Farmer P2P sharing and benchmarks

Some thoughts on how the scorecard and peer benchmark pilot we did in FRAME leveraging the data collected as part of MRV (link coming), could be extended to the FDN concept.

Brainstorm

• Farmers capture photos (timestamped and geotagged) at key junctures during the season; this gives them something tangible to go back and reference from prior years and makes the peer comparisons more visual. Need to think through the workflow here in cases where data entry is VRP assisted (attach a photo to a specific farmer)

• Issue tokens for data collection and verification (eg, Kisan Coin). Earlier, we had the notion of issuing badges as data on specific topics was input to gamify the experience; this would be more compelling if we figure out some way for the tokens to have real value for the farmers (DG could even be a buyer initially). As a reminder, here are a couple screens on the badge idea. Full flow is here

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From Alesha (Jan 18)

The way I'm thinking about it: If I'm prompted to take a photo on a day I plant (which provides date and location) that could be useful for: 1) benchmarking when I plant versus peers, which could (with some AI) determine if there's a better ideal planting window---to be recommended in a future season) 2) could be data that's used for insurance products. 3) Perhaps this gives me a token in my FDN, per the exchange on confluence about weighting the initial data collected more heavily than subsequent.
Then, if I'm prompted to capture a photo again mid-season (perhaps related to an advisory prompt like applying fertilizer OR simply based on the plants maturation cycle, asking for a photo measurement) the data could be used for things like 1) making a more accurate yield estimate (for a buyer/creditor) 2) collective learning in a peer group about different field outcomes in my area (seeing with my own eyes the effects of different practices 3) perhaps there would be indication of certain preferable practices related to ecosystem services, but these would vary by crop or in the future a photo of a soil sensor could indicate something about on-site condition of the soil

Then finally, right before/during harvest you could capture data that could be useful for 1) buyers 2) creditors 3) farmer groups collective learning and farmer producer groups looking to aggregate and needing to know available product 4) public bodies trying to revise advisories and improve/customize recommendations for farmers 5) seed companies wanting to see variable performance of their product

I think there's a valid question here about farmer benefit. If we assume that farmers are more cash-strapped in the early part of the season often, after buying inputs and after exhausting stored food, then compensating them for entering this data, at least initially makes sense to me. Or, as we're doing in FRAME, compensating the VRPs that are supporting this data collection. Your question on farmer behavior, Rikin, can only really be answered as an experiment, but it seems aligned to our prior experience that if farmers could visually see the progression of different fields/outcomes with different practices applied, this would provide a useful basis for thinking about alternative practices and adoption of better options----ideally highly localized to what is working in my area.