Amul was a successful milk producer co-operative that was able to use technology to quickly quantify the quality of the producer’s performance, or specifically the fat content of the milk. The technology they used was a hydrometer. 
With this quick check and a delivery mechanism that brought the products of the milk to Mumbai quickly, they were able to provide their customers a cheap, consistent brand experience and to outcompete Polson butter, which dominated the market till then.
No wonder Amul, the flagship for a host of dairy products marketed by the Gujarat Co-operative Milk Marketing Federation (GCMMF), has become Asia’s largest milk brand and now aims to become the No 1 in the world soon. Something that is substantiated by facts: milk collection has jumped from 10,908 lakh litres in 1995-96 to 22,826 lakh litres in 2005-06; the number of producer-members (read farmers), too, has grown from 17,94,919 in 1995-96 to 24,88,232 today, and the number of village societies has increased from 9,413 to 11,962. And there’s more. It is clearly a market leader in the milk category in Gujarat and Kolkata. It has 35% of the ice cream market, 88% of butter, 65% of milk powder, 70% of condensed milk and around 50% of shrikhand.
Amul created a structure in a market with a loose collection of unaggregated producers and consumers without formalizing either side into a rigid company, but by deducing the implicit structure and judging and incentivizing participants more appropriately than they were being done by the previous structure. Structures and value judgments can come from Benevolent Dictators whose credibility flows from extraordinary contribution as with Linus in the Linux developer network. They can come from algorithms as in Google’s Pagerank applied to the loose federation of web content producers or in the case of Google’s Adwords ranking which improved upon previous ad ranking systems by incorporating the information contained in ad CTRs. They can also come from direct voting by consumers as in Reddit or Uber or from combinations of service metrics (location) and voting as in Airbnb.
This is a theme that we will see more of as the costs and risks of building tightly coupled networks continue to rise while the flexibility of loose networks becomes more and more attractive in contrast.
Marketing in unfamiliar terrain is filled with examples of these loose federations. The key is judging implicit structure and value quickly, correctly and in a “seen to be fair” manner. Coming back to the context where we started (rural marketing), this HBR paper on Unlocking India’s Rural Wealth gives several example of such networks assembled or identified by companies targeting the Indian rural market.
Similarly, when Tata Motors interviewed more than 2,000 rural users of its SCVs in its target areas, it discovered three new customer segments: underemployed and unemployed 21- to 30-year-olds, who see owning and operating an SCV as a viable means of self-employment; families involved in large-scale agriculture who seek additional income; and shopkeepers, small businesses, and schools looking for local transport for students and supplies.
