As state and local governments continue to lead the coronavirus response efforts, they are being tasked with making critical policy decisions and coordinating across overburdened agencies. One of the key tools these governments can leverage to strengthen their efforts is administrative data — data already collected for operational purposes.

Here are three ways this data can help governments respond effectively to the pandemic's economic impact on Americans and their families:

Improve situational awareness: Administrative data provides critical insights into how the crisis is affecting demand for services. As hospitals face a surge of patients, social service agencies and contract providers are experiencing a similar surge of requests for economic assistance. When indicators such as monthly unemployment reports come too slowly, governments can rely on finer-grained information, such as the volume of requests for assistance programs and corresponding wait times, to understand where to deploy services.

Understanding what is going on in one department is relatively easy, but understanding the situation across departments and agencies is more difficult. For jurisdictions that already have integrated data systems, the ability to link data across departments and agencies will allow for a more complete picture and response. Integrating data from different agencies, 911 calls, hospitals and even non-governmental resources like Google searches for unemployment benefits can help leaders understand the full scope of the pandemic's impact.

Identify populations to target for assistance: Benefits like the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF) and unemployment insurance are often left unclaimed by people who qualify. As our colleagues Amy Finkelstein and Matthew Notowidigdo wrote recently in Governing, research shows that simply alerting people to their eligibility increases take-up. And to address confusion about and recent changes to eligibility, governments can do some of the work of identifying potentially eligible people and connecting them to programs.

Many governments already do this. For example, in a randomized evaluation, Virginia's Department of Social Services and researchers are studying outreach methods to encourage individuals to claim the federal Earned Income Tax Credit (EITC). Virginia identifies potentially eligible individuals from those enrolled in other social services who do not claim the EITC. Similar data is used by the Benefits Data Trust, in partnership with states, to identify potentially eligible SNAP beneficiaries.

The pandemic is not only causing a loss in wages, but is generating additional gaps in social service provision. School closures, for example, are disrupting vital services like the free or reduced-price school lunches that some 30 million students depend on. Many schools have moved quickly to set up pickups or deliveries along bus routes, but meals may be left unclaimed. Real-time geographic and program data can shed light on where these substitutes are working and where resources could be better redeployed.

Facilitate benefit enrollment and delivery: Auto-filling applications with data used to determine eligibility can lower the burden not only on applicants but also on already overstretched government agencies. Individuals can even be auto-enrolled in programs on the basis of existing data, particularly if it shows that they are experiencing gaps in service provision due to disruptions like school closures.

States already have experience doing this through direct certification for food assistance. Under this system, states use existing data from other programs, such as SNAP or TANF, to provide free meals to eligible children without the families having to fill out another application. And new programs explicitly allow for this: The federal Families First Coronavirus Response Act, for example, allows for automatically enrolling children receiving school lunches into supplemental SNAP benefits.

State and local governments can also use data across programs to get stimulus payments to those in need. Traditional methods of sending these payments, such as mailed checks, will miss some of the most vulnerable, who may not have filed tax returns that determine eligibility or are unbanked and unable to cash a check. Existing data can identify individuals whose payments could be added to their electronic benefits cards.

Government service provision is often fragmented, with programs like unemployment insurance, SNAP, TANF and school meals run by different agencies. But as the combined health and economic nature of this crisis makes clear, our response — and the data we use to inform it — cannot be siloed. To begin data integration, governments can connect with programs like the IDEA Initiative, run by our Abdul Latif Jameel Poverty Action Lab. Other organizations, like Actionable Intelligence for Social Policy and US Digital Response, also have launched calls to connect governments and data analysts.

Investment in data infrastructure is not a quick process, but it will pay dividends in allowing agencies to make decisions informed by evidence, in this crisis and the next, and to learn from these actions to continuously improve their responses.

Governing's opinion columns reflect the views of their authors and not necessarily those of Governing editors or management.