This piece was originally published on the ICTWorks blog. It has been cross-posted here with their permission.
Vinod Sharma and
Raghav Kapoor Adlakha
lead a focus group discussion on the soil health card for IDinsight’s NITI Agriculture project in Dhubri, Assam.
While India’s total fertiliser consumption is less than the global average, it is the second-largest consumer of urea (a nitrogen-based fertilizer) in the world. Fertiliser misapplication has led to a reduction in both long-term soil fertility and agricultural productivity for farmers.
To solve this problem, the government of India launched the Soil Health Card (SHC) Scheme, under which every farmer in India was to receive a customised set of crop-specific fertiliser recommendations that would ensure the long-term productivity of their soil. These recommendations are printed onto cards and distributed by agricultural extension workers, who are expected to explain the general purpose and recommendations of the card to farmers.
However, in a qualitative study conducted in 2018 covering ~450 farmers, we found that across 8 districts, overburdened extension workers are unable to adequately explain soil health card recommendations to farmers. Rather than individually visiting each farmer, extension workers often distribute cards en masse in villages.
Experimental evidence from Gujarat, authored by Shawn Cole and Garima Sharma of Precision Agriculture for Development (PAD), suggests that supplementing an in-person explanation of the soil health cards with either audio recordings or video clips may enhance understanding.
When benchmarked against in-person extension practices, the audio and video supplements perform comparably both in terms of enabling comprehension of soil health card recommendations and eliciting trust in their accuracy. Audio and video supplements perform significantly better on both measures than just providing a farmer with a soil health card. This is insightful since in-person interactions are more expensive than remote options.
The experiment also suggests that these approaches might hold particular promise in reaching illiterate farmers, who are 32% of all farmers in Gujarat.
Building on this experiment, IDinsight conducted several ICT-based campaigns with farmers. Their smartphone usage was low, limiting the set of feasible mediums to text messages and automated calls.
Over January and February 2019, we designed and recorded a set of educational messages on the soil health card scheme, that were sent to farmers through mobile phones. These were designed to be feasible for the government to implement through their existing systems of mobile-based extension.
Two mediums were considered for this exercise:
To develop the content, we used findings from our study on farmers’ knowledge and attitudes towards the soil health card scheme. The messages had three objectives:
The team wrote scripts of messages to be sent through IVR and SMSes, which were then translated into Hindi and recorded using a simple smartphone recorder. We also produced a literature review of best practices around ICT interventions in rural settings and interviewed other organisations with experience using IVR calls in rural India.
After reviewing our experiment’s results, we came away with four key findings that can help other organizations reach farmers with key agricultural information services.
It is essential to design message-based interventions around the work schedules of the target respondents. Calls at 12:30 PM, 5:30 PM, 7.30 PM and 8:30 PM have the highest chance of being answered by farmers — likely matching the farmers’ work schedules, which start early in the morning and include breaks in the late morning, afternoon and night.
Unfortunately, we were not permitted to make IVR calls before 9:00 AM, so we were unable to test the success of early morning calls. Without express permission from the Telecommunications Ministry, calls and SMS can only be delivered between 6AM and 6PM.
With three callbacks (made 4, 24 and 48 hours after the first call), our final conversion rate was 32.2 per cent. This suggests that it is possible to move some non-respondents to engage with the system with low-cost call-backs. However, these returns diminish after 2–3 callback attempts.
Farmers were highly unlikely to respond or interact with messages either through key presses or voice responses. Anecdotal evidence from a separate field study suggests that farmers are unfamiliar with the format of recorded IVR calls, and are thus unlikely to understand instructions requiring a response.
An unexpectedly high number of farmers are registered on the “Do Not Disturb” database — of the 750 numbers we scheduled for calls during the third pilot, nearly 26 per cent were registered on this call list, which prohibits broadcast messages and mass campaigns from directly contacting them without their written consent. This suggests that farmers are becoming fatigued by the overuse of low-value SMS and IVR messages.
This experiment shows that farmers are a very specific sub-group, with unique daily rhythms and habits, and we needed to experiment with different types and timings of messages to effectively reach farmers.
Even if other organizations are working with farmers, their results are likely to vary by context (like mobile usage, geography and season), as the likelihood of picking up calls is presumably linked with the intensity of agricultural activity in a given time and space.
We have incorporated these results into the design of an ICT-based intervention, the impact of which will be assessed through an RCT later this year. We will be sending farmers non-interactive voice blasts at the most successful time slots. We plan to share the results from this RCT with the readers after the analysis is complete.
9 November 2020
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