports. In order to handle short-term extraordinary needs at airports, TSA has established the National Screening Force of 615 TSOs who can be sent to airports to augment local TSO staff during periods of unusually high passenger volume. In addition, certain airports may, during the course of the year, experience significant changes to their screening operations (e.g., arrival of a new airline, opening of a new terminal, etc.). For these airports, TSA established a reserve of 329 TSO full-time equivalents for fiscal year 2006 that can be used to augment the existing force. This allocation approach allowed TSA to stay within the 43,000 full- time-equivalent TSO budgetary limit for fiscal year 2006—a staffing level that TSA’s Assistant Secretary stated is sufficient to provide passenger and checked baggage screening.

Lastly, TSA allows certain airports to hire private contract screeners in lieu of TSOs. Under the Screening Partnership Program, six airports have applied to TSA and received approval to hire private contract screener forces as of fiscal year 2006. Despite the fact that these airports do not use federal screeners, TSA still used the Staffing Allocation Model to determine the full-time equivalent screening staff at each of these airports for fiscal year 2006. These staffing levels, as determined by the model, served as a limit on the number of private screeners that the private screening contractors could employ. According to TSA, the 1,702 total full- time equivalent staffing allocation at these airports does not count against TSA’s nationwide ceiling of 45,000 full-time equivalents for TSO staff.

TSA Relies on the Assumptions in Its Staffing Allocation Model, along with Mechanisms for Monitoring Them, to Help Ensure Sufficient TSO Staffing Levels, but Some Key Assumptions Do Not Reflect Operating Conditions

TSA aims to ensure that its Staffing Allocation Model provides a sufficient number of TSOs to perform passenger and checked baggage screening by: (1) building assumptions into its allocation model that are designed to calculate the necessary levels of TSOs to ensure security and minimize wait times, and (2) employing multiple monitoring mechanisms for the sufficiency of the model’s outputs. TSA’s staffing allocation model determined the fiscal years 2005 and 2006 TSO staffing level for each airport based on built-in assumptions designed to ensure the necessary levels of security and to minimize wait times—such as assumptions regarding processing of passengers and baggage through security checkpoints and information about each airport’s baseline configuration— e.g., physical infrastructure. During the first 2 years of the Staffing Allocation Model’s use, TSA established several mechanisms to monitor the sufficiency of the model’s outputs and make adjustments in key model assumptions that do not fully reflect operating conditions for some airports. For example, TSA established a process for FSDs to request revisions to the assumptions used for their individual airports. In fiscal year 2006, TSA granted some, but not all, requests. TSA headquarters also started an assessment to evaluate selected Staffing Allocation Model assumptions, an assessment it expects to perform annually, varying the assumptions it examines each year. However, TSA does not have a mechanism for selecting and prioritizing which assumptions to review each year and for assuring that all assumptions are periodically reviewed. Additionally, FSDs and our own analysis identified concerns with the appropriateness of some of the assumptions for the fiscal year 2006 model. For example, some FSDs stated that TSA’s method of calculating screening demand (the 85th percentile day) to also account for TSO absences from screening did not provide them with sufficient surplus staffing. In addition, the model assumed a ratio of 20 percent part time to 80 percent full time (expressed in full-time equivalents), even in airports that have consistently been unable to achieve a 20 percent part-time TSO workforce; and the model had no mechanism to account for use of TSOs to perform operation support functions.

TSA’s Staffing Allocation Model Seeks to Determine the Optimal TSO Staffing Levels for Each Airport, Relying on Assumptions that Are Designed to Help Ensure Necessary Levels of Security and to Minimize Passenger Wait Times

TSA’s Staffing Allocation Model determined the fiscal years 2005 and 2006 TSO staffing level for each airport using several built-in assumptions regarding security and wait times, in addition to data that reflect each airports’ baseline configuration—e.g., permanent infrastructure and type of screening equipment.

The key built-in assumptions are adjustable and designed to help ensure the necessary levels of security while minimizing wait times and include: The minimum number of TSOs needed to staff each passenger screening checkpoint or baggage screening area based on the standard operating procedures for screening passengers and checked baggage and throughput rates for passenger and checked baggage screening equipment (see app. II).

A 10-minute maximum wait time for processing passengers and checked baggage.

Originating passenger and baggage load factors by airport based on a representative week during each airport’s peak month (the 85th percentile assumption), which TSA expects will give FSDs some time during less busy periods to allow TSOs to obtain required training, perform operational support functions, and take annual or other forms of leave.

A desired ratio of 80 percent full-time to 20 percent part-time TSO staff, expressed as full time equivalents, at each category X, I, and II airport to allow for heavier staffing during busier periods (e.g., the hours when business travelers typically depart) and to minimize overstaffing during less busy periods, times during which part-time TSOs would not be scheduled to work.

Nonpassenger throughput rate of 4 percent.

Rates at which screening equipment have historically signaled the possibility of a threat object and the consequent need for additional screening.

The Staffing Allocation Model used these assumptions, along with other inputs such as each airport’s baseline configuration—e.g., the number and type of checkpoints, security lanes, baggage screening areas, and screening equipment at each airport—to determine TSO staffing allocations for the nation’s commercial airports for fiscal years 2005 and 2006. TSA officials stated that the assumptions used in the staffing allocation model and the other inputs collectively determine the TSO full- time-equivalent allocation for each airport. For this reason, airports with similar screening demand but different checkpoint configurations and types of screening equipment may receive different allocations. For example, TSA officials identified two category I airports that have similar screening demand, yet one airport received almost 50 percent more full- time equivalent TSOs in fiscal year 2006 due to the physical infrastructure differences at these airports. Specifically, one airport has one terminal building, with three concourses, which generally enables passengers to be efficiently routed through one checkpoint in that one terminal. In contrast, the other airport has two separate terminals that prevent passengers from being routed through common checkpoints. This airport’s separate terminals make sharing TSOs among the various checkpoints more challenging, creating a need for additional TSOs, thus the larger TSO allocation. Additionally, we visited category X and I airports with similar passenger volumes and differing TSO full-time-equivalent allocations for fiscal year 2006. According to TSA, in the case of the category X airports, while the passenger volumes for the two airports were similar—17.4 and 16.5 million, respectively—the difference in the type of passengers and the type of baggage screening equipment resulted in one of these airports receiving 26 percent more full-time-equivalent TSOs. Table 1 provides a summary of the various factors that influenced full-time-equivalent TSO allocations for fiscal year 2006 at some of the airports we visited.

The Intelligence Reform and Terrorism Prevention Act of 2004 required TSA to develop staffing standards that provide for the necessary levels of security and minimize delays for passengers. According to TSA officials responsible for the Staffing Allocation Model, the model ensures that the staffing allocations provide for the necessary levels of security because the model is based on TSA’s standard operating procedures for screening passengers and their carry-on items and checked baggage and on the technology available at the passenger checkpoints and baggage screening areas. For example, the passenger checkpoint standard operating procedures require that a minimum of one TSO be staffed for each of the screening functions at a checkpoint. The staffing model includes an assumption (for larger airports) of at least 5.5 TSOs per screening lane— which responds to the need for one TSO per function at every checkpoint and includes a value for supervisors that typically oversee two lanes. In addition, the staffing model provides an allocation for each airport based, in part, on the screening technology at the airport. In addition, the model includes assumptions on alarm rates for various types of passenger and baggage screening equipment and determines the sufficient number of TSOs needed to resolve the alarms at the projected rate to be able to achieve the model’s wait time standard of 10 minutes for processing passengers and checked baggage.

Regarding minimizing passenger delays, a key assumption in the staffing allocation model is that wait times for screening passengers and checked baggage will not exceed 10 minutes when the model is set at a level referred to as the airport’s 85th percentile day, which TSA calculates by estimating screening demand at the level required for a representative week of each airport’s busiest month. TSA officials stated this assumption is based on a goal that was established when TSA was first created within the Department of Transportation. Specifically, the Secretary of the Department of Transportation established a goal that passengers be processed through passenger screening checkpoints in 10 minutes or less—a standard considered appropriate to meet the dual needs of ensuring security while maintaining national mobility. TSA officials stated that they determined that basing the Staffing Allocation Model’s demand level on the representat eiv demand week of each airport’s peak month, coincided with screening 85 percent of passengers within 10 minutes. TSA officials told us that some0 minutes at certain airports passengers will still have to wait longer than 1 that about 7 percent of an at certain times due, at least in part, to the fact the year are expected to e airport’s travel days (about 25-30 days) during xceed the 85 percentile demand day.

As shown in table 2, TSA data for fiscal years 2004 through 2006 show that the nation’s smaller airports (categories II, III, and IV) had shorter average wait times than the standard, overall, with a wait time during peak periods averaging less than 10 minutes, although wait times exceeded this level at certain airports on certain days. Average peak wait times at the nation’s larger airports (category X and I) generally exceeded the wait time standard, overall, although wait times were less than 10 minutes at certain airports on certain days. According to TSA headquarters officials, if airports are consistently exceeding the 10 minute wait time goal, it is the responsibility of the Area Directors to reach out to the FSDs at those airports in an effort to determine whether the root cause relates to staffing, equipment, capacity, or some other issue and to take appropriate remedial action.

TSA officials cited capacity issues as a factor that contributed to category X airports generally exceeding the 10-minute wait time goal during peak periods, as shown in table 2. These airports have higher screening demand than smaller airports and sometimes lack the capacity, with regard to space available for additional passenger lanes and baggage screening areas, to process passengers and baggage quickly enough to have lower wait times. Smaller airports are more likely to have a numbe of passenger lanes and baggage screening areas that are more commensurate with their screening demand than some larger airports th have higher screening demand.

TSA Has Four Mechanisms in Place to Monitor the Sufficiency of Its TSO Allocations and Is Formalizing Its Process for Revising the Model’s Assumptions

TSA has four mechanisms in place to monitor the sufficiency of the TS allocations. First, at individual airports, FSDs and the industrial engineers assigned to their airports are responsible for monitoring their pass and checked baggage screening operations to ensure that the staffing allocation model’s inputs are reliable. A process currently exists to enable FSDs to request revisions to the assumptions used for their individual airports when they believe that a model assumption is unrealistic. As part of this process, FSDs are to submit empirical data to support requests to alter assumptions. Based on TSA’s review of the data, TSA may send an “optimization team” to the airport in an effort to identify the cause of the staffing problem. Optimization teams are composed of experts in passenger and baggage screening operations and procedures , the staffing allocation model, and TSO scheduling. These teams obser ve screening operations and seek to maximize efficiencies by applying practices learned at other airports. the design of passenger and baggage checkpoints, evaluate staffing and scheduling practices, determine compliance with the standard operating procedures, validate the TSO staffing model at the airport, and make adjustments to model assumptions, if necessary. TSA officials stated they are formalizing a process for systematically collecting information o best practices identified by optimization teams so that this information be disseminated across airports. TSA’s solicitation of input from FSDs regarding changes that need to be made to the assumptions that guide their TSO allocations is consistent with our standards for internal co which call for management to ensure effective internal communicatio The reviews are used to help improve ns, for example, by establishing mechanisms for employees to recommend improvements in operations.

January 2007, captures information such as the date of the request; the airport for which the request is being made; the justification for the request; and approvals at various levels, such as the industrial engineer and TSA headquarters. TSA stated that FSDs were previously made aware of the draft form and provided instructions on using this form through various communication mechanisms, including written instructions provided to FSDs and FSD conferences held in September 2006. TSA is also developing a database to record and track the requests made by FSDs, decisions on whether to approve or deny requests, and the basis for the decisions. TSA officials stated that they expect the database to be completed by April 30, 2007.

Regarding the second mechanism to monitor the sufficiency of the model’s outputs, TSA headquarters officials said it is the responsibility of individual FSDs and the industrial engineers assigned to their airports to ensure that the staffing allocation model reflects the configuration of and operating conditions at their airports. Therefore, TSA officials stated that, just prior to the model’s annual allocation run for fiscal year 2006, they system ically solicitedat input from the industrial engineers assigned to the more than 400 commercial airports to determine whether the model contains correct information regarding the configuration of each airport. TSA expects this process to occur annually in order to help ensure the reliability of the data inputs.

As a third mechanism to monitor the sufficiency of the model’s outputs, TSA headquarters officials stated that they continually monitor performance data reported by individual airports to identify any anom that may require further investigation such as high wait times over anextended period of time, lower than expected throughput at passenger lanes, high overtime rates (in excess of 4 percent), and airports with onboard TSO staff consistently below their staffing allocation. In some cases, anomalies identified by TSA may result in an optimization team visit to an airport in an effort to determine their cause. For example, TSA headquarters officials stated that ti s (with the assistance of the staffing allocation model) to determine the an airport with consistently high wait mes (generally greater than 40 minutes during peak periods) may prompt uch a visit. During the visits, the optimization teams perform analyses causes of the problems the airport is having and suggest to the local FSD ways to increase efficiency in the passenger and baggage screening operations to overcome the problems. In some cases, the optimization team may conclude that a change to the Staffing Allocation Model’s baseline assumptions for the airport is necessary. For example, the ai may have lower throughput rates at some of its passenger or baggag e o screening areas than the Staffing Allocation Model assumes, due t different types of screening equipment or the physical layout of the airpor security checkpoints.

Finally, according to TSA officials, in September 2006, TSA completed itsl. first annual review of certain assumptions in the Staffing Allocation Mode This review included an assessment of whether the assumptions under review are still realistic, including assumptions related to screening procedures, technology, screening throughput, and nonpassenger alarm rates; and whether adjustments to the model are needed to make the full - time-equivalent allocation reflect actual operating conditions at airports. nd As a result, as shown in table 3, TSA has changed some assumptions a added others to more realistically reflect actual operating conditions. example, TSA headquarters officials responsible for the model stated the fiscal year 2007 model will provide 4.25 TSOs per passenger checkpoint screening lane rather than the 5.5 TSOs per lane provided in the fiscal y 2006 model—a change TSA officials attributed to the model directly accounting for collateral duties performed by TSOs, TSO time paid but not worked, and TSO training requirements.

Some Key Assumptions Used in the Fiscal Year 2006 Staffing Allocation Model Did Not Reflect Operating Conditions at Individual Airports

FSDs we interviewed reported that the screening allocation model is a more accurate predictor of their overall staffing needs than previous models that took into account fewer factors affecting screening operations. However, these FSDs and our own analysis identified that some of the key assumptions used in the staffing allocation model, during the first 2 years of its implementation, did not reflect actual operating conditions. Specifically, the FSDs identified five weaknesses in the model for fiscal year 2006.

First, 11 of the 14 FSDs identified concerns related to TSA’s basing its estimate of demand levels for the Staffing Allocation Model on a representative week of each airport’s peak screening demand month to allow excess time for training, leave, and other factors not directly considered by the staffing allocation model. Regarding training, 9 of the 14 FSDs expressed concern that the model did not specifically account for the training requirement of 3 hours per week averaged over a fiscal year quarter. Three of these FSDs said they faced challenges in meeting the minimum training requ irements. With respect to annual and sick leave, 5 of the 14 FSDs stated that in their view the model did not adequately account for this leave. Two FSDs stated that the use of the peak demand month to account for training and leave, though sound in principle, is particularly difficult for smaller airports because they do not have as fluctuation between their peak period and their non-peak period, which leaves little cushion in the allocation to accommodate TSO absences from screening duties such as training and annual leave.

TSA headquarters officials stated that TSA determined that using the 85th percentile day concept would more than account for training, leave, and other factors related to TSOs not being available for work because, according to TSA, on only about 7 percent of days do passenger volumes exceed it. Thus, according to TSA officials, the Staffing Allocation Mo set at a high enough demand level to cover screening demand for most days during the year and allow for the extr a time needed for necessary nonscreening time needed by TSOs such as training, leave, and other duties. TSA officials told us that they believe this method of calculating demand provides the necessary level of security and, secondarily, reflects eir responsibility to be good financial stewards of taxpayer dollars, as th using even higher volume days would result in higher costs and perhaps lo for various forms of TSO leave needs, TSA had included an allowance, for fiscal year 2007, in the Staffing Allocation Model equivalents (14.5 percent full-time-equivalent allowa sick, comp, injury, and military eave. wer overall productivity. Regarding the need for an additional allowance nce) to cover annual, Additionally, TSA fiscal 2007 Staffing Allocation Model (an additional 2 percent full-time equivalent allowance) for training that cannot be completed during operational down times. TSA specifically intended this allowance to provide additional assurance that TSOs complete the required training each month onised explosive devices—which TSA has detecting improv identified as the highest threat to commercial aviation security.

TSA officials involved in developing the staffing model stated that they did not plan to assess the extent to which the representative week of screening demand during each airport’s peak month does, in fact, represent actual screening demand for that week. However, officials acknowledged that such an assessment could help verify that, for purposes of the model’s annual allocation run, the resulting allocation provides TSO staffing levels adequate to allow for 85 percent of airline passengers at the nation’s commercial airports to wait 10 minutes or less at security ch eckpoints.

Second, 7 of the 14 FSDs we interviewed stated that the goal of a 20 me TSO workforc percent part-ti e, as measured by full-time-equivale how that the part-time TSO full-time- TSOs, is not realistic. TSA data sanged from visited, as of July 2006, r equivalent level at 13 airports we ith an average of 8 percent. FSDs stated approximately 1 to 38 percent, w 0 percent part-time goa that the 2ime workers, remote airport locations l for TSOs has been difficult to achieve fosit in some locations, TSO base pay that other things, economic conditions most airports because of, acal year 2002, the lack of benefits for part-time mongpart-time TSOs who convert to full-time leading to competition for part-then full-time positions become available. According to TSA, these coupled with a lack of mass tran has not changed since fisd TSOs, and the large number of a status w factors have made the hiring an retention of part-time TSOs particularly 0 percent in the first 2 years of difficult. As shown in figure 6, TSA d ta reflect that, nationwide, part-time ation model (fiscal years 2005 levels of TSOs had not reached 2 implementation of the current staffing allocion’s larger (category X, I, and II) and 2006) with regard to the natalso shows that in fiscal years 2005 and airports. For example, figu re 6 rts had a TSO workforce comprised 2006, the nation’s 26 category X airpoivalents. TSA officials stated that the of about 9 percent part-time equ number of part-time TSOs had increased in recent months.

TSA officials originally assumed that the 20 percent TSO part-time assumption provides the most efficient coverage for airports (especially those in categories X, I, and II) by enabling FSDs to have more flexibility in matching the daily peak-load workflow at airports. Nonetheless, figure 6 shows that, on average, only smaller airports (categories III and IV) came close to or exceeded the 20 percent part-time TSO workforce goal during fiscal years 2004 through 2006.

TSA has recognized that some airports cannot likely achieve a 20 percent part-time FTE level and others (most likely smaller airports) may ope rate more effectively with other levels of part-time TSO staff. As a result, for fiscal year 2007, TSA has modified this assumption to include a variablepart-time goal based on each airport’s historic part-time to full-time T ratio.

Third, 5 of the 14 FSDs stated that the staffing model does not appear to consider new passenger screening procedures that may require addition al TSOs at the checkpoint. For example, one FSD stated that the model h as yet to incorporate the additional TSOs that will be required by TSA’s new Screening Passengers by Observation Techniques program currently being implemented at the nation’s airports. acknowledged that changes to screening procedures could increase the number of TSOs needed at a checkpoint or, conversely, increase wait times at the checkpoint. Therefore, TSA has made changes to the staffing allocation model for fiscal year 2007 to include line item allocations for t new Screening Passengers by Observation Techniques, Bomb Appraisal Officer, and Aviation Direct Access Screening Program security initiatives.

Fourth, two of the five FSDs with in-line checked baggage screening systems stated that in their view TSA overestimated the TSO labor savi that would be achieved as a result of deploying in-line baggage scree systems. TSA headquarters officials responsible for the staffing mode stated that some adjustments had to be made to individual airports’ TSO staffing levels to adequately reflect the configuration of the airports’ in-lin systems, which permit higher throughput rates. Specifically, som have full in-line systems, while others have partial in-line systems that are installed at a particular terminal or terminals. Additionally, TSA officials cited one example in which a category X airport received a reduct TSOs in fiscal year 2005 to account for the in-line baggage screenin system at the airport. However, TSA officials responsible for the staff model later learned that the model had incorrectly assumed that th system was fully operational, when in fact it was still under constructio Officials stated that the FSD at this airport was consequently allocated additional TSO positions. TSA officials stated that the model validation process currently underw ay should help ensure that the model adequately reflects the actual operating conditions at the airport, which highlights the importance of a mechanism to provide assurance that all assumption periodically undergo validation. n.

The “Screening Passengers by Observation Technique” involves specially trained TSOs observing the behavior of passengers and resolving any suspicious behavior through casual conversation with passengers and referring suspicious passengers to selectee screening.

Finally, FSDs identified that the model does not account for TSOs being used in operational support functions. Eleven of the 14 FSDs we interviewed stated that because they are not authorized to hire a suffici ent number of mission support staff, TSOs are being routinely used to perform certain operational support functions such as payroll processing, scheduling, distribution and maintenance of uniforms, data entry, and workman’s compensation processing. At 13 airports January and August 2006, out of a total of 4,710 TSOs on-board at those airports, TSA was using 242 TSOs (about 5 percent) for operational support functions. FSDs and their staffs stated that these TSOs w spending varying amounts of time on operational support duties, some on a nearly full-time basis. As shown in figure 7, nearly 7 percent of T nationwide performed operational support (on at least a part-time basis) during a specific 2-week pay period in fiscal 2006. This percentage was slightly higher for the smaller airport categories. Also, as shown in figu 7, the TSOs performing operational support functions at the airports spent approximately half their time on these duties—38 out of 80 possible hours—during the 2-week period. In addition, TSOs perfor operational support functions at Category X airports spent significantly more time on these duties (approximately 63 out of 80 hours) than TSOs i the other airport categories.

TSA’s FSDs Are Responsible for Deploying TSO Allocations at their Airports, but Face Workforce and Other Challenges to Effective Deployment

TSA has vested its FSDs with responsibility for managing their TSO allocations while considering local circumstances that can affect the staffing allocation model’s effectiveness in deploying the TSO workforce. After receiving the annual FTE allocation from TSA headquarters, the FSD and his or her staff must prepare TSO work schedules, by using the staffing model’s optional scheduling tool or some other method, to ensure that adequate numbers of TSOs are conducting passenger and baggage screening operations, at all times, to ensure adequate security and attempt to meet the 10 minute wait time standard. However, factors outside the model’s determination of overall staffing levels can affect FSDs’ ability to effectively schedule TSOs at passenger lanes and baggage check areas. For example, as previously discussed, few airports have been able to achieve a 20 percent FTE level for part-time staff as assumed by the staffing allocation model in its first 2 years of implementation (fiscal years 2005 and 2006)—forcing FSDs to adjust the scheduling tool based on actual part-time TSOs on board. Also, as of September 30, 2006, approximately one-third of airports had less than 90 percent of their overall TSO positions filled, and nine of the 14 airports we visited were similarly below their staffing allocation. FSDs cited certain other challenges in scheduling TSO staff including injuries and absenteeism, in addition to time spent away from screening duties due to training requirements and operational support needs—factors that the scheduling tool did not directly consider in fiscal years 2005 and 2006. As previously discussed, to address some of these difficulties, TSA has revised some of the assumptions in the Staffing Allocation Model for fiscal year 2007. To address other difficulties, TSA has implemented several human capital initiatives to improve hiring and retention of TSO staff, lessen the impact of injuries and absenteeism, and study the impact of training and operational support demands on TSO time. TSA has not yet assessed the impact of these initiatives on hiring and retention, but plans to do so during fiscal year 2007.

FSDs Are Responsible for Managing to Their TSO Staffing Allocation in Light of Local Circumstances

FSDs are responsible for deploying and managing to their TSO allocation in light of local circumstances, including those that might affect scheduling and pose challenges to most efficiently deploying their resource allocations. At the beginning of each fiscal year, the staffing allocation model identifies the annual allocation of TSOs needed at each airport based on projected demand levels and other factors that make up the model. Nonetheless, this stated allocation is only a starting point. Throughout the fiscal year, FSDs are responsible for preparing TSO work schedules that adapt to changing circumstances at the local level. Specifically, FSDs are responsible for scheduling TSOs to ensure that a sufficient number of TSOs are deployed, from available staff, to meet airport screening needs.

TSA has provided FSDs with an optional tool they can use to facilitate the management of their TSO allocation. Specifically, the Staffing Allocation Model includes a scheduling component that uses the various inpu and assumptions of the model, including the number of checkpoints, la and checked baggage screening machines needed to respond to the passenger and checked baggage load and the minimum TSO staffing levels identified in the standard operating procedures for passenger and checke d baggage screening. This tool is then to produce daily workforce requirements and calculates a work schedule for each airport. The schedule identifies a recommended mix of full-time and part-time staff a total number of TSO FTEs needed to staff the airport on a given day, consistent with a goal of 10 minutes maximum wait time for processing passengers and baggage. In addition, there are several areas where TSA adjusts the scheduling tool to most accurately reflect actual conditions and needs. These areas include: Flight schedule changes. TSO training requirements (based on available times identified by t scheduling tool).

Number of TSOs needed for operational support associated with operating the checkpoint and baggage screening areas.

New passenger and checked baggage screening procedures that affect TSO utilization.

FSDs stated that because the scheduling tool does not contain this information, they must modify the input to the tool, or use an alternative scheduling tool, to deploy their TSO workforce. For example, FSDs and their staffs stated that the scheduling tool does not contain the most current flight schedule data due to the reporting practices of various airlines. During our airport visits, TSA scheduling officers reported that the scheduling tool includes data from as much as 90 days in advance, but some airlines provide their final flight schedules and anticipated passenger volume as late as 1 week in advance—sometimes leaving FSDs little time to ensure adequate TSO availability. TSA officials said that in order to keep their flight offerings competitive, airlines seek to protect their flight data from public disclosure as long as possible. For this reason, TSA headquarters officials said they expect FSDs to work with airport operators and airline officials to obtain the most current data available on which to base their scheduling efforts and to make adjustments to the scheduling tool to ensure that their deployment of TSOs most effectively meets the screening demand.

The nine FSDs we interviewed at category X and I airports reported tha the scheduling tool was useful as a starting point for developing their schedules. However, all six FSDs who said they used the scheduling tool regularly reported making adjustments to the schedule output to more accurately reflect their local conditions primarily because, accordi these FSDs, the scheduling tool does not automatically take into account the actual composition of the TSO workforce at each individual airp in some cases, unique work schedules that may be implemented at so airports (other than a standard 5-day work week). For example, the scheduling tool is based on the model’s assumption of a 20 percent part- time force expresses as a full-time-equivalent level among available staff, although few of the larger airports have been able to achieve this level of part-time staff. Specifically, only 2 of the 26 category X airports had a workforce composed of at least 20 percent part-time staff in July 20 Because the scheduling tool assumes a 20 percent part-time level for TSO FSDs at airports we visited with lower levels of part-time TSOs stated they make adjustments to the scheduling tool’s output to more accu reflect the airport’s actual mix of full-time and part-time TSOs and then develop a work schedule accordingly. In addition, as of September 30, 2006, TSA data showed that approximately one-third of the nation’s airports had less than 90 percent of their annual TSO positions filled According to FSDs we interviewed, however, the scheduling tool ass that each airport has its full TSO allocation on board. Moreover, according to TSA, the scheduling tool assumes that TSOs across all airports have standard 5-day work weeks, although individual a to work varying schedules. For example, an FSD for a category III airport told us that he requires TSOs to work a sixth day once every 4 weeks. However, the FSD at this airport stated that the scheduling tool cannot account for this schedule. 06.

In response, TSA headquarters officials stated that the scheduling tool can indeed account for the actual number of onboard TSOs, the actual mix of full-time and part-time TSOs, and most scheduling anomalies FSDs encounter. The TSA headquarters officials attributed the FSDs’ comments to misunderstandings regarding the full capabilities of the scheduling tool. The officials further explained that the agency has d better job recently in training field staff in the use of the scheduling to ol than was done earlier in the Staffing Allocation Model’s implementation.

FSDs at the four smaller (category II and III) airports we visited state d that the scheduling tool was more useful for larger airports with more complex scheduling challenges given the size of the workforce, the higher passenger volumes, and the larger number of checkpoints and terminals. These FSDs stated that smaller airports can more easily predict their screening demand and generally said they did not believe that the staffing model’s scheduling tool added value to their scheduling process— especially since they are dealing with small numbers of TSO staff and limited passenger and baggage check facilities, for example, having only one checkpoint with few lanes. Therefore, they have chosen to continue use such locally developed tools, such as spreadsheets. However, TSA headquarters officials stated that use of the scheduling tool by all airports will eliminate applications, such as these spreadsheets, that are inconsistent with the Staffing Allocation Model and TSA’s time and attendance reporting system, thereby enhancing efficiency in scheduling TSOs.

While TSA headquarters officials stated that the scheduling tool is capable of preparing schedules for any size airport and accounting for all the issues noted as problems by the FSDs we visited, officials are currently permitting each FSD to determine whether to use the scheduling tool. TS officials stated that technical improvements planned for the scheduling tool will improve its usefulness in preparing TSO schedules. For example, installation of high-speed internet connectivity and implementation of electronic time and attendance reporting will allow the scheduling tool to efficiently maintain up-to-date rosters of available TS according to TSA officials. After these technical improvements are made, w hich TSA expects to be completed in fiscal year 2007, TSA officials told us they may consider making the tool mandatory.

We did not assess the adequacy of training of FSDs because it was outside the scope o our work. scheduling and timekeeping information and provide planned schedule and actual time worked.

FSDs Cited Challenges in Deploying Their TSO Workforce to Perform Screening, and Several Efforts Are Underway to Address These Challenges

All 14 FSDs we interviewed identified challenges they faced in deploying their TSO workforce. Nine of the 14 airports we visited were below their allocation for TSOs as determined by the staffing model. FSDs at these airports cited the inability of TSA’s centralized hiring process to repl TSOs quickly. However, attrition, particularly by part-time TSOs, was also cited as a barrier to achieving and maintaining their TSO staffing levels. TSA has stated a goal of each FSD maintaining a TSO staffing lev less than 90 percent of each individual airport’s TSO allocation. Bas TSA data, approximately 53 percent (237) of commercial airports were either at, or no less than 10 percent below, their respective TSO allocations at the end of fiscal year 2006. Approximately 31 percent of airports (140) were below 90 percent of their allocation, and 16 percent (71) of airports were 110 percent or more above their allocation. Sixty- nine of the 71 airports above thei category III and IV airports. Conversely, as also shown in figure 8, 131 of the 140 airports below 90 per cent of their TSO allocations are airports in categories II, III, and IV. These smaller airports have correspondingly smaller numbers of TSOs; therefore, even small staff fluctuations have a greater impact on being above or below their TSO allocations. Overal mo TSO allocations determined by the Staffing Allocation Model. el of not ed on r allocation were among the small re large airports (categories X and I) have succeeded in meeting their According to TSA officials, airports that are above their allocation must reduce their TSO staffing levels by either (1) attrition or (2) transferring their excess TSOs to airports that are below their allocation. TSA officials also stated that airports grouped together under TSA’s “hub and spoke” organizational structure often share TSO resources as needs dictate.

FSDs we interviewed cited various reasons for attrition, including limited advancement opportunities, need for higher paying job, work hours, difficulty of work, and job dissatisfaction. At the same time, as shown in figure 9, TSO attrition rates, for both full-time and part-time staff, decreased from approximately 24 percent to 21 percent from fiscal year 2004 to fiscal year 2006. However, as previously discussed, the part-tim e TSO attrition rate remains considerably higher than the rate for full-time personnel (approximately 46 percent versus 16 percent for fiscal ye 2006). ar s from their person before going through the walk through metal detector. According to the air carrier, it spent about $15,000 to $18,000 of its own money each month in personnel costs to staff the checkpoints over a 12- hour period most days. In another case, a representative of an airport board for a category X airport told us that in response to concerns about high wait times—wait times exceeding 30 minutes—the airport board spent $1 million to hire a consultant to simulate existing checkpoint configurations and conditions to determine where and how improvements could be made to increase passenger throughput, thereby reducing wait times. As a result of this effort, several improvements were made, including posting a TSO at the front of each checkpoint to facilitate the screening process, posting signage at checkpoints to explain the items that passengers should remove from their person; adding space at end of the x- ray screening belt so that passengers can easily pick up their items without holding up the line; and providing more room for passengers to remove items from their person before they get to the x-ray machines. According to this airport official, these improvements collectively resulted in an increase in passenger throughput from 175 to 200 passengers per hour at relatively low cost. However, the official expressed concern that most airports are not in a position to fund similar projects because they do not have the resources.

TSA Reported Several Efforts Underway to Help Address Challenges in Deploying the TSO Workforce

TSA headquarters officials and FSDs we interviewed reported having several efforts underway to help address some of the challenges they face in deploying the TSO workforce. For example, to allow FSDs to more efficiently address staffing needs, TSA has shifted responsibility for hiring TSOs from TSA headquarters to FSDs at individual airports and, according to TSA officials, provided contractor support to assist in this effort. TSA data show that since local hiring began in March 2006, TSA has increased the number of new hire TSOs from approximately 180 per pay period in February 2006 to nearly 450 each pay period under the local hiring initiative. Additionally, TSA officials stated that prior to the implementation of the local hiring initiative, TSA was able to support hiring at only about 30 airports during any given period compared to more than 100 airports each pay period since the local hiring initiative was implemented. Table 4 provides a summary of the national human resource- related initiatives intended to help increase TSO retention, utilization, and effectiveness.

In addition to these workforce initiatives, TSA also continues to use from the national screening force to address short-term needs at individu airports nationwide. According to TSA, the national screening force is generally deployed only to those airports experiencing significant staffing shortfalls associated with increased seasonal traffic or when a special event—such as a Super Bowl or a large national conference—occurs requiring an immediate influx of additional, though temporary, TSO support. Of the 14 FSDs we interviewed, 6 stated that they had used the national screening force at least once. All but one of these FSDs told us that the national screening force was used to meet short-term screening demand associated with special events and unexpected circumstances, such as heavy passenger loads stemming from hurricanes Katrina and Rit In the other instance, at a category X airport, the FSD stated that, because of challenges in hiring and retaining TSOs for this airport, he has had to rely on about 60 members of the National Screening Force deployed to his airport since 2004. However, in November 2006, TSA officials stated that as of November 1, 2006, there were no National Screening Force TSOs assigned to this airport, which they attributed to TSA’s local hiring initiative. a.

TSA officials stated that they are examining methods for addressing hiring and retention challenges at specific airports where these problems are particularly acute. For example, as shown in table 4 above, TSA has implemented a $500 retention incentive for TSOs at 22 “hard-to-hire” airports who were on-board as of April 15, 2006. As also shown in the table, to help with hiring and retention of part-time TSOs, TSA is piloting a program that offers full health benefits to part-time TSOs at six airports. A these airports, part-time TSOs receive the same health benefits as full-ti TSOs. At all other airports, part-time TSOs do not receive health benefits. In addition to incentives and expanding health benefits, TSA is considering other options for attracting and retaining TSOs. For example, these options include (1) parking allowances, (2) child care, (3) elder care, and (4) tuition assistance.

In addition to the national initiatives underway, several FSDs at the 14 airports we visited were implementing their own local initiatives to address some of the staffing challenges they faced at their airports. For example, after receiving local hiring authority under the nationwide local hiring initiative, one FSD we spoke to stated that he puts brand-new TSO hires out on the passenger lanes as “helpers” so that they may better understand what the job entails. He expects that this will cut down on attrition at his airport and help reduce wasted training resources for TSOs who leave within short periods of being hired. Regarding absenteeism, all the FSDs we spoke to stated that they monitored unscheduled absences and counseled TSOs as needed. To help reduce the number of on the jobinjuries, 6 of the 14 FSDs we interviewed said they had local initiatives, such as injury prevention committees and detailed instruction on safe lifting techniques. To help mitigate inadequate numbers of part-time TSOs two TSA managers we interviewed said that they asked some of their fu ll- time TSOs to work “split” shifts to cover demands in peak periods tha would normally go to part-time TSOs, one of whom might work the first peak period shift and another who might work the second peak period shift. The result was that it eliminated the staffing of full-time TSOs non-peak periods when they were most likely to be idle. The experience these managers illustrates an attempt at an efficient use of TSOs and also the primary reason that TSA has tried to achieve a mix of 20 percent part- time to 80 percent full-time TSOs. Specifically, using part-time TSOs can help to permit adequate staffing during peak periods while avoiding the consequent overstaffing stemming from having the same number of TSOs on duty during non-peak periods. Additionally, to maximize the flexibi lity in staffing passenger and checked baggage screening checkpoints, 3 of the 10 FSDs whose TSOs were not all dual-trained stated that they were working to increase the number of dual-trained TSOs—TSOs trained and certified in both pass 14 airports we visited already had dual-trained TSOs at the time of our v enger and checked baggage screening. Four of the isits.

Given that many of TSA’s workforce initiatives were only recently implemented or are in the planning stages, we could not assess the extent to which these initiatives achieved the intended results. TSA human capital officials told us that they plan to establish performance metrics to use in evaluating their workforce initiatives and use the results of the evaluations to make any needed changes to their approach.

Conclusions

Given the extent to which TSOs hav support functions at airports, TSA h first time in the staffing allocati that FSDs may have to rely on TSOs at some times. However, overrelian limits the availability of TSOs to pe perform, contributes to challenges i number of TSOs are at the right che the investment TSA has made in tra could over time limit on-the-job trai important for TSA to determine under what circumstances it is apprse TSOs to perfopriate to u provide Fs with guidance on when TSOsSD e been used to perform operational as directly accounted for this for the on model for fiscal year 2007. We recogniz to perform operational support du ce on TSOs for operational support rform the functions they were hired to n scheduling TSOs so that the right ckpoints at the right times, undermines ining them in screening functions, and ning opportunities. Therefore, it is orm operational support functions and to can be used this way.

Recommendations for Executive Action

To assist TSA in its efforts to identify TSO staffing levels that reasonably reflect the operating conditions at i that TSOs are effectively utilized, we recommend that the Secretary of ndividual airports and to help ensure Homeland Security direct the Assistant Secretary for Transportation Security to take the following two actions: a formal, documented assumptions in the Staffing Allo ensur he assumptions res accure that t ately r staffing allocations that eflect operating conditions that may change over time. plan for reviewing all of the cation Model on a periodic basis to ult in TSO SOs can be used to provide operational support.

Agency Comments and Our Evaluation

We p February t report, which are reproduced in full in appendix III. DHS concurred with our findings and recommendations and stated that the findings and recommendations are constructive and useful. rt to DHS for review and comment. On 7, we received written comments on the draf TSA also provided comments on our draft report, which are also reproduced in full in appendix III. In its comments, TSA stated that the conclusions of our study are valuable, but TSA wants to ensure that a full and current picture of the state of its workforce management is portrayed. TSA orkforce management initiatives it hhighlighted several of the was implemented. These initiatives were already discussed in the draft report provided and TSA for comm to DHSent.

Rega plan for reviewing all of the assump on a periodic basis, DHS concurred implementing this recommendation as part of its review of the Staffing Alloc TSA has identify a ed that, as partnd prioritize the staffing model assumptions for periodic review. We a irical data to valida studies a methods that should enhance the v to document this new assumption validation process and have it approved by senior leadership. that TSA establish a formal, documented tions in the Staffing Allocation Model and stated that TSA has already begun el assumptions f developing a formal and systematic process that would or fiscal year 2007. DHS also stated of this process, TSA plans to use form te the staffing model’s assumption alidity of TS A’s efforts. TSA also plans rred with our recom DHS also when TS be used to provide TSA’s Offices of Security Operation together to develop a policy that wo to provide operational support. DH final FSDs concerning the use of TSOs in mendation to establish a policy for operational support. DHS stated that s and Human Capital are working uld define when TSOs might be used S also stated that TSA e r degree of structure and guidance to operational support positions.

We will spies of this report tend co the Assistant Secretary of Homeland Security for interested congressional committees as appropriate. o the Secretary of Homeland Security; Transportation; and If you or your staff have any questions about this report, please contact m at (202) 512-4523 or leporeb@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff that made major contributions to this report are listed in appendix IV.

Appendix I: Objectives, Scope, and Methodology

Objectives

The Intelligence Reform and Terrorism Prevention Act of 2004, enacted in December 2004, required the Transportation Security Administration (TSA) to develop and submit to the Senate Committee on Commerce, Science, and Transportation, and the House of Representatives Committee on Transportation and Infrastructure, standards for determining the aviation security staffing for all airports at which TSA provides or overse screening services by March 2005. These standards are to provide the necessary levels of aviation security and ensure that the average aviation security-related delay experienced by passengers is minimized. This provision of the act also mandated that we conduct an analysis of TSA’s staffing standards. To assess TSA’s efforts in developing a staffing allocation model that ensures that it provides the necessary levels of aviation security and that the average aviation security-related delay experienced by passengers is minimized, we addressed the following questions: How does TSA ensure its Staffing Allocation Model provides a sufficient number of Transportation Security Officers (TSO) to pe passenger and checked baggage screening at each airport and what challenges has it faced while implementing the model?

How does TSA deploy its TSO allocation and what factors affect the model’s effectiveness in helping TSA accomplish this deployment?

Scope and Methodology

Our work generally focused on the two major components of TSA’s determination of TSO staffing at the nation’s airports. First, at the T headquarters level, we interviewed (and reviewed documentation provided by) officials responsible for the development, implementation, and ongoing monitoring of the Staffing Allocation Model and its determination of the annual allocation of TSOs to each of the nation’s commercial airports. Second, at the field level, we interviewed TSA staff at selected airports who were responsible for working within their allocation to deploy sufficient TSO staff to their airports’ passenger and checked baggage screening operations.

SA During our design phase, we visited six airports selected based on location, airport category, and participation in TSA’s Screening Partnership Program. Table 5 provides information on the airports we visited during the design phase.

Aft air small airports. We select of categories X, I, and II with a similar number of annual passenger enplanements er completing the design phase of our study, we visited eight additio ports, shown in table 6, representing a geographic mix of large and ed these airports by choosing two airports in each , but which have significantly different passenger wait times and full time equivalent allocations under the Screening Allocation Model. We also selected two additional airports in category III based solely on their geographic proximity to two of the airports we visited in the larger airport categories. All of the nation’s airports in the categories we select (categories X, I, II, and III) to visit collectively comprise more than 90 percent of TSA’s total TSO allocation nationwide.

In total, since we selected a limited nonprobability sample of 14 airports, the information and results obtained cannot be generalized to all airports nationwide. Rather, the results from our airport visits were designed to help identify aspects of the Screening Allocation Model that may not be adequately addressing unique airport characteristics. Also, on a year-to- year basis, TSA may change the data inputs and assumptions used to calculate TSO allocations nationwide and at individual airports.

In reviewing TSA’s Staffing Allocation Model, we did not (1) review the statistical algorithm used in the model, (2) verify the model’s computer programming, or (3) run test data through the model.

More details about the scope and methodology of our work regarding each of the objectives are presented in the following sections, respectively.

Objective One: Use of the Staffing Allocation Model to Provide a Sufficient Number of TSOs to Perform Passenger and Checked Baggage Screening at Each Airport and Challenges Faced While Implementing the Model

To determine how TSA ensures its Staffing Allocation Model provides a sufficient number of Transportation Security Officers (TSO) to perform passenger and checked baggage screening at each airport and what challenges it has faced while implementing the model, we first sought to obtain an understanding of how the Staffing Allocation Model works to provide the appropriate number of TSO staff at the nation’s airports. We interviewed key officials in TSA headquarters responsible for the development and implementation of the model about the inputs and assumptions to the model and how these elements are used to determine appropriate TSO staffing levels. We also reviewed documentation, provided by these officials, on the design and operation of the model. Additionally, we interviewed Federal Security Directors (FSD) and their staff at the 14 airports about how the Staffing Allocation Model considers factors unique to their airports in determining the allocation of TSOs to perform passenger and baggage screening functions. In addition, we asked FSDs and staff about the adequacy of their allocation and their ability to make changes to the model input, for their airport, if necessary. During the visits to category X, I, and II airports, we also interviewed representatives of each airport’s governing authority and one or more of each airport’s significant airline operators, to obtain their perspectives on the adequacy of TSA’s staffing allocations and TSO scheduling practices at the respective airports. In addition, we interviewed representatives of two airline industry associations—the Air Transport Association and the Regional Airline Association—about their perspectives on TSO staffing levels at the nation’s commercial airports. checkpoints and checked baggage screening areas. We also obtained data on the changes in nationwide TSO allocations since 2004 and examined how TSA, using the model, ensures that it has a sufficient number of TSOs to perform passenger and checked baggage screening.

We also examined how TSA ensures the model complies with statutory ry requirements—specifically, whether the model (1) provides the necessa levels of passenger and baggage security, (2) minimizes average passengerwait times, and (3) ensures that TSA remains in compliance with the congressionally mandated full-time-equivalent TSO cap. To that end, we interviewed TSA headquarters officials and reviewed Screening Allo Model-related documentation to ascertain TSA’s approach to monitor performance of the model. We also analyzed TSA’s airport-specific performance data to determine how, if at all, various workforce indica have chang passenger wait times, TSO absenteeism rates, TSO attrition rates, TSO overtime usage, TSO injury rates, number of TSOs devoted to adm Na tors ed since the model was implemented. These indicators include inistrative duties, level of usage of part-time TSOs, and use of the tional TSO force. t the 14 airports, we met with FSDs and other TSA officials to determine e ffing Allocation Model and their level of input into the model’s annu SO allocation process. During our discussions with the FSDs, we iscussed how well the airport’s allocation, as determined by the model, A details on the extent to which they participated in the development of th Sta T d takes into account the unique characteristics of the airport and the T workforce. These characteristics include airport layout, passenger checkpoint configuration, and passenger and baggage screening procedures and equipment. We also examined how the Staffing Allocatio Model addresses changes in air traffic and airport layout, change s in security screening procedures, and changes in screening equipment.

In addition to the discussions with FSDs and other TSA officials, during our airport visits we also physically observed the airport’s passenger checkpoints and baggage screening areas in order to better understand any unique situations or airport characteristics that affect screening operations and assessed the impact of these situations on the model’s allocation of TSOs to the airport.

During the visits to the two similar airports in each of categories X, I, and II, we attempted to determine (1) why one airport received a larger TSO allocation under the Screening Allocation Model, (2) reasons for differences in passenger wait times, and (3) how the SAM allocations at these two airports affected the FSD’s ability to schedule TSOs to pe required security screening activities.

Objective Two: TSA’s Deployment of Its TSO Allocation at Individual Airports and Factors That Impact the Allocation Model’s Effectiveness in Helping TSA Accomplish This Deployment

To determine how TSA deploys its allocation of TSOs at individual airports and addresses other factors affecting the deployment, we interviewed TSA staff at headquarters and at the airports we visited, regarding TSO scheduling and workforce-related factors that can affect these efforts. We also obtained and reviewed various TSO workforce-related data from TSA headquarters pertaining to these factors than can affect TSA’s scheduling efforts at individual airports. These data include airport-specific information on the number of part-time TSOs, absenteeism rates, attrition, overtime, workman’s compensation injury claims, and number of TSOs being used for operational support. In addition, we interviewed TSA headquarters officials, and FSDs at individual airports, about various human capital initiatives TSA is implementing to address TSO workforce issues (e.g., TSO attrition, lack of sufficient part-time staff, TSO absenteeism, injuries, etc.) that affect the deployment of TSOs allocated to individual airports.

At the 14 airports we visited, we met with FSDs and other TSA officials to determine details on their methods for scheduling TSOs allocated to them by the model and their use of the model for this purpose. During our discussions with the FSDs, we discussed challenges they face in scheduling the required number of TSOs to perform screening functions. These challenges include airport layout and associated physical infrastructure limitations, type of passenger and baggage screening procedures employed and type of equipment available, number and mix of available full-time/part-time TSOs, number of TSOs unavailable for work (including those on leave, absent, injured, in training, or performing administrative duties), and experience level of TSOs. We also examined how each airport’s scheduling operation addresses changes in air traffic and airport layout, changes in security screening procedures, and changes in screening equipment.

We also analyzed certain TSA airport-specific performance data to determine how these factors impact FSDs’ ability to effectively schedule their TSO allocation. Finally, we interviewed TSA airport and human capital officials to determine workforce actions TSA has taken to improve or enhance the Screening Allocation Model’s ability to effectively allocate TSOs to the nation’s airports and what other efforts, if any, TSA has underway to enhance its ability to deploy TSOs—specifically with respect to the indicators noted above.

Data Reliability

In addressing our objectives, we obtained the following data from TSA: Staffing by airport, in full-time equivalents, as of September 30, 2006.

TSO staffing allocation, by airport, for fiscal years 2004, 2005, and 2006.

TSO full-time and part-time full-time equivalents levels for fiscal years 2004, 2005, and 2006.

TSO absenteeism for fiscal years 2004, 2005, and 2006.

Workman’s compensation historical claims activity for calendar years 2004, 2005, and first half of 2006.

TSO attrition data for fiscal years 2004, 2005, and 2006.

TSO overtime rates for fiscal years 2004, 2005, and 2006. Number and percentage of TSOs used for operational support for 2-week period ending September 30, 2006.

Deployment of the National Screening Force TSOs as of October 10, 2006.

Airport passenger wait times for fiscal years 2004, 2005, and 2006.

Appendix II: Development and Description of TSA’s Staffing Allocation Model

TSA’s Development of Its Staffing Allocation Model

The Aviation and Transportation Security Act, enacted in November 2001, significantly changed how passenger and checked baggage screening is conducted in the United States. ATSA removed screening responsibility from air carriers and the contractors who conducted screening for them, and placed this responsibility with TSA. As a result, TSA hired and deployed approximately 55,000 federal passenger and baggage Transportation Security Officers (TSO) (formerly known as screeners) to more than 400 airports nationwide. This initial deployment was based on input from a contract consultant and the number of private sector screeners that had been in place prior to TSA. After this initial roll-out of TSOs, TSA developed a demand-driven staffing model called the “GRA” model in order to improve screening operations and make them more efficient. To derive a TSO staffing allocation for each airport, the GRA model used flight schedules, load factors and connecting flight data, passenger arrival distribution curves, and the number of passenger baggage. However, according to TSA, the GRA model did not provide flexibility to react to dynamic changes in the transportation industry. An initial run of the GRA model in 2003 called for an overall staffing level of 49,600 despite a congressionally imposed 45,000 full-time-equivalent cap on the number of TSOs TSA could hire. As a result, TSA had to impose a 7 percent TSO reduction across the board to comply with the congressional cap by the end of the year. TSA decided it needed to improve its existing demand-driven staffing model—the GRA model—to create a more dynamic model that takes into account information about each airport’s configuration, as well as assumptions about passenger and baggage processing.

TSA developed its new model, the Staffing Allocation Model (SAM), with the assistance of a contractor, Regal Decisions (the model was originally called the “Regal” model). As part of the contract requirements, Regal staff and TSA industrial engineers visited airports and met with their Federal Security Directors (FSD) to collect baseline information such as number of lanes, and number of checked baggage processing nodes, along with unique characteuration) of the airports. FSDs had ristics (physical config some input (mostly verification of the model input data specific to their airports) into the process, but were not directly involved in creating the model. Overall, it took Regal and TSA almost a year to get the new Staffing Allocation Model stabilized and ready for initial roll-out. TSA obtained data for, developed, and began deploying the model for testing in the summer of 2004 and first used it for the fiscal year 2005 TSO staffing allocation for the nation’s airports. The latest TSO staffing numbers based on the model (for fiscal year 2006) were sent out to the field in October 2005. TSA was in the process of developing allocations for fiscal year 2007 at the time of our report.

Staffing Allocation Model Components

The Staffing Allocation Model consists of three different components. The first is the “GRA” flight data, which provides information to the model on flight schedules and passenger and baggage volume. These data are fed into the “Regal” software (from Regal Decision Systems), which is a simulation model that replicates each airpornfiguration and t’s co screening process. Finally, the “Sabre” software is a scheduling tool that takes the Regal output, expressed in numbers of TSOs needed to staff security checkpoints in 5-minute increments during the day, and produces an FTE requirement and corresponding TSO work schedules for each airport. Below is a detailed description of the three components that combine to make up TSA’s Staffing Allocation Model.

GRA Flight Data

The GRA flight data uses historical data to determine screening demand at each airport. These historical data include baggage volume, flight and passenger distribution curves, size/type of aircraft, and load factors. The GRA firm obtains these data mainly from the various airport authorities and from published sources such as the Official Airlines Guide. The guide’s flight schedules are provided to the airports 60-90 days in advance. This allows airports enough time to react to potential changes in their passenger flow, and for the FSDs to make any needed changes to the flight schedules listed in the model, so as to account for last minute scheduling changes or added flights that were not originally published in the guide. The updated flight schedules and passenger loads (which represent the screening demand) from the GRA model serve as the input for the Regal software, which determines the number of open lanes and the amount of baggage equipment needed.

Regal Software

The annual staffing allocation for each airport is based on the peak month demand level (derived by reviewing historical flight and passenger/baggage load data available from the GRA software) input into the Regal software, together w configurations and ith data on airport assumptions about passenger and baggage processing (that were not a part of the old GRA demand-driven model). The Regal software uses these input data to simulate the actual flow of passengers and baggage through the airport. The final oeach airport’s requirements (in numberutput— of TSO staff for all passenger lanes and baggage pods, expressed in 5 minute increments throughout the day)—is determined based on the various assumptions outlined in table 7 and discussed as follows: —This is the additional demand for personnel screening checkpoints created by nonpassengers (e.g., airline crews, concession staff, and airport vendors). Based on discussions with TSA leadership and estim s by industrial engineate the model constant for nonpassenger screening demand was set at 4 percent of passenger lane volume. —This is the amount of time passengers have to wait to undergo reening at the security checkpoint. The model sets a threshold of a 10-minute wait before opening additional lanes, if available, based on passenger volumes.

Peak month screening demand—TSA derives the Staffing Allocation Model’s allocations based on originating passenger load factors for the 85th percentile day of each airport’s peak month. In determining the 85th percentile day, TSA must first determine each airport’s peak month by reviewing historical monthly passenger lo month in the airport’s year. According to TSA industrial engineers, selection of the peak month is based on the average demand day (based on passenger load) for each month with the peak month being the month with the highest average demand day. Since daily screening demand data are not reported by the airlines (and, is therefore, not available) TSA must approximate each month’s average demand day b dividing the monthly passenger load data by the number of days in th month. This assumption is linked to TSA’s 10-minute wait time goal fo processing passengers and baggage through security. That is, accordin to TSA industrial engineers, basing the Staffing Allocation Model on th average peak demand day is intended to ensure that, on an annual basis, 85 percent or more of the total passengers screened in U.S. airports will not have to wait more than 10 minutes to be scree Further, based on TSA’s analysis, basing the model on this level ofned. demand may result in TSA taking longer than 10 minutes to screen passengers during 7 percent of an airport’s days during the year. According to TSA, these 25 to 30 days are typically the exceptionall high travel days such as the days before the Thanksgiving and Christmas holidays. Conversely, for purposes of the annual allocation, TSA industrial engineers added that basing the model’s demand level on the average peak demand day may result in TSA screening passengers in 10 minutes or less during 93 percent of the airport’s day s during the year (approximately 335 to 340 travel days over the airport’s year). Lastly, when determining the annual allocation, TSA officials run the model on a representative week during the peak month.

By basing airports’ staffing allocations on their peak month pa volume, TSA intends to ensure that airports will have some staff to accommodate nonscreening activities such as training and annual leave during off-peak periods. In addition, the peak month-based allocation is intended to provide airports with excess staffing capacity to respond to ssenger unforeseen events such as changes in flight schedules, injuries, and sick leave. In addition to nonpassenger screening demand, pass processing wait time, and the calculation of demand, the following assumptions were included in the fiscal year 2007 model: Line item full-time-equivalent allocation for TSO time paid but not worked—In fiscal year 2007, TSA, for the first time, provided a sep line item allocation for the various categories of TSO time paid not worked. These categories include vacation, sick, comp, injury, and military leave. Prior to fiscal year 2007, TSO time paid not worked was indirectly accounted for within the peak month screening demand/85 percentile day assumption.

Part-time staff—TSA sets the SAM to run at a staffing mix of full-time and part-time TSO full-time equivalents based on each airport’s individual part-time to full-time TSO ratio. Prior to fiscal year 2007, TSA assumed the same part-time goal for all category X, I, and II airports— regardless of their actual ratios.

Passenger checkpoint throughput—The passenger checkpoint throughput is the number of passengers that are processed per security checkpoint lane, per hour. The model assumes this to be 200.

Checked baggage processing rates—The checked baggage processing rate is the number of bags that various types of screening equipment will process per hour. Table 7 shows baggage processing rates basedon type of screening equipment and whether the baggage sc system is in-line or stand-alone.

Baggage staffing requirements required to adequately staff screening equipment. As with checked baggage processing rates, baggage staffing requirements vary by screening equipment, whether the equipment is stand-alone or inline, and by airport category. —This is the number of TSO FTEs Staffing per lane by airport category—The model allocates staffing by airport category and by lane type. A standard checkpoint lane is a lane that processes only passengers who are not selectees (i.e., those passengers selected for more intense screening). An integrated checkpoint lane is a lane that processes both standard passengers a selectees. A dedicated checkpo int lane is a lane that processes only passengers who are selectees.

Standard alarm rates—The model assumes specific rates for alarms o screening equipment used at both passenger checkpoints and check areas. The model also assumes a selectee rate for passenger checkpoints.

Sabre Software

Sa re Airline Solutions, Inc., provides the commercial, off-the-shelf b sfo tware for the staffing allocation model’s scheduling tool. The Sabre scheduling tool has three features—Staff Admin, Staff Manager, and Staff Plan. (TSA did not purchase the Staff Manager component.) Staff Admin rosters an airport’s employee group in a database (shifts, schedules, personal information, training, etc.) while Staff Plan recommends a m ix of full-time and part-time TSOs and generates a daily work schedule based on the Regal software’s staffing requirement output. Sabre takes th output and converts it into an full-time-equivalent figure and it determines scheduling plans based on that figure (if the airport uses Sabre for scheduling) using the 80/20 full-time/part-time TSO mix for category X and II airports.

TSA’s Use of the Staffing Allocation Model

TSA uses the Staffing Allocation Model in three different ways—first, it is run once a year to determine the staffing allocation for all airports (annual allocation run). Second, it is run at other times to perform capacity analysis for both lanes required and number and types of baggage equipment required. Third, it is run at other times of the year where airports can tweak certain aspects of the model for scheduling runs without approval from TSA headquarters—for example, to conduct “what- if” scheduling scenarios by changing different inputs, such as passenger flow, or flight schedules. However, they cannot do so for an annual allocation run unless TSA headquarters grants approval to change an assumption for a specific airport. The baseline for an annual allocation run always stays the same and cannot be changed by an airport without TSA headquarters approval. TSA models each airport according to its unique configuration—that is, no two airports are modeled the same because no two airports look the same (nor do they have the same airline traffic profile). FSDs and their staffs typically meet with airline carriers on a continuing basis to obtain updated flight schedules. The scheduling runs to determine TSO schedules incorporate these updated flight schedules whereas, the fiscal runs to determine overall full-time-equivalent allocation, using peak month passenger volumes from historical flight data. If the historical flight schedule used for an annual allocation run is significantly different from current flight schedules at an airport (e.g., a new airline carrier joins the airport), the FSD can submit an appeal to TSA headquarters to re-run the model using the current flight schedule in order to obtain a more accurate staffing allocation for his or her airport. (This has been done on an annual basis or when a significant change in the airport’s flight schedule occurs.) Unlike for annual allocation runs, updated flight schedules are used more frequently for scheduling runs at the local airports without headquarters intervention. elements and assumptions are accurate for their airports and bringing to headquarters’ attention any factors that should be reviewed to determine changes to the model for their airports may be appropriate.

Appendix III: Comments from the Department of Homeland Security

Appendix IV: GAO Contact and Staff Acknowledgments

GAO Contact

Brian J. Lepore (202) 512-4523 or leporeb@gao.gov.

Acknowledgments

In addition to those named above, Maria Strudwick, Assistant Director; David Alexander; Richard Ascarate; Philip Caramia; Kathryn Godfrey; Michael Harmond; Thomas Lombardi; Enemencio Sanchez; Edith S Pamela Valentine; Vaughn Williams; and Greg Wilmoth made key contributions to this report.

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