Our ADP Model Will Unlock The Power Of Data To Improve Lives

Context: The United Nations Development Program recently lauded India’s Aspirational Districts Programme (ADP) for significant improvements in health, nutrition and education outcomes. The programme could count on the support of a new strategy to improve data-driven governance.

The ADP model – Result based data governance structure

• Data is at the very foundation of the ADP: Data is collected at the most granular levels and reported at a high frequency. Every month, districts are ranked based on the progress they have made on key indicators of health, education, agriculture, basic infrastructure, financial inclusion and skills development.
• Transparency: A public dashboard transparently display district ranks.
• Accountability standards: Third-party household surveys to get independent district-level data on the monitored sectoral outcomes.
• Leveraging technology: Automated systems for data quality checking and worked closely with districts to address the issues that these systems detected.
• Cost-effective: There is little or no cost associated with administrative data since departments already collect such data independent of the ADP to administer their programmes effectively.
• Opens up a realm of possibilities for policymakers: By better understanding and identification of areas of intervention, allowing for an accurate assessment of effectiveness and impact of interventions undertaken.

Way forward: ADP has provided a scalable template for harnessing the speed, granularity and affordability of administrative data while strengthening data quality

• Improving existing scheme-supervision processes: Opportunity to address data quality problems by various strategies such as -
• Randomized selection of check-visits to cover all types of geographies and beneficiaries within a district.
• Evolve a standardized verification protocol, ensuring consistency across districts, and provide a mobile application to help supervisors efficiently document useful photo, audio and GPS data.
• Frequent third-party back-checking of administrative data, where independent surveyors will verify a sub-sample of the beneficiaries to ascertain whether services are actually received.
• Tap the power of automation: To check large volumes of data efficiently, regularly, and with minimal human intervention. 
• Build an open-source widget that runs core quality checks and delivers user-friendly feedback reports for district authorities.

Conclusion: Results-based governance ultimately aims to improve government service delivery by giving decision-makers the tools and incentives to craft appropriate policies and programmes. To this end, the data quality strategy for ADP can be adopted as a template for unlocking the power of administrative data.