Context:

  • The Aspirational Districts Programme (ADP) is one of the largest experiments on outcomes-focused Governance in the world. Spread across 115 of India’s socio-economically challenged districts.
  • Initial evidence suggests that the ADP has already contributed towards improving lakhs of lives. If successful, the ADP can present a new template for governance. It is therefore critical to try and get it right.

What is Aspirational District Programme?

  • Launched in January 2018 by NITI Aayog, the ‘Transformation of Aspirational Districts’ programme aims to quickly and effectively transform some of the most underdeveloped districts of the country.
  • The broad contours of the programme are Convergence (of Central & State Schemes), Collaboration (of Central, State level ‘Prabhari’ Officers & District Collectors), and Competition among districts driven by a Mass Movement or a Jan Andolan.
  • With States as the main drivers, this program will focus on the strength of each district, identify low-hanging fruits for immediate improvement, measure progress, and rank districts.

Focus of the Programme:

  • To enable optimum utilization of their potential, this program focuses closely on improving people’s ability to participate fully in the burgeoning economy. Health & Nutrition, Education, Agriculture & Water Resources, Financial Inclusion & Skill Development, and Basic Infrastructure are this programme’s core areas of focus.
  • The ADP’s theory of change rests on three pillars: Competition, convergence, and collaboration.
  • Competition Fosters Accountability on district governments for final outcomes (instead of inputs) using high-quality data. Convergence creatively brings together the horizontal and vertical tiers of the government. Collaboration enables Impactful Partnerships between Government, Philanthropy and civil society.
  • Health outcomes in the mentored districts reveal significant improvements between the first and second third-party household surveys. While a deeper mixed-methods analysis is required to clearly understand what explains these results, we hypothesise the following four factors play a role.
  • One, pioneering state and district-level initiatives in both the ADP and non-ADP districts in areas prioritised under the programme.
  • Two, spurred by competition on outcomes, local governments target their efforts and improve programme Implementation and Design.
  • Three, the focus on outcomes enables local experimentation based on a firm appreciation of ground realities.
  • Four, partnerships between various philanthropic and civil society organisations with district governments augment local capacity.

Supplementary Efforts:

  • While the initial evidence on the ADP’s impact has been encouraging, there is always room for supplementing our efforts. “High-performing organisations are characterised by autonomy to front-level officialson [processes], combined with accountability for outcomes.” The ADP is built precisely on this mantra, and the district-ranking index can be improved further to fully reflect this.
  • A Simplified Ranking Index— with few but carefully chosen output and outcome measures — will more clearly signal national development targets, while providing autonomy to local governments.
  • High quality Administrative Data is critical to improve programme implementation and design at the local level.  Building each district’s internal capacity to produce reliable and actionable data, and promoting a culture of data use, can be made a priority for the ADP.

Conclusion:

  • ADP is a laboratory of various cutting-edge governance reforms. First and foremost, the programme has shifted focus away from inputs and budgets to outcomes, such as learning and malnutrition, at the highest echelons of the government.
  • It has also introduced non-financial incentives to encourage government officials to deliver results and actively encourages forging partnerships with philanthropies and civil society to create better impact using the same amount of budgetary spends.
  • The programme has also developed a lean data infrastructure that smartly exploits complementary strengths of administrative and survey data.
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