Collecting and Sharing of Operations and Safety Data (2020)

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7 Operations and Safety Data and Their Uses Airport owners and operators share a common responsibility to provide an efficient and safe environment for their users and are responsible for investigating ways to mitigate risks that may compromise safety and efficiency. Many have collectively expressed an interest to determine if their issues are unique or shared by other airports. Chapter 3 describes data sources maintained or captured internally by an airport (Section 3.1), data sources available nationally (Section 3.2), and data analysis approaches an airport can take with available data (Section 3.3). Knowledge and tracking of this type of data and information can help airports analyze and learn from their data to manage operations and safety risks. Using the right data for bench- marking can help airports improve operating levels, efficiency, and performance. Analysis of operations and safety data can help airports identify trends to assist with strategic planning for needed improvements and to raise awareness for potential hazards. Chapter 3 serves as a self-help guide drawn from airport industry experts to provide “how to” guidance for the application of operations and safety data from various internal and external sources. Many airports readily collect data for these data sources; however, they may be uncertain or inexperienced in how to interpret the data to identify issues or challenges for their operations and safety or how to determine solutions and best practices. This chapter is intended to serve as a resource to fill in data gaps and identify best practices and tools that airports can use to address operations and safety issues. The best practices and tools associated with this Guidebook include items such as data sources, examples, tables, and graphics to provide guidance and additional resources for data collection and review. Figure 3-1 is a flowchart of steps to take when an inspection report indicates a concern in the areas of operations or safety. The steps proceed from the initial report to analysis of trends, identification of root cause, mitigation, documentation, monitoring for effectiveness, and sharing results. This process is also of use for benchmarking and sharing data. 3.1 Internal Data Sources The operations and safety data currently collected by airports are primarily driven by the federal mandates of 14 Code of Federal Regulations (CFR) Part 139—Airport Certification (FAA 2019b; 14 CFR Part 139—Certification of Airports 2013). Safety issues are reported to the FAA; however, many of them are not publicly reported. The following sections provide an overview of the data source, description of the data, an example of data usage by an airport, and data collection requirements (see Table 3-1). These are maintained or captured internally by an airport through the normal course of business. If an airport is CFR Part 139 certificated, C H A P T E R 3

8 Collecting and Sharing of Operations and Safety Data the airport operator has an obligation to collect, document, and retain certain data specific to regulatory compliance. These include Part 139 daily inspections results and corrections, Aircraft Rescue and Firefighting (ARFF) inspections, driver training, movement area incursions, obstruction surveys, and so forth. For airports that are not Part 139 certificated, operators should consider using established data points and collecting operations data as needed to obtain a more complete safety performance picture. Figure 3-1. Flowchart for addressing an operations or safety concern identified in an inspection report. Section # Data Source 3.1.1 Part 139 Self-Inspection Reports 3.1.2 ARFF and Aircraft Fueling Equipment and Facility Inspection Reports 3.1.3 ARFF Runs (Non-Aircraft-Related) Reports 3.1.4 Airport Training Records 3.1.5 FOD Program Reports 3.1.6 Baggage Handling Area Inspection Reports 3.1.7 Ramp Inspection Reports 3.1.8 Terminal and Landside Inspection Reports 3.1.9 Safety and Incident Reporting Table 3-1. Internal data sources covered in this Guidebook.

Operations and Safety Data and Their Uses 9 3.1.1 Part 139 Self-Inspection Reports In the United States, commercial airports must be certificated under 14 CFR Part 139 (referred to as Part 139) for scheduled passenger air carrier service to operate (14 CFR Part 139—Certification of Airports 2013). Part 139 certification is established with four different classes (Classes I, II, III, and IV) based on the scheduled commercial service and aircraft type operating at the airport. Class I airports are those certificated to serve scheduled operations of large air carrier aircraft, unscheduled passenger operations of large air carrier aircraft, and scheduled operations of small air carrier aircraft. Airports designated as Classes II, III, and IV are primarily designated for airports with smaller aircraft (regional jets and turboprop aircraft), nonscheduled charter operations, or combinations thereof. While the classifications vary, the fundamental requirements are consistent (FAA 2019b; 14 CFR Part 139—Certification of Airports 2013). This data source focuses on those fundamental requirements, and more specifically on the inspections that are required of Part 139 certificated airports. These inspections are a continuous source of data on the state of airport movement area and support to airport operations and safety. The types of data captured during inspections can be trended and shared with other airports for the purpose of identifying potential improvements to operations and safety performance. Advisory Circular (AC) 150/5200-18D: Airport Safety Self-Inspection provides guidance to an airport operator on what, when, and how self-inspections are to be conducted (FAA Advisory Circular 150/5200-18D 2019). The AC does not apply to all airports, but the inspection process benefits any size airport because it provides a relatively standardized way of collecting data related to the operational condition and safety readiness of the airport, which benefits all airport operators. According to the AC, the areas on which the inspection should focus are designated as follows: Primary attention should be given to such operational items as pavement areas, safety areas, markings, signs, lighting, ARFF, fueling operations, navigational aids, ground vehicles, obstructions, public protec- tion, wildlife hazard management, construction, and snow and ice control (FAA Advisory Circular 150/ 5200-18D 2019). The AC does not limit the areas that can be monitored on a periodic basis. The airport operator may designate specific areas where conditions might impact safety of operations. Part 139 regularly scheduled self-inspections should be conducted “. . . at least daily during times when aircraft activity is minimal in order to create the least impact on airport operations” and part of the inspection process “should be done during the hours of darkness at those airports that serve air carriers after dark” (FAA Advisory Circular 150/5200-18D 2019). This guidance provides a level of standardization to ensure data collected and shared can be compared with relevancy and accuracy. The AC also notes that self-inspections may trigger special inspections to investigate discrepancies “after receipt of a complaint or when an unusual circumstance or unusual event occurs on the airport, such as a significant meteorological event or an accident or incident” (FAA Advisory Circular 150/5200-18D 2019). Special inspections can generate additional detailed data and root causes of discrepancies that can provide key and sharable information that can identify systematic safety risks or trends. Part 139 self-inspections are typically performed by the airport owner and/or operator at least twice daily (once during daylight hours and once at nightfall) and involve the physical inspection of the airfield and aircraft movement areas. Each airport operator must have an FAA-approved checklist that covers all the areas called out in the regulation. Each area of the inspection checklist has a minimum criterion for acceptable conditions. Items that are observed as not acceptable (a discrepancy) must be documented and corrected within a reasonable amount of time. The discrepancy must be documented and followed by corrective action. The

10 Collecting and Sharing of Operations and Safety Data airport must maintain the Records of Correction and make them available for the FAA Airport’s Division Certification annual inspection (FAA Advisory Circular 150/5200-18D 2019). The data collected by airports during self-inspections depends on whether the conditions are acceptable, and equipment and facilities at the airport meet minimum criteria. Thus, the primary sharable data includes the number of “No” tallies where standards are not met, the type and location of the discrepancy, causes of the discrepancy, the time lapse between discovery and correction, and when a special inspection is performed. Checklists should be made more usable for data collection and sharing by including the means to record the frequency, number, and location of discrepancies. 3.1.1.1 Data Description Table 3-2 provides a list of airport inspection areas from the FAA-recommended checklist, along with the types of data an airport operator should collect to benefit data sharing. This information should be used as a starting point for including Part 139 self-inspections as a source of sharable airport data. Part 139 self-inspection data sources allow for the measurement of the airport operator’s effi- ciency at maintaining compliance with federal airfield standards. Measuring performance of stan- dards should allow an airport operator to ensure successful Part 139 compliance during annual inspections. By measuring the time and resources invested, the airport operator can quantify the cost of compliance. This is critically important when understanding the true costs of the airfield. 3.1.1.2 Data Collection Characteristics For the airfield lighting example, there are some assumptions made about the data that an airport collects and/or inherently knows about its lighting systems. There is an assumption that the number of lighting outages is collected, tracked, and, at some point, analyzed for trends. An important point in this case is the type of lights (LED) and bulb part number were also known and included in the analysis. This type of information must be available when needed. Data Items Description Paved and Unpaved Areas Number of pavement discrepancies noted along with type and location of discrepancy. Safety Areas Number of safety area discrepancies noted along with type and location of discrepancy. Markings and Signs Number of marking and sign discrepancies noted along with type and location of discrepancy. Lighting Number of lighting discrepancies noted along with type and location of discrepancy and cataloged by area of the airport where the discrepancy occurs. Navigational Aids (NAVAIDs) Number of NAVAID discrepancies noted along with type and location of discrepancy. Wildlife Wildlife activity noted along with changes to environment impacting wildlife activity (wetlands expansion, trash accumulation, changes outside the airport property, etc.). Fueling Number of fuel spills and number of fire code violations noted. Obstructions Number of obstructions along with type and location of obstruction. Hazmat Number of storage tanks and leaks along with type and location of discrepancy. Snow and Ice Number of lights and signs damaged, FOD left on pavement following snow removal activities (equipment parts, ice chunks, etc.), along with number and type, time required to clear, means and methods used, and amount of snow/ice accumulation. Public Protection Number of security discrepancies noted along with type and location of discrepancy. ARFF Number of fire hazard discrepancies noted along with type and location of discrepancy. Construction FOD collected/reported (type and amount) and number of violations by construction workers. Wind Indicators Number of wind indicators and type and condition of wind indicators. Table 3-2. Data items from airport inspection areas.

Operations and Safety Data and Their Uses 11 EXAMPLE: DATA SHARING FOR AIRFIELD LIGHTING Given that Part 139 airports collect and manage the results from self-inspections, there are significant similarities in data collected and how data is managed airport to airport. While there are no technical requirements for data management, some large airports have sophisticated software, and others use spreadsheets to track data. Despite differences in the methods of documentation, airports can and should share Part 139 inspection data given the possible benefits. The following is a brief example using airfield lighting. Part 139 airports inspect lighting nightly. If lights are out in the movement area, this is documented and fixed as soon as possible. If more than two lights are out in a row, the lights must be corrected immediately. This requirement is even more stringent in Instrument Flight Rules (IFR) conditions. To this end, if an airport begins to note light failures in one specific area of the airfield, either on one taxiway or perhaps one side of a runway edge, and the frequency of outages is increasing, the airport operator must assume this situation is more than just normal bulb failure and investigate. Upon investigation, the airport operator discovers that the lighting systems are working normally. There are no excessive ground faults, the regulators are operating normally, and the power supply is smooth and efficient. The operator determines that this taxiway (example) was recently transitioned to a new light fixture with light emitting diode (LED) bulbs to save energy as part of a construction project. Upon review, the operator discovers that the LED lights used meet the specifications in the project. The airport operator meets with the engineers and contractors to determine the root cause of the lighting issue. Based on further review, it was determined that the bulbs used were manufactured overseas and a Buy-American waiver was granted to the contractor. This issue was then elevated to the FAA for consideration, and it was determined that this brand of bulb would no longer be allowed under a Buy-American waiver request. The contractor was required to replace all the bulbs with different, acceptable, LED lights. The information from Part 139 self-inspections enabled the airport operator to identify a problem based on trending data (light bulb failures). This facilitated a focused investigation on that particular lighting circuit resulting in the discovery of an issue with national implications. The lighting and inspection results data, including the number of outages and frequency, can be useful to other airports when they manage and design their own facilities. In this example, it would be important for airports who share lighting inspection results to also document the types of lights and bulb part number(s). Many airports have this information as a matter of course given its usefulness regarding maintenance activities and parts management.

12 Collecting and Sharing of Operations and Safety Data For this example to work effectively across several airports, airports would need to provide the following information: • Type of light (taxiway, runway, threshold, other) • Location (as exact as practicable) • Lighting system (e.g., which regulator, homerun, circuit) • Light product, including part number This list provides enough information for the airports to determine if a similar situation may exist at their airports. The challenge is that most of this information is not typically captured on the daily inspection checklist. The location and type of light are documented, but the exact system and product are not. That information resides with the maintenance team responsible for correcting the outage. Therefore, for this example to be effective, it is imperative that at least two to three levels of analysis occur. For airports to capitalize on data sharing, there needs to be a minimum of two levels of analysis performed. In the example, the initial analysis is kept locally (as in, not reported to or shared with stakeholders outside the airport) to determine if the overall system is operating within acceptable ranges (e.g., lights are burning out at an anticipated rate). When a negative trend is identified (lights burning out frequently), the analysis moves to finding the root cause. After the root cause is identified, a fix is put in place and monitored for effectiveness. Only after the problem is identified, root causes found, and corrections made and monitored should it be shared with other airports. A complete and informative picture of the issue can provide benefits and lessons learned to other organizations. This is true in almost every situation related to Part 139 self-inspection areas. Approaching one’s data collection and analysis in a systematic and consistent manner provides lessons learned, and trends can be shared, thus driving the need for industrywide attention and evaluation. Table 3-3 provides an example of Part 139 components that can be used for data sharing. 3.1.2 ARFF and Aircraft Fueling Equipment and Facility Inspections Reports ARFF inspection reports account for compliance costs and can be demonstrated to stake- holders and business partners (such as airlines). ARFF personnel are frequently assigned responsibility for fire safety inspections but not always. This data provides the airport operator with the tools and information needed to discuss operational improvements with fueling and fuel storage companies, enabling a better understanding of how well the individual organiza- tions are conducting their operations in terms of operations and safety efficiency. Typically, at Part 139 airports, ARFF staff conduct inspections of aircraft fueling facilities as well as the vehicles assigned to ARFF response. Therefore, for the purposes of providing concise examples, they are both included in this section. Further, ARFF inspections also review the fueling apparatus themselves, such as fuel trucks, fuel carts, hydrant systems, and storage. This represents valuable information about the use and condition of the facilities, even those owned and operated by tenants and stakeholders such as the airlines and fueling consortiums or FBOs. 3.1.2.1 Data Description ARFF and fueling facility inspection data should be reviewed as three distinct categories: aircraft fuel trucks, aircraft fuel storage and dispensing facilities, and ARFF response vehicle inspection and testing (see Table 3-4).

Part 139 Item Sub-System (Location) Issue Issue Source Frequency (per Month) Time Between Discovery and Correction (Average) Shared Data Benefit Lighting Runway Edge Burning too frequently Part 139 nightly inspection results 6; approach end of Runway 5L 24 hours • Results of root cause analysis and possible fix (acquire new LED bulbs) are shared • Share: circumstance and bulb manufacturer Cost savings, ensures improved safety through more reliable airfield lighting Pavement Markings Runway Edge Markings Cracking and peeling shortly after repainting Part 139 daily inspection results 12 x 10-ft sections 1 week • Results of root cause analysis shows poor paint quality (acquire new paint and inform FAA of specification variations) • Share: circumstance and paint manufacturer Cost savings, improved safety through improved longevity of markings Airfield Signage Runway Hold Position Signage Face panel fading within 1st year of deployment Part 139 nightly inspection results 2 signs 1 to 2 days • Results of root cause analysis show poor quality signage panels; thus, fading prematurely • Share: circumstance and signage panel manufacturer Cost savings, improved safety through improved longevity of signage Snow Removal Operation Plow Blades Damaging In- Pavement Lights Parts of polyurethane blades are breaking off in- pavement light lenses Part 139 inspections post- snow removal events 5 lights 2 days (time for analysis, change to procedures) • Results of root cause analysis revealed poly blades angled at 45 degrees are more likely to damage light fixtures. Rotating blades on edge (90 degrees to pavement) rarely damages lenses • Share: circumstance and blade manufacturer Cost savings, improved lighting performance during snow removal; does not result in degrad- ation of snow removal Wildlife Hazard Management Program (WHMP) Migratory Birds Large flocks of migratory birds are overflying the airport Continuous monitoring of WHMP 3 times per day on average over 2-week period As soon as possible • Root cause analysis shows geese flight patterns changed due to above average rainfall filling low- lying areas near the airport Understanding hazards (flocks of large birds) enables a proactive approach to WHMP Construction Activities Haul Routes Crossing Active Movement Areas Escorts are losing contact with all pieces of equipment going to/from work areas Continuous monitoring of construction 18 1 week (time for analysis, change to procedures) • Airport policy allows two pieces of equipment to be escorted across movement areas. Second piece has been losing contact with escort and appears alone on the airfield. Root cause analysis determines that single pieces of equipment escorts are more appropriate. Additional costs for escorts; however, improved safety as escort policy was changed to 100% control and single vehicles Table 3-3. Data sharing examples.

14 Collecting and Sharing of Operations and Safety Data The types of ARFF response vehicles used and their reliability are crucial to the operational compliance of all commercial airports. To this end, the ARFF response vehicles are tested daily to ensure any issues are corrected as soon as practicable. Should a front line ARFF unit (one responsible for meeting an airport’s ARFF Index) be taken offline for more than 24 hours, the airport has the obligation to provide a Notice to Airmen (NOTAM) placing the truck out of service. The NOTAM informs airline flight crews operating at that airport that there are not enough ARFF capabilities onsite to meet requirements (FAA Advisory Circular 150/5200-28C 2008). The obligation then passes to the flight crews to determine if they should continue with flights until such time that the issue is corrected. Data Items Description ARFF Response Vehicle Inspection Results ARFF response vehicles must be inspected and tested daily. This requirement is performed by ARFF personnel assigned to the units. When issues are identified, the issues are documented and tracked for correction. Results and correction data can be useful to other airports. Typical Aircraft Fuel Trucks Inspection Discrepancies Aircraft fuel trucks must be inspected by airport personnel on a regular basis. This requirement is typically managed by the airport’s ARFF department. Because these inspections are recorded and tracked for correction, the data can be valuable and can provide insight for other airports. Fuel Storage Facility Discrepancies Aircraft fuel storage and dispensing facilities must be inspected by airport personnel on a regular basis. This requirement is typically managed by the airport’s ARFF department. Because these inspections are recorded and tracked for correction, the data they provide is valuable and can provide insight for other airports. Table 3-4. Data items for ARFF and aircraft fueling and equipment facility inspections. EXAMPLE: DATA SHARING FROM ARFF RESPONSE VEHICLE INSPECTIONS ARFF response vehicles are produced by several manufacturers around the world. The information regarding their reliability, strengths, and weaknesses can and should be used by airports to determine which vehicles best suit their operations (i.e., climate might play a factor) and where to invest their money. In order to provide this information to airports, the results of ARFF response vehicle inspections could be made available to a national database where ARFF personnel and equipment maintenance staff could access the information to help them make decisions. The results of inspections and testing could identify issues with water pumps, engines, fit and finish of vehicles, and normal operational capabilities. Information sharing among ARFF personnel could help them make decisions regarding their fleet. Information sharing also results in more open communications between airport ARFF personnel. For example, an ARFF inspection may identify a water pump issue. ARFF units must be able to dispense their allotment of water or chemical in a specific amount of time. The pumps used to accomplish this task are crucial to the ability of the unit to function. If pumps begin to slow or fail, the unit is put out of service until it is repaired. Sharing information about the type of pump, the issue encountered, and the correction required helps other airports determine equipment to acquire or maintenance to be performed on existing equipment.

Operations and Safety Data and Their Uses 15 3.1.2.2 Data Collection Characteristics Data collection requirements for ARFF inspection reports should include the following: • Type and brand of vehicle • Model year of the unit • Specific issue identified (i.e., water pump not holding pressure, etc.) • Correction requirements (i.e., new pump, different pump, etc.) • Time for correction • Date the issue is detected or recorded and date of correction • Fuel storage system condition (leaks, rust, corrosion, etc.) • Fuel dispensing apparatus condition (worn or frayed hoses, couplings, corrosion, etc.) • Fuel truck conditions (Deadman switch operational, tires, pumps, etc.). ARFF inspection report data collection can easily be gathered and shared among ARFF personnel through industry professional organizations such as the American Association of Airport Executives (AAAE) and Airports Council International (ACI) as well as ARFF working groups at the local, state, and national levels. 3.1.3 ARFF Runs (Non-Aircraft-Related) Reports Many airport ARFF departments respond to more than aircraft-related incidents. Some airport ARFF departments have a structural component and response apparatus, such as one might find in a city department, requiring them to respond to building fires and alarms. In addition, airport ARFF departments often have medical units (paramedics) that respond to medical emergencies. The information associated with these ARFF runs (non-aircraft-related) can be valuable to airports in determining the right size of their ARFF department and making decisions about equipment acquisition and staffing. 3.1.3.1 Data Description The data collected for airport ARFF runs (non-aircraft-related) is broken into two practical areas: structural (building) runs and medical runs (see Table 3-5). The details collected concern- ing the type of response and responding units are valuable to the airport and other airports. 3.1.3.2 Data Collection Characteristics The data collection requirements for structural responses can be broken into three funda- mental categories: • Number of personnel planned for structural responses • Number of runs annually • Equipment used for the response The data sharing example for data sharing of structure ARFF runs helps airports benchmark their airport in comparison with other similar sized airports, and the data collection provides insight into what works and what can be applied to other airports. Data Items Description Structural (Building) Runs Number of runs annually accounted for by type (fire, alarm, other), type of facility responded to (terminal, hangar, cargo facility, other), and location. Medical Runs Number of runs per enplanements (rough order of magnitude), type of run, and location. Response Time The amount of time required for ARFF response to the terminals, or locations on the airport, such as aircraft hangars, office buildings, and critical infrastructure. Table 3-5. Data items for ARFF runs (non-aircraft-related).

16 Collecting and Sharing of Operations and Safety Data 3.1.4 Airport Training Records For an airport to operate effectively and safely, airport personnel need to be trained effec- tively on their responsibilities as well as the aspects of operations on the airfield that may affect their safety. For airports certificated in the United States, training requirements are identified under Part 139. An airport’s compliance with these training requirements is documented in the Airport Certification Manual (ACM). An airport creates and maintains the ACM, outlining specific training requirements. The ACM calls for the airport to maintain personnel training records for airport personnel and emergency personnel, along with training for those granted access to the airport movement and safety areas. Additionally, when airports are inspected by the FAA, they are required to provide their training, records, and accident/incident recordkeeping system for the inspector. There are dozens of ACs issued by the FAA as guidance to certificated airports that assist the airport operator in complying with FAA requirements for certification, and to help non- certificated airports improve their operations and safety performance. Many FAA ACs are mandatory. Thus, although the FAA recommends the types and key aspects of training for the varied airport functions, it is up to the individual airports to design their own training and to educate their personnel on the unique conditions and processes used at their airport. 3.1.4.1 Data Description Table 3-6 contains an example of the training records airports are required to maintain for their personnel. While not required by the FAA, airports may choose to archive test results for each employee. Airport operators are required to show compliance with training requirements under Part 139 EXAMPLE: DATA SHARING OF STRUCTURAL ARFF RUNS Helpful information for other airports to use in sizing and equipping their own ARFF departments include the number of runs and their location based on facility type. ARFF departments should learn from their peers by reviewing the types of runs (alarms, fires, other) responded to. This information can directly translate into how many staff should be on station to cover this type of response and still meet the required ARFF Index for airfield responses. ARFF units are evaluated annually to determine their required and regulated response times. These response times are measured from the moment an alert is issued to the times the first and second ARFF trucks arrive at the midpoint of the furthest runway. This data and information are important for demonstrating the impacts or potential impacts to response times resulting from pavements and facilities at the airport. ARFF units responding in structural equipment cannot be counted on to meet required airfield response needs from the time they depart the facility to when they return because they are not operating an ARFF response vehicle or are too far from the ARFF station to be recalled and meet response requirements. To this end, if an airport has a structural response component, the airport must plan to staff for that response and for the required ARFF Index response. This requirement speaks to staffing and equipment needs. Airports that share this data as a benchmark should use the information for budgeting purposes, training requirements, and long-term planning by the ARFF departments.

Operations and Safety Data and Their Uses 17 (i.e., ARFF, fuel fire safety, and ground vehicle training requirements). Training records are only required to be kept for a 24-month period. There are benefits that can be realized by collecting and sharing the data available in airport training records. As with other categories of data, it will depend on what the airport does with the data to create actionable knowledge. For training records, an airport can • Analyze the results of testing following training completion to discover items with the most incorrect answers and use the results to improve training. • Investigate incidents, accidents, and hazards to identify training deficiencies. • Investigate airport rules and regulations violations to identify training deficiencies. Data Items Description Employee Name Employee receiving training and their organization. Subject Trained Course information (what was the information conveyed). Type of Training Initial training for new employees, recurring, or remedial. Date Date when training occurred. Table 3-6. Training records. EXAMPLE: TRAINING RECORDS To illustrate how training record data can use collected, analyzed, and shared for the betterment of airport processes, operating ground vehicles in the airside environment will be used as an example. All airports, whether certificated or not, have vehicles operating on the airport for a variety of purposes. AC 150/5210-20A: Ground Vehicle Operations to Include Taxiing or Towing an Aircraft on Airports provides guidance in this area. This AC addresses several training issues and recommends areas for which airport vehicle drivers should be trained as well as containing a sample training curriculum, a sample vehicle operations training manual, and a sample training record form within its appendices (FAA Advisory Circular 150/5210-20A 2015). The AC discusses the following under the “Training Requirements” section: “Under Part 139, all personnel with duties requiring access to the movement and safety areas are required to have initial and recurrent training. We encourage non-certificated airports to develop a driver training program appropriate to their airports’ needs. . . . The airport operator or his/her designated representative will retain records of this training for 24 months . . . (and) [t]he airport operator is accountable for the training and actions of all airfield vehicle operators approved to operate on the airport” (FAA Advisory Circular 150/5210-20A 2015). To ensure a degree of standardization in training from airport to airport, the AC recommends that training address the following topic areas (FAA Advisory Circular 150/5210-20A 2015): • Runway incursions, airfield safety, and security. • Airport signage, runway markings, lighting, and the terms used on an airport. • Vehicle operating requirements. • Requirements for taxiing or towing an aircraft. • Ground vehicle and aircraft taxiing and towing rules and regulations. • Airport configuration and familiarization. (continued on next page)

18 Collecting and Sharing of Operations and Safety Data EXAMPLE: TRAINING RECORDS (Continued) More specifically, the AC proposes the following specific issues that are known to be the cause of violations, vehicle incidents, or accidents: • Infield aircraft navigation aids • Identifying a given point on a grid map or other standard map used at the airport • Applicable airport rules, regulations, or procedures for vehicle operations • Airport layout, including runways and taxiway designations • Known hot spots • Boundaries of movement, non-movement, and safety areas • Interpretation and color coding of airfield signs, pavement markings, and lighting • Location and understanding of critical areas associated with Instrument Landing System (ILS) and Very High Frequency Omnidirectional Ranges (VORs) • Proper terminology (including phonetic alphabet) and procedures for radio communications with the ATCT • ATCT light gun signals • Established routes for emergency response vehicles • Dangers associated with jet blast and prop wash • Traffic patterns associated with each runway (left or right) and location of each leg (i.e., downwind, base, final, and crosswind) • Situational awareness (staying alert in the environment of operation) Given these specifics for training of personnel who operate vehicles within the airport, an airport should design their training syllabus to ensure these areas are covered and tested to complete the training. The airport should track test results on specific topics, record scores and areas of deficiency on the individual training records, or capture the test results in a cumulative training record. From this, the airport should have a database of quantitative test results that can be compared with violation records, as well as incident and accident investigation findings. The root causes determined in the findings of the investigations can then be tied to the post-training test results to discover deficiencies in the airport ground vehicle training process, making improvements if necessary. 3.1.4.2 Data Collection Characteristics For the example to benefit the airport, additional information needs to be captured in indi- vidual training records so that knowledge based trends can be analyzed and compared with human performance of the operations tasks. Typically, job performance is tracked by accounting for undesirable actions that result in a violation, near miss, or an accident. Two items must be incorporated into airport processes to connect actions with the personnel training. First, additional information can be collected relating to individual training. Apart from the name of the individual and the type and date of training, an airport benefits from capturing and trending the following data points: • Percentage of examination questions answered correctly • Percentage of examination questions answered incorrectly • Number of individual examination questions answered incorrectly per topic area (e.g., airport markings, airport communications, airport hot spots, etc.)

Operations and Safety Data and Their Uses 19 These data points provide additional information to trend training results as a function of undesirable outcomes on the airfield (such as airfield driving violations, vehicle accidents, aircraft or airport equipment damage as a result of vehicle collisions, etc.). The challenge is that most of this information is not usually captured in a training record; investigation find- ings and root causes are not typically analyzed to assess training deficiencies by an airport. Therefore, for this example to be effective, it is important to go beyond the collection and archiving of training data and make the effort to find connections to other data that exists on the airport. For airports to benefit from sharing training record data, the airports would need to be willing to share safety-related data regarding accidents and incidents. Local and state Sunshine laws as well as individual airport policies may preclude the sharing of such information. Sharing data collected by Part 139, Safety Management System (SMS), and other areas of safety concerns can contribute to a broader awareness of the potential risks and strategies for mitigation. Certain generic aspects of incident data and the relationship to airport training and training examination results can be shared without sacrificing sensitive airport data. Potential data elements that could be shared are illustrated in Table 3-7. At present, sharing relevant training record data needs to occur between partner airports because of the lack of national or organizational airport data sharing tools and processes. Air- ports should share the information with partner airports near their location or of like size and operational tempo. 3.1.5 FOD Program Reports The effective management of FOD is vital to safe and efficient operations on an airport. The existence of FOD in the airport operations area (AOA) is a safety hazard to aircraft, personnel, and equipment. The collection, analysis, and trending of FOD at an airport can result in solutions to the sources of FOD, and the implementation of risk mitigations that may reduce the impact of this safety and operations hazard. The knowledge gained through the assessment of FOD-related data should be shared with other airports so that common issues and effective control measures (best practices) can be brought to the attention of airports and airport stakeholders. Having an established FOD program that tracks and determines the root cause of FOD (where it was generated from) allows the airport operator to set goals and objectives and manage them at their source. This allows for the costs associated with the FOD program to be accounted for and justifies the investment made into the FOD program. This data also provides valuable operations data for the airlines and other aircraft operators at the airport about how well their internal systems are working. Area of Training Airfield Issue Outcome Frequency (Per Month) Shared Data Benefit/Action Taken Airside Driving Speeding • Violations • Number of citations in month • Type of vehicle • Vehicle owner • Testing results related to rules • Reduced number of vehicle accidents • Reduced cost for vehicle maintenance Airside Driving Operating off designated routes • Violations • Accidents • Number of citations in month • Number of accidents: vehicle to equipment • Testing results related to rules • Review and revision of airport rules conducted • Review and revision of training curriculum and testing questions completed Table 3-7. Data sharing examples.

20 Collecting and Sharing of Operations and Safety Data 3.1.5.1 Data Description AC 150/5210-24: Airport Foreign Object Debris (FOD) Management addresses FOD evalua- tion in Chapter 6. This includes data collection and analysis regarding FOD that an airport should consider incorporating into a FOD prevention program (FAA Advisory Circular 150/5210-24 2010). The guidance in the AC suggests the following regarding the collection of FOD data: “The FOD manager will ultimately determine the documentation guidelines in a FOD management program. Certain small items, such as plastic wrappers or baggage tags, may simply warrant efficient collection and disposal. A consistent trend of small items, such as those coming from a particular entity or operation, or particularly large or hazardous FOD, may require detailed documentation for effective analysis and prevention efforts.” Additionally, regarding reporting on FOD, the AC suggests the following: “Depending on the potential hazard of FOD collected, a reoccurrence of FOD from the same source, and the personnel available at an airport, the FOD management program may contain provisions to notify the FOD source of a FOD occurrence.” The AC further recommends that the data elements in Table 3-8 be collected by the airport for analysis. The FAA requires that records regarding FOD should be maintained for a period of 2 years but does not suggest a designated manner or method for documenting FOD information for sharing. The FAA also recommends that the airport investigate “major FOD incidents (as determined or classified by the airport operator). . . .” (FAA Advisory Circular 150/5210-24 2010). As stated, there could be many and varied definitions of a major FOD event. A typical airport will likely define such an event as one where damage to an aircraft or to equipment, or injury to airport personnel is involved. While undesired events need to be investigated, airports gain more knowledge upon which to base airport risk decisions if airport management also regularly investigates FOD occurrences based on analysis of collected FOD. 3.1.5.2 Data Collection Characteristics In the Airfield FOD example, there are some assumptions made regarding the data that an airport collects or inherently knows about FOD detection, collection, and analysis. It is assumed that airport personnel understand that debris in the AOA is not merely garbage to be thrown in trash bins but hazards to flight operations that need to be assessed; that a user-friendly FOD reporting and data collection system exists and is used by all airport personnel; and that there is Name of Personnel Detecting/ Investigating FOD Item Name of person who discovered FOD and who dealt with the FOD Operations and Weather Data Pertinent operations data (wind, rain, snow, etc., and if the airfield was being operated in any special configuration) Data Items Description How Was FOD Detected? A description of how the FOD was detected (inspection, pilot report, other) Date/Time of FOD Detection and Retrieval Date and time the FOD was detected and when it was removed Description of FOD Retrieved and/or Image (if Available) A description of the item(s), including category, size, and color to assist with determining origin or cause Location of FOD Object [Coordinates and Reference to Airport Operations Area (AOA) Location] Location on the airport Possible Source Following examination, identify possible source Table 3-8. FOD data.

Operations and Safety Data and Their Uses 21 EXAMPLE: AIRFIELD FOD Given that Part 139 airports collect and manage the information about the FOD they collect, there will be significant similarities in what is collected and how the information is managed from airport to airport. There are recommendations on the information that should be collected in the AC on FOD, and a synthesis of airport practices relating to FOD can be found in ACRP Synthesis 26: Current Airport Inspection Practices Regarding FOD (Foreign Object Debris/Damage (Prather 2011). However, there are no technical requirements for data management and sharing of FOD information. This allows the airports to be innovative in what information they collect, how they collect it, and how they share the information. The following is an example of how FOD information might be collected, analyzed, acted on, and shared in an effort to proactively mitigate this safety risk that all airports face. During a routine inspection of the ramp area, an airport operations specialist parks and walks the area around the gates leased by Airline A. The operations specialist looks at the contents of the FOD buckets positioned near or on each boarding bridge. In one of the buckets, the operations specialist finds several luggage zipper parts along with an assortment of food wrappers, pebbles, and a couple of small bolts. The luggage zipper parts intrigue the operations specialist who continues to conduct an FOD walk around the other gates. During the walk, the operations specialist finds more than a dozen additional luggage zipper parts on the deck and in the concrete expansion joints. The zipper parts are collected, and the pertinent information is entered into the FOD reporting system. The following day, the operations specialist speaks with a supervisor about the findings. Based on the discussion, the operations supervisor assigns an analyst in the Operations Department to review the FOD trends for the last 12 months for occurrences and sources of luggage zipper part FOD. The analysis reveals that zipper parts are found frequently on the ramp by airport employees and around all gates, but Airline A and Airline C have a higher number of occurrences than the other four airlines that serve the airport. The airport Operations Manager is briefed on the analysis and the decision to take additional steps that involve data sharing, evaluating the value of the data, and discovering the root causes of the FOD hazard. These steps include the following: • Sharing the results of the analysis with all airline station managers and other airport stakeholders in the baggage handling process • Calling for an airport safety committee meeting to discuss the FOD analysis • Designing a month-long FOD campaign to study the extent of the luggage zipper part FOD problem and assess the risk and the causes • Sharing the results of the campaign and FOD analysis with other regional airports with whom they regularly communicate on safety issues • Contacting multiple luggage manufactures to investigate their awareness of the issue With such a process in place, an airport can determine a number of data-related aspects that might need improvement or greater attention. The data sharing process with other airports will lead to the discovery of lessons learned and perhaps more effective practices from other airports that can be adopted.

22 Collecting and Sharing of Operations and Safety Data open data sharing between the airport and tenants regarding FOD and safety in general. It also assumes that the airport has an established FOD management program in accordance with AC 150/5210-24 and that the airport plays a leading role in airportwide FOD management. For such a scenario and process to work effectively across several airports, it is important for the airports to provide the following information in addition to the data elements outlined in the AC: • Number of FOD inspections performed daily • Number of categorized pieces of FOD collected with periodicity (e.g., number of zipper parts collected daily) • Number of passenger bags handled daily (for comparison purposes and normalization of the data) • Specific information on the FOD pieces collected (e.g., luggage manufacturer, zipper manufacturer) This list provides enough information for the airports to determine if a similar situation exists at their airport. The challenge is that broken baggage parts may be viewed as trash rather than as a safety hazard, and therefore may be discarded rather than analyzed for root causes. Additionally, airlines leasing gates at the airport may collect their own data and not share the information with the airport. Thus, an airportwide program with the means to share data produces better outcomes. Potential data elements that could be shared are illustrated in Table 3-9. 3.1.6 Baggage Handling Area Inspection Reports Many airports have implemented baggage handling area inspections. This was a topic of interest during the FAA-sponsored SMS Pilot Studies in 2010−2012 featuring SMS data from 24 airports (FAA 2019c). Baggage handling areas represent an important component in over- all airport operation. The equipment and staff that operate in these areas provide a much misunderstood, yet critical path for airline performance. In those areas where the airport is responsible for the maintenance of baggage handling equipment, it is vital that this equip- ment operate with a high rate of reliability. To this end, the equipment should be inspected regularly. Inspections of baggage handling areas, ramps, and other facility provide valuable data regard- ing sources of FOD, unreported property damage, and hazardous conditions. Inspecting these areas regularly can produce analytical data about airlines that are not keeping their lease space clean and identify issues associated with the handling process itself that can damage bags or cause debris to get outside the area and become FOD on the airfield. FOD Type How FOD Was Detected (FOD Pieces Found per Month) Sources of FOD H B Monthly Passengers/ ags andled Shared Data Benefit Baggage: Zipper Parts FOD bucket contents: boarding gate area, visual inspections 256 zippers collected in May High frequency of zippers from ACME luggage, highest numbers localized to two sets of leased gates 350,500 passengers/ 466,165 checked bags handled • Results of root cause analysis and fixes are shared (key sources, process changes) • Share: practices causing FOD, zipper FOD rate per passenger or per bags handled FOD removal from the AOA, reduced baggage damage claims, reduction in Frequency aircraft and vehicle tire damage Table 3-9. Data sharing examples.

Operations and Safety Data and Their Uses 23 3.1.6.1 Data Description The data needs to reflect the equipment being inspected, issues and/or faults with it, frequency of those faults, and time needed to correct (see Table 3-10). 3.1.6.2 Data Collection Characteristics The collection requirements for baggage handling data include type of equipment, manufac- turer, age, and use order of magnitude (such as hours of operation and/or run time). Collecting this information can help airports understand the complete picture of managing and maintain- ing a baggage handling system. The performance of baggage handling equipment is crucial to the operational flow of any commercial airport. 3.1.7 Ramp Inspection Reports While ramp inspections are not required under Part 139, many airports inspect ramps for safety-related reasons and for lease compliance. Ramp inspections were a topic of interest during the FAA-sponsored SMS Pilot Studies in 2010–2012 featuring SMS data from 24 air- ports (FAA 2019c). In general, airports are looking at aircraft parking, fueling, ground service equipment (GSE) operation, condition and location, and FOD control. All these factors con- tribute to safe ramp operations. 3.1.7.1 Data Description Table 3-11 provides high priority items routinely reviewed during ramp inspections. 3.1.7.2 Data Collection Characteristics The data collection requirements are relatively straight forward; using the GSE example, one would capture the type of equipment and the issue identified, location, time of day, and origin of the issue. This information can help an airport identify systemic issues with the operation or EXAMPLE: BAGGAGE HANDLING EQUIPMENT By tracking and trending baggage handling equipment issues, airports can review what equipment has a higher reliability factor and, therefore, what equipment should be invested in for the future. Airports can gather and share the results of baggage handling equipment performance. Even airports that contract out the maintenance of this equipment can and should be receiving performance reports from their contractor. Equipment data shared across airports will help drive system upgrades and maintenance practices going forward. This information can help to identify faulting equipment and help airports learn from one another and perhaps avoid similar mistakes. Data Items Description Equipment: Baggage Belt, Motors, etc. Identifying the location; equipment information (condition, type, model, age); issue(s); and time needed to correct are all pertinent to trending problems and finding root causes to be avoided in the future. FOD Location, Type, Source By identifying the type of FOD, location, and its source (a particular airline), the airport can track and trend this information and put corrections in place going forward. Table 3-10. Data items.

24 Collecting and Sharing of Operations and Safety Data an operator. Corrective actions can then be made, and lessons learned can, and should, be shared across multiple airports. 3.1.8 Terminal and Landside Inspection Reports Terminal and landside inspections are not a requirement of Part 139; however, they are required by the International Civil Aviation Organization (ICAO) (International Civil Aviation Organization 2004). To this end, airports that wish to set up terminal or landside inspections could use ICAO inspection requirements as guidelines. Several airports have organized formal terminal and landside inspection programs. Several U.S. large hub airports even have split operations departments into one dedicated to terminals and the other to landside. Inspection protocols are not required or regulated in the United States; it is up to the individual airport operator to establish them. 3.1.8.1 Data Description The data necessary to collect and make useful for terminal and landside inspection reports is wide ranging and will vary widely from airport to airport (see Table 3-12). The basic data for these areas is as follows: • Landside: Facility conditions (roadway paint markings, curbing and sidewalks, signage, and lighting) • Terminal: Equipment operations (moving walks, escalators, elevators, lights, signage, etc.) By gathering this data, airports can begin to trend areas and equipment that might be, by their nature, problematic. Further, the issues might begin to trend based on time of day, or year, or as associated with events in the community that impact airport operations. EXAMPLE: GSE CONDITION The condition of GSE is a product of the age and care the equipment has and is given. Most airports have established standards for the condition of GSE; they typically center around safety and environmental issues, such as tires, leaks, seatbelts, and the like. By inspecting and tracking the results of these inspections with enough detail, airports can begin to build a picture of who and what are causing the most GSE issues. Further, it is very important that this equipment remain in good conditions so as not to negatively impact the operations of the airport. Data Items Description Aircraft Parking Note if airlines are parking aircraft in accordance with ramp markings and if the size of aircraft is correct for the gate area. Ground Service Equipment (GSE) Parking Equipment parked in the designated locations. GSE Operations Operators obeying speed limits and staying on designated roadways. GSE Condition GSE in good condition (not leaking fluids, tread on tires, etc.). Personal Protective Equipment (PPE) Airlines and GSP wearing appropriate PPE (such as reflective vests). Night High Mast Lighting Working lights providing sufficient lighting or too much illumination. Table 3-11. Data items for ramp inspections.

Operations and Safety Data and Their Uses 25 3.1.8.2 Data Collection Characteristics The data collection requirements for terminal and landside areas include type of equipment (manufacturer), location, time of day, and issue. This information helps an airport identify systemic issues with the operation and or an operator. Corrective actions can then be made, and lessons learned can, and should, be shared across multiple airports. 3.1.9 Safety and Incident Reporting Monitoring safety accidents and incidents is important for revealing systemic problems or issues within an organization that need to be addressed, in addition to reporting to regulators and insurance companies. The collection and sharing of specific safety data available to the airport operator can be a challenging and, in many ways, complicated process. There are many factors that impact the ability to collect such data as well as additional factors that impact the ability to share such information. The move toward airports developing and implementing the processes that constitute an SMS is having a positive effect on collecting and sharing of such safety information. Airports that have yet to implement an SMS can learn a great deal from those that have. EXAMPLE: TERMINAL EQUIPMENT Passenger conveyance equipment such as elevators, escalators, and moving walkways present several hazards to passengers and employees alike. If a moving walkway or an escalator is constantly out of service, then people are forced to walk farther, and customer service goals are not being met. Moving walkways are particularly challenging because they should be checked to ensure the safety equipment is in place and correct, such as the guards to prevent a foot from getting caught. Signage that signals the end of the moving walkway (or voice cues) are crucial to ensuring proper safety. The information gained from recurring inspections of these facilities and equipment can shed light on what equipment is performing better than others across the industry. Also, when this data is compared with passenger data and the number of users on a daily, weekly, monthly, and annual basis, one can begin to paint an overall picture of performance. Lastly, the performance of terminal equipment can also be used along with accident and incident data (slips, trips, and falls), and combined with individuals’ data, such as age, to determine what equipment works best with a certain demographic. Data Items Description Roadway Paint Markings The condition of lane dividers, cross walks, turn arrows, etc. Curbing and Sidewalks The condition of these areas can introduce trip hazards to pedestrians. Signage The condition of all traffic and informational signage, that is, clear and easy to read and see, etc. Lighting Roadway lights are clear and in good working order, same for traffic signals. Terminal Equipment Passenger conveyance systems are operating properly. Terminal Lighting Lighting is working as it should. Terminal Signage Signage, both static and digital, is working as it should. Table 3-12. Data items for terminal and landslide inspections.

26 Collecting and Sharing of Operations and Safety Data For the purposes of this section, the term Safety Records will be used to refer to required reports and records an airport must create and archive, and in certain cases, report to specific governmental organizations. 3.1.9.1 Data Description For safety and incident reporting, nearly all airports capture information to create data records as required by law, rule, or regulation (see Table 3-13). Airports with an SMS in place are more likely to have a formalized system for reporting safety hazards such as reports of conditions that could result in an incident or accident involving injury to personnel or damage to airport assets. Safety hazard reports are not required. They rely on the proactive actions of those working or observing operations on the airport and are more likely to be in a narrative, subjective format. In general, safety records have two common characteristics: • Safety records are reactive in nature in that an undesirable event must occur for data to be captured. • Safety records are only required to capture the who, what, when, and where of a safety-related incident. Thus, data can be used to compare safety performance in the form of numbers of incidents from month to month, or year to year. The sharing of such information with other airports or airport stakeholders will allow the airport operator to compare numerical results on undesirable outcomes with those of organizations of similar size and complexity. The real value of safety record data rests in the rigor an airport operator puts into investigating the reason a report was submitted. 3.1.9.2 OSHA Recordkeeping Characteristics If an airport is required to report under Occupational Safety and Health Administration (OSHA) regulations, the information required in the reports include the following: • Employee name and job title • Date and time of the event • Location of the event • Result of the event (amount of time away from the job) • Type of injury or illness • Descriptions of what happened to cause the injury or illness (short one or two sentence responses) These reports are required to be kept by the organization for 5 years. More detailed infor- mation on OSHA requirements can be found on the OSHA Injury and Illness Recordkeeping and Reporting Requirements website (https://www.osha.gov/recordkeeping/). Data Record Occupational Safety and Health Administration (OSHA) logs and records (or similar recordkeeping required by state or local requirements) Property damage reports Incident and accident reports (non-aircraft-related) Safety hazard reports Table 3-13. Data records for safety and incident reports.

Operations and Safety Data and Their Uses 27 Airport Property Damage Reports and Incident and Accident Reports (Non-Aircraft- Related). Safety data collected on airport property damage incidents and incidents and accidents not involving aircraft will vary from airport to airport depending on their oper- ating rules and regulations. In many cases, the data will be collected by local law enforcement personnel called to respond to the incidents. Law enforcement personnel will be trained in investigation processes but may not be intimately familiar with airport operations or with airport safety management processes. The information captured regarding these types of events will likely be similar to the information required by OSHA. The data elements can include the following: • Type of safety event • Date and time of the event • Location of the event on the airport • Personnel and equipment involved • Descriptions of the damage and/or injuries • Narrative description of the incident and its causes Safety records are reactive reports of events that have occurred and are reliant on personnel at the airport to report them to the proper people within the organization. The quantitative data captured in such reports, analyzed by airport personnel, and potentially shared with other organizations is limited in general to counts of events. Safety Hazard Reports. With the introduction of SMS, more airports are collecting safety data in the form of Safety Hazard Reports. Safety hazard reports differ from incident and accident reports in that damage or injury is not a prerequisite for submitting such a report. A safety hazard report is a proactive way for airports to collect safety data that could result in damage or injury if left uncorrected, thus allowing the airport to implement mitigations to correct the conditions before they result in a reportable accident. The information collected and the forms used for safety hazard reporting vary from airport to airport. Two sources of examples of safety hazard reporting forms are the FAA’s Draft AC 150/5200-37A: Safety Management Systems for Airports (FAA Draft Advisory Circular 2016) and ACRP Report 1: Safety Management Systems for Airports, Volume 2: Guidebook (Ayres et al. 2009). The data recommended to be collected in each example is nearly identical and includes the following: • Date and time of discovery • Location of the hazard • Narrative description of the hazard • Witnesses (yes or no) • Type of hazard (health/safety, property damage, environmental, near miss, other) • Potential outcomes (fatality, hospitalization, first aid, other) The form also includes the following optional information: • Name of the person reporting • Position of the person reporting • Contact information for the person reporting • Names of witnesses This information is optional to allow the reporter to remain anonymous and avoid potential repercussions for reporting.

28 Collecting and Sharing of Operations and Safety Data 3.1.9.3 Data Collection Characteristics For the example to benefit the airport, no additional information needs to be captured on the front end; however, how the numerical data is used and analyzed can improve investiga- tion results. However, with the introduction of an airport SMS, additional data on incidents and hazards can be collected to enhance the analysis, trending, and sharing of safety information. This additional data captured can include the following (see Table 3-14): • Hazards impacting the incident • Frequency of similar incidents (running total per month) EXAMPLE: SAFETY RECORDS DATA To illustrate how safety records data can be collected, analyzed, and shared for the betterment of airport processes, the following example of airport-to-airport information sharing is presented to describe a scenario where cooperative efforts may lead to the successful use of safety records information for airport improvement. ABC Airport collects injury information on passengers using the terminal. The information collected is in line with state and local safety incident reporting laws and regulations. Over the course of an 8-month period, the Safety Manager of ABC notices a trend where the number of passenger injury claims has increased by 20% over the same period from the previous year and is higher than at any point in the airport’s history. While the information available in the reports varies in how it is reported (the descriptions use different words and phrases to describe what seem to be similar types of events), the Safety Manager decides that a more formal investigation of the incidents occurring over this period is warranted. The results of the investigation showed that 60% of the injury cases occurred when passengers used escalators, and more than 40% of the escalator incidents occurred when only a single escalator located in Terminal A was available. With this information, the Safety Manager contacts his fellow Safety Manager at XYZ Airport. XYZ Airport implemented an airportwide SMS just over 2 years ago. The XYZ Safety Manager explained that they noticed a similar problem at their facility and convened a Safety Risk Assessment Panel to assess the risk and develop mitigation strategies for safer use of their escalators. In this sharing of safety information, the two airports discovered that they had similar numbers of injuries and claims during the periods of the highest frequency of incidents. XYZ Airport had acted on their safety data analysis and implemented two airport terminal changes: (1) signs describing the hazards posed by using the escalator were enlarged and placed in more visible locations, and (2) cameras were installed so that activity on the escalators could be monitored and additional information on the use of the escalators could be analyzed. Since the mitigations were put into place, XYZ Airport had 60% fewer injury incidents occur, and their insurance underwriter reduced their rates and deductible. The ABC Airport Safety Manager took the information to the Airport Manager, and subsequently proceeded to empanel a Safety Risk Assessment Panel (with the assistance of XYZ Airport) to study and more thoroughly assess a revised approach to terminal safety and escalator use.

Operations and Safety Data and Their Uses 29 • Root causes of the hazards (recorded post-investigation) • Cost of repairs or equipment replacement • Cost of medical treatments • Mitigations implemented (information provided during event follow-up and close out) Two ways in which safety records data can be valuable to an airport in analyzing individual airport data is to (1) discover correctable trends in airport processes and personnel actions, and (2) compare safety records data with similar airports to provide a catalyst for correcting like deficiencies. To realize these positive effects, an airport must not only track the number of safety-related occurrences but also ensure that thorough, effective safety investigations and data analyses be conducted. Tracking safety events is a required task for nearly all airports to comply with governmental regulations. When an airport takes the next steps to analyze these numbers and associated infor- mation for root causes and trends, deficiencies in airport processes and rules can be discovered and corrected. These corrective actions will result in fewer injuries and less damage to airport property which in turn can lead to lower costs for repairs and replacements, and potentially lower insurance rates from airport underwriters. When an airport shares and compares safety statistics with airports of similar size and com- plexity, operational deficiencies and hazards may be discovered through the process of asking why there are differences in the data. No airport is the same, and small airports may not have the operational exposure to reveal existing hazards, because they have yet to result in a bad outcome. Thus, comparing data with other like airports, and then analyzing the reasons for the differences, may provide a proactive means to correct deficiencies before they result in an accident. 3.2 National Data Sources A variety of operations and safety data sources are available online that airports can use for identifying and comparing characteristics of peer airports and other evaluations (see Table 3-15). Many of these databases are in the public domain and can be queried or down- loaded at no expense. Data sources relevant to airport operations and safety include aircraft Incident Type Location Date/Time Frequency Root Causes Cost of Claim Mitigation Status Passenger Injury Terminal A escalator July 25/1930 4 to date • Slippery surface due to rain • Improper use with large luggage $7,000.00 TBD Open Table 3-14. Data sharing example. Section # Data Source 3.2.1 Airport Data (FAA Form 5010) 3.2.2 Operations Network (OPSNET) 3.2.3 Passenger Enplanements and Cargo (BTS T-100) 3.2.4 Airport Financial Data (via CATS) 3.2.5 Airport Weather 3.2.6 Aviation Safety Reporting System (ASRS) 3.2.7 NTSB Accident Reports 3.2.8 FAA Aviation Incident Data System (AIDS) Table 3-15. National data sources.

30 Collecting and Sharing of Operations and Safety Data operations, airport characteristics, passenger enplanements, airport financial data, weather, aviation safety reports (FAA 2019a), aviation accident reports from the National Transportation Safety Board (NTSB), and accident and incident reports from the FAA. Publicly available data sources, including data content, how to access and query the data, and examples of how the data may be applied, are described in the following subsections. 3.2.1 Airport Data (FAA Form 5010) The FAA maintains a comprehensive database of information on all active civilian, joint-use military, and private-use airports, heliports, seaplane bases, and other facilities in the United States. The database contains physical and operational characteristics as well as ownership and manage- ment contacts and other data about each facility. The facility data is primarily recorded and reported using FAA Form 5010, Airport Master Record, which is updated regularly through onsite inspections and form reviews (FAA 2003). The FAA Form 5010 data is maintained by the FAA’s Office of Airport Safety and Standards and can be accessed through the Airport Data and Information Portal (ADIP). Data obtained from the FAA Form 5010 database can be used to compare and contrast physical and operational characteristics of peer airports. Factors for comparison may include ownership, runway dimensions, based aircraft (including jets), aircraft operations, and control tower facilities among other data. Airport data can be useful as part of a broader analysis of operations and safety issues because the data provide context for representing airfield characteristics and other criteria. 3.2.1.1 Data Description A variety of airport-specific data is contained in the Form 5010 database from ownership details to runway dimensions and based aircraft and operations. Principal data contained on Form 5010 is included in Table 3-16. The Form 5010 data is used to update other FAA publications such as the U.S. Chart Supplements, formerly known as the Airport/Facility Directory (AFD), and aeronautical charts (FAA 2019m). The database is also source data used by many other non-FAA entities such as AirportIQ 5010 (AirportIQ5010.com), AirNav.com (AirNav.com 2019), and Airport-Data.com (Airport-Data.com 2019). Data Item Description General Ownership Public/Private Owner Name/Address/Phone Manager Name/Address/Phone Runway Dimensions Length/Width Pavement Condition/Weight Capacity/Pavement Classification Number Lighting and Approach Aids Lights/Marking/Visual Aids and Angle Obstructions Controlling Obstructions to Runway Approaches, including Clearance Angle Declared Distances Take Off Run Available (TORA)/Take Off Distance Available (TODA)/ Accelerate-Stop Distance Available (ASDA)/Landing Distance Available (LDA) (for non-standard runway design criteria) Services and Facilities Services Fuel/Repairs/Storage Facilities Beacon/Universal Communications (UNICOM) Frequency/Control Tower Based Aircraft and Operations Based Aircraft Type/Number Operations Type/Number Remarks Special Conditions Example: Noise Abatement/Wildlife Restrictions Example: Aircraft Weight Limitations Table 3-16. Airport data.

Operations and Safety Data and Their Uses 31 Airport data contained in the Form 5010 database is useful for comparing physical or operational characteristics among airports as a benchmarking tool. The data is also useful for quickly finding airport contact information. 3.2.1.2 Data Collection Requirements Airport data is updated on a regular basis. Information is collected by airport owners, state aviation agencies, FAA, or others through onsite inspections. Changes are reviewed by airport management and submitted via the ADIP (formerly Airport GIS) (FAA 2019d) and delivered to the FAA’s repository database for storage and dissemination (FAA 2019e). 3.2.2 Operations Network (OPSNET) For airports with air traffic control towers, daily aircraft operations (arrivals and departures) are recorded by the ATCT controllers based on three descriptors. These data points can be accessed through the FAA’s OPSNET (FAA 2019f). Aircraft operations data is useful for a variety of analytical purposes because the data represents the principal activity on the airfield. Operations are a main component driving Part 139 certification responsibilities and require- ments, safety, and justification for facility improvements. The data can be used to identify weekly or seasonal patterns, changes from period to period, and emerging trends. Operations are often used as a component for developing key performance indicators (KPIs) initially to establish a baseline metric and then for subsequent evaluation of the effectiveness of a change. Comparisons of operations types (e.g., air carrier) with other airports can help identify peer airports for benchmarking and further analyses. EXAMPLE: FINDING DATA SPECIFIC TO AN AIRPORT To find data for a specific airport, a search can be initiated through the FAA’s ADIP at https:/adip.faa.gov. The user enters the airport location identifier or airport name as shown in Figure 3-2. For example, to obtain airport data for Orlando Melbourne International Airport, the user would search for “MLB” in the [Search Facilities] box. The resulting data is shown in Figure 3-3. Once the query is entered, the user has the option to view detailed information regarding available facilities and services. The FAA Form 5010 information can be downloaded in a PDF format (Figure 3-4). Another option is to view a base map of the airport environs with an overlay of the runway(s). Various base maps can be selected, including recent aerial photography, topographic details, or a street map. A PDF version of the results can be downloaded using the link in the upper right- hand corner (see Adobe PDF logo). The resulting pdf report or Airport Master Record is shown in Figure 3-4. The current and complete 5010 airport database can also be downloaded following the instructions found at: https://www.faa.gov/airports/ airport_safety/airportdata_5010/#5010 under Airport Data and Information Portal— Repository Search (FAA 2019e).

32 Collecting and Sharing of Operations and Safety Data Figure 3-2. FAA ADIP search form (example). Figure 3-3. FAA ADIP search results (example).

Operations and Safety Data and Their Uses 33 Figure 3-4. FAA Form 5010—Airport Master Record (example).

34 Collecting and Sharing of Operations and Safety Data 3.2.2.1 Data Description FAA classifies aircraft operations based on a description of the flight’s operator, purpose, and weather conditions. Table 3-17 lists these classifications of class, category, and condition. Operations data can be obtained daily, monthly, or annually [calendar year (CY) or fiscal year (FY)] or based on day of the week, or for a custom range of dates. Within the OPSNET interface, there are eight modules that generate a series of reports. The most useful module for an airport is the [Airports Operations] module. This module reports aircraft movements, including IFR and VFR itinerant operations as well as local operations as logged by ATCTs. [Tower Operations] will include all takeoffs and landings at the airport, as well as overflights handled by the ATCT. [Facility Information] includes the official name of the facility, its classification, and hours of operation. The [Delays] function includes summa- rized information about reportable delays (FAA 2019f). Aircraft operations data is useful for a variety of purposes. An airport can review the data and identify weekly or seasonal patterns, changes from period to period, and emerging trends. Operations data can be used as a component for developing KPIs to establish a baseline metric and then for subsequent evaluation of the effectiveness of change. Comparisons of operations types (e.g., air carrier) with other airports can help identify peer airports for benchmarking and further analyses. 3.2.2.2 Data Collection Requirements Aircraft operations data is collected by ATCT personnel on a contemporaneous basis and submitted daily to the FAA OPSNET central database. In some cases, missing data can be identified by the airport and corrected through the ATCT facility. 3.2.3 Passenger Enplanements and Cargo (BTS T-100) Airline data is perhaps the most significant topic of interest to airports because it is an indicator of a broad variety of airport activity. Decisions related to capital funding [Airport Improvement Data Item Description CLASS Air Carrier Operation carrying passengers or cargo for hire or compensation (commercial) using an aircraft with a passenger seating capacity of more than 60 seats or a maximum payload capacity of more than 18,000 pounds. Air Taxi Operation carrying passengers or cargo for hire or compensation (commercial) using an aircraft with a passenger seating capacity of up to 60 seats or a maximum payload capacity of less than 18,000 pounds. GA Operation performed by any noncommercial civil aircraft. Military Operation performed by any non-civilian aircraft. CATEGORY Itinerant Operation performed by an aircraft arriving from or departing to another airport. Local Operation performed by an aircraft that remains in the local traffic pattern, executes simulated instrument approaches or low passes at the airport, or arriving from or departing to a designated practice area within a 20-mile radius of the airport. Overflight Operation that transitions through the airspace controlled by the air traffic control tower (ATCT) but not taking off or landing at the airport. CONDITION VFR Operation conducted under Visual Flight Rules (VFR), as described in Federal Aviation Regulation (FAR) Part 91, where specific minimum weather conditions are extant. Generally, these conditions include a ceiling of 1,000 feet above ground level and 3 statute mile visibility. IFR Operation conducted under Instrument Flight Rules (IFR), as described in FAR Part 91, where the aircraft is flown in contact with ATCT and following a filed IFR flight plan often in weather conditions requiring reference to instruments in the aircraft. Table 3-17. Data items for aircraft classifications.

Operations and Safety Data and Their Uses 35 Program (AIP), Passenger Facility Charges (PFC), etc.], parking and ground transportation, safety and security, airfield operations, and revenues are just a few examples of where airline data is important. Passenger enplanements and cargo carried are reported to the U.S. DOT Bureau of Trans- portation Statistics (BTS) by U.S. scheduled and non-scheduled certificated air carriers, commuter air carriers, and small certificated air carriers (Bureau of Transportation Statistics 2019). The term “enplanement” is broadly defined as a passenger boarding a commercial aircraft; however, there is a distinction regarding how enplanements are reported. Enplane- ments can be classified based on whether the travel was paid for or not. This includes a revenue enplaned passenger (i.e., traveling by a paid ticket or other remuneration) and a non-revenue enplaned passenger (traveling by voucher or pass, an airline employee, a lap child, or other person traveling for free). In most cases, only revenue enplanements for specific airports are reported by the U.S. DOT. While airlines are not required to report non-revenue enplaned passengers to the U.S. DOT, the airlines will report this data to each airport. Enplaned passengers can also be categorized based on their trip characteristics. An origin and destination enplanement is a passenger boarding an aircraft at the first or last point of their one-way itinerary. A connecting enplanement will include a passenger boarding an aircraft at an EXAMPLE: PEAK-YEAR AIRPORT OPERATIONS The FAA’s OPSNET database provides an airport access to historical aircraft operations from the previous month (posted after 20 days) and as far as the fiscal year for any airport with an ATCT. Access to the FAA’s OPSNET is available at the following link: https://aspm.faa.gov/opsnet/sys/main.asp. Figure 3-5 shows a screenshot of the OPSNET website (FAA 2019f). Using the previous example of Orlando Melbourne International Airport, or MLB, accessing OPSNET allows the user to identify airport characteristics for the peak year (FY 2014−2018). First, under [Output], the user checks the necessary boxes to retrieve data points. From the display, the user will highlight [Standard Report] with the option to [Show Itinerant] and [Show Local], choosing the format as [MS Excel]. Next, the user selects the [Dates] for the report. In this example, under Years, from [2014] and to [2018], selecting [Fiscal Year] and [All Days]. The third step identifies the airport; the user selects the airport(s) to report under [Facilities] and enters the airport code, [MLB]. The fourth step requires the user to select the filters for the report; for this example, the user would select [No filters] (default). The next step, under [Groupings], allows the user to select the sorting criteria. Then, the user chooses the available fields by [+ Date]. Lastly, the user selects [Run] to generate the report. A pop-up window will notify the user that “You have chosen to open: Web-Report-nnnnn.xls,” and offer an option to open or save the report file. For this example, using the resulting report (see Figure 3-6), FY 2014 was a peak year for operations at MLB. In reviewing the data within the report, the user can see that the following year (FY 2015) recorded the least number of operations for the period. Further review identifies that the decline can be attributed to a significant decrease in GA itinerant and local operations.

36 Collecting and Sharing of Operations and Safety Data Figure 3-5. OPSNET form (example). Figure 3-6. OPSNET airport operations report (example).

Operations and Safety Data and Their Uses 37 intermediate stop for their ultimate destination. Enplanements can also be classified as domestic if the itinerary remains within the borders of the United States as opposed to an international enplanement where the origination or destination is outside the United States. One other distinction among enplanements is whether the air travel occurs on a scheduled or non-scheduled commercial air service provider. Scheduled and non-scheduled air carriers certified to operate under 14 CFR Part 121 will use Form 41, Schedule T-100, U.S. Air Carrier Traffic and Capacity Data by Nonstop Segment and On-Flight Market, to report their enplane- ments. Non-scheduled commuter and on-demand (charter) air carriers operating under 14 CFR Part 135 can voluntarily report their enplanement using FAA Form 1800-31, Airport Activity Survey (FAA 2019n). Passenger enplanement counts are one factor used to categorize commercial service airports and determine the amount of funding an airport receives from the AIP as annual entitlements. Commercial airports are categorized based on the percentage of local enplanements to total U.S. enplanements. The categories are described in Table 3-18. Another airport classification the FAA uses is “cargo service” airport. Cargo service airports accommodate all-cargo aircraft (such as FedEx, UPS, etc.) in addition to commercial and GA aircraft and record a total annual landed weight of 100 million pounds or more. The landed weight is measured by the maximum gross landed weight of each cargo aircraft regardless of specific load carried. Similar to enplanements, the cargo airport classification helps determine the amount of cargo entitlement funding an airport receives from the AIP. Commercial airlines file Form 41, Schedule T-100, monthly, and this data is compiled and published in the U.S. DOT’s BTS database. Quarterly T-100 data filed since 1991 for enplanements is accessible at https://www.bts.dot.gov/browse-statistical-products-and-data/ bts-publications/data-bank-21-form-41-schedule-t-2-t-100 (Bureau of Transportation Statis- tics 2019). This database is used for a variety of intergovernmental uses. For example, the FAA uses the T-100 data for the Air Carrier Activity Information System (ACAIS), which serves as a database for enplanements at commercial service airports (FAA 2019g). An ACAIS report is published for each airport annually. It includes enplanement data for each operator in the following categories: • Large certificated air carriers (operate air carrier aircraft with seating capacity of more than 60 seats or a maximum payload capacity of more than 18,000 pounds) • Small certificated air carriers • Non-scheduled/on-demand air carriers (charters) • Foreign air carriers Unlike aircraft operations data, which is reported annually for the fiscal year and is current up to the previous month, the FAA only reports enplanement and cargo data from ACAIS for the previous calendar year. Many airports publish their own up-to-date enplaned passenger and other data from monthly airline reports and other sources. Category Criteria Large Hub Primary Greater than/equal to 1% Medium Hub Greater than/equal to 0.25% but less than 1% Small Hub Greater than/equal to 0.05% but less than 0.25% Nonhub Greater than/equal to 10,000 but less than 0.05% Non-Primary Commercial Service Airport Greater than/equal to 2,500 but less than 10,000 Note: Percentages are in terms of percent of total U.S. enplanements. Table 3-18. FAA commercial airport classifications.

38 Collecting and Sharing of Operations and Safety Data Airline data is useful for assessing the state of the airport’s air service market measured in the level of passenger activity collectively and for specific markets, for instance, load factors (percent of passengers versus available seats) between city-pairs to demonstrate the relative strength of that market. A consistently high load factor may indicate that additional service could be con- sidered, whereas a low load factor may trigger efforts to stimulate the market. Enplanements are a common component used for developing KPIs for evaluating the effectiveness of change. 3.2.3.1 Data Description The annual ACAIS passenger and cargo data is published by the FAA twice a year; first as preliminary data during late July, which provides an opportunity for airports to update and reconcile their records, and then as final data in September. This operations data goes as far back as CY 2000 and can be downloaded from the site. Current ASIAS passenger and cargo data can be accessed in hard copy or spreadsheet format (FAA 2019g). There is more current and robust airline data available online through the U.S. DOT BTS database (Bureau of Transportation Statistics 2019). However, the data is reported in a raw format and requires substantial manipulation to extract data useful for specific analyses. Form 41, Schedule T-100, contains several data points that are relevant to airport interests. Table 3-19 describes these query variables and the report data. The Form 41, Schedule T-100, data can report data on other airline activities such as freight (cargo) and mail, in addition to many other variables, such as the number of departures (scheduled versus performed) and distance between segments. 3.2.3.2 Data Collection Requirements Enplanement data is collected by the U.S. DOT through airline’s filing of their Form 41, Schedule T-100. The FAA uses the U.S. DOT’s data to support the ACAIS database, which is used Commercial Airline Data FILTERS Filter Year Year Period of data set to be reported Filter Period Month Period of data set to be reported VARIABLES Variable Field Name Description Time Period Month Period of reported data (quarter or year) Carrier UniqueCarrier International Air Transport Association (IATA) Code for reporting air carrier UniqueCarrierName Name of reporting air carrier Segment Origin Originating airport of trip segment Dest Destination airport of trip segment Aircraft Type Aircraft Type FAA aircraft type SUMMARIES Field Name Description Seats Available seats per segment per period Passengers Enplaned passengers per segment per period Table 3-19. Commercial airline data.

Operations and Safety Data and Their Uses 39 EXAMPLE: PASSENGER ENPLANEMENTS The process to identify the number of passenger enplanements by a specific airline at an airport in a time period can be completed using the BTS T-100 database (Bureau of Transportation Statistics 2019). For example, to determine Delta’s passenger load factors and passengers per departure at Orlando Melbourne International Airport (MLB) for the month of November 2018, the user would access data from the BTS T-100 database. First, the user selects the [Air Carrier Statistics (Form 41 Traffic) - U.S. Carriers] database. Next, the user chooses the [T-100 Domestic Segment (U.S. Carriers)] list and selects [Download]. From here, the user has a choice of filters found at the top of the page. From the available filters, the user selects: Filter Geography: [All] (Default/specific states can be selected) Filter Year: [2018] (Default = current year/specific year can be selected) Filter Period: [All] (Default/months can be selected) In addition, the user should also select other specific data filters as follows: Summaries: [DepPerformed] [Seats] [Passengers] Carrier: [UniqueCarrier] [UniqueCarrierName] Origin: [OriginAirportID] [Origin] Destination: [DestAirportID] [Dest] Time Period: [Month] Lastly, the user enters [Download] from the upper right-hand corner. The data report can be downloaded as a compressed (.zip) file. The extracted file provides a comma delimited (.csv) text file that can be opened or imported into a spreadsheet. The data report file contains the entire Form 41, Schedule T-100 data for every airline and every airport for the period, which may be useful for a variety of analyses. The data can be indexed to facilitate sorting, analysis, and reporting. When using MS Excel, [Data] [Filter] are the options used to index the data. There are many other analyses that can be conducted from the raw data using spreadsheet tools (e.g., Pivot Tables, etc.). For this example, filtering the raw airline data Delta at MLB would include [UniqueCarrier = DL] and [Origin = MLB]. The results yield the following data: Seats = 17,476 Passengers = 15,486 Load Factor = (15,486/17,476) = 88.6% Passengers per Departure = 15,486/142 = 109 (Bureau of Transportation Statistics 2019).

40 Collecting and Sharing of Operations and Safety Data primarily to establish AIP funding levels among the commercial airports (FAA 2019g). Airports are given an opportunity to correct preliminary ACAIS enplanement data each year based on locally reported numbers. 3.2.4 Airport Financial Data (via CATS) Since the mid-1990s, the FAA has collected detailed financial data from commercial service airports via its Certification Activity Tracking System (CATS). The FAA requires all commercial service airports (2,500 or more annual enplanements) to file two forms. FAA Form 5100-126, Financial Government Payment Report, is used to report any payments made to governmental entities for services rendered or for services the airport performed for other governmental entities, including the value of any land and facilities the airport provides to such entities (FAA 2019h). FAA Form 5100-127, Operating and Financial Summary, is used for reporting the airport’s annual revenues, expenses, and other financial information (FAA 2019i). Both forms are completed online by airports via CATS. Reports are due no later than 90 days after the end of the airport’s fiscal year. The information contained in the reports must be certified as accurate by the airport’s chief financial officer or designated representative. 3.2.4.1 Data Description The data contained on FAA Form 5100-127 resembles an airport income statement but with additional information for characterizing airport activity. The data is used by the FAA primarily to monitor the financial performance of commercial airports particularly for assessing if an airport is financially self-sustaining (i.e., operating revenues meet operating expenses). The fact that the data is publicly accessible makes the CATS a useful tool for performing financial analyses. Tables 3-20 and 3-21 present outlines of the major categories of data included in FAA Form 5100-127. As can be seen, the focus is on revenues from specific activities at the airport (Table 3-20), while expenses are not broken out by the same activities (Table 3-21). Aeronautical Operating Revenue Non-Aeronautical Operating Revenue Airline Revenue Non-terminal facility and land leases Passenger airline landing fees Terminal (food and beverage) Terminal arrival fees, rents, and utilities Terminal (retail and duty free) Terminal area apron charges/tiedowns Rental cars Non-Airline Aeronautical Revenue Parking and ground transportation Landing fees Hotel FBO revenue; contract or sponsor-operated Non-Operating Revenue Cargo and hangar rentals Interest income Fuel sales net profit/loss or fuel flowage fees Grants Security reimbursement from federal government Passenger facility charges (PFCs) Capital contributions Table 3-20. Airport financial data (revenues). Operating Expenses Personnel compensation and benefits Communications and utilities Supplies and materials Contractual services Insurance claims and settlements Depreciation Table 3-21. Airport financial data (expenses).

Operations and Safety Data and Their Uses 41 Form 5100-127 also contains information as shown in Table 3-22 that is helpful for trend analysis benchmarking against other airports. Data from the CATS can be reported for individual airports or collectively by airport hub category (large, medium, etc.). Airport financial data contained in the CATS database can be used for a variety of purposes, such as comparing financial characteristics among airports as a benchmarking tool as well as assessing revenue and expense trends against operations, enplanements, full-time employees, and so forth. For example, the data could be used to compare a specific airport’s revenue per enplanement with that for all nonhub airports. Other examples can include identifying average ARFF costs, landing fees, or personnel costs as a percentage of total operating expenses. Readily available financial data for commercial airports can be employed as a part of a broader analysis of operations and safety issues. Concurrent with the filing of Form 5100-127, Form 126 is designed to provide FAA with data related to payments to other governmental units in cash, services rendered, or other compensa- tion to municipalities, including internal departments, county, state, federal agencies, and other political subdivisions. Compensation may be for cash, inter-departmental transfers, use of property, or for services using airport personnel and equipment. For payments other than cash, the fair market value rents of airport property, or the value of personnel and/or equipment expenses as in-kind services, are reported. Other Airport Data Enplanements Landed weights in pounds Signatory landing fee rate per 1,000 lb Annual aircraft operations Passenger airline cost per enplanement Full-time equivalent employees Security and law enforcement costs ARFF costs Repairs and maintenance Marketing/Advertising/Promotions Table 3-22. Other airport data. EXAMPLE: PASSENGER ENPLANEMENTS FINANCIAL RECORDS Accessing the financial reports of passenger enplanements at an airport for a given time period can be easily done using the Form 5100-127 database. For example, to obtain downloadable financial reports for passenger enplanements at Orlando Melbourne International Airport (MLB) for FY 2017−2018, the user would access data from the Form 5100-127 database. Airport financial data can be accessed via CATS (FAA 2019j). Figure 3-7 illustrates the data from the CATS search form. For a specific airport, a search can be initiated by entering the airport location identifier or the airport name. The range of years is also required. Options for the report results include a screen view or an Excel spreadsheet. For this example, searching [MLB] for [FY 2018] and [FY 2017] with a screen view yields the results found in Figure 3-8.

42 Collecting and Sharing of Operations and Safety Data Figure 3-7. CATS search form (example). 3.2.4.2 Data Collection Requirements Financial data is collected by the FAA through each commercial airport’s annual filing of their Forms 126 and 127, certified by the airport’s chief financial officer. 3.2.5 Airport Weather Most airports use an automated weather observation system for weather reporting. There are currently over 2,000 automated weather observation systems at airports throughout the United States that are owned and maintained by the National Weather Service, FAA, and airport sponsors (Switzer et al. 2019). An Automated Surface Observing System (ASOS) is a weather reporting system owned and operated by the federal government. An Automated Weather Observing System (AWOS) can have similar components as an ASOS and, while some of them are also federally owned and operated, the majority of AWOS units belong to airport sponsors. Regardless of ownership, the distinction between the two systems is primarily in their capabilities. An ASOS will have a complete array of weather sensors that monitor and report data continu- ously, including the type and intensity of precipitation and wind gusts. AWOS units may have fewer components and lesser capabilities. Each of these stations report weather data to a central

Operations and Safety Data and Their Uses 43 Figure 3-8. Airport financial data using CATS (example).

44 Collecting and Sharing of Operations and Safety Data database maintained by the National Oceanic and Atmospheric Administration’s (NOAA’s) National Centers for Environmental Information (NCEI). The FAA identifies ASOS and AWOS station types located across the United States by state or airport identifier (FAA 2019k). Typical weather data that are reported by these stations include the following: • Date and time of observation • Temperature • Dew point • Wind speed and direction • Barometric pressure • Visibility • Cloud ceiling • Cloud cover • Weather conditions (rain, snow, thunderstorms, etc.) Weather reports are usually transmitted to the central database on a 1-min- or 5-min-interval basis; however, the data may be reported as an hourly average. Weather data can be useful for a variety of purposes from evaluating specific observations as part of an accident or incident investigation to analyzing evidence regarding long-term climatic impacts that may be affecting airport operations, for example, measuring the number of closures or delays related to adverse weather, identifying snow removal activities as a function of cumulative snowfall, or identifying periods of extended visibility constraints. The FAA, airports, and their consultants use wind data for determining the need for cross- wind runways and ceiling and visibility data for justifying navigation instrumentation. Weather data is also useful for determining the prevailing conditions at a specific time or cumulatively over an extended period. Weather may have been a contributing factor for a major incident and having official weather data could help describe the environment during the event. Using weather data to determine the number of rain days during a construction period could be useful when analyzing project management issues. 3.2.5.1 Data Description Historical weather data reported by these weather stations are archived by NCEI and available as a downloadable file. Table 3-23 presents the categories of data included in the weather station report. The velocity of wind gusts, amount of precipitation (e.g., rainfall), and other data may also be reported if the sensors are available. Data Description Date and Time Date and time of averaged observation (no adjustment for Daylight Saving Time (DST) Altimeter Setting Barometric pressure (in Hg) Temperature Ambient air temperature (in ⁰F) Dewpoint Temperature water vapor condenses Relative Humidity Ratio of dewpoint to temperature Wind Direction Direction wind is coming from (in 10⁰ increments) Wind Speed Speed (in knots) Visibility Distance to farthest known visible object (in statute miles) Sky Condition Characteristics of observed clouds Cloud Cover Percent of clouds (FEW (1/8 to 2/8 cloud coverage); SCT (SCATTERED, 3/8 to 4/8 cloud coverage; BKN (broken sky, 5/8 to 7/8 cloud coverage); OVC (OVERCAST, 8/8 complete cloud coverage) Ceiling Height to cloud cover base (in feet) Weather Type Classification and intensity of precipitation or another obscuration Table 3-23. Airport weather data.

Operations and Safety Data and Their Uses 45 EXAMPLE: WEATHER DATA Weather data for a specific airport can be accessed through the NCEI’s Climate Data Online at https://www.ncdc.noaa.gov/cdo-web/datatools/lcd (NOAA 2019). The NCEI website uses a commerce-based platform; however, there is no fee associated with accessing the data. The website provides a series of search tools to allow the user to download the raw weather data from a specific query that can then be used for further analysis. An airport can search for weather data as part of an investigation of a vehicle incident. For example, an aircraft/ground service vehicle mishap occurred at MLB on the morning of December 4, 2018. To determine prevailing weather conditions at MLB, the user would need to know the date and time of the incident. • Date of incident: 2018-12-04 • Time of incident: 0635 Using the Map Tool, the user selects the [Zip Code] location search parameter and enters the 5-digit zip code for MLB [32901], as shown in Figure 3-9. The user selects [Melbourne International Airport, FL, US] and [ADD TO CART]. The next steps are based on data relevant only to MLB. After adding to cart, the user selects the link in the upper right corner. Then, the user selects the Output Format. Selecting [LCD CSV] will deliver a comma delimited (.csv) text file that can be imported into a spreadsheet for analysis. To identify the date, select the date range using the calendar feature. The user selects [Year] [Month] [Day] for both start and end dates of the data. Once entered, the user selects [Apply] and then [Continue]. After checking the Requested Data Review, the user enters their email address (first time users will be asked to validate an email address) and then selects [Confirm Order]. A confirmation page will indicate the request was successfully submitted, and an email with a link to the requested data will be sent shortly. When the data request has been completed, the [Download] option should be available for selection. Once the document has been downloaded, the user can access the data by opening or importing the file as a spreadsheet and looking up the specific date and time for weather observations. Table 3-24 presents the weather observations for the date and time of the MLB incident example. A review of the weather data indicates a thunderstorm occurred in the area beginning around 06:10:00 with rapidly diminishing visibility down to ½ mile due to heavy rain and fog. These conditions may indicate that the incident occurred while ramp activities should have been suspended. There are many forms of analyses that can be conducted using the raw data using spreadsheet tools (e.g., pivot tables, etc.). 3.2.5.2 Data Collection Requirements Weather data is collected through various sensors located at the airport and automatically transmitted to the NCEI database where the data is archived. Current weather observations from each station are disseminated to the FAA and other outlets for flight planning purposes.

46 Collecting and Sharing of Operations and Safety Data 3.2.6 Aviation Safety Reporting System (ASRS) The National Aeronautics and Space Administration’s (NASA’s) ASRS was established in 1976 as a joint venture with FAA to collect voluntarily submitted aviation safety reports from pilots and flight crews, ATC, aircraft mechanics, and others. The primary purpose of the ASRS is to collect data to identify potential safety issues relevant to the National Airspace System (NAS) that will help FAA and others consider mitigation measures and thus enhance the safety of the Figure 3-9. Weather report data page (example). Date/Time Altimeter Dew Point Temperature Precipitation Type Visibility Wind Direction Wind Speed 2018-12-04T06:02:00 29.97 72 74 0.01 -RA:02 BR:1 |RA |RA 3 340 5 2018-12-04T06:10:00 29.98 71 73 0.01 TS:7 |TS TS | 10 320 6 2018-12-04T06:16:00 29.98 71 73 0.09 TS:7 BR:1 |TS TS | 1.75 330 5 2018-12-04T06:24:00 29.98 72 73 - TS:7 BR:1 |TS | 1 340 5 2018-12-04T06:31:00 29.98 71 73 0.39 TS:7 BR:1 |TS TS | 0.75 290 7 2018-12-04T06:39:00 29.99 71 72 0.52 +RA:02 FG:2 |FG RA |RA 0.5 300 5 2018-12-04T06:46:00 29.99 71 72 0.53 RA:02 BR:1 |RA |RA 2.00V 290 5 2018-12-04T06:49:00 29.99 72 72 0.53 -RA:02 BR:1 |RA |RA 4 300 5 2018-12-04T06:53:00 29.99 71 72 0.52 -RA:02 |RA |RA 7 320 5 TS = thunderstorm; BR = mist or light fog; −RA = light rain; RA = moderate rain; +RA = heavy rain; FG = fog. Table 3-24. Select weather data.

Operations and Safety Data and Their Uses 47 NAS (NASA 2019b). The ASRS database is a public repository serving the research needs of a variety of governmental, organization, and academic interests. ASRS data can be useful for identifying similar incidents of safety-related issues. Common issues affecting airport operations can reveal a pattern of concerns that relate to the operation of the airport. A series of search tools enable the user to download relevant ASRS reports based on a specific query. The results can then be used for further analysis. 3.2.6.1 Data Description The ASRS database contains a broad set of variables that can be used in queries. Table 3-25 presents the major categories of data included in the ASRS database. Any number and mix of these variables can be used to define a query of the database. Querying the ASRS database is initiated by identifying the lookup values for a data category. Selecting each variable of interest will return specific instances where an ASRS report has been submitted. Null selection will return all incidents of other selected variables going as far back as the ARSR has records for. The ASRS has a robust set of incident reports affecting safety. Even though ASRS is a volun- tary reporting system, the information contained therein is considered comprehensive and reliable given its overwhelming use and industry acceptance. The data is useful for identifying the number of and extent of the incidents in question as well as common circumstances and other factors contributing to the issue. While the ASRS appears to be focused on flight activity, there are also substantial records related to reported ground operations that could useful in analyzing issues. 3.2.6.2 Data Collection Requirements ASRS data is collected by NASA through the submittal of reports by individuals who observed or were involved in a circumstance where safety was compromised. The data is archived and made available publicly to serve research interests involving aviation safety. Data Description Date and Report Number Period of Research (or report number if known) Place Location (LOCID) and/or State Environment Lighting Dawn/Daylight/Night, etc. Weather Conditions (Rain/Snow/Fog, etc.) Person Reporter Organization Air Carrier/FBO/Personal, etc. (Note: Airport not a choice) Reporter Function Air Traffic Control (ATC)/Flight Crew/Ground Personnel, etc. Aircraft Operation (FAR) Regulatory Authority (FAR Part 91/121/135, etc.) Flight Phase Takeoff/Landing/Taxiing/Parked, etc.) Flight Plan VFR/IFR, etc. In-Flight Characteristics of observed clouds Make/Model Aircraft Type (B737-800/Challenger 650, etc.) Mission Passenger/Cargo/Training, etc. Event Assessment Classification and Description Event Type Anomaly (Ground incursion/excursion, etc.). Also, Critical versus Less Severe Detector Automation versus Person [also ATC, air conditioning (A/C) equipment, etc.] Primary Problem Procedure, staffing, airport, etc. Contributing Factors Company policy, human factors, environment (non-weather), etc. Human Factors Distraction, fatigue, situational awareness, etc. Result ATC/Flight crew (also Issued Advisory/Provided Assistance, etc.) Text (Narrative/Synopsis) Keywords with Boolean functions (“AND”, “OR”) and Wildcards (“%”) Table 3-25. ASRS data.

48 Collecting and Sharing of Operations and Safety Data EXAMPLE: RAMP INCIDENTS INVOLVING MARSHALLING AIRCRAFT TO GATES To determine the magnitude and extent of ramp incidents reported to ASRS at an airport, one can access data from the ASRS database. The ASRS database can be accessed through NASA’s website at https://asrs.arc.nasa.gov/search/database.html (NASA 2019a). For example, an airport can obtain data on all ramp incidents reported to the ASRS involving marshalling aircraft to the gate. Figure 3-10 shows the search page for the ASRS database. Using the ASRS search interface (see Figure 3-10), the user should select the following variables: Flight Phase: [Taxi] Mission: [Passenger] Human Factors: [Distraction] OR [Situational Awareness] Result: [Aircraft Damaged] Text contains: [Marshall] OR [marshalling] Once the variables are selected, the database search returns all incidents that match the criteria selected. For this example, 14 incidents matched the criteria. The ASRS system provides options for reporting the data as shown in Figure 3-11. An example of the narrative report using the retrieved weather data follows: As we pulled into the gate area, we both looked closely at the Safety Zone; our aircraft was a scimitar equipped -800 and it appeared clear. The Ramp Agent had Wing Walkers and wands. We followed the Ramp Agent’s guidance closely and parked directly and right on the spot. After setting the parking brake and shutting down, the First Officer noticed the Wing Walker trying to communicate something. After the completion of our Parking Checklist, I went down to the ramp to investigate. Apparently, the nose cone of our aircraft had made contact with the top of a pushback tug. Maintenance and Dispatch were notified. The Marshalling Ramp Agent needs to walk to the back-end of Safety Zone to double check that no part of the pushback tug hangs over the line, before focusing attention on guiding the aircraft in on the line. All Company pushback tugs need to have a flag installed on the front so we know their exact location at eye level. The weather data indicated there was a thunderstorm in the area beginning around 0610 with rapidly diminishing visibility down to ½ mile due to heavy rain and fog. These conditions may indicate that the incident occurred while ramp activities should have been suspended. 3.2.7 NTSB Accident Reports The NTSB was created in 1967 as an independent agency within the U.S. DOT. Later, it became a fully independent investigative agency outside of other governmental administrations. The NTSB is charged with “conducting thorough, accurate, and independent investigations and for producing timely, well-considered recommendations to enhance transportation safety” (NTSB 2017). In most cases, the NTSB (or its assignees) will investigate aircraft accidents where a person is fatally or seriously injured, the aircraft sustains significant damage or structural failure, or the aircraft goes missing. Certain incidents that do not fit the description of an accident are also included if the event is considered significant to aviation safety. The investigation and subsequent report of their factual findings and opinion regarding probable cause are documented with the goal of ensuring that similar accidents never happen again.

Operations and Safety Data and Their Uses 49 Figure 3-10. ASRS search form (example). Figure 3-11. ASRS search results (example).

50 Collecting and Sharing of Operations and Safety Data As part of this mission, the NTSB maintains a public searchable database of aviation accidents and certain significant incidents that have been investigated or otherwise reported. The data goes back to 1962, and it ranges from preliminary accident reports posted only a few days after an accident to a fully detailed description of the accident, including its probable cause. The NTSB data can be highly effective in identifying similar incidents where safety was compromised, providing substantial information about events that have been classified as accidents and which tend to have more significant consequences. 3.2.7.1 Data Description The NTSB database contains detailed factual data regarding aviation accidents, including the categorization of the conditions and circumstances relevant to the event, the type of accident, time and place, physical and environmental conditions, and affected people and property. A text narrative is also available that describes the event and adds context. The NTSB database contains a broad set of variables that can be selected for queries, as shown in Table 3-26. Any number and mix of these variables can be used to define a query of the database. Querying the NTSB database can be initiated by selecting or specifying the lookup values among the various categories. Null selection will return all incidents of other selected vari- ables going as far back as NTSB has records for. Full narrative data may not be available for reports dated before 1993. The NTSB’s set of accident and incident reports are useful for identifying the magnitude and extent of the events involving common circumstances and other factors contributing to the case. The data may be useful for assessing the consequences of ground operation accidents and other circumstances where the airport was directly or indirectly involved, such as accidents Operation Operation (Regulatory) Part 91/Part 121/Part 135, etc. Purpose of Flight Business/Instructional/Personal, etc. Schedule Scheduled/Non-Scheduled Air Carrier Specific Air Carrier Name (American/Delta, etc.) NTSB Status Accident Number Specific NTSB Report Number (Example: DCA06MA064) Report Status Preliminary/Factual/Final Probable Cause Issue NTSB Issues Probable Cause Event Details Airport Name Specific Airport Name Airport Code LOCID (example: MLB) Weather Condition Visual Meteorological Conditions (VMC)/Instrument Meteorological Conditions (IMC) Broad Phase of Flight Takeoff/Approach/Taxi, etc. Narrative/Synopsis Search Keywords with Boolean Functions (“AND”, “OR”) and Wildcards (“%”) Data Description Accident/Incident Information Event Dates Period of Research Location City/State/Country Investigation Type Accident/Incident Injury Severity Fatal/Non-Fatal Aircraft Category Airplane/Helicopter/Glider, etc. Amateur Built Include in Search? (Yes/No) Make/Model Example: Boeing/B737-800 Registration U.S. or International A/C Tail Number (Example: N123X/C-DNEK) Damage Minor/Substantial/Destroyed Number of Engines 1/2/3, etc. Engine Type Reciprocating/Turbo Fan/Electric, etc. Table 3-26. NTSB aviation accident database.

Operations and Safety Data and Their Uses 51 EXAMPLE: AIRCRAFT RAMP ACCIDENTS An airport can review the aircraft ramp accidents occurring at their airport by accessing the NTSB database: https://www.ntsb.gov/_layouts/ntsb.aviation/index.aspx (NTSB 2019). Figure 3-12 illustrates the data search form. Using the NTSB search interface, the user can select from a variety of variables. For this example, the following variables were selected: Operation: [Part 121: Air Carrier] Broad Phase of Flight: [Taxi] Text contains: [vehicle] After selecting the variables, the user runs a search from the search form. For this example, the NTSB database search returned 60 incidents that matched the criteria. An example of one accident report is shown in Figure 3-13. The NTSB database system provides options for reporting the data as an XML or comma delimited (.csv) text file. occurring on the ramp during snow removal operations, or where facility deficiencies may have been identified. 3.2.7.2 Data Collection Requirements The NTSB files preliminary reports, factual details, and final reports for each accident investigation in which the NTSB participates. The objective data from the factual details are categorized, and the narrative report text is published in a searchable database that is publicly available. 3.2.8 FAA Aviation Incident Data System (AIDS) The FAA’s AIDS database contains records for incidents involving aircraft that do not meet the thresholds defined by the NTSB for the level of aircraft damage or the severity of an injury. The FAA AIDS database serves as a repository for minor aircraft mishaps to help quantify persistent and emerging aviation safety issues and to provide context for further analyses. The FAA AIDS database contains incidents that occurred between 1978 and the present, with full narratives for all incident reports occurring from January 1, 1995, to the present. The data in the FAA AIDS database is gathered from a variety of sources, including incident reports on FAA Form 8020-5. The FAA AIDS database contains accident information that may reflect the same incident from the NTSB database (FAA 2019l). The FAA issues a separate report for each aircraft involved in an aviation incident. For example, as the FAA receives reports of bird strikes, subsequent investigations reveal that the aircraft damage did not meet the NTSB’s definition of an accident. While these incidents are not significant to the NTSB, they are still considered valuable information by the FAA (e.g., they add to a cumulative total of similar bird strike events near a particular airport revealing a potential wildlife hazard that can be mitigated to improve aviation safety). Like the NTSB and ASRS data, the FAA AIDS data is helpful in identifying similar circum- stances where safety has been compromised. While limited in detail and searchable content, the

52 Collecting and Sharing of Operations and Safety Data Figure 3-12. NTSB search form (example). FAA AIDS data provides insightful information about mishaps that had a lesser consequence than an accident but could have resulted in significant property damage, injuries, or worse. 3.2.8.1 Data Description While the AIDS database contains a limited set of variables compared with NTSB data, facts related to specific aviation incidents include the time, place, and type of the incident, and operational conditions. A text narrative is also available describing the event and adding context. Table 3-27 presents the searchable data contained in the AIDS database. 3.2.8.2 Data Collection Requirements The FAA AIDS data is collected and maintained by the FAA’s Aviation Data System Branch, Regulatory Support Division, Flight Standards Service. The data comes from the FAA’s investigations and standardized reporting of aircraft mishaps that do not exceed the NTSB’s threshold for significance.

Operations and Safety Data and Their Uses 53 Figure 3-13. NTSB aviation accident final report (example). 3.3 Data Analysis Operations and safety benchmarking and trend analysis are used to provide a systematic method to determine safety performance of a process. Understanding how benchmarking and trend analysis relate to business processes and then adapting these practices to help organizations improve their performance are the major benefits associated with benchmarking and trend analysis. Further, a robust benchmarking process can ultimately result in continual improve- ment of safety systems and a cultural sustainability. 3.3.1 Benchmarking and Trend Analysis Benchmarking and trend analysis are activities that use data for improvement, produc- tivity, and efficiency enhancements. Benchmarking refers to comparing performance of one airport to another in the same time period. Trend analysis refers to analyzing performance

54 Collecting and Sharing of Operations and Safety Data EXAMPLE: AIRCRAFT VERSUS VEHICLE MISHAPS While the FAA AIDS database can be searched for any number of the categorized selections, the most useful search for airports is to use a text search of the narrative reports. Date ranges may also be effective to omit older reports. Aircraft incident reports can be accessed using the following link: https://www.asias.faa.gov/apex/ f?p=100:12 (FAA 2019l). Figure 3-14 illustrates the FAA AIDS data search form. An airport can retrieve FAA AIDS data on accidents or incidents occurring at their airport from the FAA AIDS database. To retrieve available data on incidents involving aircraft and vehicles, the user accesses the FAA AIDS search form. For this example, the user adds the term [vehicle] in the [Narrative Search] box and then in the upper right-hand corner, selects [Search AIDS]. For this example, the AIDS database search returned 370 incidents. An example of one incident report includes the following narrative report: AT APPROXIMATELY 10:35 AM ON OCTOBER 8, 2011 A SKYWEST AIRLINES BOMBARDIER CL-600-2B19 AIRCRAFT, REGISTRATION NUMBER N952SW, FLIGHT NUMBER 6478 SUSTAINED MINOR DAMAGE TO RIGHT WING TIP AND WINGLET DURING DEICING OPERATIONS IN DENVER, CO. A SERVISAIR SINGLE OPERATOR DEICE VEHICLE STRUCK THE AIRCRAFT WHILE PARKED ON THE DEICE PAD. NO INJURIES WERE REPORTED. THE CREW AND PASSENGERS DEPLANED THROUGH THE MAIN CABIN DOOR AND WERE BUSSED BACK TO THE TERMINAL. TEMPORARY REPAIRS WERE INSTALLED AND THE AIRCRAFT WAS MAINTENANCE FERRIED TO SALT LAKE CITY FOR PERMANENT REPAIRS. The FAA AIDS system provides an option for reporting the data as a comma delimited (.csv) text file. Data Description Narrative Text (search keywords) Event AIDS Report No. If Known Event Start Date Date Range Event End Date Date Range Location State Incident State Airport Name Incident Airport Operations Flight Conduct Regulatory Authority (FAR Part 91/121/135 etc.) Flight Phase Takeoff/Landing/Taxiing/Parked, etc. Operator Name Commercial/Charter Operator (Delta Airlines/NetJets, etc.). Flight Phase Characteristics of Observed Clouds Aircraft Aircraft Registration # If Known Aircraft Make Manufacturer (Boeing, Cessna, Canadair-Bombardier, etc.) Aircraft Model 737, CE 172, CRJ900, etc. Aircraft (Sub)Model 800, All Models, etc. Table 3-27. AIDS data.

Operations and Safety Data and Their Uses 55 over time. Benchmarking and trend analysis of a data set requires organizations to establish performance goals with standards and measures for a specified time period. Comparison of the actual performance with the performance goals provides the means to identify best practices that lead to improved operating levels, improved organizational efficiency, and performance. Airport benchmarking and trend analysis are categorized into two types of comparisons: • Internal (or self-benchmarking) is when an airport compares its performance of a process against the performance of other similar/related processes at the airport. • External (or peer benchmarking) is when an airport compares its performance against other airports, either at a single point in time or over a period of time. Examples of airport benchmarking are shown in Table 3-28. Figure 3-14. FAA AIDS search form (example).

56 Collecting and Sharing of Operations and Safety Data 3.3.1.1 Process for Operations and Safety Benchmarking and Trend Analysis The process of benchmarking and trend analysis can be performed in four sequential steps. Step 1. Establish Goals and Implementation. The first phase in the benchmarking process consists of establishing the goals and objectives of the benchmark. These goals can be based on one or more of the following: • Performance assessment/process improvement • Risk assessment • Regulatory compliance reporting • Emerging trends analysis • Competitive analysis • Strategic planning During this step, it is necessary to obtain a full understanding of these goals and how they are measured. The airport must then decide what data is required and the method of data collection. Step 2. Data Collection. The second step relates to data collection, and the methods used to collect the data. Research is conducted to identify the metrics that will be used, to select candidates for the benchmark process, and to collect the data used in the benchmarking perfor- mance process. Understanding the function of the airport’s core competencies and processes is essential to the success of this step. Data collection can be achieved in a variety of ways. Many data sets are now collected auto- matically and are available in digital format. Other data is available from checklists, surveys, interviews, questionnaires, and published data. Data collection should be conducted in a uniform manner to ensure that results will be continually consistent. It is also crucial to obtain accurate data from reliable sources; otherwise, the interpretation of the results may be skewed. Step 3. Analysis. There are two classes of benchmarking: trend and comparative. • Trend benchmarking evaluates performance and safety over time, specifically looking for decaying or improving performance. • Comparative benchmarking evaluates performance and safety by comparing the same or similar processes. Comparative benchmarking is generally performed across airports but Category Trends Analysis (Benchmark over Time; e.g., Year to Year) Comparisons (Benchmark Against Peers) Internal (Benchmarking Against Self) • Incidents • Accidents • Security line queue times • Wages (comparing internal wages to similar departments) • Staff per operation (staffing requirements and efforts to improve efficiencies) External (Benchmarking Against Peers) • Passengers serviced • Operations per day • Wages (comparing internal wages to similar sized airports) • Staff per operation (staffing requirements and efforts to improve efficiencies) • Wildlife • Ramp space • Number of facilities • Cargo throughput • Passenger throughput Table 3-28. Examples of benchmarking and trend analysis.

Operations and Safety Data and Their Uses 57 could also be performed by comparing the same process internally year to year to gauge improvements. From this information, strategic planning can be used to make improvements to the pro- cesses. Understanding the reasons why the benchmark performance was superior to actual performance will expose the root cause of problem areas and allow for subsequent modification and improvement. The results should be analyzed to determine whether there are any gaps between the airport’s processes and those that have been used for benchmarking purposes. This analysis can be conducted within various timeframes, depending on whether an airport is looking at current trends or focusing on long-term trends. Step 4. Adaptation. The final phase of the benchmarking process is specifically linked to the adaptation of best practices and continuous improvement practices. Support of the various stakeholders involved in the process is necessary to ensure that newly acquired best practices can be applied. This can be achieved through effective communication with the relevant parties involved. Goals can then be set, and an action plan can be implemented to address the task of closing performance gaps and instituting processes for continuous improvement. 3.3.1.2 Notes on Benchmarking and Trend Analysis The benchmarking process is not a one-time event. It must be sustained to ensure that con- stant improvement is being made and that best practices are continually benchmarked against. Care should be taken when using voluntarily reported data. Counts of voluntarily reported data should not be benchmarked for trends or for comparison, because the data may not include all events, or may include all events for one period but not for others. Benchmarking from the voluntary reports can highlight the type of incidents reported. The sequence of events leading up to the event, environmental circumstances, and response to the event can be shared and used for lessons learned. The development and use of safety and performance “dashboards” can significantly enhance and provide real-time, hourly, daily, weekly, and monthly visualizations of an airport enterprise. One of the applications of these dashboards can include benchmarking. Linking the business process to customer needs is an essential part of benchmarking. It is also important to address confidentiality because organizations may consider certain information and data to be sensitive and for internal uses only. To maximize the effectiveness of the process, reciprocity with other airports and enterprises should be considered in order to capitalize on the quantity of data in the benchmark. It may be necessary to de-identify the data if it is made public. 3.3.1.3 Benefits of Operations and Safety Benchmarking Airports and enterprises interviewed rely on benchmarking to evaluate enterprise perfor- mance to • Better understand and manage the business elements of airport processes. • Anticipate potential problem areas or issues to be more responsive to the service requirements of tenants and users. • Reflect airport performance accurately to their governing bodies. • Understand their competitive position in the marketplace. • Monitor individual performance of stakeholders. • Achieve performance standards (which can be the deciding factor when determining who is awarded business or how to route air cargo in or out of a country or region). • Advance technology and improve supply chain and modal transportation processes. These coupled with forecasted growth in the air cargo business present airports with many challenges.

58 Collecting and Sharing of Operations and Safety Data EXAMPLE: WILDLIFE STRIKE BENCHMARKING A wildlife strike is the collision of one or more animals [i.e., birds, flying mammals (bats), terrestrial mammals, or reptiles] with an aircraft determined by direct observation of the collision or by indirect evidence (i.e., animal carcass or remains) found on the aircraft or on the ground. The FAA reported about 115,000 wildlife strikes from 1990 to 2011. Of these, the vast majority (97%) involved birds, 2% involved terrestrial mammals, and less than 1% involved flying mammals (bats) or reptiles (FAA Advisory Circular 150/5200-3B 2013). Bird and other wildlife strikes annually cause more than $380 million in damage to aircraft in U.S. civil and military aviation (direct and indirect costs vary annually) and place the lives of the aircraft crew and passengers at risk, and more than 300 people have been killed in the United States as a result of bird strikes (U.S. Fish and Wildlife Service 2018). Class I, II, and III Part 139 airports must comply with Part 139 regulations for Wildlife Hazard Management, whereas Class IV airports are exempt. Class I, II, and III airports are required to conduct an assessment (that should be followed by creation of a WHMP) only when triggering events are experienced. An airport can be in compliance regardless of whether it has an assessment or a WHMP. This benchmark example (see Table 3-29) is derived from data contained in “Wildlife Strikes to Civil Aircraft in the United States 1990–2018” (Dolbeer et al. 2019). Step 1. Establish Goals of Benchmark The purpose of benchmarking is to determine bird strike risk at the airport and guide improvements to the airport WHMP for bird strike risk. Benchmarking is conducted by making comparisons with other airports. Step 2. Data Collection Collect strike incidents and categorize as follows: • Region: airport environment (i) < 1,500 ft, (ii) approach and climb above 1,500 ft • Impact: (i) damage, (ii) negative impact on flight (e.g., aborted takeoff, precautionary/emergency landing, engine shutdown) • Species: (i) swallow, (ii) goose, etc. • Evidence: (i) property damage, (ii) carcass, etc. Step 3. Analysis • The example airport has an adverse effect strike rate of 0.6. An adverse effect strike rate of 0.6 puts this airport at the low risk end of the scale. Step 4. Adaptation • Is there a relationship between aircraft movements and adverse effect bird strikes? This example airport experienced a lower percentage of strikes with adverse effects below 1,500 ft (2.2%) than the national average (5.9%) of strikes. This airport experienced a lower percentage of strikes with adverse effects at or above 1,500 ft (7.6%) than the national average (11.9%) of strikes. There is no relationship between aircraft movements and adverse effect strike rate for the 100 busiest airports.

Operations and Safety Data and Their Uses 59 EXAMPLE: WILDLIFE STRIKE BENCHMARKING (Continued) • Do we need a separate benchmark for strikes on approach/departure at >1,500 ft above ground level? These strikes occurred >8 km from the airport. These strikes are important for risk analysis and mitigation, but they are not typically addressed in an airport’s WHMP. By creating a separate benchmark, the airport will assess the risk for these off airport strikes. Separate benchmarks also provide an objective basis to incorporate mitigation strategies for “off airport” strikes into the WHMP. The WHMP should include all mitigation measures and responsible parties to ensure effectiveness; this is inclusive of any off airport mitigations, which, in many cases, are the most effective. • What is an objective benchmark for the airport’s performance in mitigating risk? Comparison of the reported strike rate at an airport in relation to rates at other airports is not a valid metric because airports may vary in hazard level of species struck (e.g., swallow versus goose), completeness of reporting all strikes (e.g., carcasses found on runway), or number and type of migrating bird species over an airport. • Should the benchmark be the adverse effect strike rate? The bottom line of an airport’s WHMP is to reduce adverse effect strikes. Comparison of adverse effect strike rate at an airport in relation to rates at other airports is a valid metric because adverse effect strike rates incorporate the hazard level of species struck (e.g., swallow versus dove versus goose). There is also less bias among airports in reporting adverse effect strikes compared with all strikes. Location of Strike % Strikes with Adverse Effect <=1,500 ft 5.9% >1,500 ft 11.9% Source: Dolbeer and Begier 2012. Table 3-29. Sample national benchmark. 3.3.2 Key Performance Indicators for Operations and Safety Data Airport operations and safety data typically collected by Part 139 and non-Part 139 airports, such as GA airports large enough to invest in collecting operations data, provide the basis for operations and safety data. This data can be used for benchmarking, contextual analysis, and common situational awareness. Examples of operations data may include number of days required for snow removal, number of aircraft “turns” per aircraft parking area/gate, runway use, taxi times, and so forth. This type of data can provide valuable context when making crucial decisions that impact airport operations efficiency. Knowledge and tracking this type of information can help airports analyze and learn from data to manage operations and safety risks. Using the right data for benchmarking can help airports improve operating levels, efficiency, and performance. Analysis of operations and safety data can help airports identify trends to assist with strategic planning for needed improvements and can also be used to raise awareness for potential hazards before they become an issue.

60 Collecting and Sharing of Operations and Safety Data KPIs are a set of quantifiable measures used to gauge or compare performance in terms of meeting strategic and operations goals. KPIs vary between companies and industries, depend- ing on their priorities or performance criteria. In addition, there are also Safety Performance Indicators (SPIs). An airport needs the means and methods to identify their safety perfor- mance. The indicators need to be measurable and in line with an organization’s goals and objectives. These indicators can change and should be updated as progress is made toward established goals and objectives. The following list contains narrative examples of data fields associated with both Part 139 and non-Part 139 airports. These examples also contextualize the value of the data itself. Table 3-30 includes a list of airport data sources and the types of analysis that could be performed. This list identifies KPIs, SPIs, and other potential metrics that all airports should consider collecting, organizing, and analyzing. • Part 139 inspection data sources allow for the measurement of the airport operator’s effi- ciency at maintaining compliance with federal airfield standards. Measuring performance of compliance should allow an airport operator to ensure successful Part 139 compliance during annual inspections. By measuring the time and resources invested, the airport operator can quantify the cost of compliance. This is critically important when determining the true costs of the airfield. • ARFF inspection data is similar to Part 139 inspections data; it accounts for compliance costs and can be shown to stakeholders and business partners (such as airlines). This data provides the airport operator the tools and information needed to discuss operational improvements with fueling and fuel storage companies, enabling a better understanding of how well the individual organizations are conducting their operations in terms of operations and safety efficiency. • Having an established FOD program that tracks and determines the root cause of FOD (where it originated) allows the airport operator to set goals and objectives and manage them at their source. This allows for the costs associated with the FOD program to be accounted for and justifies the investment made into the FOD program. This data also provides valuable operations data for the airlines and other aircraft operators at the airport about how well their internal systems are working. • Monitoring OSHA-reportable accidents and incidents is important for revealing systemic problems or issues within an organization that need to be addressed, in addition to reporting to regulators and insurance companies. • Much like OSHA, reportable property damage reports can and should be used to look for systemic problems and issues that need to be addressed. • Maintaining training records is crucial. For example, these records can be reviewed after an event in a restricted area to determine whether or not the staff who accessed the area during the event had the required training to do so. If a significant number of staff did not have the required training to enter the area, there could be a higher likelihood of an event occurring. Or if staff with access to the area had undertaken training, an assessment of the effectiveness or ineffectiveness of the training for this event could be made. Training records provide an important metric when determining the effectiveness of training. • Baggage handling areas, ramps, and other facility inspections provide valuable data regarding sources of FOD, unreported property damage, and hazardous conditions. • Hazard reports provide information about what the local airport community is reporting or willing to report, and the types and trends of hazards. These reports should be addressed to reinforce a collaborative culture at the airport (e.g., if someone reports a condition, a response to that person indicating the condition has been or will be investigated is an important reinforcement). • Landside operations reports such as number of parked cars by parking product provide key context for how landside operations are performing in terms of operations and safety efficiencies.

Operations and Safety Data and Their Uses 61 Source Type of Data Trend Analysis Results/Benefits Part 139 Self- Inspections Reports • Number of discrepancies • Time to correct • Location (assets/systems) • Physical circumstances (winter, night, etc.) • Reason for time to correct (organization/dept. responsible for corrective action, parts, tools, access to area, etc.) • Identify systemic issues issues• Identify facility • Monitor corrective actions for effectiveness Fueling Operations Inspection Reports • Number of discrepancies by location and tenant • Time to correct • Location (e.g., fuel trucks) • Type • Responsible party • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds ARFF Runs (Non-Aircraft- Related) Reports • Number of runs • Runs by topic (fire, alarm, system alarms, etc.) • Location • Physical circumstances • Tenant and operation • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds ARFF Runs (Aircraft- Related) Reports • Number of runs • Operator • Aircraft type • Type of emergency or incident • Response times • Location • Physical circumstances • Tenant and operation • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds Medical Runs (Only Completed by Designated ARFF Staff) Reports • Number of runs • Type (heart, slip trip fall, accident, etc.) • Location • Physical circumstances • Tenant and operation • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds Training Records • Number of individuals trained • Testing results • Recurring or initial only • Organizations, other than airport staff with the most/least number of individuals trained, (helps to understand which organizations have the most potential to impact compliance) • Compare accidents and incidents • Compare organizations with pass/fail results • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds FOD Program Reports • Amount • Location • Type • Source • Environmental factors • Amount by source (identify root cause) • Measure the results of cleanup efforts, stop-at-the-source efforts, or both • Identify responsible party’s shortcomings • Identify systemic issues • Prioritize funds Baggage Handling Area, Ramp, Terminal, and Landside Inspection Reports • Number of completed inspections • Results (FOD, damage, lease violations, etc.) • Tenant and airline participation • Number of inspections for a relative sample size • Participation • Result trends over certain time periods • Areas to improve (less damage, less FOD, improved results from implementing mitigation measures) Airport Owner/ Operator OSHA (Personnel Safety Standards) Logs/Records • Reportable/ non-reportable events • Lost time • Type of injuries • Jobs and activities when events occurred • Costs associated with injuries • Jobs and activities with the highest event rate • Type of events • Individuals and/or departments • Costs over time • Identify departments and individuals who need improvement • Effectiveness of mitigation measures • Cost reduction (ideally) Table 3-30. 14 CFR Part 139-related airport data sources and analysis. (continued on next page)

62 Collecting and Sharing of Operations and Safety Data Safety Training Records (Non- OSHA) • Number of tenant or airline employees trained in safety reporting orientation • Airport operator staff and employees trained in safety reporting • Number of individuals and organizations trained • Test results over time • Number of individuals requiring retraining • Training effectiveness • Effectiveness of improvements and/ or redirection of training efforts Parking Revenue • Revenue by product o Long- and short- term, valet, garage, or shuttle operations o Off-airport companies • Product sales by time of year, day of the week, and time of day (manage demand) • Demographics willingness to spend for convenience • Demands modeling to maximize revenue Ground Transport Revenue • Revenue by product o Shared ride o Uber/Lyft o Taxis • Product sales by time of year, day of the week, and time of day (manage demand) • Demographics willingness to spend for convenience • Demands modeling to maximize revenue Concessions and Retail Sales • Sales per enplanement o Revenue by area (terminal and concourses) o Type of products sold • Product sales by time of year, day of week, and time of day (manage demand) • Sales by passenger type (assumptions can be made based on flight times, days of week, and time of year about whether passengers were on leisure or business). Airlines know most of their frequent flyers are business travelers, and agreements can be considered that will allow the exchange of this information • Cross-compare results with passenger demographics— maximize offerings to specific passenger types Property Damage Reports • Locations • Responsible organization or individual • Severity of event • Root cause (ideally) • Physical conditions (weather, etc.) • Trends in the type of data over time • Effectiveness of mitigation measures put in place Hazard Reports • Types of reports include: o Public reports o Internal airport reports o Tenant and airline reports • Time to investigate • Time to corrective action completion • Number of reports by organization or individual • Time spent on investigations • Time spent on actions • Progress toward safety goals and objectives • Feedback loop to reporters • Insight into the safety culture Incident and Accident Reports (Non- Aircraft- Related) • Public reports • Internal airport operator reports • Tenant and airline reports • Time to investigate • Time to corrective action(s) completion • Number of reports by organization or individual • Time spent on investigations • Time spent on actions • Identify organizations that might need assistance • Effectiveness of mitigation measures • Systemic issues with physical plant/ facilities that need to be addressed Source Type of Data Trend Analysis Results/Benefits Property Rent • Square foot revenue by space • Gross and net revenue by property • Benchmarking with surrounding areas that have similar type properties Table 3-30. (Continued).