By Atithi Bharth

– Executive Summary –

Passenger-screening operations at U.S. airports fail to use human capabilities fully for decision-making. Transportation security officers primarily follow a rigid set of procedures by rote instead of leveraging capacities of discovery and curiosity. As standard operating procedures (SOPs) prescribe the set of actions, officers must follow each procedure exactly as described, and they cannot deviate in any way in executing the assigned duties.

Despite—and because of—these requirements, human error has been recognized as the main cause of failure in aviation security in covert testing reports by the Federal Aviation Administration (FAA), the Government Accountability Office, the Department of Homeland Security’s Office of the Inspector General, and the Transportation Security Administration (TSA)’s Red Team from the Office of Inspection.^[1] TSA’s standardized procedures crowd out any opportunity to develop or manage human capabilities or follow human factors principles that influence decision-making, leading to mishaps, as demonstrated by all of the reports, investigations, and negative publicity. Given these challenges, this thesis explored the question of how TSA can optimize human performance at aviation security-screening checkpoints across the United States.

One aspect of the persistent problem involves human factors. In this regard, TSA need not reinvent the wheel. The study of human factors is a rich discipline with substantive data and extensively validated theory. Human error represents a primary cause of failure in numerous covert tests in aviation security passenger screening, but it is not as simple as failing to follow the prescribed procedures and, thus, not detecting the threat. For human operators, errors can happen in one of two ways: either the plan is correct, but the human operator’s performance is deficient (execution failure), or the action occurs as planned, but the plan in place is inappropriate for the situation (planning failure).^[2]

Cognitive and physical factors form the basis of a good human performance model.^[3] Human performance depends on many internal and external factors. For example, internal factors include intelligence, expertise, personality, emotion, and attitude, and external factors include fatigue, time, and stress.^[4] Moreover, neglecting any of these factors can be detrimental to organizations that rely heavily on people to conduct day-to-day operations—such as in airport security.

Several agencies and organizations in the United States and elsewhere manage high-risk or high-consequence occupational hazards with mature policies that account for human factors—for example, Boeing, the FAA, NASA, Australia’s Civil Aviation Safety Authority, the Canadian Nuclear Safety Commission, the U.S. healthcare sector, and the International Civil Aviation Organization. Thus, this thesis aimed to identify practices to optimize human performance while minimizing human error that TSA could implement. Each of these agencies employs effective human error prevention practices and policies as well as continually collects human error data. TSA has the data, but the organization does not analyze it from the perspective of finding the root cause of mishaps.

This thesis focused on human factors that influence performance, so it analyzed human factors policies from these other institutions for their application in processes at TSA airport checkpoints. The purpose was to better understand how leadership views, the agency’s vision, and agency initiatives—all of which make up organizational culture—enhance performance. The thesis also explored how the overall culture within the organizations affected human performance, applying shared perspectives on organizations, different organizational systems, and models that either enhance or hinder performance.

This thesis arrived at the following conclusions about TSA’s need to optimize human performance among its passenger-screening personnel:

1. Assessments of these failings lack human factors’ guiding principles, a perspective of organizational causes, and insight into why the failures occur.
2. Automation, advanced equipment, and rigorous procedures do not eliminate human error.
3. The term “human error” signals a need to investigate the reasons for the mistake related to organizational processes, technology’s impact on cognition, and the behavior of human operators.
4. TSA’s nine-member human factors team is significantly smaller than that of other agencies.
5. Although TSA’s human factors staff is small with a minimal budget, it has collected significant data.
6. Employees’ noticeable lack of trust in the agency and lack of motivation characterize TSA’s organizational culture.
7. TSA’s SOPs are too prescriptive and do not allow for autonomy, mastery, and purpose—three core principles of intrinsic motivation that drive performance.

TSA’s operational model for security operations is manageable as it is. Thus, the following recommendations should be implemented according to TSA’s most current model, as differences in the make-up of the workforce, culture, and environment may have unique impacts specific to each location.

Human Factors Team

1. TSA should augment the human factors team with more resources and financial support, as well as develop formal human factors doctrine and policies outlining duties, responsibilities, and expectations.
2. The human factors team should coordinate with the International Civil Aviation Organization to glean best practices, as it has implemented a robust human factors program within the aviation-screening environment.
3. TSA human factors team should develop a comprehensive training program that educates all leaders of the aviation security operation about the pitfalls of pinpointing a single cause or assigning blame.
4. TSA’s human factors team should be at the forefront of developing a framework for new SOPs that allows TSA officers to use discretion, working especially with leadership at the Office of Security Operations and the Security Requirements and Capability divisions.

Training Model

1. TSA should move away from a one-size-fits-all training model.
2. TSA headquarters should provide solely a framework for SOPs—in other words, a catalog of standards to drive clear performance outcomes—while local training departments develop and execute technical training for each new hire based on their needs.
3. The overall efforts of the training department should build skills rather than issue remedial sessions that reinforce a mindset of following the SOP.

Data Collection/Analysis

1. Existing data should be analyzed by region to identify, report, and resolve problems affecting performance locally, perhaps requiring at least one human factors specialist per region to lead such efforts.
2. TSA should conduct a Federal Employee Viewpoint Survey at the local level to narrow down problems related to morale and turnover, communication failures and team conflicts, employee perceptions of policies and procedures, and workforce motivators.
3. TSA should sponsor a pilot study at select airports to gauge the effectiveness of a new training and operational model vis-à-vis the status quo.

TSA must understand that rapid gains in technology and procedures alone cannot achieve the desired performance in the aviation ecosystem because people are vital links in the chain. TSA must continue to focus on providing the framework and optimal operating systems for officers to exercise good judgment so that decisions related to human performance are well guided.

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^[1] Gerald L. Dillingham and John R. Schulze, Aviation Security: Long-Standing Problems Impair Airport Screeners’ Performance, GAO/RCED-00-75 (Washington, DC: General Accounting Office, 2000), https://www.‌gao.‌gov/assets/rced-00-75.pdf; Gerald L. Dillingham, Aviation Security: Slow Progress in Addressing Long-Standing Screener Performance Problems,GAO/T-RCED-00-125 (Washington, DC: General Accounting Office, 2000), https://www.gao.gov/assets/t-rced-00-125.pdf; Gregory D. Kutz and John W. Cooney, Aviation Security: Vulnerabilities Exposed through Covert Testing of TSA’s Passenger Screening Process, GAO-08-48T (Washington, DC: Government Accountability Office, 2007), https://www.gao.gov/assets/gao-08-48t.pdf.

^[2] “Human Error Types,” SKYbrary, accessed November 11, 2017, https://www.skybrary.aero/‌index.‌php/Human_Error_Types.

[3] Khaliah Hughes et al., “A Preliminary Study of an Integrated Human Performance Model,” Proceedings of the IIE Annual Conference (2010), ProQuest.

[4] Hughes et al.