Harnessing the private sector for better development data

Data is at the heart of development, powering the decisions and investments that help to reduce poverty and build a sustainable future. Yet most national statistical systems in low- and middle-income countries are under-resourced and ill-equipped to provide the timely, granular, and policy-relevant data needed for sound decision-making. Traditional surveys, which are often cross-sectional, infrequent, and costly, struggle to keep up with the blistering pace of economic and social change.

As data become more essential than ever, it’s time to consider a bold question: What if the private sector became not only a user of data, but also its investor, builder, and partner? The statistical systems we need—real-time, digital-first, interoperable—demand the kind of capital intensity, risk appetite, and innovation capacity that often only the private sector can provide.

The private sector increasingly has the tools, capital, and incentives to build and operate the systems that generate data. Whether through cloud-based platforms, artificial intelligence (AI)-driven analytics or satellite infrastructure, private sector entities are at the frontier of the technologies that can revolutionize development data. 

Partnering with the private sector on data will not only improve transparency and timeliness, but it will also unlock new labor markets, boost demand for skilled jobs, and allow firms to design services aligned with actual needs. When we build outcome-focused partnerships, we create feedback loops that benefit both policy and profit.

Data is mission critical

Strong national data systems are not just a public good, they are a market good. Reliable, disaggregated, and up-to-date data is mission critical for companies expanding into frontier markets, investing in resilient supply chains or designing inclusive financial services.

The business case is clear: Companies can unlock new markets, design better-targeted products, and lower operational and compliance costs in data-rich environments. This is especially true in developing economies, where uncertainty is high and reach depends on hyper-local understanding.

The cost of poor data is steep. A study by the Overseas Development Institute estimated that data gaps cost African economies up to 2 percent of gross domestic product annually. For the private sector, this translates into higher due diligence costs, greater regulatory exposure, and longer time-to-market cycles.

Different and better results 

The prevailing model of national data systems rely heavily on legacy survey instruments such as household surveys and censuses, which are delivered every five to 10 years with data release lags of 12 to 24 months. This leaves governments and investors operating with outdated maps and critical data vacuums. New, alternative data systems should build on these legacy systems to produce the data urgently needed to more efficiently face today’s development challenges. 

The World Bank Group is helping countries to modernize national statistical strategies, upgrade information and communication technology infrastructure, and build AI-ready regulatory environments. Our operational toolkit is supporting results-based financing, blended platforms to co-finance modernization, data-as-a-service models with contributions from the private sector, and capacity building. But we can’t do it alone. We need a new model where the private sector is a trusted, incentivized, and accountable partner in delivering public-good data. 

Better data systems must be modular, real-time, and user centered. That means moving from point-in-time data capture to continuous and dynamic data streams, from siloed databases to interoperable platforms, and from analog methods to digital-first, cloud-based infrastructure.

This transformation will be capital intensive, fast moving, and deeply reliant on technological expertise—traits not typically associated with bureaucratically constrained public agencies. But these are hallmarks of high-performing private firms. Public-private data partnerships should leverage comparative advantages: government oversight and legitimacy combined with private sector speed, capital, and innovation.

There are already a number of innovative examples of how private sector-built technology can deliver fast, granular, and actionable data. In Indonesia, for example, statistical agencies are using Bayesian small area estimation and AI-assisted imputation to derive district-level poverty maps from satellite imagery combined with census microdata. Colombia is using geospatial analytics built on Google Earth Engine to track land degradation and inform subsidy allocations in agriculture. During COVID-19, Togo’s Novissi program leveraged machine learning on call detail records and satellite-derived poverty proxies to deliver emergency cash transfers.

Building A new compact for data and jobs

What’s really needed to jumpstart private-sector investment is a new Data Compact for development and jobs: public institutions and private entities co-investing in national data systems. Key pillars should include:

1. Statistical co-investment funds: Structured vehicles where venture capital, foundations, and development banks jointly fund core data infrastructure.

2. Data quality standards: Strengthening data quality standards to promote trustworthy data and AI-readiness. 

3. Data innovation accelerators: Embedded units within statistical offices to co-create tools with startups, academic labs, and industry partners.

4. Real-time data platforms: Open application programming interfaces and cloud-native systems that allow continuous integration of diverse data streams.

5. Governance for shared use: Agreements on data privacy, interoperability, and accountability to ensure public trust in privately enabled systems.

6. Outcome-based procurement: Pay-for-results models where firms are compensated based on improvements in data quality, accessibility, and impact.

While governments remain essential stewards of official statistics, the future of an integrated data system will be co-built, co-governed, and co-financed by private sector players—much like energy grids or telecom networks. Now is the time to embrace these changes to unleash the power of the private sector and fuel a sea-shift in how data can be used to improve lives across the world.