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V O L U M E 1 Research Report
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C O N T E N T S V O L U M E 1 Research Report I-15 Chapter 1 Introduction I-15 1.1 Project Purpose I-15 1.2 Project Approach I-15 1.3 Organization of the Report I-17 Chapter 2 Performance-Based Resource Allocation I-19 2.1 Current Practice Among State DOTs I-22 Chapter 3 Performance Targets I-22 3.1 The Role of Targets in Performance-Based Resource Allocation I-28 3.2 Factors Influencing Target-Setting I-35 3.3 Approaches for Target-Setting I-45 3.4 Role of Economic Models and Management Systems in Target-Setting and Tradeoff Analysis I-54 3.5 Topic Areas for Volume II Guidance I-55 Chapter 4 Data Stewardship and Management I-55 4.1 Introduction I-56 4.2 Elements of Effective Data Stewardship and Management I-58 4.3 Organization and Governance I-62 4.4 Data Sharing I-64 4.5 Documentation and Reporting I-65 4.6 Technology I-70 4.7 Relationships to Target-Setting and Resource Allocation I-72 4.8 Summary of Success Factors and Obstacles I-74 4.9 Future Research
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1.2 Project Approach The report proceeded through three phases. In Phase 1, the research team accomplished the following objectives: • Describe the purpose, desired outcomes, and essential elements of PBRA; • Develop a list of public and private organizations reviewed that use all or part of the performance management process, including examples of how organizations apply each element but with a focus on target-setting; • Identify the fundamental differences and similarities between objectives for a public sector agency and a private sector organization; • Develop the criteria that will be used for selecting case studies and the form that case study documentation will take; and • Prepare the questionnaire that will be used in case studies.
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It applies the research conducted in Phase 3 into practical guidance for transportation agencies. The Guide is organized under the following headings: • 2.1 Establishing the Need for Data Management/Governance; • 2.2 Establishing Goals for Data Management; • 2.3 Assessing the Current State of Data Programs; • 2.4 Establish Data Governance Programs; • 2.5 Technology for Data Management; and • 2.6 Linking Data to Planning, Performance Measures, and Target-Setting Processes.
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The methods, including underlying data support systems, by which the measures and targets are established, play a critical role in the overall success of a public agency or private company. PBRA takes place within an overall Performance Management Framework, depicted in Figure 2.1, which is comprised of six basic elements described in the following paragraphs.
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"Good" data is the foundation of performance management. Effective decisionmaking in each element of the performance management framework requires that data be collected, cleaned, accessed, I-18 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 2.1.
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2.1 Current Practice Among State DOTs Within transportation the application of performance measures has an especially long history. These historical roots are likely due in part to the fact that transportation programs deal with engineered facilities and ongoing operational services that have been supported by well-established funding mechanisms, a strong research culture, and extensive statistical reporting.
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• Several agencies look at organizational performance, as well as transportation system performance, and a subset of these links the two concepts: i.e., transportation system performance influences the performance evaluation of agency business units and employees. This concept has existed for some time in the private sector but now is being considered by public sector DOTs.
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DOTs.3 Asset management is by definition a policy-driven, performance-based process that stresses, among other attributes, the use of quality data and analytic tools, including predictive models. Management principles, methods, and decision criteria that are rooted in asset management thus permit a long-term view of options and their consequences, in addition to programming and budgeting in the medium- and near-term.
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The corresponding target provides the perspective for evaluating the impact of the investment decision in relation to the desired end-state, i.e., how significant is a particular investment in helping an agency attain a particular goal. Targets provide the means in which the relative effectiveness of a particular investment decision can be clearly communicated.
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This process, first identified in 2003 and refined over the last 5 years, is illustrated in Figure 3.1. This five-step investment process, described in the 2009 Statewide Transportation Plan, provides the framework and guidance for developing Mn/DOT district 20-Year highway investment plans.
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While infrastructure preservation continues to be an important priority for Mn/DOT, it cannot be the exclusive priority. The goal for the 2009 District Plan updates is to lay out a balanced program of investments that achieves three objectives: I-24 Step 1 Identify Investment Needs Step 2 Project Future Revenues Step 3 Set Investment Goals Step 4 Develop Investment Plan Step 5 Prioritize Unfunded Investment Needs Investments to Meet Performance Targets Regional and Community Improvement Priorities Revenue Outlook Total Unfunded Statewide High Priority 20-Year Highway Investment Plan STIP 2009-2012 Mid-Range HIP 2013-2018 Long-Range HIP 2019-2028 Investment Goals: Balanced Program Legislative Direction (Chapter 152)
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Step 4 -- Develop Investment Plan. Given the needs, projected revenues and investment goals, each district developed investment plans for 2009–2028.
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For example, the brand equity that can be gained by emphasizing that rail transport is "greener" than road haulage can measurably increase the shareholder value and the market penetration of a railroad. Also, there may be a difference between the way the private and public sector DOTs disburse funds, which may result in a difference in the method and the timing of data collection and aggregation and in the timing of allocation of resources.
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That being said, not all private sector companies practice all five elements of the PBRA model. While the vast majority of companies have goals and track performance data, many do not set targets and many do not have explicit feedback mechanisms to allocate resources based on varying levels of performance.
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has been addressing as part of its recent regional transportation planning activities or in Atlanta where the Governor's Congestion Mitigation Task Force resulted in a recommendation that a travel time index target of 1.354 be adopted for the region. The latter situation, in which political bodies develop targets themselves, can be difficult to negotiate, if the process is not properly informed by knowledgeable transportation staff who will guide the development of reasonable, attainable targets.
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" Agencies that have a history with performance-based planning and application of targets in the resource allocation process understand the need to keep the target-setting aspect relatively simple and easy to understand. When adding the target-setting dimension to the PBRA process, it could easily become a much more difficult system to manage.
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publishes a monthly report entitled "Expressway Travel Time Performance" which documents the morning and evening peak travel times per lane on the designated roads which are under the operation of OOCEA. This report is critical to the OOCEA as a "performance management" tool to assess the effectiveness of managing the travel time for the public on the toll system.
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In all instances, the level of influence that the department has over a particular measure affects the target that is eventually set. Within DOTs, standard siloing of functions has led to strong asset management I-31 Source: Road Bureau, MLIT, "Outcome-Based Road Administration Management in Japan." Figure 3.3.
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Timeframe is sometimes determined by stakeholder and internal agency needs but also can be dictated by forecasting capabilities. At Japan's MLIT, annual targets are derived in part from the latest major subjects of policy, planning, and programming to emerge from the funding reports from the MLIT and Road Bureau, the Road Bureau's Mid-term Visioning Report, and the national government's 5-year Major Infrastructure Development Plan.
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The various offices within the districts report to the district secretary and not to their counterparts in the central office. The district secretaries report to the Secretary, and also sit on the FDOT Executive Board.
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Private sector companies take a different approach to PBRA based on the different nature of the resources that they manage. Staff, capital assets, and budgets may have different targets as well as different target-setting approaches due to their different composition compared to their public sector counterparts, as described in the following paragraphs: • Staff.
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Unique to this study is the in-depth review of private sector applications of PBRA and its best-practice examples of target-setting approaches. Some private sector best practices are applicable to the public transportation sector and can be applied within transportation agencies to improve the public sector application of the PBRA process.
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Oftentimes this occurs in response to public outcry or growing public discontent over a transportation issue, with direct action from elected officials being called for. Under this approach, agency senior management or a political body defines targets in the context of larger transportation goals or policies; staff is tasked with developing a transportation investment plan to meet the target and conducting modeling and technical analysis needed to demonstrate attainment of the target under a future funding scenario.
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However, there is political pressure to add highway capacity expansion projects with any available resources left over. Consultant targets are set so that the level of engineering activity is maintained and the production pipeline keeps going.
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Customer satisfaction is a fundamental aspect of performance for these organizations and permeates the process for how potential investments are evaluated and selected to receive funding. Coral Springs, Florida, provides a very strong example of a municipality that has taken a very direct customer-service approach towards its resource investment process, in which customer input drives the decision-making process for a wide range of services, to include transportation.
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It allows peer agencies to observe realistic performance outcomes for various types of transportation improvements and investment levels, and therefore supports a realistic target-setting approach. In the case of the Maryland State Highway Administration (SHA)
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Consensus-Based • Insures broad understanding and acceptance within agency • May flounder in effort to be inclusive • Appoint internal champion to lead effort to identify the "critical few" measures and targets Customer Feedback • Insures more transparent process • May be confusing to discuss technical measures with public • Describe measures and targets in the simplest terms possible Benchmarking • Provides a peer group comparison • Can be misused for comparative rankings • Continue to refine comparative analysis techniques Table 3.1. Managing risk of public sector target-setting approaches.
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Then, through a process that may be automated to varying degrees, Production, Procurement, Operations, and Logistics all share important information that is used to facilitate the control and feedback loop. The actual metrics depend greatly on the company itself and on the mission, vision, objectives, and targets set in the Planning process.
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These increased sales then require more infrastructure to handle a higher volume of goods moving through the distribution network. Aside from the budgeting process, private sector companies' approach to resource allocation also includes the use of variable compensation, team competition, wide access to performance data, and simple and stable performance metrics.
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Develop long-term goals based on consideration of technical and economic factors; 4. Consider current and future funding availability; I-43 Target-Setting Approach Advantage Disadvantages Approach to Balancing Advantages with Disadvantages Incentive Bonuses Strong motivator Inequalities Team or group bonuses Results in a "natural" target Could sacrifice performance on one parameter in trying to maximize another Nonmonetary rewards Intra-Organizational Competition Results in a "natural" target Stimulates sharing of best practices Could sacrifice performance on one parameter in trying to maximize another Stimulate internal competition based on a balanced scorecard of metrics Wide Access to Targets and Data Facilitates more improvement ideas Education and interaction with peripheral users of the data could derail progress Apply varying levels of access permissions Technology to disseminate the information could be costly Use web-based gathering and filtering of input Simple Metrics Focuses effort, resulting in quicker target attainment Could encourage gaming, whereby people sacrifice performance in some areas in order to hit a simplistically defined target Use a set of simple metrics that prevent gaming by imposing tradeoffs Stable Metrics Deeper penetration of targets into processes Slow to adapt to changing external environments Periodic review cycle to ensure metrics are optimal Baldrige Awards Process focus allows for evolution of targets Targets may not be simple or easy to remember Hybrid approach Balanced Scorecard Prevents gaming and suboptimization Complex; diversity of metrics inhibits the progress that often results from focusing on one simple target Hierarchy of metrics Total Quality Management Deep penetration into culture when fully implemented Requires a long-term commitment Hybrid approach Source: Boston Strategies International, Inc.
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For approaches based on Customer Feedback, the sevenstep process is not as applicable because the primary driver in the process is developing targets that communicate to the customer the investment performance in terms that the customer cares about, as opposed to communicating performance in terms of transportation planning and development standards. The target-setting process is still informed by and supported by transportation practitioners that provide the appropriate context for establishing targets (e.g., what percentage of crashes might be expected given certain funding levels, or how much speed may decrease as a result of traffic calming measures)
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Economic models and management systems also are useful for determining the impacts of projects on performance targets or for doing project level tradeoff analysis. While examples are provided from current practice, and the potential for extensions of current practice are discussed, it is important to keep in mind that economic models and management systems are by no means sufficient in themselves for setting performance targets or assessing tradeoffs.
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Figure 3.5 taken from the 2008 C&P illustrates the relationship between alternative investment levels and overall conI-46 Annual Percent Change Relative Total Spending Non- Fixed Variable Non- Fixed Variable to Capital Modeled User Rate User Rate User User Rate User Rate User 2006 Outlay in HERS Sources Charges Charges Sources Charges Charges 7.76% $188.9 $115.7 -1.8% -29.7% 7.45% $182.0 $111.5 -0.3% -4.6% -28.3% -33.1% 6.70% $166.5 $102.0 3.0% -0.7% -24.9% -29.2% 6.41% $160.9 $98.6 4.3% 0.6% -23.7% -27.5% 5.25% $140.6 $86.1 8.8% 5.8% -17.5% -20.8% 5.15% $139.0 $85.1 9.3% 6.5% -17.0% -20.0% 5.03% $137.1 $84.0 9.8% 6.9% -16.4% -19.4% 4.65% $131.2 $80.4 11.2% 8.8% -14.6% -17.1% 4.55% $129.7 $79.5 11.8% 9.4% -8.3% -14.1% -16.7% -36.6% 4.17% $124.2 $76.1 13.3% 11.1% -7.3% -12.7% -14.9% -35.4% 3.30% $112.6 $69.0 17.1% 15.5% -5.4% -8.2% -9.4% -32.7% 3.21% $111.5 $68.3 17.5% 15.9% -5.2% -8.0% -9.1% -32.5% 3.07% $109.7 $67.2 18.1% 16.7% -4.8% -7.4% -8.6% -32.2% 2.96% $108.4 $66.4 18.4% 17.0% -4.6% -6.9% -8.1% -31.9% 2.93% $108.0 $66.2 18.5% 17.1% -4.5% -6.8% -8.0% -31.8% 1.67% $94.0 $57.6 22.8% 22.1% -1.6% -2.3% -2.9% -27.8% 0.83% $85.9 $52.6 25.6% 25.4% 0.0% 1.1% 1.0% -25.4% 0.34% $81.5 $50.0 27.2% 27.3% 1.1% 2.8% 2.8% -23.8% 0.00% $78.7 $48.2 28.4% 28.6% 1.8% 4.0% 4.2% -22.6% -0.78% $72.5 $44.4 31.7% 32.2% 3.0% 8.2% 8.7% -20.5% -0.86% $71.9 $44.1 32.0% 32.5% 3.2% 8.6% 9.1% -20.3% -1.37% $68.3 $41.8 33.9% 34.6% 4.0% 10.6% 11.4% -19.0% -4.95% $48.2 $29.5 44.1% 45.9% 8.9% 23.3% 24.9% -10.7% -7.64% $37.9 $23.2 50.4% 53.0% 10.7% 32.0% 34.1% -7.7% Percent Change in Delay on Roads Modeled in HERS Funding Mechanism 2(Billions of 2006 Dollars) 1 Average Annual Funding Mechanism 2 Incident Delay per VMTCongestion Delay per VMTCapital Investment Projected Changes in 2026 Congestion Delay and Incident Delay Compared With 2006 Levels for Different Possible Funding Levels and Financing Mechanisms Figure 3.5.
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In this case, the fixed-rate user charges and the non-user charges are so close that although they are numerically different the level of detail I-47 Annual Percent Change Total Spending Relative Capital Modeled Non- Fixed Variable Non- Fixed Variable to Outlay in HERS User Rate User Rate User User Rate User Rate User 2006 Sources Charges Charges Sources Charges Charges 7.76% $188.9 $115.7 $51.4 -23.8% 7.45% $182.0 $111.5 $50.0 $50.2 -22.4% -23.1% 6.70% $166.5 $102.0 $46.2 $46.5 -19.1% -19.4% 6.41% $160.9 $98.6 $45.0 $45.4 -17.5% -18.1% 5.25% $140.6 $86.1 $40.2 $40.6 -11.7% -12.2% 5.15% $139.0 $85.1 $39.8 $40.3 -11.1% -11.8% 5.03% $137.1 $84.0 $39.4 $39.7 -10.5% -11.2% 4.65% $131.2 $80.4 $38.0 $38.2 -8.7% -9.1% 4.55% $129.7 $79.5 $37.7 $37.9 $46.2 -8.2% -8.6% -19.3% 4.17% $124.2 $76.1 $36.4 $36.6 $44.7 -6.3% -6.6% -17.6% 3.30% $112.6 $69.0 $33.6 $33.7 $41.2 -1.9% -2.3% -14.0% 3.21% $111.5 $68.3 $33.4 $33.5 $40.9 -1.5% -1.9% -13.6% 3.07% $109.7 $67.2 $33.1 $33.2 $40.5 -0.7% -1.0% -13.0% 2.96% $108.4 $66.4 $32.7 $32.9 $40.1 0.0% -0.2% -12.5% 2.93% $108.0 $66.2 $32.6 $32.8 $40.0 0.3% 0.0% -12.5% 1.67% $94.0 $57.6 $28.7 $28.8 $35.7 7.9% 7.9% -6.7% 0.83% $85.9 $52.6 $26.4 $26.5 $33.0 12.5% 12.4% -2.6% 0.34% $81.5 $50.0 $25.2 $25.3 $31.5 15.0% 15.1% 0.0% 0.00% $78.7 $48.2 $24.5 $24.5 $30.6 17.0% 17.1% 1.8% -0.78% $72.5 $44.4 $23.0 $23.0 $28.5 20.4% 20.8% 5.7% -0.86% $71.9 $44.1 $22.8 $22.8 $28.3 20.8% 21.2% 6.0% -1.37% $68.3 $41.8 $21.8 $21.8 $27.1 23.3% 23.8% 8.4% -4.95% $48.2 $29.5 $15.7 $15.6 $19.9 41.3% 42.0% 25.2% -7.64% $37.9 $23.2 $12.7 $12.7 $16.0 52.3% 53.1% 37.1% HERS System Rehabilitation 2 1 Funding MechanismFunding Mechanism Percent Change in Average IRI on Roads Modeled in HERS Average Annual Investment (Billions of $2006) -24% -12% 0% 12% 24% 36% 48% 60% $20.0 $30.0 $40.0 $50.0 $60.0 $70.0 $80.0 $90.0 $100.0 $110.0 $120.0 Average Annual Investment Modeled in HERS (Billions of Dollars)
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1 The amounts shown represent the average annual investment over 20 years that would occur if annual investment grows by the percentage shown in each row in constant dollar terms. The performance impacts identified in this table are driven by portion of NBIAS-modeled spending on the NHS.
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In the context of the overall performance management framework, this type of analysis can help agencies establish relative priorities, set targets, allocate resources, and better manage stakeholder expectations. As with the discussion of target-setting, this discussion of tradeoff analysis addresses the system or program level rather than the project level.
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It includes the following four scenarios: I-50 Program Area Measures of Effectiveness Pavement Preservation Percent of pavement in good or fair condition Highway Capacity Hours of congestion delay per 1,000 vehicle miles traveled Bridge Preservation Percent of bridges in good or fair condition Safety Fatalities per 100 million vehicle miles traveled Transit Extent of the transit network (the existing network or the region's transit vision) Nonmotorized Percent of population and employment within ½ mile of a nonmotorized facility Roadway operations Not applicable Source: SEMCOG and Cambridge Systematics Table 3.4.
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After producing results for each program and scenario and for the alternative funding levels, the information was assembled in a manner which illustrated what level of performance results the region would achieve at alternative funding levels for each of the program areas. These results that inform the tradeoff analysis are shown in Figures 3.9 through 3.13.
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Pe rc en t i n G oo d or F ai r C on di tio n Figure 3.10. Bridge performance versus funding.
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Figure 3.13. Nonmotorized performance versus funding.
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The SEMCOG analysis provides a blueprint for using available economic models and management systems and other procedures to progress through target-setting and through a tradeoff analysis for the types of performance measures that were recommended in the overall performance management framework. SEMCOG provides an excellent example of the use of tradeoff analysis in decision-making; however, future research should likely focus on how agencies could implement tradeoffs into their performance management processes.
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This section summarizes the findings of the case studies in Volume III and includes many specific and relevant examples to demonstrate how data programs are supporting decision-making in many private and public sector agencies. 4.1 Introduction The term data program in this report refers to specific data systems that support a business area of the organization.
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This includes data on the extent, condition, and performance of the transportation network in the state. A strong performance-based management program, such as the one adopted at the Mn/DOT, helps that agency to align its strategic goals with its business and supporting data programs in order to best meet the needs of the citizens of Minnesota.
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The management of data assets for an organization or state DOT is usually accomplished through a data governance board or council. This role is critical in successfully managing data programs that meet business needs and in supporting a comprehensive data business plan for the organization.
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For example, the underlying data programs that support performance measures at Washington DOT were critical in convincing the State legislature to continue investments in a fish barrier removal program versus other programs that may have a higher legislative priority. Figure 4.2 illustrates the important link between an agency or company's strategic mission and goals and the data governance framework that is in place to manage the data programs to ensure that the highest quality data are available in a consistent and timely manner to support core business functions in all areas of the organization.
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and Goals Data Steward and Custodians Figure 4.2. Overview of a general data governance framework.
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Washington State Department of Transportation (WSDOT) Several public sector organizations have been proactive in implementing some type of data governance framework or are in the process of doing so.
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to guide the development of their Data Business Plan, which will ultimately include the implementation of a data governance framework for the department. Alaska and Mn/DOT Advantages The advantages of developing a data governance framework at DOTs such as in Alaska and Minnesota are yet to be fully realized, as each of these agencies are in the preliminary stages of defining what their data governance model will look like and how it will be implemented at their respective agencies.
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Some agencies are more successful than others in gaining initial executive support. There also is the need to assess the current state of data programs, identify areas where gaps in data and information exist, and prioritize those needs as part of short-term and long-term investment plans for data programs.
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Some organizations also support data sharing internally with a Knowledge Management (KM) system, which is an electronic repository of all types of information such as the following: • Data standards, policies and definitions for all business application data, including metadata; • Work processes used to support a business program using a specific data system; • Lessons learned regarding use of IT tools, or other similar data systems; • Agency or department policy and standards regarding the use of data; • Reports which monitor the performance of a given data program; and • Data models for critical data systems.
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As part of their Data Business Plan implementation, the ADOT&PF Program Development Division also is investigating the ways in which a KM system can benefit the division and regional offices that support statewide planning programs. Data sharing, internally and externally, is often done through the use of published monthly or annual reports.
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The city uses a web-based system known as Active Strategy to handle the functions for managing their performance data. Just as implementing data governance does not follow a one-size-fits-all approach, each agency should determine their needs for managing their data systems and their documentation and reporting requirements, and invest in systems that best suit their business needs.
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RCG Information Technology Company found that many times business executives were not aware of the relationship of which data systems were used to support key business functions. Developing data business models helps to identify this for executives who also have authority over funding for those data programs.
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In this example, the risk universe describes potential risks associated with asset management where the asset is bridges. Risk management programs for asset management also are very applicable to data programs, since data are a type of asset.
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Based on these preliminary case studies, private sector companies are increasingly using technology to support their resource allocation and their target-setting in the following ways: • Software is used to generate optimal solutions in the planning phase. Software applications (usually customized)
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Supply Chain Planning Inspection Network design and site location Network optimization Specification of order types, terms, and conditions Trading partner collaboration 2. Transportation Planning Mode selection Routing and scheduling Transportation Management Systems (TMS)
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Many public organizations and departments allocate resources this way, but private sector companies largely switched from this approach to a zero-based budgeting approach. A second approach to allocating resources is to base the resource allocation on achievement of the target.
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Hennepin County has indicated that while specific department areas may have excellent performance measures data that can be used to allocate resources, there is a need to have more data available on a countywide basis. Likewise, the MTC has recognized the need to improve the connection between the use of performance measures and those who collect data for the various programs and make funding decisions on data programs.
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• Use a Data Business Plan to strategically manage data programs similar to other strategically managed programs within the organization. • Manage expectations of how data governance can help an organization by explaining the benefits of such models for supporting business operations.
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• Use data sharing agreements to reduce costs associated with data collection and maintenance of data systems. • Invest in the staff by providing training in new technology and tools to gain their buy-in for support of data programs and data governance initiatives.
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Need to improve data quality. • Non-integrated data systems limit the sharing of information and sound decision-making, based on data programs.
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Transportation Research Board of the National Academies. Washington, DC.
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Key Terms
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