The US economy is changing faster than public data systems can keep up.

That’s because these systems were built for a very different economy: one with slower-moving production cycles and clearer categories of economic activity. In contrast, today’s economy is more hyperlocal and more uneven across people and places. At the same time, staffing reductions have led to delays in data releases and low response rates on national surveys like the decennial census.

These challenges have made it more difficult for federal statistical infrastructure—typically a backbone for economic data—to provide timely indicators. In particular, it’s a serious challenge for state and local policymakers, who for decades have relied on federal datasets for essential insights into the job market, affordability, and financial security in their communities. 

Data collected by private companies could help fill this gap. Banks, supermarkets, online job boards, and other companies are already collecting consumer data that can surface early warning signs of financial instability weeks or months before they’re captured in official statistics.

At a recent Urban Institute convening, representatives from the private sector explored which warning signs are captured in private data and what data are most useful to policymakers. As part of the discussion, we examined public data use and private data availability to develop a set of hypothetical personas that highlight where current public data fall short and where private data can help, all while protecting privacy.

Below we explore three hypothetical examples of how private sector insights could help local policymakers make more timely and effective economic policy.

Transaction data captures a father’s tightening household budget

James is a young father living in Columbus, Ohio, who works as a sales representative. With his in-office work requirement, James purchases lunch around his downtown office every day. Based on Consumer Price Index data from the Bureau of Labor Statistics (BLS) for the Midwest region and the BLS Consumer Expenditure Quarterly Interview Survey from the last quarter of 2025, we might assume James’ finances are stable, with price pressures on food easing because James is stably employed.

But his transaction and budgeting data, similar to many other workers, tell a different story. In late 2025, James used to buy a $9 lunch near his office every day. Since the beginning of 2026, his spending has decreased, and he now goes to a grocery store to buy a $3 sandwich.

A credit card company might infer from changes in transaction data for people like James that household budgets are tightening, but these microadjustments rarely register in federal data, which aren’t collected daily like consumer transaction data.

More-timely data on consumer spending habits could help policymakers target interventions to address problems with workers’ daily finances and food affordability. These data could also help Columbus’s economic development office identify weakening demand in food service corridors or rising pressure on small businesses well before sales tax receipts or payroll data reflect it.

A young renter’s partial payments reflect her city’s increasing housing cost burden

Jade is a 23-year-old renter living in Phoenix, Arizona. Federal surveys would not classify her as housing cost burdened; her rent-to-income ratio sat just below 30 percent in 2025.

But recently, the platform she uses to pay her rent noticed something public data could not. After years of paying her rent on time, Jade’s payments started arriving later each month. Then, she started making partial payments. She also redeemed a small rent reward balance (accumulated through credit card or other cash-back reward programs) she had never touched before.

Using these aggregated platform data, policymakers could’ve spotted the increasing housing cost burden in Jade’s zip code and had time to intervene, well before eviction filings started to rise. This early visibility and granularity doesn’t exist in datasets like the US Department of Housing and Urban Development’s Comprehensive Housing Affordability Strategy data and is captured less frequently on the American Community Survey.

Private-sector insights help the head of a workforce board get ahead of labor market changes

Marisol runs a local workforce board in El Paso, Texas. Her job is to spot labor market shifts early enough to adjust the city’s training programs, support dislocated workers, and advise employers.

In fall 2025, El Paso’s regional unemployment rate looked stable in BLS data, and national job openings data in the Job Openings and Labor Turnover Survey showed no obvious signs of softening labor market demand.

But job posting data collected directly by online job boards revealed a more nuanced picture: Postings for warehouse and logistics roles dropped in recent months, and the average length of time it took to fill a job doubled. At the same time, aggregated scheduling and ADP payroll data showed consecutive dips in hospitality hours worked.

These private-sector indicators suggested job availability, hours worked, and quality were deteriorating before job losses appeared. With this information, Marisol could’ve prompted her team to expand outreach weeks earlier than they otherwise would have.

Moving toward shared insights

Private sector data can’t replace public statistics, which remain essential for providing consistent, representative economic benchmarks. But they often offer something public data cannot: earlier visibility into changing conditions on the ground. When used thoughtfully, these signals can help local leaders identify emerging risks, respond more quickly to shifts in affordability or labor markets, and better target resources to the communities that need them most.

Policymakers don’t need to build entirely new data systems to incorporate private data into their decisionmaking. Instead, they can broaden the range of insights they consider by engaging new partners, exploring new indicators, and asking where earlier signals might already exist.

At a moment when the economy is evolving quickly and the data landscape is shifting with it, better integrating both public and private data will be critical for identifying key insights with enough time to act. Businesses with frequent trend data also may find it useful to share insights with policymakers so they can ensure communities have the policies and conditions that support personal well-being and thriving.