A Cost Misperformance in Infrastructure Projects:Project Controls and PMO Perspective on Capacity, Governance, and Feasibility

Despite significant advances in estimating techniques, risk modeling, and performance measurement, infrastructure projects continue to exhibit persistent cost overruns. From a Project Management Office (PMO) and Project Controls standpoint, this persistence suggests that the root cause of cost misperformance lies not in technical inadequacy, but in how projects are governed, approved, and controlled under institutional constraints.

Recent academic work has correctly reframed cost overruns as systemic rather than individual phenomena, emphasizing the role of institutional pressures in shaping estimating behavior. However, an additional explanatory gap remains: the limited treatment of delivery capacity as a governing control variable within mainstream project controls practice.

This article argues that many projects are approved as cost-feasible while remaining fundamentally capacity-infeasible, and that this misalignment sits squarely within the PMO and controls governance domain.

Cost Control Without Capacity Control

Traditional project controls frameworks emphasize:

Cost baselines and contingency Schedule logic and critical path Earned Value metrics (CPI, SPI, SV, CV) Risk registers and quantitative risk analysis

These instruments are effective at measuring performance against an approved plan. They are far less effective at validating whether the plan itself was executable within real-world constraints.

In practice, many baseline assumptions remain implicit rather than controlled:

Labor availability is assumed elastic Physical space is assumed unconstrained Logistics, access, and shared services are assumed scalable Temporal congestion (simultaneous work, peak access demand) is rarely modeled

From a controls perspective, this represents a material blind spot: cost variance often emerges not from scope change or inefficiency, but from unmanaged constraint saturation.

Capacity as a First-Class Control Variable

Empirical delivery experience consistently demonstrates that cost growth is strongly correlated with:

Labor crowding and crew interference Spatial congestion and workface competition Logistics bottlenecks (access, laydown, transport, inspections) Shared service overload (parking, security, temporary power, outages) Resequencing driven by constraint conflicts rather than technical logic

These are not execution anomalies — they are predictable outcomes when demand exceeds finite supply.

Yet within many PMOs, these constraints are managed operationally rather than governed structurally. They are treated as site issues rather than baseline risks, resulting in reactive mitigation instead of proactive feasibility assurance.

Institutional Reinforcement and Baseline Fragility

The persistence of this gap is not accidental. From an institutional theory perspective, PMOs and controls functions operate within environments that apply competing pressures:

Coercive pressures favor early approval and funding certainty Mimetic pressures encourage replication of prior baselining practices Normative pressures reward confidence, alignment, and optimism

Within this context, introducing explicit capacity constraints into baselines often:

Complicates approval narratives Challenges precedent Extends front-end timelines

As a result, controls systems may unintentionally legitimize baselines that are internally coherent but externally infeasible. Once approved, these baselines become defended artifacts, even as execution evidence contradicts their assumptions.

From a PMO perspective, this represents a governance failure, not a technical one.

Implications for PMOs and Project Controls Functions

If cost misperformance is to be reduced in a meaningful way, PMOs must evolve beyond performance measurement toward feasibility assurance.

This requires expanding the definition of “control” to include:

Explicit modeling of capacity limits Demand–supply reconciliation at the system level Spatial and temporal congestion analysis Validation that resource loading reflects physical reality, not nominal availability

Critically, this is not a call for additional tools alone. It is a call for controls authority — the mandate to challenge whether a baseline is executable, not merely whether it is compliant.

Reframing the PMO Value Proposition

In many organizations, PMOs are positioned as reporters of variance rather than guardians of feasibility. This limits their influence to retrospective analysis instead of preventative governance.

A more mature PMO role would:

Require demonstration of delivery feasibility prior to baseline approval Treat capacity constraints as baseline-defining, not execution-managed Elevate constraint realism as a professional standard Protect controls functions when uncomfortable truths delay approval

Until this shift occurs, cost overruns will continue to be explained after the fact — rather than prevented by design.

Conclusion

Infrastructure projects rarely exceed budgets because estimating methods fail. They exceed budgets because institutionalized planning practices approve baselines that assume away finite capacity.

From a Project Controls and PMO standpoint, the path forward is clear:

cost control without capacity governance is incomplete control.

If PMOs are to remain relevant in complex infrastructure delivery, they must evolve from measuring adherence to plans toward ensuring that the plans themselves are grounded in executable reality.