Results and Impact

BCI is committed to measuring sustainability improvements everywhere Better Cotton is produced and to evaluating the environmental, social, and economic impact of the Better Cotton Standard System.

Results Indicator data: BCI’s Results Indicators quantitatively measure differences between licensed BCI Farmers and non-BCI Farmers in the same geographic area who are not participating in the BCI Programme (also referred to as Comparison Farmers) and are integrated into the Better Cotton Assurance Programme. Data is collected every season from a representative random sample of participating smallholders, and from all medium and large farms. In addition to the data recorded by licensed BCI Farmers, BCI collects data from Comparison Farmers.

Independent case studies: BCI also commissions independent case studies to collect data from samples of BCI Farmers and non-BCI Farmers. The findings of these case studies are then compared to the Results Indicator data reported by farmers, and used to check general directional similarities in results. The case studies also provide an opportunity to gather qualitative information about the Better Cotton experience directly from farmers, hearing in their own words how they feel that Better Cotton is driving change.

By ‘impact’, we mean the positive and negative long-term effects resulting from the implementation of a Better Cotton Standard System, either directly or indirectly, intended or unintended (from the ISEAL Impacts Code, adapted from OECD Glossary).

Impact takes time to achieve and measure, but BCI has already commissioned studies and partnered with academic institutions to seek greater understanding of the impact of Better Cotton on the people who produce it and on the environment. Further studies are in progress and findings will be shared as they become available.

Policy on Communicating Data

BCI is committed to ensuring that credible data demonstrating progress and results is communicated to BCI members, partners, funders, farmers, and the public. The reputation of BCI rests in large part with the credibility of its data. Data is therefore provided at strategic moments throughout the cotton production cycle to allow actors engaged in the Better Cotton network to effectively use and learn from it. The BCI Policy on Communicating Data specifically addresses:

  • types of data about which BCI communicate
  • the rationale for any limitations on data use
  • when and how data is made available by BCI

Links to Learn More

BCI’s Policy on Communicating Data
Working with Results Indicators
Find out more about our research below.

For any enquiries please use our contact form.

Research

Please use the links below to read research conducted by both BCI and external parties exploring the potential and real impact of Better Cotton as support continues to grow worldwide. While these reports show that Better Cotton is linked to positive change, BCI will be carrying out further studies in the future as more and more quantitative and qualitative data is collected each year, to evidence of the real impact of Better Cotton.

  • Summary of the Evaluation of Outcomes in Pakistan. Analysis conducted to identify outcome level deliverables as a result of BCI facilitation in Bahawalpur and Sanghar districts, Pakistan. Developed by APP, 2016.
  • Briefing Paper: Copenhagen Business School Research. Considerations for scaling impact identified from research into BCI implementation in India and Pakistan. This information is taken from a piece written for the BCI 2018 Global Cotton Conference.
  • Demonstrating and Improving Poverty Impacts (DIPI): Baseline Report (April 2016) for three-year theory-based Impact Evaluation, including a combination of randomised control trial and qualitative inquiry that will look to demonstrate the contribution that voluntary standard systems can make to poverty alleviation and pro-poor development. The study, commissioned by ISEAL and financed by the Ford Foundation, focuses on a BCI project in Andra Pradesh, India and is taking place along with two other evaluations of standard systems.