How building a government tech stack can assure MSP to farmers

The problem of assuring MSP to farmers is closely linked to matching demand and supply. If the demand is more than supply, farmers can get their assured MSP or sometimes, more than that. If supply is more than demand, it is very difficult to guarantee MSP for the excess supply.

No matter how much we try to extend shelf life and storage capacities, there is a limit to how much excess supply can be absorbed in the supply chain. This “excess supply risk”, makes a “legally guaranteed MSP” a lot more complicated.

Today, farmers decide what to produce, based on price signals coming from the market. But these are not reliable.

Let us see a simple example: when the tomato prices are high, everyone decides to put tomato and then the tomato prices crash, because more people produced tomato than what is required. If the government creates a national platform that has data on how many acres of land is seeded with tomato, it can show the expected harvest and market arrivals every week at various locations along with the predicted price.

Another farmer who is planning to sow tomato will now get an advance warning that he should not put tomato and instead put something else. Now, imagine a similar real-time data availability for all agricultural products cultivated in all lands across India.

Apart from predicting the week-wise supply of various agricultural commodities at various locations – based on actual data of what products are being cultivated, where and in how much area – the platform can then also act as a trading platform for contracts with guaranteed MSP prices to both suppliers (farmers) and buyers (private buyers/mandi traders/government agencies)

 A simple Android app (in regional language) on a smartphone with GPS can be used to collect data directly from the farmer. The cultivation area can be automatically calculated by recording the GPS coordinates as the farmer walks around the perimeter of the plot. The product and variety planned/seeded/planted can then be entered.

The rest of the information – in terms of yield, gestation time, expected harvest date, estimated date of arrival at the nearest supply location – can be automatically calculated by the tech platform based on the land location and soil data available in the master repository.

Technically, we may have the capability to build a massive system that can track real-time data across the country. However, getting the farmers to use the system and input the data has to be incentivised and encouraged. The active involvement of the state governments and the administration in rural areas and villages will be necessary.

That is why it has to be a project similar to UIDAI or UPI, which acts as the underlying infrastructure that various government agencies and agricultural departments could use.