July 2022 Product Update and Questions

Owned by Ashu Sikri (Unlicensed)
Jul 21, 2022
3 min read

Prepared July 20 for @Preeti Harsh @Sai @Satish Chandra who have recently joined to support FRAME. Also copying @Ramaskanda R S @Yogesh Sahu (Unlicensed) for context. @Falguni Ganguli (Unlicensed), @Amitesh Anand (Unlicensed) @Akash Asthana (Unlicensed) @ashok please add if I missed anything.

Context

We are one year in to a two year program in Bihar called FRAME. The primary funder is Sequoia Climate Fund who is keen to see reductions in yield-scaled GHG emission via farmers adopting climate smart practices and commitment from GoB towards resources / programs that further scale up emission reduction from agriculture. See more on project objectives here.

Establishing a credible and pragmatic MRV approach which captures farmer practices and quantifies their GHG emission impact is critical for this.

We also have some complementary funding from Cisco to experiment with farmer and VRP facing interfaces which support the project objectives (esp capturing data about farmer production practices).

You will see that a lot of the concepts and approaches developed during FRAME appear front and center in our current strategy (see here).

Data Flow

  • See MIRO board here

  • Note, this flow does NOT cover our work with JEEViKA to promote climate smart practices. See list of promoted practices for kharif 2022 here

  1. JEEViKA VRPs capture critical data about farmer practices and agro-ecological parameters through the Kobo collect app. See data collection forms for rabi 2022 here.

  2. Random entries are selected for data validation by DG and JEEViKA staff. See dashboard for visibility. @Amitesh Anand (Unlicensed) is driving this process and can share more.

  3. Generate emission estimates based on farmer practices and estimate reduction in emissions from new practices vs BAU. We have emission estimates from CFT and working on generating from Regrow. @Ramaskanda R S is leading and can share more.

  4. See above; rather than a model inter-comparison, we are exploring how to simplify a really complicated model (DNDC) into a few key input parameters.

  5. Share data back with farmers via a scorecard to drive engagement and increase practice adoption. See here for detail

Product Questions

  1. How can we improve the data collection and validation interfaces? Can we experiment with farmers recording their own data and VRPs validating (this is our longer-term vision and what we pitched Cisco). We have previously discussed introducing some basic data validation logic in the Kobo collect forms. Have also discussed capturing data through alternative channels like Whatsapp.

  2. We have a notion that the captured data is “owned” by farmers and sits in their “data wallet” but what does this practically mean? Right now we don’t have a UID that connects farmer data across forms and it is stored in a DB maintained by DG. We have fielded some questions from JEEViKA about the data captured as part of this work (data privacy, security, access, ownership etc). @Gautam Mandewalker

  3. How can we build upon the farmer scorecard experiments? Can analytics and peer benchmarks support farmer decision making? JEEViKA is keen to see the scorecard evolve to more of a targeted recommendation; could we partner with someone to make that a reality?