Team 1: TSA

Process Inefficiencies, Upstream Data Collection, Customer Segmentation

TSA Process Inefficiency

Manon, Fabrizio, Justine

Problem Statement

The TSA is the government-established airport security program that aims to provide safety and security for passengers traveling through airports and other public forms of transport in America. TSA protects the nation’s transportation system that screens 2 million passengers daily. Currently, the TSA does not instill a policy that requires travelers to provide any personal data due to the Privacy Act of 1974. The lack of data has made it difficult to do profiling on travelers which creates segmentations on the level of screening process. Therefore, the lack of TSA process efficiency has led to increase security risk and an increase in wait times which is 30 minutes or longer for regular standard lanes.

How should the TSA improve their processes to ensure security and efficiency?

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Strategy

Consistent Improvement

Integrated Systems

TSA needs improvement on the current screening methods for safety:

• Increase weapon detection rate above 30%,
• Decrease wait time averages from 30 minutes
• Optimize TSA’s process segmentation operations to fully utilize technology for pre-screening

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Collect data Do profiling Asses risk of traveler Customer segmentation Utilize in person security screening technology

Key Insight: TSA maintains its position as securing traveler safety with gradual improvements that attempt to enhance the process efficiency to improve passenger safety, and reduce time.

Trade-off

FAST TURNAROUND (WAIT TIMES) (-)

• Wait times are long. Travelers wait 30 minutes or longer to pass by TSA security lanes on Standard lines and 10 - 20 mins on Pre checks.
• Screening times are long because of security inspection procedures (taking off belts shoes, laptops, carry-ons into x-rays, going through body scanners and metal detectors and random baggage inspections) for standard lines which may take 30 minutes or longer.

HIGH QUALITY (SECURITY) (-)

• TSA has low weapons detection rate with only 30% of weapons detected in 2017.
• Some travelers out of the 740 Million pose more risk than others but are screened in the same lanes as people with less risk, making screening process less efficient by putting less focus on higher risk travelers.
• Only 10 Million travelers follow policies to in showing background data to be eligible for pre-check lines, which are more secure and faster than standard lines.

LOW COST (BUDGET) (+)

• TSA has sufficient budget for staff, training

(2,000 officers trained in behavior detection, 1,000 canine teams) and technology (x-ray machines, metal detectors and body scanners) for inspection but not efficient security process procedures that results to fast turnaround and high quality screening.

Key Insight: TSA is trading off long wait times and low quality security detection due to the current TSA screening process used for all types of travelers since there are no policies that that helps identify travelers with higher risk for more focused screening.

Triple Constraints

Technology: (10%): There are 950 advanced imaging technology machines with privacy protecting software working at the airports in the U.S. For standard lines, TSA use full body scanners and full body pat down; for PreCheck lines, they use metal detectors. The TSA currently uses biometric technology but is used voluntarily based on traveler consent and not mandatory due to consent policy

People: (30%): By making more specific security screenings, 43,000 transportation security officers and 600 aviation transportation security inspectors should be familiar with different screening equipments and know which technology should be used for different traveler risk level. The travelers also has a role in their safety by providing their data for background checks as a source of information to create segmentation for different levels of screening processes.

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Process: (60%): The TSA is responsible for the process of doing policies in acquiring traveler data to create travel profiles for segmentations in order to improve the efficiency through strengthening the security processes through the diversion of different levels of screening processes therefore cutting down current waiting times of 30 minutes or more and increasing security detection rate of more than 30%.

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Key Insight: Process inefficiency resulting in security issue and long lines is due to the process of forming policies to gather data for customer profiles for different security levels of segmentations in order to better direct the people to proper action as well as the use of technology according to the appropriate procedures of each segmentations to maximize efficiency.

SIPOC

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Key Insight: Limited Segmentation process causes increase in wait times due to the long process of screening for standard lines. Increase in traveler segmentations based on background status, criminal record status, flying frequency records will improve process in security screenings therefore improving efficiency in security and in effect create faster wait times and shorter lines. This can be achieved through revision of privacy policy of 1974 to update TSA’s right to collect useful information for segmentation.

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3 Questions

1. What are we trying to accomplish?
1. Implementing a more effective use of proven successful processes that will increase efficiency while increasing traveler safety.

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• How will we know when a change is an improvement?
• We could measure the change as an improvement by comparing ourselves to the most progressive security processes around the world, such as the one in Israel. A measurable improvement would be a significant decrease in profiled passengers based on behavioral detection processes and a decrease in wait time through TSA checkpoints.

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• What changes can we make that will result in an improvement?
• A critical change in which the TSA could make would be to implement more advanced technology such as using biometric data to quickly identify and give the TSA concrete data on passengers. Testing shows that biometric data screening yields over 99% positive matches in identifying passengers using facial recognition.

Key Insight: The TSA needs to implement more progressive processes in order to increase security and efficiency throughout all airports. In order to achieve this, they will need to implement more biometric data which would decrease both profiled travelers based on behavioral detection and wait times through TSA checkpoints.

Ladder of Inference: Frequent vs Infrequent Travelers

Ladder of Inference: TSA management vs TSA employees

5 Why’s

Key Insight: There is an overall process inefficiency problem in making policies for collecting traveler data in order to create profiles for customer segmentations with different levels of screening process to better focus on travelers with

higher risk. Improvement on security detection rate and wait times heavily relies on overall process efficiency.

Problem: Process inefficiency resulting in security risk and longer wait times.

Root Cause Analysis

Problem:

Process inefficiency resulting in security risk and longer wait times.

Domain: Policy on Data Privacy

Domain: Traveler Data

Domain: Traveler Profiling

Domain: Screening Process

Key Insight: There are no policies that support process of gathering data to create traveler profiles for segmentations

on screening process based on risk.

Gain Insight: There are no policies that support process of gathering data for profiling and segmentations screening process based on risk

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Subcause:

Only gathered for Precheck travelers.

Subcause:

No Policy due to Privacy Act of 1974

Subcause: Biometric Background check is only voluntary

Subcause: Screening Process takes longer than 20 - 30 minutes

Subcause: Goes through a lot of screening procedures about 5.

Subcause: No Data to base different customer profiles

Subcause: Equal Assessment of travelers

Subcause: Background checks only mandatory for Pre-check eligibility.

Subcause: Takes time and process to gather data records on flight frequency and criminal records.

Subcause:

Biometric technology collects Insufficient data due to the voluntary policy due to the privacy act

Subcause: Equal screening for different types of travelers regardless of risk level.

Subcause: There are experimented proposals such as expedited lanes for certain travelers but was never implemented

Subcause:

No source of data for most travelers.

Flexibility Matrix

Schedule (Least): The U.S. and screens more than 2 million air passengers daily. It takes time to make everyone involved, so the schedule should be strict in order to shorten the transitional period and achieve improved segmentation process as well as eliminate inefficient processes routines that have lead to failure

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Scope (Most): The segmentation process will be implemented to 440 U.S. airports and 750 Million total travelers which is a large scope. The security issue could be related to each corner of the nation and a huge number of the US population, so the scope of segmentation process to increase process efficiency and safety should cover all security checkpoints and passengers independent of airport size, or population

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Resources (Somewhat): Efficient processes corrections can be improved through technology and privacy policy improvements, however TSA employees, (including over 43,000 transportation security officers and 600 aviation transportation security inspectors) are essential in contributing their working hours, capabilities, and morals toward the changing process

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Key Insight: The constraint of least flexibility for improving process inefficiencies would be schedule. Being that TSA serves such a large amount of foot traffic daily, this duty requires efficient allocation of time spent ensuring the safety of passengers while being considerate of their time. Scope would be the most flexible being that a strong implementation of process would be applicable to airports at any scope, small, medium, and large.

Change Curve

Project Complexity

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Key Insight: The process segmentation falls under Type 3. The clarity of solution is unclear since we have no evidence or assurance of whether privatizing tsa, modifying the privacy policy or implementing new technology will actually improve safety for travelers and reduce lines. Therefore, it is a type 3 project for the management or analyst.

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The project complexity of Process Inefficiency is Type 3. The clarity of the problem is unclear in terms of where the process breakdown is happening. We know that TSA wait times are an average of 30 minutes and that the conservative percentage for failure of weapon detection rate is 70%. However, that doesn’t tell us whether the technology is inefficient, the workers lack skills, or if the policy that withholds the current TSA screening process is faulty.

Likewise the solution is unclear since all the feedback we have from customers are that the lines are long and feedback from data collected is that the current scanning system is inefficient. It is up to the analyst or the management’s job to accelerate an evolution in figuring out the type of problem and kind of solution on the segmentations of the travelers.

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TSA Process System Map

Security

Faster Process

Safety

Efficiency

Traveler profiles

Efficient Screening

Segmentations based on risk

Policy in gathering traveler data

Use of Biometric Machines

Doing Screening Process

Traveler Data

Screening Machines

Key Insight: Without policies and biometric machines, there is no safety without efficient screening processes.

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Power of Lean

Business Scope

Problem

Data

Frameworks

Insights

Requirements/ capabilities

Scope: All 19,700 airports within the US.

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Problem: Process inefficiency resulting in security risk and longer wait times.

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Data: 740 Million Travelers going through Metal Detectors and Body Scanners in standard lines. 1.4 million Baggages going into Screening Machines daily. 10 Million Travelers going through Metal Detectors in TSA Precheck lines.

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Frameworks: strategy, trade-off, triple constraints, SIPOC, 3 questions, ladder of inference, 5 whys, root cause analysis, flexibility matrix, change curve, project complexity, system map

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Insights: All 19,700 airports within the US are sticking to the same process they have been using for years, with no plans of advancing towards more progressive and effective technologies. Their policies are restricting them from using any personal data, therefore moving towards altering their policies will eventually create a more effective and safer process for all travelers.

TSA - Upstream Data Collection

Janet, Samantha, Muaz

Problem Statement

The TSA is a government airport security program that protects the nation’s transportation system that screens 2 million passengers daily. The only current upstream tactics that TSA implements are specific passenger lists such as the No-Fly List, Terrorist-watch, and the Secure Flight program as well as data collection tactics such as behavioral detection.

However, none of these tailored activities are upstream enough to provide a sound and comprehensive approach to segmenting clients and luggage based on supposed security risk. The effect being that most customers are treated the same despite possible differences in the danger that they present. As a result, in 2014, 98% of travelers who applied for the DHS Traveler Redress Inquiry Program (DHS TRIP), which manages traveler inquiries of improper selection for secondary screening, were concluded as false positives. This suggests that the current process of “risk segmentation” that TSA performs results in a significant number of passengers who are wrongly seen by the TSA as potentially high-risk.

How can TSA move upstream in its data collection process to improve its segmentation of clients?

The Power of Lean

Strategy

• Activities that fit together in an integrated system

Apart from their own existing resources, TSA relies on other government enforcement entities, such as FBI, CBP, and DHS, to collect traveler biometric data, travel documents, and suspected terrorist lists. TSA initially tried to integrate biometric technology into TSA PreCheck program which was an existing system for expedited security screening. In June 2017, TSA collected fingerprints from PreCheck members during the criminal background checks and started to test fingerprint technology for TSA PreCheck members at Hartsfield-Jackson Atlanta International Airport and at Denver International Airport.

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• Consistent Improvement

TSA realized the current data collection process is only limited to some travelers, such as PreCheck members. Their objective was to figure out an uniform way to effectively collect traveler information without violating their privacy. According to the official TSA Biometrics Roadmap, TSA is planning to deploy Credential Authentication Technology (CAT) - authenticate the security features of passengers' ID credentials and allow Transportation Security Officers to retrieve passenger pre-screening status in near-real time. TSA also foresees the advantages of implementing facial recognition technology in a large scope within the U.S.

Key Insight: To make the data collection upstream, TSA should strategically select data from different carriers and agencies based on all types of travelers in order to make comprehensive risk segmentations prior to the security checkpoint.

Trade-offs

Cost (+)

TSA has always and will continue to work under budget constraints. It expected.

However, continuing with the current standard is cheaper than transitioning to a new system of data screening. The introduction of biometric technology proposes a high cost relative to the current budget. Furthermore, Aviation Screening Operations is approximately $5 million out of the $6.7 million sub-total set my TSA’s Mission 1: Prevent Terrorism and Enhance Security.

Public Opinion (+)

Implementation of a new system impeds threat on current public option. The general public sees further data collection as an invasion to privacy rights. Stakeholders are also resistant due to potential risk. On the other hand, TSA Pre-Check and Global travelers are open to further screening and data collection, as they willingly volunteer for biometric pilot testing. As a result of caution, TSA provides transparency to new technologies or privacy changes to the public.

Risk Segmentation (-)

As a result of maintaining consistent costs and public opinion, TSA is unable to fully implement new technologies for screening. This is also partially due to long procurement processes that restrict upstream data collection. TSA must receive aid from partners and the industry to leverage costs of new data.

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Current State: TSA uses the Secure Flight program to screen passengers through the No-Fly List, Terrorist List, and SSSS. To verify traveler’s identify, TSO’s physically check identity credentials and travel documents.

RISK

SEGMENTATION

PUBLIC

OPINION

COST

INSIGHT: TSA tradeoffs innovation within risk segmentation with a balance between public opinion and cost. When a new technology emerges from TSA, such as biometrics, which was introduced after the Modernization Act of 2018, the priorities of both public opinion and cost are compromised in turn for improved risk segmentation. TSA is currently working on balancing all three.

Triple Constraint

Technology: (20%): Data collection somehow relies on technology, but the existing technology, such as biometrics, is doing well in profiling traveler data. The number of travelers who experienced biometric exit using CBP’s matching service increased 54% from 2018 to 2019. The technologies don’t need much improvement as long as the TSA keeps the efficiency and implements to a larger scope.

People: (10%): The Security Flight program requires national and international aircraft operators to collect passengers’ both personally identifiable information and non-personally identifiable information and transmit data to TSA. People are not significantly needed if an improved data collecting process relies more on other reliable agencies.

Process: (70%): The TSA builds traveler database to determine travelers’ risk level by partnering with CBP, DHS, FBI, and airline companies. Since 2017, the TSA has begun collecting fingerprints from PreCheck members during the criminal background check before they enroll the program. To further exclude the risk, they also use No-Fly List and Terrorist-watch to ban the high-risk travelers from flying. As of June 2017, approximately 1.16 million people were on the watchlist. Up to now, TSA only does upstream data collection among a limited number of travelers.

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Key Insight: Many non-TSA PreCheck domestic travelers do not have biometric data on file with the U.S. federal government are still required to experience physical travel documents check and manual inspections which are considerably consuming TSA’s resources and making the data collecting process downstream.

3 Questions

1. What are we trying to accomplish?
1. Improve the TSA’s data collection process upstream to build up a strong and useful database of travelers.
2. Transform manual identity verification process in most of airports to a safer and automated technology-based process
3. Enhance security and improve traveler experience
2. How will we know when a change is an improvement?
4. The number of false-positives reduces
5. The biometric confirmation rate increases from 85% to 95%
6. By verifying the identifications of 2.5 million passengers fly through U.S. airports every day, TSA reduces the error rate from 2% to about 0%
3. What changes can we make that will result in an improvement?
1. Evaluate current database of travelers
2. Identify and remove the obstacle that prevent a upstream data collection process
3. Select and integrate the resources from all government intelligence agencies that TSA partnered with into a comprehensive database which covers all travelers’ information
4. Inform the public about the details of risk segmentation, including demonstrating clear and uniform standards of being on the no-fly list and terrorist watch list.

Key Insight: To move the process upstream, TSA may enlarge the scale of intelligent data collection, while keeps the performance of TSA employees and biometric technology.

System Map - Data Collection

Ability to gain upstream data collection

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Identifying traveler risk before booking

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Automate parts of the screening process (Identity verification)

Using an API between TSA technology and customer database

Limited ability to gain customer information through government databases

Ability to reduce airport screening process

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Traveler safety at the airport

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Airport security

100% of travelers are screened through the Secure Flight Program

Airlines transfering traveler booking information to TSA

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Database from government agencies (FBI, DHS, CBP, etc)

Traveler commitment/consent to privacy alterations (49% of Americans are not comfortable with the government’s ability to collect data)

Effective biometric technology (currently has 85% accuracy)

TSA employees commitment to process changes

Modernization Act of 2018

Having an API connecting TSA and customer database

Airline consent to the use of biometric technology

Airlines are mandated to provide traveler booking information to TSA

Privacy policy that allows for minimal data collection (name, date of birth)

Systems Map - Data Collection

Key Insight:

The red and orange highlights the pain points in the Data collection system, with red indicating a more severe paint point. The TSA’s limited ability to collect information from government agencies prevents the use of 3rd party websites such as travel sites, social media and tax information, resulting in the inability to move upstream in data collection. Furthermore, 49% of Americans do not feel comfortable with the government’s ability to collect data, resulting in the lack of support from travelers. This inhibits TSA’s ability to collect personal information, resulting in insufficient ability to verify traveler risk.

SIPOC: Current State of TSA Data Collection

Key Insight: TSA security officers are only present in the checkpoint phase of the passenger airport process. In addition, the information that TSA collects is only compiled and verified during the checkpoint phase. Data collection in only one phase of this process is insufficient to initiate effective customer segmentation.

5 Whys: Process

Problem: TSA’s data collection prowess is minimal compared to other airport security apparatuses in other countries. This is severely limiting their ability to collect data on possible threats from different kinds of travelers.

5 Whys: Policy

Problem: The TSA has, until very recently, lacked the legal backing from Congress and federal legislation to improve and augment its authority to effectively screen and scan passengers and luggage

Key Insight from 5 Whys: The TSA is not as ubiquitous as people may believe, only being responsible for some stages of the airport security process. In addition, the powers and capabilities it is imbued with are heavily dependent on Congressional legislation and the interplay it has with CBP and other players.

Root Cause Analysis

Key Insight: Some of the main obstacles to more comprehensive data collection are the public’s commitment to data privacy, inflexible legal policy, and slow roll-out of new technology and process innovations. These are all hindering the TSA’s ability to move further upstream.

Flexibility Matrix

Schedule (least Flexible): Since the TSA is taking charge of the security of 450 airports in the U.S. and screens more than 2 million air passengers daily and over 750 million every year, an improved data collection strategy takes a long time to make clients and employees to test and implement. To ensure the public security, they should start as soon as possible.

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Scope (most Flexible): The data collection covers 750 Million total travelers which is a large scope. The security issue could be related to each corner of the nation and a huge number of the US population.

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Resources (somewhat Flexible): To build a significant traveler database, the TSA uses their own existing resources and also greatly relies on other government intelligence agencies, such as FBI, CBP, DSL, etc.

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Key Insight: An upstream data collection should be developed by maximizing the utilization of existing database of the TSA, cooperating with other partner systems and interfacing reliable resources from outside.

Project Complexity

INSIGHT: The complexity on the use of data varies by need. By booking a ticket, personal data is collected to abide by the Secure Flight Program, but when travelers resist this process the solution becomes unclear because of policy. If travelers do not support TSA policy changes, they will be unable to board flights and TSA will experience resistance.

Project Complexity

INSIGHT: With increasing traveler risk, airport security screening procedures increase. To gain understanding of traveler security risk, data collection is moved upstream which make the problem more complex and policies regarding privacy and thus, customer acceptance is needed. Currently TSA faces complexity regarding future data collection measures to increase security segmentation while adhering to customer wants.

Change Curve - TSA

Though TSA was built on the foundation of transportation security, rules continue to be added, removed, and altered. Screening for threat continues to be a priority in the agency, but the priorities have changed. TSA began with adding additional rules prompted by threats to reinforce the physical screening process, but there was little done in prior risk assessments of passengers. In 2010, the wide implementation of Secure Flight allowed for a minimal level of security screening. The limited risk segmentation and false positives pushed TSA into further exploration, leading to a focus on technological innovation resulting in the 2018 Reauthorization act. Though TSA has committed to furthering testing and leverage resources, there is still the question of how it will occur and if these innovations will lead to upstream data collection.

Ladders of Inference

INSIGHT: With the intention to be transparent with the public to aid in the acceptance of new technologies, there is a disconnect of what biometrics will result in. TSA and Prescreened Travelers, see biometrics as a way to streamline the customer experience (prescreened travelers are experienced with TSA collected their data from background checks) while standard travelers focus on the potential of privacy invasion and unwanted data collection.

Ladders of Inference

INSIGHT: This ladder contrasts two groups with negative feelings towards TSA biometrics plans, with Digital Rights Groups being the extreme. In contrast to the previous ladder, the disconnect is lower due to the strong feelings of Digital Rights Groups. The group quickly develops a hyper focused view on biometrics concerns in both privacy and accuracy aspects with strong negative opinions against all, not just TSA’s, proposals of using saved data.

Ladders of Inference

This ladder further divides Standard Travelers into two categories - those who have experienced false positives by TSA’s Secure Flight and those who have not - to understand the perceptions on increasing upstream data collection. This disconnect begins to occur during the assumption stage as both groups understand TSA can improve, but have different assumptions according to their experiences. Those who have experienced being false positives have directly encountered TSA pre-screening flaws and are thus more willing to provide private data if it means more accurately proving their identity.

Change Curve

The process implementing biometrics has received mixed reviews from both stakeholders and the general public. The main concern for those in denial or resistance the change is due to privacy concerns. TSA outlines that privacy policies will be taken into consideration throughout the process but this generates uncertainty among the public. The purpose of being transparent with the Biometrics Roadmap is to encourage shift in opinions, but the perceived lack of privacy and data reassurance is hindering those who are in denial/resistance. TSA must now look towards those in resistance and conclude how to provide the reassurance they need.

Summary of Mental Models

The first change curve outlines the shift of priority of TSA management regarding upstream data collection from its creation to current day. Currently as a result of the passing of the Reauthorization and Modernization Act of 2018, TSA’s top management wants to focus on innovation. However, they understand that for this to happen, they need support from industry partners, stakeholders and the cooperation of travelers.

The ladder of inferences that follow show the contrasting opinions of TSA’s umbrella of support. TSA believes that being transparent with travelers will help move them from resistance to exploratory phases so eventually, they will be supportive of TSA’s future innovation. This has already occured with Prescreened travelers enrolled in Pre-Check and Global that are “eager to participate” for pilot studies.

As for resistant and exploratory industry partners and stakeholders, TSA Chief of Staff, Ryan Propis and Senior innovation officer and senior advisor to Chief of Staff, Alexis Long stated in an interview that the current culture of TSA drives high risk aversion and resistance. Thus the focus will be how to shift the mental models of these support groups in order to achieve a common goal.

Customer Segmentation

Haley, Elizabeth, Jerry

Problem Statement

The TSA is a government airport security program that protects the nation’s transportation system and screens over 2 million passengers daily. Currently, the TSA uses very few segmentation methods. TSA PreCheck and Standard lines. Standard lines often have a wait time of over 30 minutes and while TSA PreCheck gives travelers the option to pay for a faster security clearance it is only offered at 200 of the 440 airports. In addition to limited availability, TSA precheck segments customers by those willing to pay $85 for five years to join the program and those who aren’t and does not incorporate customer demographics and flight risk into their screening.

This reduces TSA efficiency due to the lack of focus on high risk travelers, which ultimately results in and increased security risk.

How can the TSA further improve the process of customer segmentation to ensure security while improving efficiency?

Strategy

Traveler books flight

TSA conducts background check

Traveler arrives at airport

Traveler goes through either standard security screening or TSA precheck

Through their unique position, the TSA is able to conduct background checks once travelers have booked their tickets. They gather personal data such as employment information and car registrations to assess potential threats and to identify low-risk passengers in an effort to lighten security screening at the airport and to target high-risk passengers. Those deemed as low risk are then able to apply to be members of TSA PreCheck which gives them access to a faster security process.

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Furthermore, the TSA is continuing the position while consistently improving. As passengers are demanding a more customized and seamless travel experience, the TSA is trying to modernize transportation vetting to improve the travel experience of passengers.

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Key Insight: The TSA does not fully utilize customer segmentation. A more efficient direction of segmentation would be to use the data gathered to further reflect different traveler types rather than paying for a faster process without considering customer demographics and flight risk.

3 Questions

1. What are we trying to accomplish?
• We are trying to improve the TSA segmentation process by creating more efficient segmentation lanes. Currently, the TSA PreCheck only benefits the 10 million people that are eligible based on their background status, criminal record, flying frequency records and willingness to pay a $85 fee to apply for TSA PreCheck.
2. How will we know when change is an improvement?
• The current wait time is over 30 minutes, improvement will show when that time is dropped to under 30 minutes
• Security screening methods will be more efficient due to the improvement of security focus.
3. What changes can we make that will result in an improvement?
• Rather than segmenting lines by those willing to pay for a “faster” security screening and those who are not, lines will be segmented based on customer demographics such as: travellers who own properties in the states, have all their paperwork, and have known destinations, travellers who are undocumented and own no property in the country, families going on vacation or students.

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Key Insight: Improving the segmentation process to segment customers based on demographics and the type of flyer, will make security faster for all travelers and more efficient for the TSA. This would both shorten the wait time and allow the TSA to allocate their resources towards more high risk travelers.

Triple Constraint

Technology: (10%): There are 950 advanced imaging technology machines with privacy protecting software working at the airports in the U.S. For standard lines, TSA use full body scanners and full body pat down; for PreCheck lines, they use metal detectors. They don’t need much improvement as long as they keep the efficiency and being assigned to different segmenting groups for security check.

People: (20%): By making more specific segmentations for security screenings, 50,000 transportation security officers and 600 aviation transportation security inspectors should be familiar with different screening equipments and know which technology should be used for different traveler risk level.

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Process: (70%): The TSA is responsible to design process segmentations based on different traveler profiles in order to improve the efficiency through strengthening the security processes through the diversion of different levels of screening processes based on customer segmentation therefore cutting down current waiting times of 30 minutes or more.

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Key Insight: Insufficient segmentation is mainly related to the process, resulting in security issue and long lines. When the process get improved, people should actively practice with the new system and technology should remain their performance in order to maximize efficiency.

Trade-offs

Key Insight: The wait times are long and the security detection rate is low due to the familiarity of the TSA screening process and how the same process has been used for a long time.

FAST TURNAROUND (WAIT TIMES) (-)

• Wait times are long in the standard lane. Travelers wait 30 minutes or longer to pass TSA security.
• Wait times may be bottlenecked by large families who do not travel much and do not know screening process.
• Screening times long because of security regulations
• Only two lines. TSA PreCheck and Standard. Leads to long lines to pass security

HIGH QUALITY (LACK OF SEGMENTATION) (-)

• Data shows TSA has low weapons detection rate with only 30% of weapons detected in 2017.
• Inefficient lines. Some travelers are familiar with process and pose less risk
• No personalization of travelers based on flight risk and credibility

LOW COST (BUDGET/COST OF TIME) (+)

• Well known program that assists with security of travelers
• Process has been very similar for long time
• Employees and travelers familiar with screening before flights
• Not a budget problem, rather is a process problem

Project Complexity

TSA Screeners

Level 2: The traveler behavior is apparent that they are unsatisfied with the problems of long lines but they could not pinpoint how to solve the problem. It is the management’s job to create an evolution in figuring out the type of problem and kind of solution on the segmentations of the travelers.

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TSA Management

Level 3: According to TSA’s privacy policy they use data to review customer satisfaction rather than using the data to further analyze the risk factor of the future flyer. It is unclear if the TSA are using their cookies to the fullest potential, and it is unclear what data is scraped from the future flyer.

Key Insight: The TSA collects cookies from their customers that visit or purchase flights but they do not collect personal information. It is unclear if the TSA have been under utilizing their data. An unclear solution of liquid restrictions could be the underlying cause of the long wait-time flyers.

Flexibility Matrix

Schedule: Least flexible because they need to implement new changes to nearly 440 airports in the U.S. Since the TSA is in charge of the security for U.S. airports and screen over 2 million air passengers daily and more than 750 million per year, the segmentation should be tested and implemented as soon as possible. It takes time make everyone involved, so the schedule should be strict in order to shorten the transitional period and achieve improved segmentation process.

Scope: The scope of the TSA is currently focused at 440 airports which is why it is a relatively unchanging number and will be implemented in all 440. The scope of segmentation process would slowly be implemented to eventually cover all security checkpoints and passengers.

Resources: Most flexible because practicing and implementing the new segmentation process, with the TSA employees, including over 50,000 transportation security officers and 600 aviation transportation security inspectors, should contribute their working hours, capabilities, and morals toward the changing process.

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Key Insight: Customer segmentation ensures different screening processes to focus on different risk-level travelers which assures traveler safety and airport security within the nation

Change Curve

Key Insight: By using data to properly segment flyers by danger levels, it could improve detection rates as well as efficiency rates. The underlying problem of the TSA could be systemic and deeply rooted in their system.

Ladder of Inference

Ladder of Inference key Insight:

Putting all types of travelers through the same line makes screening and wait times longer. Different travelers have different risk-levels and security needs that can be determined based on frequency of flying, background information and quantity of luggage. Establishing separate lines for different types of travelers will result in shorter wait times and make security screening more efficient for both the TSA and the traveler.

5 Whys

Problem: The TSA lines are long and inefficient

Root Cause Analysis

Problem:

Lack of segmentation causes long wait times by only having two main segments.

Domain 1:

Segmentation

Domain 3:

TSA PreCheck

Sub-causes:

Lack of segmentation

Domain 2:

Travelers

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Sub-causes: Significant difference between the two segments (5 mins PreCheck lines vs 30 mins Standard lines)

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Sub-causes:

Lack of personalization of travelers

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Sub-causes:

Many types of travelers daily. 1.1M Frequent business travelers, and ~2.2M travelers daily

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Sub-causes:

Infrequent travelers not familiar with traveling process

Sub-causes:

Specific PreCheck qualifications on background checks/ records and travel frequency

Sub-causes:

Lack of personalization between lanes based on security risk

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Sub-causes:

750 million travelers goes

through standard lines per year

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Gain Insights:

Not enough segmentation to accommodate different types of travelers according to their background and flight risk which further compounds on equal screenings of travelers which causes long wait times.

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Sub-causes:

35% of travelers are family travelers. Comes with larger groups and more baggage

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Sub-causes:

Few people are willing to pay fee of $85, especially infrequent travelers

Sub-causes: Many travelers are not familiar with TSA PreCheck requirements

RCA key insight:

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The initial problem of having not enough segmentation is due to the the types of segmentation, types of travelers and the existing screening process. The sub-causes are due to only having 2 segmentations and standard lines containing different travelers with different qualifications based on risk, creating delays in screening processes. In return, standard lines are longer and inefficient in security screening due to the large amount of people to focus on.

SIPOC Diagram

SIPOC Key Insight:

Limited Segmentation process causes an increase in wait times due to the long process of screening for standard lines. Increase in traveler segmentations based on background status, criminal record status, and flying frequency records rather than a willingness to pay for precheck will result in faster security screenings and therefore improving efficiency in the TSA and reducing wait times.

Reduce wait lines of 30+ minutes to ensure efficiency

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Implementation of customer Segmented based on risk

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Ability to gain customer information through government databases

Increase the current detection rates of 30%

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Ability to target high risk travelers

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Ability to collect 360 information about travelers

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System of Transparency, Public Participation, and collaboration.

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Fully utilizing 360 customer data to determine customers risk level

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Data from federal government agencies

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Travelers giving feedback through customer surveys and approval of data access by the TSA

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Accurate and efficient TSA worker performance

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TSA employees commitment to process changes

Privacy Provisions of the E-Government act of 2002

Government approval of data collection

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Airlines abiding by TSA policy of providing traveler information to TSA

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Traveler data collected by the TSA when tickets are booked

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System Map: Recommendation

System Map: Current

Airport security: improving 30% weapons detection rate

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Minimal use of customer data

Department of Homeland Security

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Efficient security screening

Customer Satisfaction

Implementation of TSA precheck that allows travellers to go through expedited security for an $85 application fee

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Use of new and improved technology and equipment

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Customer survey data collected to recognize areas in need of improvements

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Privacy Provisions of the E-Government act of 2002

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Technology and ease that was not previously available

TSA employees commitment to customer safety and satisfaction

Use of metal detectors, full body scanners, and pat downs to screen all travelers for harmful items

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System Maps Key Insight:

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TSA must implement new processes to improve customer satisfaction, safety, and overall efficiency. The 360 customer data collected would be utilized towards creating a segmentation process based on customer demographics that improves efficiency in lines and allows the TSA to separate customers based on their risk level.

RCA - Travelers without roots in the U.S.

Travelers without identifying data are screened through the same processes as long standing United States families

Domain: Policy

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Domain: Process

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Domain: People

Domain: Data

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Inability to collect data that doesn’t exist

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Limited data due to being new to US

The level of TSA screening is the same for all risk levels

Secondary Security Screening Selection (SSSS)

Limited knowledge of protocols

Lack of segmentation that separates people based on level of security screening needed and demographics

Follow the same security process as every other traveler

Use of metal detectors, full body scanners, and pat downs to screen all travelers

Lack of policy that segments people with different levels of data transparency

Lack of access to data on people makes them a greater security risk, the unknown could be dangerous

No shared government system or database

TSA collects personally identifiable information, however, deletes the data no later than 180 days

Key Insight: The lack of data for travelers without roots in the U.S. makes it more difficult to determine their flight risk. Only 35% of undocumented U.S residents are homeowners and can therefore provide sufficient data.

Only 35% of undocumented U.S. residents are homeowners, and therefore have collectable data

Currently a 30+ minute wait in the security screening line

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RCA - Frequent Flyer

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Frequent flyers are placed in the same lines as all other leisure travellers

Domain: Policy

Domain: People

Domain: Process

Domain: Data

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Willing for full data transparency that would allow the TSA to segment frequent flyers through a quicker security process

12% of all airline passengers are business travellers or frequent flyers

Are very familiar with security protocols.

Business travellers account for 75% of airline profits, putting pressure on the TSA to satisfy that customer demographic

Frequent flyers follow the same security screening process as all other customers, regardless of their risk

Saved personal information will help customers avoid filling out duplicative information

Business travellers have a higher expectation for performance, they expect efficient screening

Prioritize fast and efficient screening

TSA collects personally identifiable information, however, deletes the data no later than 180 days

If not using TSA PreCheck, would have to take off shoes and take electronics out, which adds additional time to screening

Lack of a shared government system or database that enables efficient 360 data collection

Use of metal detectors, full body scanners, and pat downs to screen all travelers

Key insight: Frequent flyers account for 12% of all airline passenger and have higher expectations for efficiency and performance. This customer demographic would be willing to share more data for a faster security check and since they contribute to 75% of airline profits, the TSA would feel pressured from the airlines to satisfy these customers.

Currently wait times are over 30 minutes

RCA - Single Mother w/ Kids

Domain: Policy

Domain: Process

No segmentation process in place for families which results in longer wait lines and unsatisfied customers.

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Domain: Safety

Domain: People

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Domain: Data

3-1-1 rule would result in additional time spent disposing liquids for kids

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Data used to determine customer satisfaction through surveys

More stressed due to making sure her and all of her kids are within policy guidelines

Parents are protective of their children's data and personal information

30+ minute wait in the security screening line which results in high numbers of missing flight time

35% of travelers are families

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Keeping track of children

Use of alternative screening procedures, although TSA knows they’re not as accurate than the main full body scanners

Children could have medication or extra products that could slow down the process of screening

2.2 million flyers per day / 440 million per year

Families come in larger groups and carry more baggage, resulting in longer screening times

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Lines get long and screeners get overwhelmed, which leads to careless screening

If segmented per risk level, policies could also allow different amounts of liquids

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Families are put through the same screening lines as all other travellers, slowing the lines down for other travellers

Key Insight: Families make up 35% of all travellers and dealing with children takes extra time. Parents might not want their children's personal information exposed, so implementing a segmentation process to give them their own line would allow the TSA to adjust their screening based on risk level and would also speed up lines for other types of customers.

The Power of Lean

Data

Business Problem

Business Scope

Framework/tools

Insight

Requirements/capabilities

Business Scope: Travelers who encounter the TSA. 750 million travelers annually at the 440 federalized airports

Business Problem: The TSA does not provide enough personalization for segmenting travelers, therefore, leading to extended wait times and inefficiency.

Data: The 750 million travelers annually, wait times at airports (PreCheck waits 5 minutes vs. Standard waits more than 30 minutes)

Frameworks/Tools: Problem Statement, Strategy, 5 Whys, 3 Questions, Triple Constraint, RCA, SIPOC, Change Curve, System Map

Insights: The TSA does not offer personalized traveler services. The current segmentation does not thoroughly cover customer demographics and flight risks. There are many different travelers that pass the TSA, all with different priorities.

Requirements/Capabilities: Required to follow federal regulations and guidelines to ensure safety while traveling. Maintain consistency of standards throughout all the federalized airports.

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