The Economics of Shared Digital Infrastructures: A framework for assessing societal value

This report argues for treating shared digital systems as foundational Digital Public Infrastructure (DPI), distinct from fragmented, project-based digitalisation efforts. It provides a framework to understand DPI’s infrastructural nature and assess its broad economic and societal value beyond simple efficiency gains, equipping policymakers and funders to make more informed investment and governance decisions.

Core Arguments & Findings

Traditional approaches to government digitalisation often result in fragmented, duplicative, and inefficient systems designed in silos (p. 6, 8). This leads to high costs, missed opportunities for innovation, barriers to inclusion, and weakened crisis response (p. 8).

In contrast, DPI adopts a foundational approach, providing shared, reusable digital systems (like digital ID, payments, data exchange) built on modular components that facilitate interoperability, efficiency, and innovation across government and society (p. 8, 14).

Defining Digital Infrastructure

The report defines infrastructure using an “attributes approach” (p. 11, Table 1 p. 15), highlighting characteristics relevant to DPI:

• Essential Inputs: Necessary for participation in markets or society (e.g., identity).
• Long-lived Collective Assets: High upfront cost, low marginal cost.
• Non-rival (up to congestion): Usable by many simultaneously.
• Collective & Non-excludable: Often implies universal access needs.
• Generic/Standardised Services: Usable as inputs for many activities.
• Dynamic Effects: Creates derived demand, spillovers, and externalities.
• Nature: Often complements/substitutes other infrastructures.

These attributes, particularly the dynamic and collective aspects, make traditional cost-benefit analysis (CBA) inadequate for evaluating DPI investments, as CBA often misses spillovers, systemic effects, and distributional outcomes (p. 12).

DPI Design Characteristics for Value Creation

The report identifies five key design characteristics that enable DPI to generate economic and societal value (Section 3, pp. 16-25; Table 2, p. 17):

1. Standardisation: Establishes common rules, formats, and protocols. This reduces transaction costs, prevents vendor lock-in (if open standards are used), and enables interoperability. However, poorly designed or prematurely set standards can stifle innovation or entrench dominant players (pp. 18-19).
2. Interoperability beyond immediate applications: Ensures different systems can exchange and use data, even across sectors beyond the original design. This minimizes redundant IT spending, facilitates spillovers and combinatorial innovation, and can shape market competition. Poor governance can lead to privacy risks or monopolies (p. 20).
3. Minimal and reusable building blocks: Uses modular components that can be repurposed across services (e.g., GOV.UK Notify, p. 22). This reduces costs, supports rapid scaling, lowers innovation costs, and enhances resilience. Risks include vendor lock-in or fragmentation if not governed well (p. 21).
4. Data as a high-value input: Leverages reliable, well-governed data systems to reduce information asymmetries, improve decision-making, enhance efficiency, and enable new services (e.g., FLOW initiative, p. 23). Poor data quality or governance can compound exclusion and undermine value (pp. 22-24).
5. Public governance and oversight: Ensures DPI operates in the public interest, balancing private participation with equitable access, security, and accountability. This prevents monopolisation, rent-seeking, and systemic risks, fostering trust and inclusion. Governance is crucial due to DPI’s ‘publicness’ and economic properties (non-rivalry, collective good) (pp. 24-25).

A Public Value Framework for DPI Evaluation

Recognizing the limitations of traditional methods, the report proposes a public value framework to assess DPI’s impact more holistically (Section 4, pp. 27-41). It moves beyond direct efficiency gains to capture systemic effects.

The framework assesses impact across three dimensions (Table 3, p. 29):

1. Direct Effects: Operational/service efficiency gains within core DPI functions (e.g., cost savings, faster processing, increased accuracy). Measurable early on.
2. Dynamic Effects: Network effects, spillovers, cross-sector externalities (e.g., new services built on DPI, cross-agency data sharing, improved targeting). Emerge as adoption scales.
3. Market-Shaping Effects: Structural transformations in industries, society, market dynamics (e.g., shifts in competition, new ecosystems, changes in state capacity, economic formalisation). Often longer-term and harder to reverse.

These effects are evaluated across three perspectives (Table 4, p. 32):

• Public Sector (Society): Impacts on government operations, costs, revenue, corruption, crisis response, governance models.
• Individual: Impacts on access, administrative burden, satisfaction, user experience, fraud, participation, trust, expectations.
• Industry: Impacts on business costs, service provision, revenue, interoperability, new business models, competition, market concentration, GDP.

This framework helps policymakers track short-term gains, anticipate scaling effects, understand broader structural implications, and consider distributional consequences (pp. 30-31).

Additional Factors and Trade-offs

Value creation is influenced by contextual factors (Section 5.1, pp. 44-47):

• Trust in Data: Poor data quality undermines DPI effectiveness and can compound exclusion.
• Inclusive Adoption & Scale: Digital divides (literacy, access) must be addressed to prevent DPI from becoming another barrier. Hybrid models (e.g., Bangladesh’s UDCs, p. 46) can help.
• Complementary DPI: Combining multiple DPI components (e.g., ID + data exchange) yields greater effects.
• Country Size: Spillover effects and economies of scale are more significant in larger populations.
• Local Accountability: Over-centralisation via DPI risks reducing local responsiveness; grievance redressal is crucial.

Key trade-offs require careful steering (Section 5.2, pp. 48-51):

• Sovereignty vs. Strategic Dependencies: National ownership vs. reliance on international providers/standards.
• Competition Effects: Lowering entry barriers vs. potential for monopolies on the DPI layer or downstream. Prioritising which effects matter most.
• Relational Value vs. Efficiencies: Reducing human intermediation for efficiency vs. potential loss of social connection or support, especially where digital literacy is low.

Methodology

The framework presented was developed through a complementary approach (p. 27):

• Conceptual: Reviewing existing frameworks for infrastructure and public value assessment (e.g., RQIV model, public value approaches) to define measurement dimensions.
• Empirical: Conducting a literature review of 69 policy and research papers (often focused on digital payments due to data availability) and interviewing policymakers from eight DPI-implementing countries to identify key themes, impacts, and measurement challenges.

The framework synthesizes these conceptual and empirical insights, aiming for a structured yet flexible approach adaptable to different contexts (p. 28).

Key Conclusions & Recommendations

The report concludes that DPI represents a fundamental shift requiring new approaches to investment, governance, and evaluation (p. 52). Realising DPI’s potential for sustainable, inclusive public value depends on deliberate strategic choices.

Policy Implications (p. 7):

1. Treat essential digital services as infrastructure: Govern, fund, and evaluate DPI with a long-term, cross-cutting perspective focused on state capability and economic dynamism.
2. Design for value from the start: Value is not automatic; it depends on technical, governance, procurement, and financing choices, which measurement must reflect.
3. Expand the role of finance ministries: Move beyond project logic to strategically shape DPI ecosystems, ensure coordination, avoid duplication, and steer systemic investments.
4. Build in dynamic measurement beyond efficiency: Move past basic adoption/cost-saving metrics to assess systemic value, long-term outcomes, and distributional trade-offs using frameworks like the one proposed.

Key Considerations & Trade-offs:

• Governments must actively manage trade-offs regarding sovereignty, competition, and the balance between efficiency and relational aspects of service delivery (pp. 48-51).
• Contextual factors like data quality, digital inclusion, country size, and local accountability significantly impact DPI outcomes (pp. 44-47).
• Effective public governance and oversight are paramount to ensure DPI serves the public interest and avoids reinforcing inequalities or monopolies (p. 24-25).

Key Questions Raised

The report highlights critical questions for policymakers and implementers moving forward (p. 52):

• Governance and Strategy: What role should finance ministries play in steering DPI adoption and investments, given its potential economic value?
• Funding and Incentives: How can funders/donors structure investments to encourage widespread, responsible DPI adoption?
• Maximizing Impact: Are current DPI implementations capturing full potential? What governance/design adjustments are needed?
• Metrics and Accountability: Are implementers tracking the right indicators? Who ensures alignment with public value?