Agriculture in India contributes to about 17% of GDP but employs nearly 55% of the population. There are about 140 m Small Holder Farmers (SHF) in India practicing subsistence farming with limited participation in markets beyond the local level. About 80% of these farmers are smallholders with landholding of less than 2 ha and nearly 62% of agriculture land has no irrigation system in place (Canal, borewell etc). It is increasingly clear that Indian Agriculture isn’t structurally well positioned to double farmer income by 2022 as envisioned by PM Modi. Digital technologies today have the potential to deliver two big themes within the agriculture sector that could potentially enable small holder farmers reach their economic potential – disintermediation and uberization.
Productivity and price are the two pillars on which small holder profitability hinges. SHFs need to increase their yields to grow more with less. Gains in productivity can be achieved through a combination of applying good quality inputs, mechanization and knowledge. Farmers can capture better prices by selling into more lucrative and transparent markets that see participation from diversified buyer groups and also through market oriented agriculture. Coincidentally, the traditional structures and systems that deliver inputs and knowledge to the farmers in the last mile are characterized by high levels of intermediation. The agriculture input and output supply chains are intermediated due to the heterogeneous, fragmented nature of demand which is a consequence of small farm sizes and smaller lot sizes. The agriculture markets that the small holders sell into are not only highly intermediated but are also subject to rampant abuse of free market principles in spot markets (Mandis) through cartelization. Digital commerce/e-commerce platforms supported by strong fulfilment processes can potentially disintermediate the agriculture input as well as output markets. This space has attracted the attention of a number of agritech startups like KhethiNext,Kalgudi, Agrostar etc. These platforms not only enable small holders buy quality inputs at lower prices directly from input manufacturers but more importantly, create a transaction history of the smallholder farmer’s economic activity which has traditionally been part of the invisible rural informal economy. A consequence of the digital capture is the ability of financial institutions (FIs) to offer institutional credit to small holder farmers. The transactional data in combination with new age analytics based techniques can enable FIs compute risk scores for small holder farmers which in turn can help FIs price various financial products for the small holder farmers. In the current system, FIs are forced to work with joint liability groups (JLGs) due to the absence of such granular farmer level data.
Agriculture knowhow/knowledge which is another critical lever to productivity enhancement has traditionally been perceived as a “public good” and is generally created in agriculture universities/research institutions. This knowledge is transferred to the SHFs through the Extension model which is part of the traditional Agriculture Knowledge Information System (AKIS) which has an overarching goal of transfer of knowledge to small holders. As per an FAO report from the year 2000, An AKIS for rural development and sustainable agriculture links people and institutions to promote mutual learning and generate, share, and utilize agriculture-related technology, knowledge, and information. As part of this model, Govts recruit agriculture graduates as agriculture extension officers (AEOs) who work in villages and undertake technology/knowledge transfer through trainings, demo plots etc. They act as a bridge between the universities and the farmers. This model however is highly expensive and has quite not yielded the intended results. Digital platforms that can build the skills and knowledge of the farmers can be an effective supplement if not an alternative to the costly extension model. Digital MOOCs platforms that can offer training and impart skills on demand are a great revelation. Digital trainings can be disemminated through pluralistic channels. While the most common template of MOOCs in agriculture has been to use experts to create crop specific learning courses, an innovation here is to design courses with progressive farmers and thereby facilitate peer to peer collaboration.
Apart from knowledge, Extension is also meant to offer advisories/support decisions of farmers on various aspects from pre-season planning (choice of crop, soil preparation etc) to in-season tactical management of crops (irrigation, pesticide etc). However, given the overstretched extension system and the absence of human capacity to deal with such complexity, public extension systems haven’t successfully delivered on these objectives. It is worth noting here that rich farmers pay for private extension services which underscores the importance of these services. Digital platforms that can collate, curate and contextualize advisories for farmers can be an effective means to plug this gap. Developing systems that offer contextualized advisories based on the famer location, weather, soil etc would need significant investment into knowledge engineering processes which could translate agriculture knowledge (which is descriptive and static) into rule based representations or algorithms. This way, descriptive knowledge can be encoded into a computer program and can be used to offer contextualized advisories to farmers at scale.
Another important lever for productivity improvement is farm mechanization. SHFs are unfortunately capital constrained and unable to invest in mechanization. This is where the sharing economy offers innovations. Uberization of tractors, harvestors and other farm equipment is emerging in a few pockets. As these models mature and stabilize, agriculture mechanization will acquire the flavors of a service and reduce the capital needs.
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Innovation Systems for the Drylands