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 officials on [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 AD

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.