i. Why Cities Struggle to Coordinate Asset Information

Structural fragmentation across agencies and owners.

Overview

Cities are collections of assets: buildings, roads, utilities, public spaces, infrastructure systems, and the organizations that operate them. A typical mid-sized city might contain hundreds of thousands of structures, thousands of miles of roads and pipes, countless pieces of equipment and systems, all generating data about their condition, performance, and maintenance needs. Yet despite physical interconnectedness creating dependencies where one system's failure cascades to others, the information describing these assets is rarely coordinated. Data lives in silos, governed by different institutions using different formats, operating under different incentives, and updating on different timelines.

Research on smart city data governance confirms this is a global phenomenon. Analysis by OECD examining 27 European cities found recurring themes: need for standardized data formats, clear data access guidelines, and stronger cross-departmental collaboration mechanisms. Studies of implementation challenges note that insufficient financial resources, lack of business models for financing data collection, limited access to skilled experts, and fragmented governance structures prevent cities from accessing adequate technology to process and store data or from upscaling smart city projects beyond pilots.

Cities do not struggle to coordinate asset information because of a lack of technology. They struggle because coordination is structurally difficult—requiring institutional alignment across autonomous entities that evolved independently, each optimized for internal mandates rather than city-wide interoperability. Technology can support coordination, but it cannot substitute for the governance structures, shared incentives, and durable stewardship models that make coordination operationally sustainable.

Cities Are Multi-Owner Systems

Unlike single-owner portfolios where one entity controls all assets and can impose unified information standards, cities contain assets owned and operated by diverse stakeholders with different legal authorities, operational responsibilities, and information needs. Public agencies at multiple levels—municipal departments, regional utilities, state transportation authorities, federal infrastructure operators—each maintain assets according to their specific mandates. Private developers and property owners control buildings and land parcels, collecting information primarily for compliance and transaction purposes. Utilities and concessionaires operate critical infrastructure under franchise agreements, generating operational data that rarely flows back to city systems. Institutional investors own substantial commercial and residential portfolios, tracking performance for financial rather than civic purposes. Individuals and households own most residential properties, typically maintaining minimal formal documentation.

Each owner collects information for their own purposes using their own standards. A municipal building department tracks permits and inspections to enforce building codes. A utility company monitors infrastructure performance to maintain service reliability and plan capital investments. A private developer documents property characteristics to support financing and sales. An institutional investor analyzes portfolio performance for reporting to stakeholders. These information systems reflect their creators' needs and workflows rather than city-wide coordination requirements.

No single entity has authority—or incentive—to harmonize how asset information is produced or maintained across the city. Municipal government can set standards for public assets and require certain disclosures from private owners, but cannot dictate internal information practices of private entities or other governmental levels. Utilities operate under regulatory frameworks focused on service delivery rather than data coordination. Private owners optimize for transaction readiness and operational efficiency, not contribution to city-wide information systems. Coordination is optional based on voluntary participation. Fragmentation is the default state requiring active effort to overcome.

Institutional Boundaries Fragment Information

City asset information is divided across institutions that evolved independently over decades, each developing systems optimized for specific functions without consideration for how they might need to integrate with other departments or external stakeholders. Planning departments track zoning designations, development rights, and entitlements to manage land use and growth patterns. Building departments manage permit applications, construction inspections, and certificate of occupancy issuance to enforce building codes. Public works departments maintain infrastructure like roads, water systems, and drainage to provide services. Utilities operate electrical grids, gas pipelines, telecommunications networks generating operational data about performance and reliability.

These systems were designed around internal mandates rather than interoperability with external systems. As a result, datasets overlap but do not align—planning records contain property information also maintained by assessors and building departments, but with different identifiers, update cycles, and levels of detail. Terminology varies across agencies—what one department calls a "structure" another calls a "building" or "improvement," with different definitions affecting what gets recorded and how. Updates propagate unevenly—a renovation permitted by the building department may not update the assessor's records for months or years, creating inconsistencies across official sources.

Research on smart city data infrastructure emphasizes that technical issues like data interoperability represent only part of the challenge. Non-technical aspects including different strategies to manage personal data, to exchange data among different stakeholders, and varying license terminology create barriers that technology alone cannot resolve. Coordination requires effort across organizational boundaries without clear ownership or mandate. No single department has authority to impose city-wide standards, and cross-functional coordination competes with operational priorities within each department's direct responsibilities and performance metrics.

Asset Data is Event-Driven, Not Continuous

Most city asset information is captured at discrete regulatory or transaction events rather than continuously throughout asset lifecycles. Permitting processes document planned work before construction begins. Inspections verify code compliance at defined milestones during construction and occupancy. Construction completion generates final documentation when projects close. Compliance reviews assess adherence to regulations at scheduled intervals or when complaints trigger investigation.

Between these formal events, assets change with limited documentation flowing to official records. Owners make modifications without permits when they believe work falls below thresholds requiring approval or when they simply bypass regulatory processes. Maintenance activities occur routinely but rarely get documented in ways accessible to city agencies. Systems age and condition deteriorates gradually without triggering formal assessment until failures occur or scheduled inspections happen. Performance drifts from original design assumptions without systematic measurement or recording.

This episodic model creates substantial blind spots in city asset knowledge. Modifications go unrecorded, creating discrepancies between official records and actual conditions that complicate future permitting, safety assessments, and emergency response. Conditions drift without visibility, preventing proactive intervention before problems escalate to failures requiring expensive emergency repairs. Performance is inferred from design specifications and age rather than observed through systematic monitoring, leading to inefficient maintenance and capital planning decisions based on assumptions rather than evidence.

Cities lack information continuity not because they do not care about asset conditions but because their information systems are designed around regulatory process milestones rather than asset lifecycle management. Building departments focus on ensuring new construction complies with codes, not tracking how assets perform after occupancy. Public works departments respond to service requests and failures rather than monitoring infrastructure condition continuously. This episodic approach reflects limited resources, regulatory constraints focusing on specific approval events, and the practical difficulty of maintaining continuous oversight across thousands of privately owned assets.

Standards Exist, Adoption Does Not

Numerous standards address built environment data across different domains and use cases. BIM schemas like IFC (Industry Foundation Classes) provide structured formats for building geometry and components. Asset classification systems like Omniclass and Uniclass enable consistent categorization. Geospatial formats like GIS standards support spatial data integration. Reporting frameworks for sustainability and energy performance establish disclosure requirements. These standards are well-developed, widely available, and proven effective in controlled implementations.

Yet cities rarely apply these standards consistently across stakeholders or even across their own departments. Barriers include legacy systems that predate current standards and would require expensive replacement or migration to comply. Procurement constraints where purchasing decisions prioritize cost over interoperability, resulting in systems that cannot exchange data easily. Limited technical capacity within municipal IT departments to implement and maintain standards compliance across complex environments. Misaligned incentives where individual departments optimize for internal efficiency rather than city-wide coordination, and vendors protect proprietary formats to maintain customer lock-in.

Standardization requires coordination across departments with different technical capabilities, budget constraints, and operational priorities, and across market participants including developers, contractors, consultants, and platform vendors who have varying incentives regarding open standards. This is fundamentally an organizational challenge that technology alone cannot solve. Even when standards are adopted formally through policy, actual implementation requires sustained effort, technical support, training, and enforcement that many cities struggle to maintain given competing demands on limited resources.

Governance Complexity Discourages Integration

Coordinating asset information across organizational boundaries raises governance questions that many cities find difficult to resolve clearly. Who owns shared data—particularly when information originates from private sources, passes through municipal processes, and becomes relevant to multiple agencies? Who is responsible for data accuracy when information flows across systems with different validation processes and quality standards? Who bears liability for errors when decisions based on coordinated data produce adverse outcomes, and multiple parties contributed to the information? Who controls access and use of integrated data, especially when some sources have privacy sensitivities or commercial value?

Without clear answers to these questions, institutions default to containment rather than sharing. Keeping data within departmental systems limits exposure to liability if information proves inaccurate. Restricting access prevents unauthorized use that might create obligations or risks. Maintaining separate systems preserves organizational autonomy and control even if coordination would improve outcomes. Research on data governance in smart cities emphasizes that establishing appropriate systems for governing various data is a critical challenge, particularly in loosely coupled settings across multiple organizations where parties do not necessarily share common security infrastructure for reliably sharing information assets.

Fragmentation is safer than integration when accountability is unclear. An agency sharing data that another party uses incorrectly may face blame for consequences even if the error occurred downstream. Integration creates dependencies where system failures or data quality problems propagate across organizational boundaries, potentially affecting operations beyond any single entity's control. These governance concerns are legitimate and require resolution through clear frameworks establishing roles, responsibilities, liabilities, and dispute resolution mechanisms—institutional work that many cities have not completed despite launching technical integration projects.

Political and Budget Cycles Disrupt Continuity

Cities operate within political and budgetary cycles that fundamentally misalign with the long-term horizon required for effective asset information stewardship. Projects are funded episodically through annual or biannual budget processes, making multi-year initiatives vulnerable to disruption when priorities shift. Leadership changes regularly through elections and administrative transitions, bringing new agendas that may deprioritize information infrastructure investments initiated by predecessors. Systems are replaced rather than maintained as new administrations seek visible improvements over incremental enhancements to existing infrastructure.

Asset information continuity requires investment beyond electoral timelines spanning multiple political cycles to achieve sustainable operations. Initial system deployment represents only a fraction of total lifecycle cost—ongoing data maintenance, quality monitoring, standards enforcement, and integration support demand sustained resources that compete with operationally visible services like public safety, transportation, and social programs. When budget constraints require cuts, information infrastructure often suffers because degradation is gradual and invisible compared to service reductions affecting constituents directly.

The global IoT market in smart cities is projected to grow from $300 billion in 2021 to over $650 billion by 2026, with US cities expected to invest $41 trillion in smart infrastructure. However, research shows that insufficient financial resources for smart city data strategies prevent cities from accessing adequate technology to process and store data and from upscaling projects beyond pilots. The challenge is not just initial capital but sustained operational funding supporting continuous improvement and adaptation as requirements evolve.

Private-Sector Misalignment Compounds the Problem

Private asset owners often have little incentive to align with city data practices beyond minimum regulatory compliance. They optimize for compliance meeting permit requirements to secure approvals, transaction readiness preparing information supporting sales or financing, and internal reporting needs serving management and ownership rather than civic purposes. Once regulatory approvals are secured and compliance obligations satisfied, information flow back to city systems slows or stops. Owners see no benefit from maintaining data in formats or systems enabling city-wide coordination.

This creates fundamental asymmetry: cities regulate assets they cannot fully observe. Building departments issue permits based on proposed plans but have limited visibility into what actually gets built or how buildings are maintained afterward. Code enforcement operates reactively responding to complaints rather than proactively monitoring compliance. Infrastructure planning depends on assumptions about private asset conditions and performance that cannot be verified systematically. This information asymmetry undermines both regulatory effectiveness and civic planning capacity.

Private sector participants face real costs from enhanced data sharing without clear benefits. Preparing information in standardized formats requires effort and expense beyond internal needs. Maintaining coordination with city systems creates operational dependencies and potential exposure to enforcement if documentation reveals violations. Sharing performance data may disadvantage owners competitively or affect property valuations. Without compelling incentives or requirements, rational private actors minimize rather than enhance data sharing with municipal systems.

The Cost of Poor Coordination is Systemic

The consequences of fragmented asset information extend well beyond administrative inconvenience or technical inefficiency. They include inefficient infrastructure planning where investments are made based on partial understanding of existing conditions and future needs, leading to over-building in some areas while unmet needs persist elsewhere. Delayed emergency response when first responders lack accurate information about building layouts, occupancies, hazardous materials, or infrastructure locations, compromising safety and effectiveness. Misaligned capital allocation across departments and agencies pursuing independent priorities without visibility into overlapping investments or missed opportunities for coordination. Difficulty achieving sustainability goals when energy use, emissions, resilience measures cannot be assessed comprehensively across public and private assets city-wide.

Cities make critical policy decisions—about growth management, infrastructure investment, climate adaptation, social equity—based on partial visibility of the systems they aim to manage. This incomplete information increases risk by hiding problems until they become crises, reduces effectiveness by preventing targeted interventions, and wastes resources through duplicative work and missed efficiency opportunities. Research on smart city challenges confirms that without robust data governance, much of urban data potential remains underexploited, resulting in inefficiencies and missed opportunities for city administrations.

Coordination failures are rarely catastrophic in the sense of causing immediate disasters. They are cumulative—gradually degrading decision quality, increasing costs, slowing response times, and reducing resilience until periodic crises reveal the accumulated consequences of years of fragmentation. By that time, addressing problems requires far more resources than maintaining coordination would have cost incrementally.

Why Technology Pilots Often Stall

Many cities launch pilots around digital twins, smart infrastructure platforms, or integrated data systems. These efforts frequently demonstrate technical feasibility—systems can be built, data can be integrated, visualizations can be created, analytics can provide insights. Yet scaling beyond pilot phase proves difficult, with projects either remaining perpetually in pilot stage, expanding slowly to limited scope, or being abandoned when funding or political support ends.

Common reasons for stalling include lack of shared data models that prevent pilot systems from integrating with production environments where formats and standards differ. Unclear integration with existing processes where pilot systems operate in parallel to production workflows rather than replacing or enhancing them, creating extra work rather than efficiency. Absence of long-term governance structures establishing who maintains systems, updates data, resolves quality issues, and funds ongoing operations after initial deployment excitement wanes.

Without addressing coordination at the institutional level—establishing governance frameworks, aligning incentives, securing sustainable funding, building organizational capacity—technical solutions remain isolated experiments demonstrating possibility without achieving operational integration. Technology pilots prove concept but cannot create the institutional foundations required for durable implementation. Research examining smart city initiatives notes they often address problems from technology perspective while disregarding stakeholders and data needs, making them susceptible to failure from inadequate stakeholder input, requirements neglecting, and information fragmentation.

Coordination is a Governance Problem First

Effective coordination requires addressing governance and institutional challenges before or alongside technical implementation. Shared definitions of asset information establishing what gets documented, in what formats, with what metadata, and at what intervals across participating entities. Clear roles and responsibilities specifying who collects data, who maintains quality, who provides access, who resolves disputes when discrepancies or problems arise. Incentives for participation making coordination beneficial rather than burdensome for stakeholders, whether through reduced regulatory friction, improved service delivery, or other value propositions. Durable stewardship models ensuring coordination survives political transitions, budget fluctuations, and technology changes through institutionalized rather than project-based structures.

Technology can support these governance foundations by enabling efficient data exchange, automating quality checks, visualizing integrated information, and supporting collaborative workflows. However, technology cannot substitute for governance. Even the most sophisticated platform fails without institutional commitment to maintaining it, political will to enforcing standards, resources for continuous operation, and stakeholder participation providing data and using outputs.

Cities coordinate traffic signals and utility operations because governance frameworks exist establishing authority, responsibility, funding, and operational processes. Asset information requires similar treatment—not as optional enhancement when resources permit but as essential infrastructure supporting core civic functions from public safety through economic development to environmental sustainability.

Why This Guide Matters

Cities are increasingly expected to deliver resilience against climate impacts and economic disruptions, sustainability achieving aggressive emissions and resource efficiency targets, and equitable service provision improving outcomes across diverse populations. These outcomes depend fundamentally on coordinated understanding of the assets composing the city—their condition, performance, interconnections, and trajectories over time.

Without coordinated asset information, cities operate reactively based on assumptions rather than evidence, responding to problems rather than preventing them, making decisions that optimize for visible politics rather than long-term systems performance. Improving coordination is not about building smarter dashboards or deploying more sensors. It is about aligning institutions around shared visibility through governance frameworks that make coordination operationally sustainable and politically durable.

Cities struggle to coordinate asset information because no one designed them to do so. Cities evolved organically through aggregation of independent systems and stakeholders, each optimizing locally without mechanisms ensuring global coordination. That design gap—the absence of governance frameworks, institutional incentives, and stewardship models treating asset information as shared infrastructure rather than departmental byproduct—now defines the challenge. Technology enables possibilities, but governance determines outcomes. The path forward requires institutional innovation matching technical capability.

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Keywords: urban asset data, city infrastructure, public asset management, data silos, municipal governance, built environment data, smart cities, infrastructure coordination, data governance, institutional fragmentation

References

• Cambridge University. (2023). The Conundrum in Smart City Governance: Interoperability and Compatibility in Digital Twins Ecosystem. Analysis of how fragmented approaches and lack of interoperability result in unsuccessful smart city developments.

• Choenni, Bargh, Busker, Netten. (2022). Data Governance in Smart Cities: Challenges and Solution Directions. Journal examining security governance, trust architecture, and data quality provisioning in distributed smart city environments.

• OECD. (2023). Smart City Data Governance: Challenges and the Way Forward. Report identifying insufficient financial resources, lack of business models, limited technical capacity, and governance gaps as primary barriers across 27 European cities.

• ScienceDirect. (2025). Assessing Data Governance Models for Smart Cities Based on European Urban Requirements. Research establishing specific requirements including standardized formats, clear access guidelines, and cross-departmental collaboration mechanisms.

• World Bank. Asset Management for Infrastructure Systems. Framework for managing public infrastructure assets emphasizing information requirements for effective stewardship.