Frequently Asked Questions

Scope of the initiative

  • What is the motivation behind the State of Aadhaar initiative?

    The State of Aadhaar initiative was launched three years ago by Omidyar Network India and IDinsight to contribute to a data-driven discourse on Aadhaar. In the 2019 edition, anchored by Dalberg, we have created the world’s largest public, primary dataset on national digital ID. Our ambition is that policymakers, researchers and industry actors engage with our findings and use the data for their own research and decision making.

    State of Aadhaar 2019 is premised on the principle that the daily users of Aadhaar are best positioned to provide valuable feedback about their lived experience - and therefore practical adjustments needed to improve Aadhaar’s functioning. We aim to give a broad cross-section of Indian residents a voice in the national discourse on Aadhaar, in order to augment efforts to move towards a more effective digital identity for all residents of India who desire it.

  • Why did you only look at the user’s perspective on Aadhaar?

    There are of course many important perspectives on Aadhaar - legal, technological and others. We believe the success of Aadhaar will ultimately depend on how well the programme can learn from the experiences and concerns of those who use (or are unable to use) Aadhaar across a wide range of circumstances in their daily lives. Yet national household data has been thin on what Aadhaar has done (and not done) for the residents of India. In what ways has Aadhaar empowered or excluded them? To what extent do they trust and use the identification system? In which aspects is it serving them well or poorly—or not at all? Our study set out to answer some of these questions with data.

    The research is premised on the principle that the daily users of Aadhaar are best positioned to provide valuable feedback about their lived experience—and therefore practical adjustments needed to improve Aadhaar’s functioning. We hope these findings can augment a data-driven discourse and eventually, efforts to move towards a more effective digital identity for all residents of India who desire it.

  • What is next for the State of Aadhaar initiative?

    State of Aadhaar 2019 is planned as a series of research outputs drawing on the dataset we created. State of Aadhaar: A People’s Perspective, encompassing the key findings, along with the entire raw dataset and interactive dashboard were launched on 25th November 2019.

    Over the coming weeks and months, we will publish three deep-dive reports on specific themes. We hope to collaborate with policymakers, technologists, and researchers (including international organisations) on these pipeline initiatives, to truly build a shared knowledge platform on Aadhaar. Please reach out to us on [email protected] if you are interested.

  • How can State of Aadhaar inform other countries’ digital ID efforts?

    We believe that digital ID platforms and policies should be rooted in a sound understanding of people’s experiences, perceptions, and how IDs affect them directly or indirectly. The State of Aadhaar 2019 report and dataset can shed light on key benefits and concerns as well as important implementation features of any digital ID system. We believe the report and dataset can be resources for designers of digital ID platforms and policies in other jurisdictions to learn from India’s experience with Aadhaar.

    Please reach out to us on [email protected] if you would like to engage more deeply on this topic.

  • How can I get involved?

    We would like to collaborate with many of you on the findings of State of Aadhaar 2019. We are open to various models for collaboration - such as informational discussions, research workshops to familiarise with the dataset, research collaboration on deep dive topics and many others.

    If you are a policy maker, research organisation, or any other interested party, please write to us on [email protected] and we will be in touch.

Methodology

  • Why did you do two surveys? What other methods did you use for data collection?

    The ambition of State of Aadhaar 2019 was to cover the breadth and depth of people’s experience with the Aadhaar ecosystem in India. To that end, for breadth - we conducted a pulse survey (10-15 minutes) with 147,868 households across 28 states and union territories. For richness and depth, we followed up with an in-depth survey (45-60 minutes) with 19,209 respondents in 16 states and 1 union territory.

    To further understand the nuances of people’s experience, especially in the edge cases (such as the 3% of adults in India who do not have Aadhaar), we conducted human-centered design research (120-160 minutes) with 103 respondents in four states.

    In addition, we conducted multiple rounds of field research at different junctures of the project, beginning with exploratory field visits in seven locations in Maharashtra and Jharkhand. These visits allowed us to test the key areas of enquiry and inform questionnaire design. Once the questionnaire was ready, we conducted multiple rounds of pilots to inform areas of improvement for the instruments. With the help of our survey partners, we piloted the surveys in 10 languages with over 10,000 people across 28 states and union territories.

  • What was the sampling frame – Who was sampled and why? Why were certain states not included?

    The pulse survey was a 10-minute questionnaire added to the trinannual Consumer Household Panel conducted by the Centre for Monitoring Indian Economy (CMIE). Hence, for this survey, a pre-selected panel of 170,000 respondents (households) was approached for the interviews (of which 147,868 respondents answered).

    The in-depth survey employed stratified random sampling across the country. With an objective to achieve both national and regional representation, we selected the states for this study to cover all regions of India, a high share of the population of the country, and to ensure that we covered specific states of interest for our research question (e.g. Jharkhand where a substantial amount of research on Aadhaar has already been conducted). Within each state, we selected 5-6 districts, at least one in each socio-economically homogeneous region (as defined by NSSO). We then selected rural villages and urban wards in each district for our primary sampling units (PSUs), and randomly selected 10 households in each PSU for the survey. Within each household a respondent was randomly selected to answer questions about their experience.

    We recognised that special population groups, such as people who are homeless or who identify as third gender, elderly people, and migrant labourers, are not usually covered in the household surveys. Our literature review suggested that these groups experience Aadhaar differently from the majority, hence we oversampled them for the in-depth survey. Our survey included 845 elderly people (>70 years of age), 478 homeless people, 459 third-gender people, and 3,271 labourers (including 266 migrant labourers).
    More details on the survey methodology, including sampling, can be found here.

  • How did you measure and analyse perception questions like ‘satisfaction with Aadhaar’?

    Our approach was to collect data on people’s experience with the entire Aadhaar journey - from enrolment to using Aadhaar for services to their summative experience. For the enquiry on overall experience, we recognised the need to include perception questions because of the extent and variety of ways in which Aadhaar affects people’s lives. Not all aspects of this experience can be captured through factual questions (like cost and time incurred in updating one’s address on Aadhaar).

    Key indicators where perception questions were used are: (i) ease of Aadhaar processes, (ii) satisfaction, (iii) trust and perception of fraud. In terms of measurement, a 3 or 5-point Likert scale was used (along with a don’t know/ no response option).

    For more details on exact question framing and sequencing, please refer to our detailed questionnaire available here.

  • How did you define ‘exclusion’ and ‘denial’?

    We define exclusion from a service as lack of access to the service because of inability to enrol or cancellation of existing enrolment.
    Denial of service is defined as not receiving a service for which one is enrolled (as reported by the respondents) at the time of expected service delivery, such as collection of rations.

  • What is Human Centred Design and what did the research entail?

    Human Centred Design (HCD) research uses a combination of design and qualitative research methods with an aim to deeply understand users: their underlying needs, motivations, behaviours and aspirations. We used HCD research to strengthen and deepen the survey insights by providing the “why” and “how” behind it, at a smaller scale. It was conducted after the first phase of survey analysis was completed.

    We employed a mix of four distinct HCD research methods: in-depth interviews, small group discussions, intercept interviews (spontaneous conversations that allow us to connect with people while they are immersed in specific contexts), and observational walk-throughs (shadowing select stakeholders in their natural environments, such as e-seva kendras, ration shops, SIM card shops).

  • How did you engage with your technical panel, advisory panel, and expert advisors?

    Our technical panel, comprising four experts, provided content and technical guidance through reviews of our research design, questionnaire, analyses and report drafts. The Advisory Panel, comprising five experts, helped us frame the report and identify the research questions, and also reviewed report drafts. We engaged with them 1:1 through a series of conversations conducted at the inception stage, questionnaire and sampling design stage, when the preliminary results were obtained, and finally once the report was drafted.

    In addition, we consulted over 50 experts ranging from policymakers, lawyers and activists, to researchers and technologists. Their perspectives and knowledge helped us refine our research design and sharpen the analyses. We are grateful to them all for their time and advice.