India could use quick inputs from citizens for better public policy responses

What persists as a gap is the ability to understand dynamic situations in need of immediate policy responses. Frequent citizen inputs and data gathering from sub-populations that are typically hard to reach through traditional methods could change that.

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The way forward should involve an integrated approach in which the strengths of both administrative data and traditional surveys are leveraged to understand socioeconomic realities in a holistic way, with ‘rapid citizen data’—collected directly from people via quick field surveys, phone calls, etc—offering a picture of developing situations. The Artha Centre for Rapid Insights has tested use-cases where such data can be helpful for responsive policy.

First, in situations that require an immediate policy response—like heatwaves—administrative data often falls short. While the meteorological department can track temperature spikes and the health department can report hospital admissions, these don’t capture how people are coping on the ground. Are outdoor workers shifting their hours? Do low-income households have access to cooling? Rapid phone surveys in the summer have shown that it is possible to collect such information quickly at scale. When paired with geospatial data, it helps understand the link between unplanned urbanization and heat vulnerability—insights that can support health campaigns and urban planning.

Second, in the context of dynamic social or economic change, traditional surveys often lag. Internal migration is a case in point. While the pandemic highlighted its scale, seasonal and circular migration is an ongoing and evolving pattern. Rapid field surveys have demonstrated how migration affects household labour patterns, particularly for women. In one such effort across rural districts in north and central India, we were able to capture variations in paid and unpaid work based on migration status and household wealth—data that can inform timely decisions on employment support and welfare targeting.

Third, rapid surveys can help reach populations that are often missed by traditional sampling methods—such as daily commuters. Again, through geospatial analysis combined with short phone surveys, we have been able to identify gaps in public transport access in areas that are urban in character but not officially recognized as such. The findings revealed that a large proportion of residents in these areas rely on private transport and face longer commutes, underscoring the need for better urban planning and public services.

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While there is immense value in investing in such rapid citizen data, this cannot be the sole input for such decisions. The value lies in triangulating it with data from administrative processes and traditional surveys.

Collecting rapid citizen data in a way that is both reliable and actionable requires careful design. One key lesson we’ve learnt is that good sampling is possible even on short timelines. For instance, publicly available voter lists—organized by polling booths—that include basic demographic details of age and gender can be used to draw random samples at the constituency level. Where precise stratified sampling isn’t feasible, especially in interactive-voice-response (IVR) surveys, statistical techniques like multilevel regression with post-stratification can help correct for sampling biases. Anchoring rapid surveys in reference data-sets such as the Census, National Sample Survey and National Family Health Survey makes it possible to generate reasonable estimates for specific geographies or population groups.

Ensuring data quality is important. Simple checks like re-calling a small sample of respondents, reviewing outlier responses or examining the length of calls can improve confidence in the results. Triangulating survey data with other sources also enhances reliability. IVR surveys are a cost-effective way of collecting data at scale, especially from populations without smartphones. They can generate wide coverage, but their data must be cleaned up and modelled carefully to ensure accuracy.

When several sources align, decision-makers can act with confidence. If these sources diverge, it highlights the need for further investigation.

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So what can the government do? One, routinely compare findings from various sources to confirm trends or detect divergences. Two, collaborate with universities, research institutes and tech firms to pilot and scale high-frequency surveys. Three, create accessible data repositories where official statistics can be viewed alongside citizen-generated data (ensuring independent verification and supporting continued research).

Of course, any collection of citizen data, especially through mobile or digital platforms, must include safeguards for privacy, consent and transparency. Trust is paramount. If people fear any misuse of the information they part with, their willingness to participate and the quality of findings will suffer.

The authors are, respectively, director and principal at Artha Global’s Centre for Rapid Insights