India

Agile Data & Resilience

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  • Agile Approaches
  • Methodology
  • Overview
  • Findings
  • Research Indicators

Tracking Time, Cost & Validity

Glossary

Agile Data Technologies

  • Computer Assisted Personal Interviews (CAPI)

    Computer Assisted Personal Interviews (CAPI) is a survey method where interviewers conduct face-to-face interviews using a handheld computer or tablet to ask questions and record responses. This technique enhances data accuracy and efficiency by allowing for real-time data entry and the use of complex question formats, making it effective for collecting detailed information in various research settings.
  • Computer Assisted Telephone Interviews (CATI)

    Computer Assisted Telephone Interviews (CATI) is a survey method where interviewers conduct telephone interviews using a computer system to manage questions and responses. This approach improves data accuracy and efficiency by reducing human error and allowing for immediate data entry. CATI is widely used in market research and public opinion polling to collect quantitative data from various respondents.

Agile Data Indicators

Time

  • Survey Duration

    The mean amount of time it takes for a respondent to complete a survey from start to finish. It is calculated by taking the total time spent by all respondents to complete the survey and dividing it by the number of respondents. This metric is important for assessing the survey’s efficiency.
  • Number of call attempts

    Number of calls made before receiving an answer.

Cost

  • Data Collection Cost

    The reduction in expenses achieved during the data collection phase of a research project compared to the standard costs.

    It reflects the overall financial benefit of optimizing the data collection process.
  • Sample Size Reached

    Refers to the percentage of individuals that responded to the survey out of the total number of people in the sample.
  • Survey Cost

    The amount of money saved on each individual survey compared to the traditional survey mode Computer Assisted Personal Interviews (CAPI) cost per survey.

    This metric helps assess the financial efficiency of data collection on a per-unit basis, reflecting how much less it costs to collect data from each respondent.

Validity

  • Data Accuracy

    Inaccuracies or deviations between the recorded values and the true values of the variables being measured in a study.
    Sources of measurement errors include:

    • Respondent errors (e.g., misunderstanding questions, providing inaccurate responses).
    • Interviewer errors (e.g., inconsistent question delivery, leading the respondent).
    • Instrument errors (e.g., faulty survey tools, miscalibrated equipment).
    • Environmental factors (e.g., distractions during data collection).

    Minimizing measurement errors improves data quality and ensures that the findings of a study are more accurate and reliable.
  • Replacement Rate

    The percentage of individuals who were successfully reached by using phone numbers from a secondary or replacement list over the total number of realized interviews.
  • Response Rate

    The percentage of individuals that respond to the survey out of the total number of people invited to participate.

    It is a key indicator of the survey’s success and representativeness, reflecting how well the target population was reached and how engaged they were.

The Methodology

COSA’s recent collaboration with Better Cotton (BC) in India demonstrates the power of Agile data collection in practice. The goal was to assess baseline levels of resilience among cotton-producing households in Karnataka and Telangana, informing the Better Cotton Sustainable Livelihoods program. This initiative aims to increase farmer incomes and bolster household resilience in the face of recurring shocks, such as climate change, market fluctuations, or health crises. To do this, COSA deployed a double resilience lens, based on two key indicators: the Resilience Ability to Recover Index and the Resilience Capacities Index.
We also compared two different data collection methodologies for key indicators (land size and yield); Computer-Assisted Telephone Interviews (CATI) and in-person Computer-Assisted Personal Interviewing (CAPI), to determine the most accurate, cost-effective, and scalable method for future interventions.

Survey

The hypothesis testing wanted to verify whether farmers with higher resilience capacities were the ones facing higher recovery ability. Therefore COSA built a novel resilience conceptual framework for this project. In particular, COSA used a  Monitoring and Evaluation (M&E) framework for resilience programming interventions, following a Theory of Change approach (ToC) proposed by Béné et al. (2015; 2017) and USAID (2018). In this framework COSA combined two measures of resilience that are usually considered alternative measures of resilience by the literature. In particular, COSA considered resilience capacities resulting from the program activities (i.e. outputs) which represent the resilience intermediate outcome as in the literature (Béné et al. 2015; 2017; USAID 2018; Constas et al. 2014). This resilience intermediate outcome was measured through a Resilience Capacities Index. Further COSA introduced another resilience outcome in the framework, often considered as an independent measure of resilience, the recovery ability. This outcome constituted the resilience response outcome, and it was captured by the  IFAD’s Resilience Ability to Recover Index.

Sampling

The Deshpande Foundation shared a listing of master farmers and their associated telephone numbers. In the listing, the population was composed of 38966 farmers in total (430 in Karnataka and 38536 in Telangana). Most of the farmers are male with only 1 female farmer (0.2%) in Karnataka and 1709 female farmers (4.4%) in Telangana.

To determine the optimal sample size, COSA applied simple random sampling to estimate a proportion within each state with a 95% confidence interval and a 5% margin of error. The optimal sample size accounts for a 15% non-response rate (87 farmers). The non-response rate was set to 15% due to previous experience with CATI surveys in Uganda, Malawi, and Zimbabwe.

Technology

Cotton farmers were interviewed using CATI (Computer Assisted Telephone Interviews).

Overview

Risk, Resilience and Climate

Resilience is the ability of individuals, households, and communities to prevent, resist, absorb, adapt, respond and recover positively, efficiently and effectively when faced with a wide range of risks, while maintaining an acceptable level of functioning without compromising long-term prospects for sustainable development, peace and security, human rights and well-being for all.
UN(2020)

The Resilience Ability to Recover Index  (ATR) is a resilience measure adopted by  IFAD  (2015). The Ability to Recover Index is easily measured through farmers’ self-assessment of their  perceived ability to recover from shocks.

The ATR index is the mean value of respondents’ responses across all shocks experienced. The variable “incidence of experience” for each shock is equal to 1 if the shock was experienced, and 0 if not.

 

Business Development

Business development involves strategies and activities aimed at enhancing their economic viability and market presence.

Productivity

Productivity refers to the efficiency and effectiveness with which resources are utilized to produce crops. It encompasses various indicators that measure the output relative to inputs used.

Producer Livelihoods

Producer livelihood refers to the means in which a producer earns a living and sustains their well-being. This includes economic indicators on their diversification of income.

Indicators

The right data drives clear insights
COSA indicators are recognized for their practicality, precision, and ease of adoption, providing managers and researchers with clarity while minimizing data costs. Proven globally, these credible indicators are tested across thousands of applications, delivering science-based data on sustainability.