An interesting combination of headlines caught my attention today. “Agriculture sector suffers loss of Rs.40 crore this monsoon” while “Madhya Pradesh registers 13% agriculture growth for 2012-13”. Such is the divide that even when “Fund utilization by agriculture department is near total”. This is a symptom of an underlying issue. But, even before I could assimilate what I had read, ponder over the issue, there was a sighting of the solution in a headline, “New ventures that build technology-based solutions to boost agriculture”.
The farming as a profession is very interestingly similar to investment banking. Neither of them can be sure of reaping what they sow. The environmental factors, economic, socio-economic may not even give them a chance to reap anything. In these times of uncertainties, what solution do we have?
What causes these imbalances? The standard answer in Investments or in the fields is information… information of the future. Of course, there is a variety of information that a farmer needs: climate/weather, monsoon, government policies, market rates, best practices and much more… And in agriculture, all this information is available online for free, like we find on Google. So where is the problem then?
The problem is two folds: access to the medium of this information (a desktop, internet, and literacy of English, mind it!!) and the usability of the generic information.
The second point is what differentiates intelligence from information. Usability demands the identification of the user. It (usability) is highest when the product is designed to cater to specifically the user’s needs. Intelligence is this tool. It answers these questions for each farmer: What crop should I grow? Is the soil quality right for growing this crop? What seeds are right? What inputs are right? Where do I find the optimal quality of seed? When is it going to rain? Will it rain enough this monsoon for the crop variety I am growing? Where can I get the best market rate for this crop? and more.
This intelligence if built on the right mix of practical field expertize and Lab research, can bring innovation to the field and also infuse practicality in the labs. It is again similar to the analyst groups in investment banking firms that analyze and support the sales teams with practical leads. It tracks particular stocks (read crops), reads environmental factors (read market prices, govt policies, monsoon and weather).
Based on these personalized inputs till the harvest is sold (and if possible even after that), farmers can invest in a profitable manner.
But, can this be done? How much will it cost? Will farmer pay for it? If not, then why any institution would be interested in making this system effective? Will the farmer actually trust these intelligence inputs and follow them?
Not all the questions can be answered here…
But, ideally, this model has to be applied in a public private partnership or a private-cooperative partnership. Here, the farmer is in the dire need of these services but, cannot pay for it. But, let’s not announce the death of commercial viability so soon. There are more stakeholders in the farming activity: a contract farming company like PepsiCo, or an aggregating company like Cargill, Reliance etc. and fresh food and cereal retailers like Reliance, Wal-Mart. If the interests of the farmers can be aligned with that of PepsiCo or Reliance, with value-levers like higher productivity/yield (for contract farming), assured supply (aggregators and retailers) and quality (all), the tool of intelligence becomes commercially viable.
This model increases the credibility of the intelligence, to the farmers, since it comes from the prospective buyers or confirmed buyers (contract farming). This can generate more compliance from farmers too.
To sum it up, an ideal intelligence system should be:
· A support system to farmer’s decision making and mass-adoption of innovations in the field
· Usable:
o More efficient to use—takes less time to accomplish a particular task
o Easier to learn—operation can be learned by observing the object
o More satisfying to use
· Accessible: using the right medium, a medium accessible by the farmer
· Personalized to each scenario
· Aligned with the interest of the whole ecosystem, most importantly, the ‘customer’ and the ‘consumer’ of the service
lalaji Speaks 