Practitioners' Perspective on Value for Money (VfM) Analysis

1. Introduction

Value for Money (VfM) analysis is the formal mechanism by which U.S. state agencies evaluate whether a highway project should be delivered through a public-private partnership (P3) or through conventional public procurement (Federal Highway Administration, 2012, 2013). By comparing the risk-adjusted lifecycle costs of public delivery, represented by the Public Sector Comparator (PSC), with the corresponding costs of a P3 arrangement, VfM analysis is intended to support procurement decisions by identifying the option expected to provide greater value over the life of the asset (Grimsey & Lewis, 2005). While the U.S. highway P3 market has grown considerably over the past two decades, the application of VfM analysis has been selective and inconsistent, varying considerably across state agencies and project types (FHWA, 2016).

Despite its role in high-stakes procurement decisions, less is known about how these analyses are implemented in practice (A. Boardman & Hellowell, 2017). The development of a VfM assessment requires numerous professional judgments regarding model structure, data sources, cost estimates, risk allocation, financing assumptions, and review procedures. These decisions are made within organizational, regulatory, and project-specific contexts that are often difficult to observe through project documentation alone (A. Boardman & Hellowell, 2017; Morallos & Amekudzi, 2008). Understanding how practitioners approach applying VfM analysis is important for evaluating both the strengths and limitations of current practice.

This study addresses that gap directly. Drawing on semi-structured interviews with practitioners who have contributed to VfM analyses across multiple U.S. highway P3 projects, it examines the methodological approaches, critical success factors, and improvement recommendations that emerge from direct practitioner experience. The study is one component of a broader two-part investigation of VfM reliability in U.S. highway P3s, the first part of which addresses the quantitative dimension through ex-ante and ex-post comparison of VfM model outcomes. This paper focuses exclusively on the qualitative dimension: the practitioner’s view from inside the analysis.

2. Research Objectives

The main objective of this study is to examine how VfM analysis is implemented in practice by U.S. highway P3 practitioners, identifying the methodological approaches, institutional factors, and critical success factors that shape analytical quality and consistency.

3. Literature Review

Value for Money (VfM) analysis is often presented as a structured and objective decision-support tool, yet literature suggests that its implementation is fundamentally shaped by professional judgment. Practitioners conducting a VfM assessment must select analytical frameworks, develop cost and revenue assumptions, construct Public Sector Comparators (PSCs) and shadow bids, quantify and allocate risks, and evaluate the sensitivity of results to alternative scenarios. These activities are undertaken before procurement is complete and frequently before detailed design information is available, requiring practitioners to make consequential decisions under conditions of uncertainty, incomplete information, and time pressure. Consequently, the gap between what VfM guidance documents prescribe and what practitioners can realistically achieve has emerged as a recurring theme in the literature.

The development of VfM practice in the United States has occurred within a comparatively limited institutional environment. Early surveys of state transportation agencies found that only a small number had adopted tools resembled formal VfM analysis, and that applications varied considerably across jurisdictions (Morallos et al., 2009; Morallos & Amekudzi, 2008). Although the FHWA P3-VALUE Toolkit subsequently established a common methodological reference point, its application remains largely discretionary. As a result, methodological consistency often depends less on institutionalized procedures than on the experience and judgment of the practitioners conducting the analysis. Comparative international evidence suggests that the most credible VfM processes are typically supported by established methodological protocols, experienced P3 units, and robust review mechanisms, features more commonly found in mature P3 jurisdictions than in the United States (Burger & Hawkesworth, 2011).

A central challenge identified throughout the literature is the tension between the information required to conduct a reliable VfM assessment and the information available when the assessment must be performed. Because analyses are conducted early in project development, practitioners must estimate lifecycle costs, operations and maintenance expenditures, financing assumptions, traffic and revenue forecasts, and discount rates using incomplete and often project-specific information. Studies of actual VfM applications demonstrate that practitioners routinely exercise judgment in ways that diverge from formal guidance and that these decisions are not always transparently documented (Khadaroo, 2008). Other research shows that relatively small changes in key assumptions can materially alter VfM outcomes, highlighting the sensitivity of procurement recommendations to analyst choices regarding costs, financing parameters, and discount rates (Coulson, 2008; Cruz & Marques, 2012). These findings suggest that the reliability of VfM analysis depends not only on the technical robustness of the framework itself but also on how practitioners interpret guidance, manage uncertainty, and construct assumptions in the face of incomplete information.

Risk assessment represents the clearest manifestation of these challenges. Although risk transfer is frequently identified as the principal source of value attributed to P3 delivery, the literature consistently characterizes risk quantification as one of the most judgment-intensive aspects of VfM practice. Practitioners are often required to assign monetary values to uncertain future events despite limited empirical evidence regarding their likelihood or consequences. Existing studies have highlighted challenges associated with risk pricing, Monte Carlo simulation and the construction of defensible risk registers, particularly in sectors where similar project experience is limited (Makovšek & Moszoro, 2018). While prevailing guidance frameworks recommend grounding risk estimates in historical project data, this objective remains difficult to achieve in the U.S. highway sector, where the number of completed P3 projects remains relatively small (Federal Highway Administration, 2015; Victoria, 2001). Consequently, risk assessment is not merely another analytical step within the VfM process; it is the area where professional judgment, data limitations and methodological uncertainty converge most directly.

The literature further suggests that these judgments are not made within a neutral analytical environment. A substantial body of research argues that VfM analysis serves both analytical and institutional functions and is often conducted within procurement environments where preferences regarding project delivery may already exist. In this context, VfM may function simultaneously as an evaluation tool and as a mechanism for legitimizing procurement decisions (Hodge & Greve, 2007, 2017). Research on U.S. P3 adoption indicates that political orientation, fiscal incentives, and institutional structures can influence procurement choices independently of project economics (Casady et al., 2020; Geddes & Wagner, 2013; Maskin & Tirole, 2008). More broadly, studies of infrastructure planning have documented how organizational incentives and approval processes can shape analytical assumptions and forecasts (Flyvbjerg, 2008; Wachs, 1990). These findings suggest that VfM analyses are embedded within broader institutional contexts that influence how assumptions are developed, how uncertainty is interpreted, and how results are ultimately used.

Taken together, the literature portrays VfM practice as simultaneously a technical modeling exercise, an organizational process, and an institutional activity. Research has identified a range of conditions associated with more credible and effective VfM assessments, including transparent cost estimation, realistic risk valuation, strong project management capability, independent review processes, experienced analytical teams, and access to standardized project data (A. E. Boardman et al., 2016; Nisar, 2007; Vining & Boardman, 2008). However, relatively little is known about how practitioners themselves understand these issues following multiple VfM analyses. The experiential knowledge accumulated through practice, including recurring challenges, critical success factors and recommendations for improvement, remains largely undocumented, particularly within the U.S. highway sector. Capturing that knowledge is therefore essential for understanding not only how VfM analyses are conducted, but also how their reliability and usefulness might be strengthened in future applications.

4. Gaps in Literature

While prior research has examined the technical, institutional, and economic dimensions of VfM analysis, the practitioner perspective remains largely undocumented in the U.S. highway sector. Existing literature provides limited insight into how practitioners develop assumptions under data scarcity, resolve methodological ambiguities, navigate institutional pressures, and assess the methodology’s strengths and limitations based on their experience across multiple projects. By capturing the perspectives of practitioners directly involved in U.S. highway P3 evaluations, this study contributes empirical evidence on how VfM is implemented in practice, where practitioners perceive its greatest strengths and weaknesses, and what improvements they believe would enhance its reliability and usefulness.

5. Methodology

A qualitative research approach was used to collect data and achieve the objectives of this study. All data were obtained through semi-structured interviews with practitioners who had direct experience in conducting or reviewing VfM analyses for US highway projects. The study methodology followed four stages: (1) identification of potential interviewees, (2) development of the interview questionnaire, (3) data collection, and (4) data analysis. This approach is consistent with expert interview practice in applied policy research (Bogner et al., 2009) and with qualitative methodologies used in prior studies of project delivery and procurement decision-making (Creswell & Poth, 2018; Merriam & Tisdell, 2016).

5.1. Identification of Potential Interviewees

Participants were selected for their direct involvement in VfM analyses of U.S. highway P3 projects. Initial outreach was conducted through email to practitioners known to have worked on U.S. highway P3 transactions, asking whether they had been directly involved in a VfM analysis and, if so, whether they would be willing to participate. Recipients were also asked to refer other practitioners they knew who had relevant experience. Individuals were contacted by email to confirm their eligibility and willingness to participate. Eligibility was defined as direct involvement in one or more pre-project VfM analyses for a U.S. highway P3 project, in a capacity that included meaningful engagement with model development, assumption setting, risk assessment, financing structure, or review activities. Ten practitioners agreed to participate and were scheduled for interviews. To preserve confidentiality, participant and project names are not reported in this study.

Table 1 summarizes the professional positions held by participants at the time of the projects under discussion. The sample included four participants in project management or chief engineering roles, two program directors, three consultants, and one financial analyst. Participants had experience across a range of project types, including availability-payment Design-build-finance-operation-maintenance (DBFOM) concessions, toll-revenue P3s, managed lane projects, and a social-infrastructure P3.

5.2. Questionnaire Development

A semi-structured interview questionnaire was developed to examine practitioner experiences with VfM analysis across all major components of the assessment process. The questionnaire was organized around five thematic areas:

• Background and Project Context: project role, objectives, challenges, and rationale for P3 consideration.
• PSC and P3 Assumptions: construction cost estimation, operation & maintenance (O&M) and lifecycle cost modeling, traffic and revenue forecasting, and shadow bid development.
• Risk Identification, Quantification and Allocation: risk identification processes, quantification methods, risk register development, and retrospective assessments of risk allocation.
• Financing Structure and Discount Rate: financing sources, debt-equity structure, payment mechanism selection, discount rate assumptions, and sensitivity analysis.
• Critical Success Factors, Lessons Learned, and Recommendations: practitioner assessments of analytical quality, improvement recommendations, and transferable guidance for future VfM practice.

The questionnaire was developed with reference to both the VfM literature and established practitioner guidance, including the FHWA P3-VALUE Toolkit, the Partnerships British Columbia methodology, the HM Treasury Green Book, and state-level P3 evaluation frameworks. The interview protocol was structured around the core components of a VfM assessment to ensure comprehensive coverage of key areas, including Public Sector Comparator (PSC) development, P3 bid assumptions, risk allocation and analysis, financing assumptions, discount rate selection, and model review procedures. Content validity was enhanced through the systematic alignment of interview questions with concepts and practices identified in both academic literature and professional guidance. Prior to the main data collection phase, the questionnaire was reviewed to assess its clarity, relevance, and completeness. Minor revisions were made to the wording of several questions to improve accessibility for participants from diverse professional backgrounds, including public-sector practitioners and external consultants. The final instrument comprised a series of structured questions organized by thematic area, supported by targeted follow-up probes to elicit additional detail and clarification where required.

5.3. Data Collection

Data was collected through semi-structured interviews conducted by video conference or telephone. A semi-structured interview format was selected because it provides a consistent framework across interviews while allowing participants the flexibility to elaborate on issues they considered most relevant to their professional experience. This approach is particularly well-suited to expert interviews, where the depth and specificity of practitioner knowledge represent a valuable source of insight and analytical evidence (Bogner et al., 2009). Interviews were not audio recorded. This decision was made to facilitate open and candid discussion of commercially sensitive, project-specific, and organizationally sensitive information. The choice not to record interviews is consistent with established expert interview practice in contexts where recording may inhibit participant disclosure or limit the depth of responses (Bogner et al., 2009). Instead, the research team took detailed notes throughout each interview. These notes were reviewed, clarified, and expanded immediately following each interview to enhance completeness and minimize the risk of information loss. The interview protocol provided a common structure across all interviews while retaining sufficient flexibility to explore issues raised by participants in greater depth. Follow-up questions were used where clarification or additional detail was required. Interviews typically lasted 45-60 minutes, and all 10 participants completed the full interview process.

5.4. Data Analysis

Framework analysis (Ritchie & Spencer, 1994) served as the primary method for organizing and interpreting the interview data. The approach follows five stages: familiarization, development of an analytical framework, indexing, charting and mapping, and interpretation. It is particularly well-suited to studies that seek to examine predefined areas of inquiry while retaining flexibility to accommodate issues that emerge from participant responses. In the familiarization stage, all interview notes were read carefully and systematically to develop an initial understanding of the data and to identify recurring issues and practitioner concerns. The analytical framework was developed to correspond to the five thematic domains of the questionnaire: (1) purpose of VfM analysis; (2) PSC and P3 assumptions; (3) risk identification, quantification, and allocation; (4) financing structure and discount rate; and (5) critical success factors, lessons learned, and recommendations. This framework provided a consistent structure for indexing and comparing responses across participants while remaining open to issues that emerged from the interviews.

In the indexing stage, each interview record was systematically reviewed, and relevant passages were assigned to one or more domains of the analytical framework. Responses were then charted in a matrix format, with participants in rows and analytical domains in columns. This enabled direct comparison of responses across participants within each domain and facilitated the identification of patterns, commonalities, and divergences.

In the interpretation stage, the charted data were examined within and across domains to develop substantive findings. Frequencies were tabulated for critical success factors and lessons learned to indicate the relative prominence of specific observations within the sample. Where responses reflected substantively different perspectives or outlying views, these were noted and retained in the analysis rather than subsumed into consensus characterizations. The findings are reported as practitioner perspectives and are not intended to represent statistically generalizable conclusions.

6. Results

6.1. Purpose of VfM Analysis

Participants generally described the purpose of VfM analysis as evaluating alternative procurement approaches and determining which delivery method offered the greatest value over the project lifecycle. Most respondents characterized the analysis as a comparative decision-support tool intended to inform procurement decisions. One participant, however, described the objective as demonstrating that the P3 option was superior to conventional delivery. While this was an isolated observation, it suggests that the perceived role of VfM may differ across organizations, ranging from an open-ended evaluation of alternatives to a process focused on supporting a preferred procurement approach.

Funding and fiscal constraints were the most frequently cited reasons for P3 consideration. Participants commonly described project environments in which conventional public funding was insufficient or subject to political constraints, and private financing was considered for project delivery. In several cases, these constraints also influenced the selection of payment mechanisms. Several participants mentioned that tolling was not considered feasible because of political opposition, insufficient traffic demand, or limited revenue potential, making availability payment structures the preferred alternative. In projects that had tolls, the decision was commonly linked to the lack of public funding sources. Responses also indicated that concession periods were typically determined using a combination of similar project experience, financing requirements, and precedents from previous transactions.

6.2. PSC and P3 Assumptions

Construction costs in both cases were commonly derived from engineer estimates, environmental impact statement (EIS) cost estimates, consultant-prepared market estimates, planning level cost estimates and estimates developed jointly by design consultants and DOT staff using historical unit-cost data. One participant described using practical design workshops to refine estimates collaboratively. Several respondents also indicated that contingency allowances for cost and schedule overruns were incorporated into the construction costs, with one participant noting that historical project performance data was used to inform the magnitude of these adjustments.

O&M and lifecycle cost assumptions were typically based on a combination of agency maintenance manuals, historical maintenance data, cost benchmarks, and engineering judgment. Several participants reported conducting lifecycle cost analyses for both the PSC and P3 alternatives to support consistent comparison. Where agency maintenance standards and cost databases were available, these served as the primary source of information, supplemented by professional judgment when project-specific data were limited. One participant noted that common baseline assumptions were applied across both delivery options to maintain comparability.

For toll-based projects, traffic and revenue forecasts were generally developed using regional travel-demand forecasts and tolling scenario analyses. Participants described using alternative demand and revenue scenarios, sensitivity testing, and different tolling assumptions to assess forecast uncertainty. One respondent observed that actual traffic volumes ultimately exceeded the original forecast. Revenue forecasting was not applicable for projects using availability payment structures.

Approaches to shadow bid development varied across participants. Several respondents described constructing hypothetical private-sector bids using financial models, market benchmarks, similar P3 transactions, and input from external advisors. In some cases, the shadow bid was developed using the same project scope and performance requirements as the PSC while incorporating private financing assumptions, risk transfer provisions, and contractual performance obligations. One participant reported using actual bid data as the basis for comparison. Another noted that where a previous project phase had already been completed, differences between the PSC and P3 cases were driven largely by schedule certainty, observed construction costs, and the inclusion of historical cost-overrun experience in the PSC assumptions.

6.3. Risk Identification, Quantification, and Allocation

Risk identification approaches varied across projects. Participants described identifying risks through expert judgment, discussions with project stakeholders, engagement with project sponsors, consultant-led processes based on similar P3 projects, and agency-led assessments of major project risks. Financial advisors, engineers, and other technical specialists were involved in the process in several cases. One respondent highlighted project-specific risks related to flooding and the limited availability of specialist subcontractors, while another indicated that risks were generally well identified and assigned to the appropriate parties.

Risk quantification methods also differed across projects. Monte Carlo simulation was the most frequently cited approach and was used either independently or in combination with risk matrices. One project employed a hybrid approach in which probability and consequence were evaluated for 88 individually identified risks. Other participants described incorporating risk allowances directly into cost, schedule, and financing assumptions rather than quantifying risks as separate line items. Historical contract data, sensitivity analysis, expert judgment, and information from similar projects were also used to support risk estimation.

Retrospective assessments of risk allocation were generally positive, with most participants not identifying major instances of risk misallocation or underestimation. One respondent attributed the process’s effectiveness to strong team composition and communication among project participants. However, isolated observations suggested that some risks may not have been fully anticipated. In one case, a governance-related issue involving trustee participation emerged during implementation but had not been included in the original assessment. Another participant noted that external factors had attempted to influence the risk process, although no additional details were provided.

6.4. Financing Structure and Discount Rate

Financing structures described across the projects were multi-layered, combining public and private sources. Participants cited state funding, federal grants, the Transportation Infrastructure Finance and Innovation Act (TIFIA) loans, tax-exempt debt, bonds, private equity, commercial debt, and equity investors as components of the financing model. In one project, PSC financing was based on TIFIA and tax-exempt debt priced from a similar project, while P3 financing was provided by a financial advisor. In another, availability payments were selected alongside pay-as-you-go public funding. In at least one project, an upfront investment structure was described. The differences between PSC and P3 financing cases were reflected through risk allocations and financing assumptions in the model.

On discount rates and sensitivity, participants described a range of approaches. In one project, the discount rate was selected by a study of similar projects in the UK, with a risk adjustment applied. In others, historical data from similar projects and project-specific factors were used as the basis. Sensitivity analysis was conducted across several projects, covering discount rate alternatives, cost overrun assumptions, different payment profiles, lower interest rate scenarios, and alternative traffic revenue forecasts.

6.5. Critical Success Factors, Lessons Learned, and Recommendations

When asked to identify the critical success factors for a reliable VfM analysis, participants highlighted a range of conditions they considered important to the assessment’s quality and credibility. Table 2 below summarizes the factors identified across the ten interviews. Because participants frequently identified more than one factor, the frequencies reported does not sum to the total number of participants.

The most frequently identified factor was the quality and transparency of data and assumptions, which were mentioned in eight of the ten interviews. Communication and stakeholder engagement were the second-most-commonly cited factors, followed by realistic risk valuation. Other factors identified by participants included neutrality and the absence of bias, post-completion evaluation, appropriate selection of the discount rate, institutional capacity, and consistency of assumptions. While the relative frequency of these responses indicates their prominence within the sample, the findings should be interpreted as practitioners’ perspectives rather than measures of importance. Table 3 below summarizes the lessons learned and recommendations identified by participants. The table presents the responses as reported by interviewees and groups similar observations into common categories. Because participants often identified multiple lessons or recommendations, frequencies do not sum to the total number of participants.

7. Discussion & Conclusions

This study provides a practitioner perspective on how Value for Money (VfM) analysis is conducted in the U.S. highway public-private partnership (P3) sector. Drawing on interviews with practitioners from public agencies and consulting organizations, the findings highlight three interrelated characteristics of contemporary VfM practice: the influence of funding constraints on procurement decisions, the reliance on professional judgment and historical benchmarks in the absence of project-specific empirical data, and the importance of communication and stakeholder engagement in developing credible analyses.

Participants frequently described situations in which conventional public funding was insufficient, unavailable, or politically constrained, making private finance an important consideration in project delivery. These constraints also influenced the selection of payment mechanisms, with availability-payment structures often adopted where tolling was considered infeasible and tolling pursued where alternative funding sources were limited. This finding is consistent with previous research suggesting that fiscal considerations play a significant role in the adoption of P3 procurement models (Geddes & Wagner, 2013; Maskin & Tirole, 2008). The findings further suggest that funding realities may narrow the range of procurement options considered before a formal VfM assessment is undertaken. While most participants described VfM as a comparative decision-support tool, one respondent characterized it as a mechanism for demonstrating the advantages of a P3 approach. Although this view was not widespread, it supports arguments in the literature that VfM can serve both analytical and legitimizing functions within infrastructure procurement processes (Hodge & Greve, 2007, 2009).

Across all major input categories (including construction costs, O&M assumptions, traffic forecasts, financing inputs, discount rates, and risk assessments), participants reported drawing heavily on historical project experience, maintenance manuals, benchmarking data, expert opinion, and comparable transactions. The most frequently identified critical success factor was the quality and transparency of input data and assumptions, cited by eight of the ten participants. Together, these findings suggest that the reliability of VfM analysis depends as much on the quality of available information and the credibility of assumptions as on the sophistication of the modeling techniques employed. This dependence on judgment reflects a structural challenge inherent in pre-project evaluation. Many of the data required to estimate future costs, risks, and performance outcomes do not yet exist at the time the analysis is conducted. Participants therefore relied on analogous projects, professional expertise, and historical benchmarks to fill these gaps. This observation aligns with Cruz & Marques (2012), who argue that VfM outcomes can be highly sensitive to individual assumptions and input parameters. Rather than indicating a failure of methodology, the findings suggest that judgment-based estimation is an unavoidable feature of pre-procurement decision-making.

The risk assessment findings provide a clear illustration of this challenge. Although Monte Carlo simulation was the most frequently cited quantitative technique, participants generally described risk inputs as being informed by expert judgment, historical information, and experience from comparable projects. Similarly, approaches to discount rate selection varied across projects and were often based on historical benchmarks or project-specific considerations. These findings suggest that increasingly sophisticated analytical tools do not eliminate uncertainty; instead, their outputs remain dependent on assumptions whose quality is constrained by the availability of reliable data. The importance of data quality was further reflected in participant recommendations for future practice. Several respondents emphasized the need for systematic post-completion evaluation and the collection of O&M cost outcomes, risk realization records, and financing performance information from completed projects. Such information would strengthen the empirical basis for future analyses and reduce reliance on judgment where historical evidence is currently limited.

Communication and stakeholder engagement are also important features identified. Participants repeatedly emphasized the value of involving technical, financial, operational, and procurement specialists throughout the analysis process. Communication and multi-stakeholder engagement were identified as the second most frequently cited critical success factors, while collaborative working practices also featured prominently among the lessons learned and recommendations. Respondents indicated that risk identification, assumption development, and overall model credibility improved when input was obtained from individuals with direct project knowledge. This finding is consistent with Nisar’s (2007) emphasis on project management capability as a prerequisite for successful P3 delivery and with Vining & Boardman’s (2008) argument that realistic risk valuation and transparent cost assessment depend on access to informed and diverse perspectives.

Participants also identified neutrality, independence, and transparency as important conditions for credible VfM analysis. Although these factors were cited less frequently than data quality and stakeholder engagement, they reflect concerns repeatedly raised in the VfM literature. Casady et al. (2020) argue that the absence of dedicated, institutionally independent PPP units can limit analytical continuity and oversight, while A. E. Boardman et al. (2016) emphasize the importance of experienced review functions and institutional memory. The present findings provide some support for these concerns, particularly given participant recommendations for greater transparency, independent challenge of assumptions, and stronger public-sector analytical capacity.

The findings point to four practical priorities for improving VfM practice in the United States. First, the development of centralized databases that contain cost, risk, financing, and operational performance information from completed projects would strengthen the empirical foundation for future analyses. Second, greater transparency regarding assumptions and sensitivity testing would improve the interpretability of VfM results and help decision-makers understand the range of possible outcomes. Third, formal independent review mechanisms could strengthen confidence in key assumptions and reduce the risk of confirmation bias. Finally, continued investment in public-sector analytical capacity would enhance agencies’ ability to develop, evaluate, and challenge increasingly complex VfM models.

There are some limitations. The study is based on a sample of 10 practitioners and is intended to provide insight into practitioners’ experiences rather than yield statistically representative conclusions. Interviews were documented through detailed notes rather than audio recordings, and the depth of responses varied across participants.

The Bipartisan Infrastructure Law of 2021 formalized the role of VfM analysis for transportation P3 projects receiving federal support, increasing the importance of ensuring that reliable data and transparent assumptions support these evaluations. As the portfolio of completed U.S. highway P3 projects continues to expand, opportunities for post-completion assessment and institutional learning will likewise increase. Future research should extend practitioner-based investigations across additional infrastructure sectors, examine approaches to independent review and quality assurance, and develop standardized methods for incorporating post-project performance information into future VfM analyses.