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How might we increase the efficiency of data collection and documentation to ensure the cotton is produced sustainably?

What is our innovation goal for this challenge and what does success look like?

We want to identify innovations that will lead to a vastly more efficient process, in terms of time and cost, of collecting Better Cotton farming data from farmers to enable verification and certification of Better Cotton. This improvement will help drive scale with fewer resources and will lead to more sustainable cotton production globally. We recognize that this outcome can be driven through multiple and are indifferent and non-prescriptive to the pathway innovators propose.

What we will be measuring are outcomes such as reductions in the total time and cost needed in the system to collect relevant data to assess whether farmers have adopted Better Cotton practices or not and to what extent. Error rates would need to be similar to the existing system of collecting data.

What is the need for and significance of Better Cotton data collection and documentation?

Farmers and field-facilitators work together to improve cotton agriculture and produce better cotton for all. To do this well and assure brands that the cotton produced is truly ‘better’, a range of metrics are tracked by BCI. Data is collected throughout the crop cycle spanning 9-10 months. For example, at the beginning of the season, data on land size is collected, mid-season on quantity of water and pesticides used, and at the end of the season bags of cotton produced.

 

Data collection helps achieve two things – helping determine compliance of better cotton production practices on the ground and track progress of farmers on pesticide, fertilizer, and water use among other things.

© BCI 2018

How is data currently being collected, documented and verified?

Each farmer owns a Farmer Field Book where they record this information with support from Field Facilitators. Field Facilitators meet farmers about ~3 times a month for meetings / trainings and capture data in-person in a group or individually through house visits. The data entered in Farmer Field Books is also verified by Field Facilitators through field observations and bill verification.
The data verified by Field Facilitators undergoes another round of verification by the Production Unit manager that oversees the operations of the Field Facilitators in their unit. The data is verified randomly every ~15 days.

© BCI/Paulo Escudeiro 2018

What is the challenge in the existing data collection process?

The current process results in the collection of ~200,000 data points over ~12,000 interactions at the Production Unit level. Per farmer, roughly 50 data points are collected in a year. Field Facilitators spend ~50-70% of their time in data collection and verification that translates to high annual costs and time per farmer.

There is an opportunity to increase the efficiency with which this data is collected and to drastically reduce the time and cost of the program and help scale it to many more farmers.

© BCI/Khaula jamil 2018

What are some drivers of cost and time?

The current data collection process is time consuming due to a range of drivers:

  • Initial collection of data in paper format. (notebooks carried by field facilitators)
  • Poor route planning and un-optimized logistics at the last-mile.
  • Conversion of physical format of data to excel.
  • Lack of literacy for farmers and reliance on field facilitators to record data in field books.
  • The need for repeat visits by field facilitators due to farmer unavailability.
  • Fuel and transport costs to field facilitators over several months.
  • A larger number of data points than possibly necessary. (some redundancy might exist)

What kind of innovations and innovation pathways are we looking at?

Innovations over the years have made it possible to collect and document data in a resource efficient manner. These include IVRS based data collection that provides a means to collect last mile data, satellite augmented data collection that uses image recognition, artificial intelligence and machine learning that can read and digitize various formats of data, behaviour change trainings among farmers coupled with non-monetary incentives, and re-designing the farmer field book in favour of self-reporting.

 

We are looking for the next big innovation that can further improve the way the BCI program facilitates data collection and documentation.

 

Your innovation may follow one (or more) of the pathways mentioned below:

  • Capturing only a sub-set of indicators if other indicators can be derived based on the set collected.
  • Capturing all indicators by using technology advancements. (i.e., AI, Satellite augmented data capture)
  • Capturing data manually by enabling self-reporting by farmers. (i.e., IVRS)
  • Capturing data more efficiently through field facilitators. (i.e., route optimization, FF allocation to more cost intensive regions)

Note: This list of pathways above remains non-exhaustive and illustrative.

What key constraints should the solutions operate within?

The Better Cotton Initiative is a real world program operating at scale and it is essential that innovations identified or created through the Challenge operate within some key real world constraints of the program. Your innovation should be a data-capture system that reduces the cost of collection and documentation by Field Facilitators keeping in mind the following constraints:

 

  • Quality of data: The existing accuracy rate of 85% is maintained.
  • Coverage of data: BCI prescribed set of data indicators remain unchanged. Your system should be able to capture all the relevant indicators if it is a systemic solution or dramatically improve the collection efficiency of a critical piece of data that requires significant time.
  • Verifiability: The data collection system should lend itself to easy triangulation and verifiability.
  • Alignment with the ecosystem: The solution should work with the existing responsibilities and incentives of implementing partners and should not require any significant shifts in role or incentives.
  • Alignment with skillsets and capabilities at the last-mile: Solutions should not require a more advanced skillset from Field Facilitators (than is locally available) or skills/ literacy from smallholder farmers than is the average for the location.

© BCI/Paulo Escudeiro 2018

To know more about challenge 2, download ‘Challenge 2 Knowledge Pack’.