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Project

Transforming how the Indian government improves people’s lives

3 May 2021

NITI Aayog developed the Aspirational Districts Program (ADP) and hired IDinsight to measure, monitor, and rank districts according to the performance of their social programs. The program reaches 250 million people living in 100+ of India’s poorest districts.

Conducting a survey in the presence of “nudges” to promote latrine use. ©IDinsight/ Siobhan McDonough

250 million

The program reached 250 million people living in 100+ of India’s poorest districts.

From 73% to 94%

Increase in pregnant women registered into the health system

From 66% to 82%

Increase in babies delivered in health facilities

key takeaways

Decision-maker’s challenge

India was falling behind its neighbors in key social outcomes. Government leaders wanted to transform its social policies, especially those helping people living in extreme poverty. To upend the system, government leaders developed the Aspirational Districts Program (ADP) to facilitate three key changes:

  1. Shift from measuring budgets and inputs to measuring outcomes like maternal and child health indicators.
  2. Move away from top-down policies to those that support local leaders to experiment and innovate using evidence-based approaches.1
  3. Collect and analyze reliable, high-quality data on socio-economic outcomes to measure progress, identify challenges, and hold local leaders accountable for reaching their goals.

NITI Aayog, the think tank/policy innovation arm of the Indian government, launched the Aspirational Districts Program (ADP) in January 2018 to improve the socio-economic outcomes of 100+ of India’s poorest districts in five years.2

NITI Aayog hired IDinsight with support from the Bill & Melinda Gates Foundation to measure, monitor, and rank districts according to the performance of their social programs. Existing sources of data were potentially biased as they are self-reported, or were not available via admin data.3

Impact opportunity

The program reached 250 million people living in 100+ of India’s poorest districts.

Our approach

  1. Measurement: Our team collected data from ~ 27,000 households and provided the measurement strategy for the full 100+ districts.. We tracked socioeconomic outcomes at the district level to help inform district-wide ranking for the ADP. This data helps facilitate healthy competition between states and districts to achieve outcomes (not only inputs).
  2. Learning: diagnosing, piloting, and helping scale innovative and/or proven interventions to improve outcomes in four key sectors: Agriculture, Financial Services for the Poor, Health & Nutrition, and Sanitation. The goal is to help optimize government flagship programs via evidence-driven learning in the Aspirational Districts and beyond.
    1. Agriculture: The IDinsight team conducted a diagnostic and process evaluation on NITI Aayog’s nation-wide Soil Health Card Scheme, which seeks to provide fertilizer application recommendations to farmers based on the specific nutrient deficiencies in their soil.
    2. Financial Inclusion: The IDinsight team identified operational and behavioral approaches to increase the uptake and use of financial products and services among the poor across 27 focus districts. The team also informed state financial inclusion policy.
    3. Health & Nutrition: The IDinsight team helped identify nutrition-related challenges primed for evidence-based decision-making. This included work with POSHAN Abhiyaan, a program to improve nutritional outcomes among children and pregnant mothers.
    4. Sanitation: The IDinsight team identified low-cost and easy-to-implement programs to increase and sustain people’s use of latrines across the country. This includes identifying behavioral constraints to latrine usage and testing potential approaches.
  3. Data on Demand: The IDinsight team deployed an innovative field-data infrastructure 
in the 27 NITI focus districts to provide high-quality, rapid, and regular field insights to leaders in a cost-effective manner.
  4. Capacity Building: The IDinsight team supported policymakers and policy implementers in India to collect, absorb, analyze, and use high-quality data to inform decision-making and monitor program performance.

The results

There were rapid improvements in key health outputs in the 27 Aspirational Districts for which IDinsight provided rapid survey data and analytical support.

  • An increase in pregnant women registered into the health system from 73% to 94% between R1 and R3.
  • An increase in babies delivered in health facilities – from 66% to 82% from R1 to R3.
  • An increase in babies who were treated for diarrheal disease via oral rehydration therapy and zinc – from 51% to 63% for ORS and 34% to 53% for zinc treatment.
  • An increase in children and pregnant and lactating women who reported receiving at least one round of nutritious food.4

 

  1. 1. Development policy has traditionally been input-oriented and prescriptive because high-quality, regular and granular data on socio-economic outcomes are simply not available. A results-based management approach is only tenable if this data vacuum is filled. This data vacuum also helps explain why policymaking is anecdote-driven rather than data-driven, and why last-mile implementation failures go largely unaddressed. (Source)
  2. 2. “Under this initiative, districts will be ranked quarterly based on their ability to improve socio-economic outcomes. The rankings will be used to empower and incentivize District Collectors (DCs) to innovate and improve. And DCs will get policy guidance using evidence-backed best practices and a platform to learn from each other’s successes.” https://www.business-standard.com/article/news-ians/aspirational-districts-initiative-a-breath-of-fresh-air-comment-118041100318_1.html
  3. 3. “The government’s administrative data is important, but cannot fully address this data gap. While administrative data is usually frequent (real-time dashboards) and granular (often up to village level), it suffers from biases because of employee self-reporting or other conflicts of interest. And while independent surveys like the National Family Health Survey have more reliable estimates, the data is available after long intervals and is usually only reported at the state level.” https://www.business-standard.com/article/news-ians/aspirational-districts-initiative-a-breath-of-fresh-air-comment-118041100318_1.html
  4. 4. There was an increase in the reported receipt of at least one round of take-home rations for both children aged 7-36 months (by 11 percentage points) and pregnant and lactating women (by 17 percentage points).