Chicken — Data — Egg
I only hope that we never lose sight of one thing — that it was all started by a mouse — Walt Disney
That the impact of any data analysis is of some relevance only when the data is huge, to begin with, is a frequent assumption piggy-backing any data-related discussion, analysis, or decision. Our telematics device, Simha Kit, however, hits this assumption where it hurts the most: in the underlying postulate that micro-data can’t reveal a lot.
For a moment, just assume this hypothetical scenario where there is just one farmer in India who has Simha Kit installed on his tractor. What business-critical questions do you think can the Simha Kit answer about this person? Perhaps all of them! Talking in a broad sense, the urban consumer tends to Google to gather information about any purchase/need. In rural India, they physically visit! Based on the telematics data sent by Simha Kit, his app usage information, and the meta-information which he shared with us during the installation, here are the questions that we can answer about the person:
Take a moment to understand the breadth and depth of the questions in the above graphic. You can comprehend nearly everything there is to know about the person from the business perspective, from his financial situation, his business KPIs, his revenue cycles to his tractor usage, his location hotspots, and his tractor-buying anticipation factor! And all this while revolutionizing agriculture for the farmer as well. Simha Kit is a product that farmers want to buy, not only because it has the potential to increase a farmer’s incomes by an estimated 20–30%, but also because it has all the positive attributes that are more than welcome in the agriculture industry: convenience, comfort, security, delight! Simha Kit brings in accuracy and accountability in a market run primarily on word-of-mouth. So far it has proven to be a win-win for all stakeholders!
The above list of questions would have made you realize that Simha data quite convincingly breaks the chicken-egg deadlock. In a typical scenario, you may need thousands of devices to comprehend the impact of data, which would then motivate you to install thousands more. With Simha, a single device is enough! After all, in Simha’s dictionary, between Chicken and Egg, there lies Data!
Dream On!
Now, we would like to point out that the data-impact story doesn’t end with a single device. With Simha data, the whole is significantly greater than the sum of the parts. In other words, as more and more devices get installed, the insights you can gather from the aggregate data are significantly richer and remarkably seminal compared to the case of one individual device.
So far, we made you imagine a hypothetical scenario where only a single tractor in India has a Simha Kit installed! Now, pause, behold, and imagine a world where every tractor within a district/state/country has a Simha Kit installed! What will such a world look like?
It is a world where agriculture has been completely digitized. Farming rental transactions will be dispute-free, tractor owners will maintain the digital ledger and the entire vertical of tractor owners will become more profitable!
In a world with just one device, you could answer almost all relevant Wh-questions (What, When, Where, How) about a farmer. In this ideal world with every tractor having a Simha Kit installed, you can cluster or profile customers whose answers to such questions are similar. Think of any variable of interest to you, location, work type, tractor usage, or any other variable and you can profile customers according to that variable.
Say you want to advertise a new implement in Meerut. Need a list of farmers in Aligarh who primarily use tractors for rental farm work and had a very good season recently? You get it with a click! Need a list of farmers in Uttar Pradesh who are likely to recycle their tractors in the next 6 months? Another click and you have it!
The next big advantage of having a world full of Simha Kits is the ability to go from absolutes to relatives.
If you were told that a certain rental farm-work tractor has done 575 engine hours this Kharif season, you may not know whether it had a good season or not, unless you have domain knowledge. However, if you were told that this tractor has worked more than just 42% of all tractors in this Kharif season, you will immediately understand that it had a moderately bad season.
Enjoyed this article? Then be on the lookout for another two weeks later. Till then, for any data related discussions, feel free to drop us a line at datalabs@carnot.co.in.
