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Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies (2011)

Chapter: Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation

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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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Suggested Citation:"Part 1 - Applications of Risk Management to Support Performance-Based Resource Allocation." National Academies of Sciences, Engineering, and Medicine. 2011. Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies. Washington, DC: The National Academies Press. doi: 10.17226/13325.
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P A R T 1 Applications of Risk Management to Support Performance-Based Resource Allocation

1-1-1 NCHRP 8-70 research, which led to NCHRP Report 666: Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies, described a comprehensive framework and methods to set specific performance targets to guide agency policies, plans, and programs. It also detailed factors that influence target-setting and the success of performance-based resource allocation (PBRA) systems, explaining how agencies may successfully design, implement, and use such systems. Finally, it addressed the data and information needs, data acquisition and management systems, and institutional relationships required to support successful PBRA systems. Research in NCHRP 8-70 highlighted the significant un- certainties agencies face from frequent changes of important variables outside their control, such as cost inflation, changing political leadership and their priorities, and revenues available for agency programs. These uncertainties pose risks that asset- allocation decisions will be rendered inappropriate when external variables change. Some organizations in both the private and public sectors utilize risk analysis to assess whether certain resource-allocation choices and consequent system and agency performance are more susceptible to these uncertainties. Such risk analysis has been found to be helpful, but is not cur- rently in common use among transportation agencies. Based on this work, the NCHRP 8-70 Project Panel identi- fied the need for further research on how risk analysis may best be used by transportation agencies to support PBRA. This primer addresses that need and serves as an introduction to the topic. The guidance provided in this report is consistent with, but different than, the risk management approaches being explored as part of NCHRP 20-24(74). That research effort is addressing risks related to internal operations and program and project delivery. In contrast, this document focuses on the application of risk management techniques to support funding decisions, such as by helping to prioritize which proj- ects should be delivered. This section provides an introduction to PBRA, which is described in greater detail in Volume I of NCHRP Report 666. Following that is a brief summary of the five case studies discussed in more detail throughout the primer. The remainder of this document describes a process for transportation agencies to systematically assess and address risks. It also provides several examples, organized by the steps of the process, that illustrate how state departments of transportation (DOTs) are using risk management to support funding decisions. 1.1 Introduction to Performance-Based Resource Allocation Despite uneven implementation among state departments of transportation (DOTs), performance management has been evolving steadily into an effective business process that links organizational goals and objectives to resources and results. Performance measures, and their attendant targets, are the lynchpin in this process. They are the link connecting goals to specific investments. The methods by which the measures and targets are established, including underlying data support systems, play a critical role in the overall success of a public agency or private company. Performance-based resource allocation takes place within an overall Performance Management Framework, depicted in Figure 1.1.1, which is comprised of the following six basic elements: Establish Goals and Objectives. Performance-based resource allocation decisions are anchored in a set of policy goals and objectives that identify an organization’s desired direction and reflect the environment within which its business is conducted. For example, many state DOTs have well-defined goals for the transportation system, including infrastructure condition, level of service and safety, as well as goals reflecting C H A P T E R 1 Introduction

economic, environmental, and community values. Likewise, the private sector frequently establishes policy goals to guide production of products and services while defining the envi- ronmental and community context for its investment decisions. Select Performance Measures. Performance measures are a set of metrics used by organizations to monitor progress toward achieving a goal or objective. The criteria for selecting measures often include • Feasibility, • Policy sensitivity, • Ease of understanding, and • Usefulness in actual decision making. Identify Targets. Targets are a quantifiable point in time at which an organization achieves all or a portion of its goals. These points set a performance level for each organizational measure, such as achieving a 25 percent reduction in highway fatalities by 2030. The methods used to set such a target include • Establish Performance Management Framework, • Evaluate the factors influencing target-setting, • Select the appropriate method(s) for target-setting, • Establish methods for achieving targets, • Track progress toward targets, and • Adjust targets over time. Allocate Resources. The allocation of resources (time and money) is guided by the integration of the preceding steps into an organization’s planning, programming, and project development process. To the extent possible, each investment category is linked to a goal/objective, a set of performance measures, and a target. Specific investment proposals are defined in relation to specific targets. Measure and Record Results. The data for each perfor- mance measure must be regularly collected and periodically analyzed. The analysis should indicate how close the organ- ization is to achieving its targets and identify the actions necessary to improve results. Many public- and private-sector organizations have tracking systems in place to monitor performance allowing senior staff to make periodic budget adjustments. Create Data Management Systems to Ensure Quality Data. “Good” data is the foundation of performance man- agement. Effective decision making in each element of the performance management framework requires that data be collected, cleaned, accessed, analyzed, and displayed. The 1-1-2 Goals/Objectives Performance Measures Target Setting Evaluate Programs and Projects Allocate Resources Budget and Staff Measure and Report Results Actual Performance Achieved Quality Data Figure 1.1.1. Performance management framework.

organizational functions that produce these requirements are called data management systems. There are two key dimensions to creating and sustaining these systems. The two areas are equally important and must be synchronized within an organ- ization to ensure the generation and use of accurate, timely, and appropriate data. The first area centers on the technical challenges associated with data systems, including devel- opment and maintenance of hardware and software, and the specifications for data collection, analysis, archiving, and reporting. The second area focuses on the institutional issues associated with data stewardship and data governance. 1.2 Selected Case Studies Georgia DOT Pavement and Bridge Preservation Risk Assessment The Georgia Department of Transportation (GDOT) is developing an approach for incorporating risk considerations into the prioritization of pavement and bridge preservation projects. The intent of this effort is to move away from a “worst-first” resource allocation approach to a “most-at-risk” approach. The new approach considers both the current con- dition of an asset and the risk associated with its failure. GDOT is implementing this new process with the overall goal of better informing transportation investment decisions. The GDOT Office of Organizational Performance Management (OPM) initiated the risk management work as part of its responsibility for administrating the agency’s transportation asset manage- ment program. Minnesota DOT Bridge Programming Risk Assessment The Minnesota Department of Transportation (Mn/DOT) Bridge Office has undertaken a process that applies risk man- agement philosophy to programming of bridge rehabilitation and replacement projects. The primary goal of this process is to develop a communication tool that would help managers more easily explain the factors that Mn/DOT considers in programming bridge rehabilitation and replacement projects, considering the risk of an interruption to service. This process was developed at the request of the Mn/DOT Commissioner early in 2008, and is part of a larger effort to integrate risk assessment and management into the agency. Texas DOT Statewide Freight Resiliency Plan The Texas Department of Transportation (TxDOT) has developed a Statewide Freight Resiliency (SFR) Plan that iden- tifies key freight infrastructure corridors and strategies to ensure a resilient freight transportation network in Texas. TxDOT adopted the following definition of freight trans- portation resiliency: “the ability for the system to absorb the consequences of disruptions, to reduce the impacts of dis- ruptions, and to maintain freight mobility.”1 The SFR Plan is primarily focused on the key highway routes for freight traveling through Texas (Figure 1.1.2) and the potential mode shift to highways or the shift from one highway to another following a moderate-to-major disruption on/at the state’s highways, rail system, ports, or airports. By identi- fying prioritized infrastructure enhancements on the portion of the network that is vital for freight movements, TxDOT intends that the SFR Plan will help build a stronger case for increased transportation funding. Washington State DOT Bridge Retrofit Risk Assessment Washington’s Department of Emergency Management, National Guard, Department of Transportation (WSDOT), and others in the state helped determine a network of lifeline routes across the state, critical in the event of major natural or manmade disasters. These include routes to military bases, airports, and all interstate routes. As part of a separate effort, researchers have found that particular silts in Washington 1-1-3 Source: TranSystems. Figure 1.1.2. Primary highway routes in Texas. 1Ta, C., A. V. Goodchild, and K. Pitera. “Structuring a Definition of Resilience for the Freight Transportation System.” In Transportation Research Record: Journal of the Transportation Research Board, No. 2097, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 19–25.

could liquefy in the event of a major earthquake, and many of the state’s bridges are not designed to withstand this. In response, several divisions at WSDOT, including planners, bridge engineers, and materials engineers, have begun work- ing together to identify ways to evaluate bridge projects by weighing the risks of failure and impacts against other poten- tial projects. California DOT Seismic Safety Retrofit Program There are more than 12,000 bridges in the California State Highway System, plus an additional 11,500 city and county bridges. The California Department of Transportation (Caltrans) established a prioritization process in 1988 to bring California’s bridges up to seismic safety standards, which was refined following the 1989 Loma Prieta earthquake. However, since it was not possible or necessary to retrofit all structures to eliminate all damage, Caltrans used the following process so that the most critical structures were retrofitted first: 1. Identify all structures potentially needing retrofitting to ensure that they were safe from collapse during earth- quakes; 2. Identify complex or vital transportation lifeline structures; 3. Prioritize all structures requiring retrofitting, based on an algorithm that considers a weighted combination of hazards, impacts, and vulnerability of bridges; and 4. Group structures into logical projects, focusing on highest priority structures and considering geographic proximity. 1-1-4

1-2-1 Building on research conducted for NCHRP 20-74, Devel- oping an Asset Management Framework for the Interstate Highway System; NCHRP 20-24(74), Executive Strategies for Risk Management by State Departments of Transportation; NCHRP 20-59(17), Guide to Risk Management of Multi- modal Transportation Infrastructure; and other recent work, Figure 1.2.1 illustrates a risk management process for trans- portation agencies. The process is applicable to a broad range of applications (across modes, assets, and other areas) as a means to inform resource allocation decisions. The following sections are designed to guide practitioners step by step through the risk management process. They provide a definition of each step, a discussion of its general application, and examples, issues, and lessons learned from a series of case studies. 2.1 Establish Risk Tolerances Since risk management is largely consequence driven, the first step in the process involves establishing an agency’s tolerance level (or consequence threshold) for a given risk. An agency’s tolerance level is determined by establishing the level of liability, or consequences, that it can absorb before additional resources would be required. It is also in this step that an agency begins to assess the tradeoffs between its risk program and its other capital, maintenance, and operations programs. Establishing risk tolerances is generally a policy decision, but should be transparent. As described in NCHRP Report 525: Surface Transportation Security, “Volume 15, Costing Asset Protection: An All Hazards Guide for Transportation Agencies (CAPTA),” this step is best suited to the strategic, high-level planning undertaken at the executive level. Using budgetary discretion, risk tolerances should also reflect the agency’s priorities and asset characteristics. For example, the risk tolerances in the Mn/DOT and GDOT case studies are defined by an asset condition threshold (for pavements and/or bridges) that triggers major rehabilita- tion or reconstruction. This type of threshold provides a basis for identifying, evaluating, prioritizing, and managing risks in subsequent steps of the risk management framework. To support the bridge programming risk assessment at Mn/DOT, the agency sets performance targets for the percent of the system of bridges in good, satisfactory, fair, and poor condition. These goals are based on the assumptions that bridges have a 75-year life, all bridges have a similar deterioration curve, and Mn/DOT has funding available to replace approximately 2 percent of the system bridges each year. Funding targets are recommended for each Area Transportation Partnership (ATP)2 based on output of system needs for bridge rehabilita- tion and replacement in order to meet the established bridge condition targets. Similarly, GDOT has established the following service- level statements related to the condition of the state’s bridges: • Maintain interstate, U.S. route, state route, and off-system state-owned bridges such that they can carry all legal loads; • Maintain interstate bridges such that they, at a minimum, have decks that are in good condition; • Maintain U.S. route bridges such that they, at a minimum, have decks that are in satisfactory condition; and • Maintain state route and off-system, state-owned bridges such that they, at a minimum, have decks that are in fair condition. For pavements, GDOT developed an inspection protocol called the Computerized Pavement Condition Evaluation System (COPACES) where pavements are assigned a condition rating (referred to as the PACES rating) based on a combi- nation of distress type and severity. These ratings are used to define when a segment of pavement is a candidate for C H A P T E R 2 Risk Management Process 2There are eight ATPs in Minnesota (one for each Mn/DOT district area). Every year, the ATPs develop an Annual Transportation Improvement Program (ATIP) that covers a minimum 4-year period.

rehabilitation or replacement. In general, a roadway is recom- mended for resurfacing when its PACES rating falls below 70. Interstates, however, have higher condition targets. The con- dition target for interstates with greater than 50,000 average daily traffic (ADT) is 80, while the target for the remaining interstates is 75. The developers of the PACES rating established these thresholds based on historical data that suggests they are optimal triggers for resurfacing. The risk tolerance in TxDOT’s Statewide Freight Mobility Plan was defined as a moderate-to-major duration event causing a change in freight travel patterns. This definition was developed in consultation with freight carriers, shippers, and other stakeholders in the state. Stakeholders indicated that during short-term or minor disruptions lasting a few hours to a few days, drivers would likely just “wait it out,” while a disruption lasting several weeks or more would change how they operate. The Texas SFR Plan also characterizes risk tolerance in the context of a spectrum of events: recurring, episodic, or catastrophic. Freight shippers and carriers are aware of, and prepare for, recurring events, such as routine traffic congestion or icy road conditions. At the other end of the spectrum, catastrophic events result in extraordinary loss of life and property with national-level impacts that exceed capabilities of normal resources. Episodic events, the focus of the Texas SFR Plan, involve unpredictable occurrences that are manageable with available resources. The goal of the Texas SFR Plan is to prepare the freight transportation system that keeps freight moving and minimizes potential economic loss during an episodic event of moderate-to-major magnitude. Last, risk tolerance was implicit in the goals developed for the Caltrans Bridge Seismic Safety Retrofit Program, as follows: • No collapse—The prevention of direct injury or death to individuals who are on or near a structure; and • No major damage—The prevention of indirect injury due to the closure of a structure critical to a transportation system that supports emergency response to a large-scale civil disaster. Within the context of these goals, Caltrans developed a risk algorithm to categorize and prioritize the state’s bridges. 2.2 Identify Threats/Hazards The second step in the risk management framework involves identifying and categorizing the risks that could cause or contribute to unplanned or undesired circumstances. For a transportation agency, these risks range from small-scale threats impacting the quality of service provided to the trav- eling public, to large-scale threats that can result in loss of life. The identification of relevant threats and hazards, and their respective magnitudes, probabilities, and spatial dis- tribution, are typically based on historical data, experience, and judgment. The risks faced by transportation agencies come from a variety of sources, and it is possible to categorize them in a number of different ways. As an example, Table 1.2.1 cate- gorizes risks into internal and external threats. Internal risks are those within an agency’s control, often internalized in the day-to-day business practices of a transportation agency. External risks are those over which an agency has little or no control. External risks can be the result of either the nat- ural environment or human actions. The five case studies described throughout this document focus on external risks. For more information on addressing internal risks, refer to NCHRP 20-24(74). Mn/DOT’s risk management process provides an example of the types of specific risks that can be considered. The agency has identified the following threats and hazards: • Risk of service loss, such as bridge posting or closing, due to advanced deterioration of portions of structures, • Risk of structure damage or destruction due to stream erosion or storms, • Risk of damage or collapse of structures that are vulnerable to sudden fatigue cracking or other localized failure, • Risk of sudden damage to a bridge caused by passage of a heavy vehicle that exceeds the safe load capacity of the structure, 1-2-2 Source: Adapted from NCHRP Report 632: An Asset Management Framework for the Interstate Highway System. Establish Risk Tolerances Identify Threats/Hazards Assess Impacts or Consequences Identify Potential Mitigation Strategies/Countermeasures Measure and Monitor Effectiveness Prioritize Strategies and Develop Mitigation/Management Plan Fe ed ba ck L oo p Figure 1.2.1. Risk management framework for resource allocation.

• Risk of sudden damage to a structure caused by attempted passage underneath a bridge, of a vehicle whose height exceeds the available vertical clearance, and • Risk of service interruption caused by a driver’s loss of control of a vehicle, and the resultant crash. These threats and hazards were developed and refined by an expert panel. Since they are condition based, Mn/DOT esti- mates probability based on known occurrence of maintenance, inspection, repair, or replacement service interruptions. As condition degrades, the probability of a service interruption increases; therefore, the factors are scaled based on condition. For the Texas SFR Plan, TxDOT developed a hazard iden- tification and assessment methodology to identify state-level hazards to which the freight transportation system is most vulnerable. The purpose of the hazard assessment was to locate areas of vulnerability in each freight corridor to effectively understand how to eliminate or reduce risk associated with a hazard. As shown in Table 1.2.2, the Texas SFR Plan evalu- ated potential external threats resulting from 10 different 1-2-3 Source: Adapted from NCHRP Report 632: An Asset-Management Framework for the Interstate Highway System and ICF International, Executive Strategies for Risk Management by State Departments of Transportation, May 2011. Level 1 Level 2 Level 3 Organizational management Agency goals and priorities Available revenues Internal Risks Project and service delivery Design development Schedule adjustments Cost of materials Program budgets Political Leadership change Laws and regulations Environmental Weather events Structural Advanced deterioration Fatigue cracking External Risks Social Terrorist attack Asset usage (e.g., traffic volumes, fleet composition, and driver error) Table 1.2.1. Transportation agency risk environment from broad (Level 1) to specific (Level 3). Notes: Hazard rating is based on a 1–3 scale, with 1 being the lowest and 3 being the highest. *Since there are no volcanos in Texas, this is zero. Source: TranSystems. Hazard Type Frequency of Occurrence Warning Time Potential Severity Hazard Rating for Freight in Texas Earthquake Unlikely None Substantial 2 Flood Highly Likely Minimal Substantial 3 Hurricane Likely Well in advance Major 3 Landslide Occasional Minimal Minor 2 Manmade Occasional Minimal Major 3 Tornado Likely Advance Major 1 Volcano Unlikely Well in advance Minor 0* Wildfire Occasional Advance Minor 1 Wind Likely Advance Limited 1 Winter Storm Occasional Advance Limited 1 Table 1.2.2. Texas freight system hazard impact summary.

natural and manmade threats. For each of these threats, TxDOT developed hazard ratings by assessing the frequency of occurrence, warning time, and potential severity. To assess the potential threat of each hazard type, TxDOT used data from the Texas Division of Emergency Management3 and the Texas Hazard Mitigation Package4 to map the locations of historic occurrences and potential vulnerability by county (Figure 1.2.2). Using this information, the Texas SFR Plan evaluated the hazards from the perspective of potential impact to the freight transportation system to assign a rating for each hazard type (summarized in Table 1.2.2). The seismic retrofit program in California used a risk algorithm that included a weighted combination of bridge hazards, vulnerabilities, and impacts. Caltrans defined hazards to be the major factors that affect seismic performance: soil conditions, peak rock acceleration, and duration. Vulnerabil- ities pertained to physical attributes of each bridge, such as year constructed, abutment type, skew, and other design elements. Caltrans started the bridge prioritization process by looking at the physical details of about 25,000 bridges. Bridges that were already current, simple spans that were not at risk, culverts, and short multiple-span bridges in low seismic risk areas (Figure 1.2.3) were eliminated from the program. 2.3 Assess Impacts or Consequences Risk assessment is a function of the likelihood of an event (probability of occurrence, as estimated in the previous step) and the associated consequences (whether positive or negative) of the event’s occurrence. Consequences are determined by estimating the level, duration, and nature of an incident’s impact. In the risk matrix shown in Figure 1.2.4, the vertical axis represents the probability (from low to high) of a particular threat/hazard materializing, and the horizontal axis represents the consequence (from low to high) of the materialized threat/ hazard. From a risk management standpoint, it is undesirable to be in a high-hazard, high-exposure situation as represented by the upper right corner in Figure 1.2.4. The consequence threshold, defined in the first step of the framework, allows agencies to identify the most critical risks that require a higher degree of attention. Some agencies, such as GDOT and Mn/DOT, use asset condition as a surrogate for the probability of an event. For example, GDOT’s program for pavements focuses on pave- ment condition ratings. As a pavement’s condition worsens, the likelihood of its failure increases. GDOT has developed a pavement risk matrix for use in evaluating the consequences of failure. This matrix considers functional class, annual average daily traffic (AADT), truck percent, and county population served. Generally speaking, as the function of a road increases 1-2-4 Note: The overall combined risk represents the overall vulnerability of the freight transportation system to each of the hazards identified in Texas. Source: TranSystems derived from Texas Hazard Mitigation Package and USGS. Figure 1.2.2. Overall combined risk of hazard locations in Texas. 3Texas Division of Emergency Management, State of Texas Hazard Mitigation Plan 2010–2013, ftp://ftp.txdps.state.tx.us/dem/mitigation/ txHazMitPlan.pdf 4Texas Hazard Mitigation Package, http://www.thmp.info/ Source: California Geological Survey, April 2003. Figure 1.2.3. Probabilistic seismic hazards assessment in California.

(e.g., interstates that carry high volumes of traffic and serve heavily populated areas) the risk of it going out of service increases. GDOT has rated each combination of these four variables on a scale of 0.00 to 1.00. Table 1.2.3 illustrates these risk factors. Each segment of roadway is assigned a base risk unit of 1.00. This value is then adjusted using the factors illustrated in the table. The existing pavement condition rating for each pavement segment is then divided by the resulting risk factor. These modified condition ratings (referred to as adjusted PACES ratings) are the basis for prioritizing roadways (as described in a later step). Following a similar approach for bridges, GDOT uses a com- bination of functional class, traffic volume, and detour length (the length of the alternative route) to assess the consequence of a bridge going out of service. In the example of Mn/DOT’s bridge programming risk assessment, the likelihood of risks occurring, and impacts and consequences of those risks, are combined into a single indicator of bridge resilience. To estimate the resilience of each bridge, Mn/DOT develops a scaling table for each hazard based on the likelihood of the hazard occurring and the consequence 1-2-5 Source: Adapted from NCHRP Report 632: An Asset-Management Framework for the Interstate Highway System. Figure 1.2.4. Sample risk prioritization matrix. AADT Truck % County Population Functional Class Base Unit > 10 0K 50 -9 9K 35 -5 0K 25 -3 5K 15 -2 5K 7- 15 K < 7 K > 1 2% < 1 2% > 6 00 K 30 0- 60 0K 20 0- 30 0K 10 0- 20 0K 50 -1 00 K < 5 0 K Total Risk Factor Adjusted PACES Interstates Urban 1.00 0.60 0.50 0.40 0.30 0.20 0.10 0.00 0.50 0.30 0.50 0.40 0.40 0.30 0.20 0.10 Rural 1.00 0.40 0.30 0.20 0.10 0.00 0.00 0.00 0.50 0.30 0.30 0.20 0.15 0.10 0.00 0.00 Freeways Urban freeways and expressways 1.00 0.30 0.20 0.10 0.00 0.00 0.00 0.00 0.30 0.10 0.40 0.35 0.30 0.20 0.10 0.05 Arterials Urban principal arterials 1.00 0.30 0.20 0.10 0.00 0.00 0.00 0.00 0.30 0.20 0.40 0.35 0.30 0.20 0.20 0.10 Urban minor arterials 1.00 0.20 0.10 0.00 0.00 0.00 0.00 0.00 0.30 0.10 0.30 02.0 0.20 0.10 0.10 0.00 Rural principal arterials 1.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.30 0.10 0.20 0.10 0.10 0.00 0.00 0.00 Rural minor arterials 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.30 0.10 0.10 0.00 0.00 0.00 0.00 0.00 Collectors Urban collector 1.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.10 0.30 0.25 0.20 0.10 0.10 0.00 Rural major collector 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.10 0.20 0.15 0.10 0.00 0.00 0.00 Rural minor collector 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.10 0.10 0.05 0.00 0.00 0.00 0.00 Local Urban local road 1.00 Rural local road Source: Georgia DOT 1.00 Table 1.2.3. GDOT pavement risk matrix.

to the structure, as shown on the left in Figure 1.2.5. The potential impact of each bridge’s resilience on the public is then characterized by traffic volume and by the role of the bridge in the network, represented as a function of structure length, detour length, and traffic volume and network importance. Network-level resilience is thus a function of facility-level resilience and facility weight summed across the network. After assessing the hazards in the state by county (developed in the previous step of the risk management framework), TxDOT evaluated the hazard risk for each primary freight corridor. Ratings for each corridor were calculated by sum- ming the individual hazard ratings for each county through which the corridor passes and weighting by the length of the corridor in that county. Ultimately, TxDOT evaluated corridor- based results by plotting truck volumes versus hazard rating to measure the robustness of the primary and secondary cor- ridors and the potential impact to freight flows (Figure 1.2.6). Plotting the corridors in this manner allows further assessment 1-2-6 None Tiny Low Medium High 0% 100 100 100 100 100 100 10% 10 0 1 00 95 95 85 85 20% 95 95 90 90 80 80 30% 90 90 85 85 75 75 40% 75 75 70 70 55 55 50% 55 55 50 50 35 35 60% 35 35 30 30 20 20 70% 20 20 15 15 10 10 80% 10 10 5 5 0 0 90% 5 5 5 5 0 0 100% 0 0 0 0 0 0 Li ke lih oo d of h az ar d Consequence to structure Impact on the public Facility Level Resilience (0-100) Tr af fic v ol um e at fa cil ity 0 10000 100000 more Role of facility in network (Importance factor) minor major Facility Weight (0-∞) Advanced deterioration - deck Advanced deterioration - superstructure Advanced deterioration - substructure Scour - erosion at foundation Fatigue and fracture criticality Over-weight trucks - load rating Over-height trucks - vertical clearance Loss of control of vehicle - road width Flooding - waterway adequacy Source: Mn/DOT. Relative weights Network Level Resilience (0-∞) Compute weighted sum over groups of bridges or network (separate scaling table or formula for each type of risk) Compute weighted average over the types of hazards Σ Σ Extreme Figure 1.2.5. Mn/DOT bridge programming risk assessment quantifying risks, impacts, and consequences. Source: TranSystems. Hazard Risk Tr uc k Vo lu m e Ex po su re Figure 1.2.6. Texas statewide highway corridors risk vs. exposure.

of their relative risk to prioritize freight resiliency planning in the various corridors (additional discussion on corridor pri- oritization is discussed in a later step). For the bridge seismic retrofit program, Caltrans used the following series of criteria to estimate the potential impact of bridge failure: • ADT on structure; • ADT under/over structure; • Leased airspace (residential, office); • Leased airspace (parking, storage, etc.); • Facility crossed • Facility carried; • Detour length; and • Essential utilities. Caltrans assigned each criterion a weight to calculate a total “impact factor” used in the bridge prioritization algorithm (discussed in more detail in a later step). 2.4 Identify Potential Mitigation Strategies/Countermeasures Once the impacts of the risks are understood, transporta- tion agencies can begin to develop strategies to mitigate the impact of these risks. The NCHRP 20-24(74) literature review outlines four basic countermeasures to address risk as follows: • Avoid—Make adjustments to eliminate the possibility of the risk occurring or causing impact; • Transfer—Shift the risk to another party more capable of mitigating or managing the risk, thereby protecting the organization from the financial impact of the risk; • Mitigate—Develop strategies to decrease either the likeli- hood of the risk occurring, the impact of the risk, or both; and • Accept—Implement none of the three strategies above, accepting the likelihood and consequences of the risk as is. Given the distinction between the level of agency control involved in mitigating internal and external risks, it is not surprising that agencies have placed more focus on developing internal risk management strategies. As an example, WSDOT incorporated risk management concepts into its Cost Estimate and Validation Process (CEVP) and Cost Risk Assessment (CRA) to reduce the risk associated with project schedule and cost estimates for large and complex projects. Caltrans and the FTA pioneered the use of formal risk assessment practice to minimize specific risk to project delivery due to cost overruns. Although the history of approaches for addressing external risks is considerably shorter, several recent manmade and natural disasters have underscored the importance of develop- ing potential risk mitigation strategies to address both internal and external threats. Examples from the risk management case studies are summarized below. Since GDOT’s risk management approach focuses on system preservation, its strategies focus mainly on mitigation (e.g., conducting regular inspections and performing main- tenance and rehabilitation work in a timely manner) and acceptance (e.g., focusing resources on assets with a higher consequence of risk and accepting risks in other locations). Mn/DOT has identified a set of mitigation strategies for each of the bridge threats and hazards that are either in use or could be deployed. Examples of mitigation strategies include increased inspection frequency, load posting, scour monitoring during high-water events, preventative maintenance strategies, and reactionary maintenance strategies. Some of the scaling factors (developed in the previous step) are reduced due to the mitigation strategies; other strategies are output recommen- dations from risk-based bridge programming suggestions (e.g., bridge rehabilitation projects). For their bridge retrofit program, the mitigation strategies that Caltrans selected were site specific and structure depend- ent, as determined by factors such as nearest active earthquake fault, type of geology beneath the bridge, and the original bridge design. Some retrofitting strategies involved placing steel shells around columns, strengthening footings and piles, adding infill walls, extending bearing seat widths, and installing isolation bearings. Caltrans utilized peer review panels of inde- pendent seismic and structural experts to review earthquake- strengthening strategies on major, complex retrofit projects. The corridor-based analysis conducted for the Texas SFR Plan found the overall freight transportation system in the state to be robust and redundant. However, the plan identified several strategies that TxDOT can implement in a continued effort to improve freight resilience in Texas5 • Strategy 1: Support planning for a resilient, well- maintained freight transportation network by incorporat- ing freight resiliency into traditional transportation planning and programming and including other modes in planning efforts to increase awareness of systemwide needs; • Strategy 2: Prioritize infrastructure enhancements to improve the freight resilience of Texas highways by utilizing corridor assessments to identify operational bottle- necks and physical constraints, and investigating ways to fund improvements needed for other modes; • Strategy 3: Improve access to data, information, and people needed for effective resiliency planning by under- standing baseline data and continuing to build information 1-2-7 5TranSystems and RJ Rivera Associates, Statewide Freight Resiliency Plan, prepared for the Texas Department of Transportation, February 2011.

databases, defining local issues and needs, and recruiting key players to boost effectiveness of planning; and • Strategy 4: Communicate before, during, and after events by providing up to date, comprehensive status reports; holding coordination meetings among critical sector groups, and engaging the private sector. The Texas SFR Plan also acknowledged that while it is important to evaluate the potential risk to the state’s freight network from all potential hazards, most response and recov- ery strategies are not hazard specific. 2.5 Prioritize Strategies and Develop Mitigation/Management Plan Agencies can establish risk mitigation priorities by com- paring the results of the consequence analysis to the estimated costs of the mitigation strategies and countermeasures identi- fied in the previous step. Overall, prioritizing strategies helps to inform resource allocation decisions by identifying pro- grams and projects with the greatest return on investment. For example, GDOT has developed a Bridge Prioritization Formula to identify which bridges are candidates for rehabil- itation or replacement. The prioritization formula is based on the following main elements: • National Bridge Inventory (NBI) rating (measure of over- all bridge strength), • Average daily traffic, • Detour length, • Bridge condition, and • Overall risk factor. Additional elements (timber components, reduced weight limits, repairs, vertical clearance, etc.) also contribute to the prioritization score, but are weighted less than the above factors. Although the bridge prioritization formula takes into consid- eration the risk factors for bridge projects, GDOT does not use it as a standalone tool for decision making. GDOT recently began an effort to refine its approach for prioritizing pavement projects based on the modified pave- ment condition rating described previously. GDOT plans to apply the new approach initially to the Georgia Interstate System. Mn/DOT’s bridge programming risk assessment process culminates in developing a priority score for each bridge. As shown in Figure 1.2.7, the priority score is developed based on a benefit/cost ratio, computed using an improvement to perfect resilience as the benefit (identified in the previous step), and using deck area as a proxy for cost. Facility weight is calculated as Where ΠiFi is the product of a set of importance factors, ADT is daily traffic summed over all roadways on and under the bridge, DeckArea is the bridge deck area in square feet, Weight = × × × + −( ) ×( )∏F W K ADT W DeckAreai i 1 Priority = −( ) ×100 resilence FacilityWeight DeckArea 1-2-8 R es ilie nc e if br id ge im pr ov ed R es ilie nc e to da y Resilience Benefit (0-100) Facility Weight(0-∞) Cost to the network (0-∞) Benefit/cost ratio (0-∞) Co nd itio n if br id ge im pr ov ed Co nd itio n to da y Condition Benefit (0-100) Benefit to the network (0-∞) Relative weights Weighted average over performance measures Σ Total Benefit of action (0-100) Multiply Source: Mn/DOT. Figure 1.2.7. Developing a priority score.

K is a constant to equalize the contribution of ADT and deck area, W is the relative weight given to ADT. ADT includes roadways passing under bridges as well be- cause drivers on those roadways also are exposed to many of the hazards. TxDOT identified relative priorities among the state’s pri- mary freight corridors by plotting the risk assessment results on a risk versus exposure plot shown in Figure 1.2.8. None of the freight corridors in Texas fall in the high-risk category and only two corridors, I-35 and I-30, fall in the medium-risk category. Four highway corridors, I-45, I-35, I-20, and I-30, fall in the high-exposure category, while a majority of the corridors fall in the medium-exposure category. Using this risk versus exposure plot, the Texas SFR Plan concludes that I-35 and I-30 should receive the highest priority for corridor improvements, because they have the highest risk and exposure combination of all Texas highway corridors. Caltrans used an algorithm to prioritize retrofits to the state’s bridges based on risk. This algorithm, developed in 1988, was revised during the course of the program. The revised algorithm used in 1992 was defined as follows: Each variable in the algorithm is defined by adding the weighted global utility function values from all criteria that define that variable (Table 1.2.4). Recall that the vulnerabil- ity and hazard variables were developed in Step 2 of the risk management framework, and the impact variable was calcu- lated in Step 3. 2.6 Measure and Monitor Effectiveness A successful risk monitoring process will systematically track risks, invite the identification of new risks, and capture lessons learned from subsequent efforts. Given the preventa- tive nature of risk management, monitoring efforts typically included aspects of implementation (e.g., monitoring the percent of program implemented and making improvements to the risk assessment process) in addition to performance assessment. Risk Hazard= × ×( ) × × Vulnerability Impact Vul0 27. nerability Impact ( )+ ×( )[ + ×( )] 0 33 0 40 . . Hazard 1-2-9 Tr uc k Vo lu m e Ex po su re Hazard Risk Low Medium High Lo w M ed iu m H ig h v I-35 I-20 I-30 I-10 I-37I-40 US 281 US 59 US 287 Ports to Plains Source: Adapted from the Texas Statewide Freight Resiliency Plan. Figure 1.2.8. Texas statewide highway corridors’ risk vs. exposure. Criterion Weight Criterion Weight Hazard Impact Soil conditions 33% ADT on structure 28% Peak rock acceleration 38% Leased airspace (residential, office) 15% Duration 29% Leased airspace (parking, storage, etc.) 7% Vulnerability ADT under/over structure 12% Year constructed 25% Facility crossed 7% Outriggers, shared columns 22% Facility carried 7% Abutment type 8% Detour length 14% Skew 12% Essential utilities 10% Potential for drop-type failure 16.5% Bent redundancy Source: Caltrans. 16.5% Table 1.2.4. Risk criteria for Caltrans bridge prioritization algorithm.

For example, at Mn/DOT, continuous monitoring of effectiveness is accomplished through annual review of the established bridge condition performance measures. Similarly, GDOT conducts regular inspections and periodically reviews its prioritization formulas to make changes and refinements as necessary. The Texas SFR Plan recognizes that measuring and monitoring the system’s resiliency is an ongoing, internal function for TxDOT and that continuous feedback and documenting lessons learned after real events will improve the plan and ensure its relevance. In the absence of an event, TxDOT recognizes the importance of evaluating re- silience regularly and incorporating feedback into SFR Plan updates. While many of the DOT case studies highlighted in this primer are newly developing or refining their risk management programs to support resource allocation, Caltrans is nearing completion of its retrofit program. As described in earlier steps of the framework, Caltrans refined their bridge prioritization algorithm over time such that it evolved into a highly complex system—a clear example of the iterative nature of the risk management process. 1-2-10

1-3-1 As illustrated by the various case study examples presented throughout this primer, each agency’s approach to risk man- agement for resource allocation is specific to its unique needs and applications. Likewise, each agency will face different challenges for continued implementation and refinement over time. In the context of their unique programs, this section summarizes each DOT’s risk management implementation considerations and next steps. 3.1 GDOT Pavement and Bridge Preservation Risk Assessment From a technical perspective, GDOT is testing the pavement risk factors to ensure their overall validity. It also is evaluat- ing the potential for enhancing the process for application to its Interstate Highway System. The bridge risk factors were incorporated into GDOT’s latest programming cycle. In both cases, the intent of the resulting priority scores (which combine condition with risk) is to serve as one input into the decision- making process. They are combined with other factors such as legislative requirements for the equitable distribution of funds, proximity to other planned projects, and engineering judgment. The intent of GDOT’s asset management (and risk management) program is to inform—rather than dictate— resource allocation decisions. From an institutional perspective, GDOT is working to address the paradigm shift of moving from a worst-first to a most-at-risk approach. For example, it is likely that a risk-based approach will lead to GDOT letting certain low-risk assets deteriorate to a point that is lower than would have been tolerated under a worst-first approach. This, in turn, may lead to GDOT lowering its overall condition targets, which would be significant internally because GDOT historically prides itself on the overall condition of its assets relative to other agencies throughout the United States. GDOT attributes its early successes in steering the culture away from a worst-first men- tality to two things: (1) obtaining buy-in from top management (in this case, GDOT’s Chief Engineer/Deputy Commission), and (2) creating a sense of ownership among its technical ranks by asking the agency’s pavement, bridge, and maintenance experts to provide details for the new process. Looking ahead, GDOT also plans to focus on two areas that will further the implementation of its asset management and risk management efforts. The first is to develop an approach for informing the allocation of funds across program areas (e.g., pavement versus bridge versus roadway expansion) through tradeoff analysis. The second is to develop data gov- ernance standards for its condition and performance data. For example, identify each data element required to calculate each metric, and then, for each element, determine a standard definition, a data owner, a QA/QC process, a data storage pro- tocol, etc. This work will set the stage for a central repository that provides GDOT staff with ready access to timely and quality performance data. 3.2 Mn/DOT’s Bridge Programming Risk Assessment Risk assessment and management is being implemented at Mn/DOT due to leadership from the commissioner, who has hired a risk expert to incorporate these principles into the agency’s overall decision-making process. It is expected that this assessment will be used to inform decisions about project selection. The exact process of incorporating the new risk model with the existing Mn/DOT Decision Matrix for prior- itizing projects still must be determined. Agencywide, risk management implementation is going to be an organic process to ensure risk practices are used where valuable and scalable. Although the vision is to successfully integrate risk management throughout Mn/DOT, imple- mentation has been mindful of both need and demand for C H A P T E R 3 Risk Management Implementation

the service from internal customers. One tool for this is the Mn/DOT Risk Management Workshop. These workshops have increased the department’s ability to move forward with difficult projects, program goals, decisions, and initiatives. In just under 2 years, over 40 diverse risk management work- shops have helped generate cooperation and communication for a variety of topics and decisions. 3.3 TxDOT’s Statewide Freight Resiliency Plan Considering the complexity involved in developing a resiliency plan, TxDOT is proceeding with a three-staged approach to risk management, as shown in Figure 1.3.1. The SFR Plan completed in February 2011 focused on Stage 1, an assessment of the freight system’s preparedness from the per- spective of TxDOT as the managing organization. The results of the Stage 1 plan indicate that the overall freight transporta- tion system in Texas is prepared for an event, but there are physical and institutional improvements that could provide higher levels of resiliency. As a result, TxDOT’s Transportation Planning and Programming Division could use the SFR Plan to inform the planning process and to advocate for additional funding for freight-related improvements in the state. Assessing the robustness and resiliency of the freight network informs decisionmakers by providing a risk-based assessment of the state’s transportation needs. In the stages to follow, Stage 2 will focus on communication and plan implementation during response to an actual event and its recovery. Stage 3 incorporates a continuous feedback loop to update the plan on a regular basis to keep it relevant and effective over time. 3.4 Washington State’s Bridge Retrofit Risk Assessment WSDOT’s approach for programming bridge retrofits and reconstruction is still in its nascent stages, and has yet to be specifically defined. Looking ahead, WSDOT hopes to use research from this and other studies to further develop its approach and move away from a “one design fits all” approach to bridge reconstruction. In particular, WSDOT hopes to develop a risk assessment procedure that considers tradeoffs between different program areas and that incorporates flexi- bility in design standards. 3.5 Caltrans’ Bridge Seismic Safety Retrofit Program As the program comes to a close and after evaluating the program in retrospect, Caltrans identified several lessons learned from the program with implications for next steps. • The mandate resulted in a funding priority for the program over other programs; a tighter financial constraint could have resulted in a different overall process, prioritization scheme, or set of mitigation strategies. • Retrofitting as part of the program was exempt from the state environmental impact report (EIR) requirements in order to expedite the process. In some cases, replacement may have been a cheaper construction alternative but was not selected since it would have been subject to the more time- consuming and costly EIR requirements. • The availability of additional data for the bridges that were screened for potential seismic vulnerabilities would have reduced the up-front analysis time and cost for the retrofit program. Caltrans is currently working to expand its bridge database. • Some retrofit projects were incorporated into widening or other highway improvement projects. This often increased efficiency, but sometimes made the project subject to EIR requirements. 3.6 Summary of Common Themes Taken collectively, the experiences at the five agencies described above help to illustrate a number of common themes related to the development and implementation of a risk management process. These include • When developing a risk management process, there is a need to work closely with, and gather input from, all involved parties within the agency (e.g., bridge engineers, the asset management group) and/or external to the agency (system users, peer reviewers, etc.); • Agencies have, or desire to, fit risk assessment and man- agement within existing performance-based planning and programming processes, with the culmination of the process being a factor or adjustment to existing prioritization scores and therefore influencing the programming process; 1-3-2 Figure 1.3.1. Texas SFR plan stages. Source: TranSystems.

• Agencies want to evolve into performing tradeoffs between different assets within their risk management process, but this has not yet been implemented among the interviewed agencies; • During the risk management process, it is important to consider both the individual facility (often through asset- specific estimates of the likelihood of a risk) and its potential impact on the entire system (other through a systems-level view of the consequences of a risk occurring); and • Although the risk management approaches reviewed for this study all align generally with the generic risk management process described in this primer, the details vary signifi- cantly based on the individual needs of the implementing agency. 1-3-3

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Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies Get This Book
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TRB's National Cooperative Highway Research Program (NCHRP) Report 706: Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies describes how transportation agencies can use risk management and data management to support management target-setting for performance-based resource allocation.

As the final product of a second phase of NCHRP Project 08-70, "Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies," this report supplements NCHRP 666: Target Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies - Volume I: Research Report, and Volume II: Guide for Target-Setting and Data Management published in 2010.

Volume III to this report was published separately in an electronic-only format as NCHRP Web-Only Document 154. Volume III includes case studies of organizations investigated in the research used to develop NCHRP Report 666.

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