When a drought hit Bundelkhand in the late 2010s, it was not government relief, but timely MGNREGA wages that kept many families from migrating. Such stories remind us that rural livelihoods are not just about income—they are about resilience. With two of India’s flagship programs—MGNREGA and NRLM—touching over 100 million rural lives, understanding their true impact requires going beyond counting outputs. This is where evaluations become indispensable. Government programs such as the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) and the National Rural Livelihoods Mission (NRLM) aspire to play their part in building a robust rural economy that guarantees payment for work and builds productive assets as well as empowerment for women. However, there is more to consider than the program’s official indicators, such as, how many jobs were created, how many loans were disbursed? Are these programs increasing the resilience among rural people? Are they reaching the most vulnerable? When we evaluate whether they have an impact, we must go beyond counting outputs to ask whether lives have changed.
Understanding Livelihood Programs: MGNREGA and NRLM
MGNREGA, which commenced in 2006, entitles unskilled rural workers to work for 100 days each year with the aim of creating public assets like roads and irrigation ponds. The program has a legal obligation to pay wages for work completed by unskilled rural workers. Hence, this provides a permanent record of completed work, which must be paid to the worker directly into their bank account. NRLM (started in 2011) seeks to mobilize women into self-help groups (SHGs). NRLM also capacitates these SHGs to access credit, and it seeks to utilize entrepreneurship through women-led SHGs. By 2023, NRLM had mobilized 90 million households, with SHGs generating billions in collective savings and credit mobilization Both are large-scale programs, but they take two different pathways to achieve the goal. One provides immediate economic income, while the other seeks to build women’s agency over a longer period by providing in-depth skills to women’s enterprise.
Why Evaluation Matters
Tracking the number of jobs created or SHGs formed offers only a surface-level view of development outcomes. Evaluations delve deeper, uncovering not just what changes, but why and for whom. For instance, while MGNREGA wages aim to reduce rural indebtedness, delays in payments can erode community trust in government programs. Such delays signal institutional inefficiencies, reinforcing skepticism, especially among marginalized groups that rely on these earnings for survival. Similarly, poorly trained SHGs under NRLM are not inherently transformative as their success hinges on training quality, local market access, and intra-household dynamics. Women from Dalit or Adivasi communities, for example, often face layered barriers like limited mobility, lower literacy, and entrenched social norms and caste-based prejudice, which shape how and whether they can leverage SHG platforms to influence household or community decisions.
Real-time evaluations have played a pivotal role in reshaping SHG capacity-building efforts to better respond to local realities. In Tamil Nadu, NRLM uses Socio-Economic and Caste Census (SECC) data combined with community-led wealth ranking and social mapping exercises to identify target households. This dual approach ensures marginalized groups (e.g., SC/ST communities, women-headed households) are prioritized. By integrating hard data with lived experiences, these feedback loops transform evaluation from a retrospective exercise into a tool for continuous course correction.
Choosing the Right Evaluation for the Right Question
Not all evaluations are created equal. Each type—formative, process, outcome, and impact—answers a different kind of question and serves a specific stage of a program’s life cycle. Formative evaluations are most useful during the design phase, helping fine-tune interventions before full-scale implementation. Process evaluations assess how well a program is being delivered, often surfacing operational bottlenecks like delayed wage payments under MGNREGA. Outcome evaluations focus on behavioural and economic shifts—such as whether NRLM’s SHGs have increased women’s financial autonomy or improved household nutrition. Finally, impact evaluations explore long-term systemic changes, like reduced poverty cycles or strengthened local governance structures. Incorporating these frameworks ensures that evaluation is not just about accountability, but also about learning and adaptation across different program stages.
Evaluating Impact: What to Measure and How
Impact isn’t just a measure of income. It’s about whether a mother can send her children to school, or a farmer can endure a drought, or a woman can invest in her own business. The key measures are changes to food security, levels of debt, and levels of women at the panchayat level. Combining methods is most effective. Surveys can quantify changes to income but focus groups can tell us about how the MGNREGA wages in Gujarat’s drought-prone villages prevented distress migration. Impact evaluations by independent evaluators also added rigor and objectivity; like the NRLM SHGs evaluation of 5,000 groups in 2020, which showed women experienced a 300% increase in savings in states like Bihar and Odisha. Long-term tracking is also important; the five-year longitudinal study in Jind, Haryana showed that MGNREGA’s roads enabled better access to markets for farmers, raising their crop sales by 40%.
Learnings from the Field
MGNREGA’s successes are tangible. In Jind, Haryana created jobs during farming off-seasons and built durable assets like village roads. Across semi-arid regions, it provided a lifeline during droughts, cutting migration by 30%. But persistent issues like wage delays in Madhya Pradesh and uneven implementation in Maharashtra highlight systemic flaws. NRLM, meanwhile, has reshaped gender dynamics. In Tamil Nadu, SHGs partnered with local governments to design climate-resilient farms, while in Rajasthan, women used loans to start poultry businesses. Yet inconsistent SHG quality—some groups lack training—limits progress.
Scaling Up Sustainable Models: Role of Evaluation
Evaluations spotlight what works. Tamil Nadu’s climate adaptation model, where SHGs integrated drought-resistant crops and water harvesting, succeeded because local leaders owned the process. Similarly, Madhya Pradesh’s shift to millet farming under NRLM emerged from community feedback. But scaling such models requires flexibility—what works in coastal Tamil Nadu (mangroves to combat salinity) may not fit Uttarakhand’s hills. Real-time evaluations help tweak approaches; when wage delays plagued MGNREGA in Gujarat, faster payment systems were piloted. Sustainability hinges on trusting communities to lead.
As India’s rural landscape evolves under the weight of climate disruptions and demographic shifts, livelihood programs like MGNREGA and NRLM must adapt in both design and delivery. Evaluations serve not just to track past success but to inform future direction. The imperative now is clear: institutionalize rigorous, participatory, and context-sensitive evaluations. Only then can we ensure that every rupee spent on livelihoods does not just build assets—but builds futures.
