By Aarushi Gupta, Dvara Research
The report has been submitted to Azim Premji University under their COVID-19 Research Funding Programme 2020 and will be released publicly in March 2021.
The outbreak of the COVID-19 pandemic in India has had far-reaching socio-economic implications in the form of national lockdowns, consequent suspension of economic activity, and reversal of internal migration, to name a few. Relief packages by governments included ex-gratia food and cash entitlements delivered using the Direct Benefit Transfer (DBT) and the Public Distribution System (PDS) infrastructure. We also saw many returning migrant workers from cities turn towards the Mahatma Gandhi National Rural Employment Guarantee (MGNREGA) programme to seek temporary work. The pandemic has underscored the necessity of building safety nets. However, it has also brought to surface the various gaps that have continued to impede the delivery of many welfare interventions.
This post summarises the research findings from our recently concluded project on exclusion and grievance redress that was undertaken in collaboration with Gram Vaani, University of Montreal, and Tika Vaani. The project brought together the organisations’ research efforts over the last one year, covering emerging issues in welfare as the pandemic unfolded. The research plan encompassed an analysis of the typology of challenges faced by citizens in accessing their entitlements and the resolution pathways that were used by Gram Vaani volunteers to assist such citizens. We covered beneficiaries across seven DBT schemes, MGNREGA, PDS, and Employer Provident Fund (EPF) in the states of Bihar, Uttar Pradesh, Madhya Pradesh, and Tamil Nadu. The objective of this exercise was to understand citizen grievances and build a tool that would help aggregate, analyse, and act on welfare-related grievances voiced by citizens.
Figure 1: The Gram Vaani Model
Understanding Exclusionary Factors in Social Welfare
Using data from Gram Vaani’s Interactive Voice Response (IVR) platform (see Figure 1) and deep-dive interviews of beneficiaries selected through critical case sampling, we documented the various scheme-related challenges citizens faced during the period of March-November 2020. We analysed a total of 1017 citizen complaints across the aforesaid schemes; DBT (261), MGNREGA (96), PDS (542), and EPF (118). To understand the typology of challenges citizens faced in accessing welfare benefits (including those announced in the wake of the outbreak), we developed a framework that maps exclusionary factors under four key stages of welfare interventions, viz., targeting, enrolment, backend processing of benefit, and lastly, disbursement. The key insights that have emerged from processing the IVR data using this exclusion framework as a guiding tool have expanded our understanding of welfare access and the existing gaps therein. This research contributes to the emerging body of evidence on exclusion of citizens from availing social protection benefits. We summarise them below:
The highest incidence of exclusion in DBT schemes occurs during the backend processing stage. A variety of reasons (Aadhaar linkage, spelling error, blocked accounts) can lead to unsuccessful crediting of beneficiary accounts. About 55% of the total DBT-related complaints from the period March-June 2020 (the stipulated period for transfers of Pradhan Mantri Garib Kalyan Yojana (PMGKY) DBT entitlements) belonged to this category of issues.
In the context of MGNREGA, we found that 66% of all complaints pertained to either problems with work allocation or wage payment processing. About 77% of all complaints falling in the work allocation category are instances of complete exclusion, i.e., people not having been allotted any work at all. The scale of the issue has underscored that the efficacy of the scheme is seriously compromised, even while there is substantial demand for it. A similar percentage of those calling to report wage issues stated either not having been paid at all or not having received the full wage due to them.
Analysis of PDS complaints highlighted that many citizens who needed government support were excluded from in-kind transfers under PMGKY simply by virtue of not having a ration card, given the relief package’s eligibility criteria. 60% of all PMGKY (PDS) complaints fall under this category. Another interesting aspect that emerged from our analysis is the prevalence of discretionary denial of ration and quantity fraudby fair price shop officers (FPSO). Under these categories, people are denied their ration – sent away empty-handed or with less than their entitled quota. Further, they are not provided with a clear or documented reason for the shortfall. 93% of all complaints pertaining to ration collection highlighted such issues of non-compliance on the part of FPSOs.
Approximately 80% of all EPF complaints represented issues that originate from the enrolment stage of the scheme. Of these, most complaints pertained to incomplete employee records or inconsistencies in the spelling of names, dates of birth, dates of employment, etc. Lack of co-operation and absence of timely assistance by employers were found to be key reasons for these issues.
Resolving Grievances in Social Welfare
In the second stage of our research project, we studied the various modalities through which volunteers assist citizens. Through a detailed qualitative analysis of IVR recordings and volunteer interviews, we were able to create an Impact Framework (analogous to the aforementioned Exclusion Framework) that categorised volunteer actions under three broad heads (see Figure 2): Information Provision to Citizen (A0), Issue Escalation to Higher Officials (A1), and Direct Assistance by Volunteer(A2). The last action pathway can be further broken down into two sub-categories, Resolution on Citizen Behalf (A2a), under which volunteers fill forms/file complaints on citizen’s behalf, and Interaction with Access Point (A2b), under which volunteers informally negotiate with local access points to help citizens. It must be noted that the action pathways used by volunteers differ from one stage of exclusion to another for each scheme. Further, they may not always be successful, resulting in volunteers using a trial and error method to resolve grievances. These action pathways have been represented in the form of a flowchart. Figure 2 provides a prototype of the same for the PM Kisan scheme.
Figure 2: Flowchart of Action Pathways (PM Kisan)
For PM Kisan enrolment issues, volunteers prioritise A2b, which entails interaction with local access points such as the village registrar responsible for the enrolment process. In case this fails (either due to lack of co-operation or official capacity required), volunteers escalate (A1) the complaints to the higher tiers of scheme administration at the block or district-level. For payment issues in the scheme, volunteers first try to diagnose the issue through the online portal available. In case the portal provides them sufficient information, they proceed to solve the issue by first editing the details online (if applicable) (A2a) or by helping the beneficiary update their Know Your Customer (KYC) details (A2b). In case these fail, or the portal does not provide them with enough information, issue escalation or A1 is resorted to. For cash withdrawal issues, volunteers prioritise A2b or direct interaction with the cash-out point operator. In case the issue persists, A1 is employed. It must be noted that in many cases, A2b also involves warnings of issue escalation (A1) being given to local access points.
The broad insights that we obtained from analysing the aforesaid action pathways across all schemes have been summarised below:
Issue Escalation to officials at the block or district-level is the most prominent action pathway used by volunteers across schemes for a variety of citizen grievances. This is done by forwarding the voice recording of the grievance directly through the IVR to the appropriate officials, or via WhatsApp or Facebook to their official account. Our analysis shows that this action pathway is primarily used by volunteers when any one or more of the following contexts characterises citizen complaints:
The delivery mechanism of the scheme follows a top-down structure in which most crucial functions are not in the jurisdiction of local-level officials (such as those at the Panchayat-level), who, if not more effective, are usually more accessible to ordinary citizens. This necessitates that the complaint is escalated to officials at higher tiers who have the official capacity to address grievances.
In schemes which may follow a more decentralised implementation mechanism (such as the PDS) but there is a prevalence of petty corruption or lack of co-operation on the part of local-level officials.
There are inadequate or cumbersome official grievance redress mechanisms in place that make issue escalation either a more effective pathway towards quicker redressal or a necessary mechanism to gain more information.
All other action pathways have proven to be unsuccessful.
Local Advocacy by writing letters to the administration is also used as an Issue Escalation pathway for problems that are faced by many citizens in a community. Instead of taking an approach of addressing individual grievances, this method often helped initiate system-wide steps by the local administration to address the problems. For instance, routinisation of the Employment Guarantee Day under MGNREGA in some of the village panchayats.
Resolution on Citizen Behalf as an action pathway has been prominent for schemes (and certain stages within the scheme) that have some front-end mechanisms in place for complaint filing, application tracking, data correction, etc., which citizens themselves are not able to navigate. This occurs in cases where the processes are complex, or resolution requires access to online portals, which citizens are not able to access or use.
Interaction with Access Point as an action pathway has been prominent for cases where there is a lack of co-operation/non-compliant behaviour on the part of local-level officials, individual banking agents, or operators of Fair Price Shops. Such an interaction may sometimes also entail warnings by volunteers, citing possibility of issue escalation in case the said local functionary does not comply/address the grievance.
The key observation that emerges from our research is that access to social entitlements is impeded by many last-mile problems that citizens are not able to navigate on their own. In its current form, last-mile delivery architecture lacks citizen-centricity. Citizens need assistance from CSOs and social workers who are well-versed with the procedures for various government schemes and can guide them or act on their behalf for smoother citizen-state interactions. This could take the form of escalating issues to appropriate government officials who have the authority to solve problems, or report to senior officials about violations by lower-ranking officials, or assist the citizens in filling out appropriate forms, or in some cases even provide actionable information to the citizens. The introduction of technology is not a solution in itself, and in fact, the centralisation of processes that it typically initiates often makes it harder for citizens to deal with the system, disempowering the very stakeholder that it was meant to support. The resounding conclusion from our research is that until state-citizen interfaces in welfare schemes are redesigned to become more citizen-centric (and thus, more effective), CSOs and social workers will remain a critical cog in the last-mile . In addition to such improvements in the citizen-interface architecture, policy efforts must also be directed towards improving transparency and accountability in the system. Creation of public repositories that curate citizen complaints specific to welfare schemes along with the resolution pathway suggested/deployed by government officials. The creation of such repositories at a local-level , serves a two-fold purpose. First, they can help stakeholders learn about the functioning of a system that has so far been characterised with opaqueness. Second, documentation of errors and their resolution pathways will help policymakers make social protection mechanisms work better over iterations.
 Ministry of Finance. (2020). Finance Minister announces Rs 1.70 Lakh Crore relief package under Pradhan Mantri Garib Kalyan Yojana for the poor to help them fight the battle against Corona Virus. Retrieved from https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1608345
 MGNREGA in need. (2021). Retrieved 10 February 2021, from https://indianexpress.com/article/opinion/editorials/mgnrega-demand-rural-labours-migrant-workers-coronavirus-6441371/
 COVID-19: Analysis of Impact and Relief Measures, https://cse.azimpremjiuniversity.edu.in/covid19-analysis-of-impact-and-relief-measures/, Accessed September 5th 2020: A compilation of several surveys, including some specifically on access to relief measures – APU survey of 5,000 households, Gram Vaani survey of 2,400 people, Dalberg survey of 47,000 households
 These included Pradhan Mantri Kisan Samman Nidhi (PM-KISAN), Pradhan Mantri Ujjwala Yojana (PMUY), Pensions, Jan Dhan Yojana, cash transfers under the Pradhan Mantri Garib Kalyan Yojana, Welfare Board schemes (Tamil Nadu), and some other state-specific relief transfers.
 Social Protection Initiative. (2020). Falling through the Cracks: Case Studies in Exclusion from Social Protection. Retrieved 7 January 2021, from https://www.dvara.com/research/social-protection-initiative/falling-through-the-cracks-case-studies-in-exclusion-from-social-protection/
 Gupta, A. (2021). Proposing a Framework to Document Exclusion in Direct Benefit Transfers. Retrieved 18 February 2021, from https://www.dvara.com/blog/2021/02/11/proposing-a-framework-to-document-exclusion-in-direct-benefit-transfers/
 COVID-19: Analysis of Impact and Relief Measures, https://cse.azimpremjiuniversity.edu.in/covid19-analysis-of-impact-and-relief-measures/, Accessed September 5th 2020: A compilation of several surveys, including some specifically on access to relief measures – Azim Premji University survey of 5,000 households, Gram Vaani survey of 2,400 people, Dalberg survey of 47,000 households.