Agricultural Resource Planning through-IT platform —An approach

Abstract

Agriculture happens to be the mainstay of Indian Economy. Even today seventy percentage of the population depend on agriculture as the core economic activity. Nevertheless as the commodity market is the farmers — particularly the small farmer are unable even to cover their cost of production. Unlike in US-EU they do not have a back up of significant subsidy. The result is a diminished attractiveness of agriculture as a paying industry. The farmers mostly operate in production segment of the value chain and as such is not in a position the capture major share of the total value created. In fact much of the value created by this chain is captured by the segments both upstream & downstream of this chain. It is a fact that in the current scenario — the powerless (economic) farmers cannot do much because of immense competition in the production segment. However this paper makes an attempt to capture some more value with the help of some more knowledge captured through an IT platform. This paper proposes an economic model that integrates through a computer network some of the upstream segments like the producing centers, Market, logistics so that the farmers can capture some more value. This paper proposes a network environment for the producers as well as the marketing associates which can use the IT tools to forecast commodity prices in different markets and accordingly advice the farmers to shift this producer to a particular Mundi for an expected price recovery. ARP — as its called (Agricultural Resource Planning) will help the farmer to the extent that the latter knows that for maximization of value capture he needs to sell his commodity in which market. This also calls for free movement of grain / commodity to different market. This exercise will help reduce some of the uncertainty associated with today’s production-logistics-sale-scenario. This model is proposed and not tested yet. Model results can be discussed once it is put on test at least with a control group of farmers.