A Practitioner’s Case for Resource Utilization Management

constructionresourceutilization.com

March 2026

Abstract

Earned Value Management (EVM) has served as the dominant project controls methodology in the construction industry for decades, inherited largely from defence and aerospace procurement frameworks. Its core performance indicators—the Schedule Performance Index (SPI) and Cost Performance Index (CPI)—are treated as definitive measures of project health across government and private-sector mega projects alike. This paper argues that these blended, dollar-weighted metrics fundamentally obscure the resource-level dynamics that drive construction project outcomes. When labour and materials constitute between 70 and 85 percent of total project costs, yet resource utilization, workforce productivity, and material consumption rates remain largely unmanaged and unmeasured, the industry is effectively monitoring outcomes while ignoring inputs. Drawing on two decades of practitioner experience managing vendor resource load boards on government mega programmes—yielding over $100 million in documented savings—this paper presents the case for a complementary resource utilization framework that operates beneath and alongside traditional EVM. Critically, the paper introduces a practical breakthrough: a resource-loaded estimate validation methodology that forces resource-level transparency at the bid stage, enabling owners to challenge and validate vendor estimates against the Level 3 schedule before a single dollar is committed, exposing hidden contingency in project management team costs and ensuring crew sizing aligns with planned scope and duration.

1. Introduction: The Comfortable Illusion of Earned Value

The construction industry has a measurement problem. Not a shortage of measurement—quite the opposite—but a reliance on metrics that provide the appearance of control without delivering genuine insight into project health. At the centre of this problem sit SPI and CPI, the twin pillars of Earned Value Management Systems (EVMS), which have been adopted across the global construction sector as the standard language of project performance reporting.

The scale of the problem these metrics are meant to address is beyond dispute. Research across 258 major international transport infrastructure projects found an average cost overrun of 28 percent, with nine out of ten projects exceeding their original estimates (Flyvbjerg, Holm, & Buhl, 2002). McKinsey & Company’s analysis of mega projects found that 98 percent face cost overruns or delays, with some running as much as 80 percent over budget and 20 percent longer than scheduled. A separate review published by the Project Management Institute identified poor productivity, inadequate communications, and uncertainties around labour and material costs as recurring drivers of these overruns.

Yet the dominant response to these persistent failures has been to refine the EVM methodology itself—developing extensions such as Earned Schedule (ES) and Earned Duration (ED), both of which address some of the well-documented limitations of traditional SPI in schedule forecasting. A 2025 study published in Scientific Reports evaluating 30 construction projects in Egypt confirmed that Earned Schedule provides more accurate predictions during early project stages, while Earned Duration performs better at later stages. These are meaningful methodological improvements. But they remain firmly within the EVM paradigm, refining the thermometer without questioning whether temperature alone is the right diagnostic.

The fundamental question this paper poses is not whether EVM is useful—it is—but whether an industry in which resources and materials constitute the overwhelming majority of project costs can afford to treat resource management as someone else’s problem while relying on blended cost indices as its primary health indicators.

2. The Structural Limitations of SPI and CPI in Construction

2.1 The Blending Problem

SPI and CPI are ratio metrics. SPI divides Earned Value by Planned Value; CPI divides Earned Value by Actual Cost. In both cases, the calculation treats every dollar equivalently, regardless of whether it represents a labour hour, a ton of structural steel, a crane rental, or a subcontractor invoice. On a typical commercial construction project, labour may account for 40 percent of total cost, materials for 30 to 35 percent, with equipment, subcontracts, and indirect costs comprising the remainder. These cost categories are driven by entirely different factors, respond to different market conditions, and require different management interventions.

When CPI reports a value of 0.92, it communicates only that actual costs are exceeding earned value by approximately eight percent. It does not reveal whether this variance is driven by material price escalation beyond the contractor’s control, poor labour productivity on a critical path activity, equipment idle time due to sequencing failures, or some combination of all three. The metric that is treated as a definitive health indicator is, in reality, a weighted average that masks every actionable insight beneath it.

2.2 Lagging Versus Leading Indicators

A further structural limitation of SPI and CPI is their nature as lagging indicators. They report what has already occurred, not what is developing. By the time CPI drops below 1.0 by a statistically significant margin on a mega project, the cost damage is typically weeks or months old. The conditions that produced the variance—crews that were underutilized, materials that arrived late and forced out-of-sequence work, equipment that sat idle during weather delays—have already consumed budget and schedule float.

Research on EVM’s predictive limitations supports this observation. A study by Barraza and Bueno (2018) proposed that because EVM ignores activity duration variability, it consistently produces optimistic completion date forecasts. The authors used Monte Carlo simulations to demonstrate how the merge event bias phenomenon inadvertently impacts schedule performance in both time and cost dimensions, a dynamic that SPI is structurally incapable of detecting.

2.3 The Origins Mismatch

EVM was developed for the United States Department of Defence in the 1960s as the Cost/Schedule Control Systems Criteria (C/SCSC), designed for environments characterized by relatively fixed scope, salaried labour, and controlled procurement pipelines. Construction is a fundamentally different operating environment. Craft labour productivity varies with crew composition, weather, site logistics, learning curves, and fatigue. Material costs are subject to global commodity volatility. Equipment utilization depends on site access, sequencing, and maintenance schedules. Subcontractors operate as semi-autonomous entities with their own resource constraints and priorities.

The research community has increasingly acknowledged this mismatch. Aramali et al. (2022), in a review published in the Journal of Management in Engineering, documented a significant disconnect between EVM academic literature and industry practice, noting that many organizations struggle to apply EVM techniques effectively to the unique conditions of construction projects.

3. The Resource Utilization Gap: What We Are Not Measuring

3.1 Defining the Gap

If labour and materials represent the majority of project expenditure, it follows logically that the performance of these resources should be the primary focus of project controls. Yet on most construction mega projects, the following metrics are either not tracked in real time or not tracked at all: labour hours per unit of installed work by trade and activity type; actual versus planned crew sizes against schedule requirements; material consumption rates versus theoretical quantities; material waste percentages by type and installation phase; equipment utilization rates, measured as productive hours versus available hours; and the alignment between resource mobilization curves and schedule demand curves.

This gap is not theoretical. The Bureau of Labor Statistics’ Productivity Program has documented that construction labour productivity has shown inconsistent and often declining trends across multiple sectors. Their analysis of four construction industries—single-family residential, multi-family residential, industrial building, and highway construction—revealed that residential construction productivity trended downward over the 2007 to 2019 period. A 2023 report from the University of Chicago’s Becker Friedman Institute for Economics found that the amount of value produced per full-time construction worker has steadily decreased since 1950, even as the broader economy has seen per-worker output increase.

3.2 The Whitespace Problem

“Whitespace”—the periods within a project schedule where resources are underutilized, idle, or misaligned with planned activities—represents one of the most significant sources of cost and schedule leakage on mega projects. On a large programme with 500 craft workers on site, if actual productive utilization is 55 percent versus a planned 65 percent, that 10-percentage-point gap represents a substantial daily cost and schedule impact. Over a multi-year programme, the cumulative effect can reach into the hundreds of millions of dollars. Yet this gap is invisible in traditional EVM reporting.

Industry research corroborates the scale of this problem. Studies suggest that construction workers spend approximately 35 percent of their time on non-productive activities, and that material waste and delivery delays contribute to roughly 30 percent of cost overruns on commercial projects. These are resource-level phenomena that demand resource-level measurement.

4. Why the Industry Resists: Institutional, Cultural, and Contractual Barriers

4.1 Contractual Entrenchment

EVM is not merely a management tool in the construction industry; it is a contractual compliance requirement. In the United States, ANSI/EIA-748 establishes the guidelines for EVMS on government contracts, and compliance is typically a non-negotiable element of contract performance reporting. When a methodology is embedded in contract law, the incentive to supplement or challenge it diminishes significantly, regardless of its limitations.

4.2 The Oversight-Interference Confusion

In government project delivery, a pervasive and damaging misconception holds that monitoring contractor resource performance constitutes interference with the contractor’s means and methods. This concern is rooted in a legitimate legal principle—government owners should not direct how a contractor executes work—but it has metastasized into a justification for wilful blindness regarding resource management.

There is a critical distinction between directing a contractor’s resources and requiring transparency into resource planning as part of oversight responsibility. The former is interference. The latter is the fundamental duty of a project owner spending public funds.

4.3 Cultural and Organizational Inertia

Many government programme managers enter their roles from engineering, procurement, or contracting backgrounds rather than construction operations. They may never have managed a site or developed an intuitive understanding of what productive utilization looks and feels like in the field. For these professionals, the EVMS report is the project. The field is an abstraction managed by the contractor.

This cultural barrier is reinforced by institutional incentive structures. In large government organizations, career advancement rewards compliance with established processes. An organization that has been recognised with industry awards for its project management methodology has powerful psychological and institutional reasons to resist any suggestion that its methodology contains a significant blind spot.

4.4 Data Collection Barriers

Real resource tracking requires field-level data discipline that many construction organizations have not achieved. It requires daily recording of quantities installed and hours worked at the task level, consistent material receipt and consumption tracking, and equipment utilization logging. Recent research has highlighted the potential of digital technologies—computer vision, wearable sensors, real-time location systems, and BIM integration—to address this gap, yet adoption remains limited and uneven.

5. The Pre-Construction Breakthrough: Challenging the Estimate Before the First Dollar Is Spent

The preceding sections have argued that resource management during project execution is inadequately served by traditional EVM. But there is an equally critical—and even more overlooked—opportunity to apply resource management principles before the project begins: at the estimate and bid stage. If the industry is reluctant to manage resources during execution, it should at minimum demand resource-level transparency before committing funds.

5.1 The Opacity of Traditional Estimates

Conventional construction estimates are typically submitted as lump-sum or unit-rate proposals, offering limited visibility into the resource assumptions underlying the total price. The vendor presents a number; the owner evaluates it against benchmarks, historical data, and competing bids. What is rarely interrogated is the resource composition of the estimate—specifically, who is being charged to the project, for how long, at what level of effort, and whether that level of effort is congruent with the scope and schedule the vendor has committed to deliver.

This opacity is particularly acute in project management team (PMT) costs. PMT expenditure—encompassing project managers, schedulers, project controls staff, QA/QC personnel, document controllers, safety officers, and other indirect roles—can represent a substantial percentage of total project cost on mega programmes. Vendors routinely embed contingency within PMT estimates by extending durations beyond what the schedule requires, inflating the number of resources assigned to support functions, or assigning full-time personnel to roles that are genuinely part-time in nature. Without a methodology that forces these assumptions into the open at the individual-resource level, the owner has no practical means of challenging them.

5.2 The Science of Resource-Loaded Estimate Validation

The concept is deceptively simple and grounded in a single principle: every resource charged to a project must be justified against the schedule that governs the work. This principle, when applied rigorously at the bid stage, exposes hidden contingency through three interlocking analytical mechanisms.

The first is utilization analysis. For every indirect or PMT role proposed in the estimate, the owner requires the vendor to declare the assignment’s start date, end date, hours per shift, and total hours charged. From these inputs, a utilization percentage is derived: total hours charged divided by total hours available within the stated duration. This single ratio is the most powerful diagnostic in pre-construction resource management. A project scheduler billed from initiation through closeout at 100 percent utilization, when the schedule only requires active scheduling support during planning and execution phases, will show a utilization figure that is immediately and mathematically indefensible. The contingency is not hidden in narrative or judgement—it is exposed by arithmetic.

The second mechanism is production rate validation. For direct trade labour, the owner requires the vendor to declare crew sizes, durations, quantities, and unit rates for every construction activity. From these inputs, install norms are derived: total labour hours divided by installed quantity. These unit-hour metrics can be benchmarked against historical performance data, industry standards, and the production rates implied by the Level 3 schedule logic. When a vendor has inflated crew sizes, extended durations beyond what the production rates support, or assumed norms that are inconsistent with the schedule’s critical path, the discrepancy is quantifiable and challengeable.

The third mechanism is time-phased resource profiling. The vendor is required to distribute every resource hour across the project timeline at the individual level—not aggregated by trade or role, but for each person charging the project. This daily or weekly profile must reconcile with both the estimate totals and the Level 3 schedule. If the schedule shows a construction phase running from month 4 through month 10, but the resource profile shows trade workers allocated from month 2 through month 12, the discrepancy is immediately visible. This prevents resource grouping, which is the primary mechanism through which vendors obscure contingency in aggregate estimates.

5.3 The Three Forms of Hidden Contingency

When these three mechanisms are applied in concert, three distinct forms of embedded contingency become systematically identifiable.

Duration padding is the practice of extending resource assignments beyond the schedule phases they support. It is detected through utilization analysis: when the ratio of hours charged to hours available falls significantly below the level that the scope of work justifies, the excess represents contingency embedded in duration rather than in rate or quantity.

Resource inflation is the practice of assigning more individuals to a function than the scope requires. It is detected through benchmarking: when the number of resources proposed for a given function exceeds what comparable projects or industry norms indicate, the excess headcount represents contingency embedded in volume rather than in price.

Rate arbitrage is the practice of assigning senior-level resources to tasks that could be performed by less expensive personnel. It is detected through scope-to-role alignment analysis: when the work description associated with a line item suggests junior-level requirements but the proposed resource carries a senior-level rate, the rate differential represents embedded margin.

The critical insight is that none of these forms of contingency are visible in a traditional lump-sum or even a reasonably detailed cost breakdown. They become visible only when the estimate is decomposed to the individual resource level and validated against the schedule. The conversation with the vendor shifts from “justify your total PMT cost”—which is easily deflected with broad narratives about complexity and risk—to “explain why this specific role is charged at this utilization level for this specific period when the schedule shows limited active work in that scope.” That level of specificity, grounded in the vendor’s own declared data, is very difficult to deflect.

5.4 The Closed Loop: Estimate, Schedule, and Execution Baseline

The full power of resource-loaded estimate validation is realized when it creates a closed loop between the estimate, the Level 3 schedule, and the execution baseline. The schedule defines the work sequence and duration. The resource-loaded estimate defines the people, trades, and materials required to execute that work. The time-phased resource profile provides the day-by-day reconciliation between the two. When all three are aligned, the project begins with a resource baseline that is not merely a financial abstraction but a verifiable commitment to deploy specific resources at specific times to perform specific work.

This integration transforms bid evaluation from a purely financial exercise into a resource planning exercise. The owner is no longer simply asking “Is the price reasonable?” but rather “Do the resources proposed in this estimate actually support the schedule this vendor has committed to deliver?” If crew sizes are insufficient to achieve planned production rates, or if indirect resources are profiled beyond the phases they support, the vendor must reconcile the gap before the estimate is accepted.

This represents resource management at the earliest possible intervention point: before the first dollar is spent, before the baseline is set, and before hidden contingency becomes embedded in the project’s cost structure where it will eventually appear as “favourable variance” in the EVMS—or worse, where it will be consumed without ever being identified. The resource-loaded estimate becomes the foundation upon which all subsequent resource performance tracking during execution is built.

6. A Practitioner’s Case: $100 Million in Recovered Value

The argument presented in this paper is not theoretical. Over more than two decades of managing government mega programmes, the author has implemented a resource utilization tracking approach that operates alongside traditional EVMS. The methodology is straightforward: contractors are held accountable to their own submitted resource load boards, and the gaps between committed resource plans and actual deployment are tracked, visualized, and acted upon.

This approach, combined with the pre-construction estimate challenge methodology described in Section 5, has generated over $100 million in documented savings on government programmes. The savings come from two sources: contingency removed at the bid stage through rigorous resource-level estimate validation, and cost avoidance during execution through early identification of mobilization gaps and resource underperformance.

It is essential to note what this approach does not do. It does not direct the contractor’s means and methods. It does not dictate crew composition or resource allocation. It simply holds contractors accountable to their own commitments and makes resource performance visible at a level of granularity that blended EVM metrics cannot provide.

Despite the scale of documented savings, the organizational response has been one of acknowledgement without adoption. The savings are recognized. The methodology is not institutionalized. This outcome illustrates the depth of institutional resistance described in the preceding sections and underscores the extent to which the barriers to resource management are cultural and organizational rather than technical or methodological.

7. Toward a Complementary Framework: Resource Performance Indicators

The proposal advanced in this paper is not to abandon EVM but to supplement it with a resource performance layer that provides the leading indicators SPI and CPI cannot deliver. This framework would operate at four levels:

Level 0: Pre-Construction Estimate Validation

Require resource-level estimate decomposition aligned to the Level 3 schedule as a condition of bid acceptance. Apply utilization analysis to all indirect and PMT roles, exposing hidden contingency through the ratio of hours charged to hours available. Validate construction crew sizing and production rates against install norms and schedule logic. Establish the resource baseline before the project begins, creating the foundation for all subsequent resource performance tracking.

Level 1: Resource Mobilization Alignment

Track actual resource deployment against the contractor’s committed resource plan on a weekly basis. Measure headcount by trade against scheduled requirements. Identify mobilization gaps before they manifest as schedule variance. Calculate a Resource Alignment Index (RAI) as the ratio of actual deployed resources to planned resources.

Level 2: Labour Productivity Tracking

Measure labour hours per unit of installed work by trade and activity type. Track productivity trends over time. Compare actual production rates against the rates assumed in the baseline estimate and schedule.

Level 3: Material and Equipment Performance

Track material consumption rates against planned quantities. Monitor equipment utilization as productive hours versus available hours. Measure alignment between material delivery schedules and installation sequences.

Together, these four levels create a resource performance system that begins at the estimate stage and extends through execution, sitting beneath EVM and feeding into it. The resource metrics become the diagnostic; the EVM metrics become the summary.

8. Conclusion: The Cost of Not Looking

The construction industry’s reliance on SPI and CPI as primary health indicators for mega projects is not merely a methodological preference; it is a structural blind spot with measurable financial consequences. When 85 percent of construction projects exceed their budgets, when the average overrun is 28 percent, and when 98 percent of mega projects face cost overruns or delays, the question is not whether the current approach is working. It is how much value is being lost because the industry monitors the wrong metrics at the wrong level of granularity.

The pre-construction estimate challenge demonstrated in this paper—using structured tools that force vendors to justify their resource assumptions at the individual level against the project schedule—represents a practical, implementable breakthrough that requires no new technology, no contractual innovation, and no organizational transformation. It requires only the will to look beneath the total price and ask: do these resources match this schedule? That single question, applied rigorously at the bid stage and tracked through execution, has generated over $100 million in documented savings on a single government programme.

Resources and materials are the project. They represent where the money goes, where productivity is won or lost, and where the earliest signals of trouble emerge. An industry that delegates resource management entirely to contractors while monitoring blended cost indices from a reporting system designed for Cold War defence procurement is not managing its projects. It is documenting their outcomes after the fact.

The $100 million in documented savings is not the ceiling of what is possible. It is the floor. The opportunity that exists across the global construction industry, if resource utilization management were adopted as a standard complement to EVM—beginning at the estimate stage and extending through project closeout—is measured not in millions but in billions. The only question is how long the industry will continue to accept the comfortable illusion of project health that SPI and CPI provide, when the true picture is available to anyone willing to look.

 

References

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Flyvbjerg, B., Holm, M. S., & Buhl, S. (2002). Underestimating costs in public works projects: Error or lie? Journal of the American Planning Association, 68(3), 279–295.

Flyvbjerg, B., & Gardner, D. (2023). How Big Things Get Done. Currency.

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McKinsey & Company. (2017). The construction productivity imperative. McKinsey Global Institute.

Morris, P. W. G., & Hough, G. H. (1987). The Anatomy of Major Projects. John Wiley & Sons.

Project Management Institute. (2011). Practice Standard for Earned Value Management. PMI.

University of Chicago, Becker Friedman Institute for Economics. (2023). Construction Productivity in the United States.

 

Published at constructionresourceutilization.com

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