Disrupting today’s disruptors
An algorithm that allows for both sides of these markets: demand and supply, to dynamically adjust without friction as goods or services traded increase in perishability would disrupt today’s disruptors
Gerard Rego, the founder of Aggrigator, a California-based start-up, is of Indian origin, and grew up in Bengaluru before the software services boom. He earned a Bachelor’s degree in mathematics at Bengaluru University, followed by a Master’s in sociology. He has since been a fellow at Wharton, Stanford, and INSEAD, at the last of which he spent six years, honing his mathematical skills among French academics before venturing into the start-up world.
Rego’s advanced mathematics powers a start-up which is focused on solving some of the invisible problems that you and I face in our daily lives by changing the way markets work. Aggrigator focuses on agricultural markets. Evidently, the spoilage of fresh farm produce such as fruits and vegetables is extremely high even in developed markets like France and the US, despite transparent and efficient agricultural markets, sophisticated logistics handling systems and reliable cold-chains. The wastage of these perishable items is even higher in India, which despite having transparent mandi pricing information, simply does not yet have the infrastructure to allow for the quick transport of perishable farm produce.
Aggrigator brings together small farmers and buyers to achieve economies of scale, create a market signal for price, and provide access to adjacencies to reduce friction with third parties in the marketplace such as financial services firms that bankroll the marketplace’s transactions. The start-up has also announced a “Farm to School” programme wherein it seeks to provide fresh produce from California’s vegetable and fruit farmers directly to the state’s public schools. It hopes to bring the volume and consistency needed to supply California public school districts, which feed all children attending their schools, by allowing them to buy from multiple small farmers at a single contact point through the Aggrigator marketplace.
Aggrigator has based its business model on the bet that the $700 billion food service, food brokerage, food processor, and end-user market in the US needs a network orchestrator to reduce the current friction in the system. Not unlike India, the target market suffers from extreme fragmentation, leading to poor price discovery and predictability, negatively impacting the bottom-line of farmers, midstream distributors and downstream buyers. As a network orchestrator, the Aggrigator team uses an interdisciplinary background in supply chains, agricultural science, mathematical algorithms, data sciences, and economics to create an aggregated farm-to-shelf marketplace, with which it will attempt to connect a largely offline ecosystem. It claims it is designed to enable farmers, buyers, fleet owners (of any size) and service providers to access markets across the entire fresh produce value chain. Bringing together isolated, fragmented participants with the use of the appropriate algorithms helps create viable economies of scale and a supply chain capable of servicing large demand markets.
For commercial and institutional buyers, procurement processes via the network effect of the Aggrigator platform can now be routed through an online marketplace. The farmers who connect to the platform have the opportunity to access and participate directly with these large demand markets, giving them predictable markets and fast payment mechanisms.
External economic conditions have forced sellers and individual buyers to organize themselves within defined, traditional agricultural market constructs since these constructs used to provide a more cost-effective way for people to trade with one another than a free-for-all market. So instead of thousands of buyers and sellers forming independent relationships, a Wal-Mart Stores or a Whole Foods (which is now owned by Amazon) formed a company which in turn employed thousands of people in order to aggregate the demand and then disaggregate the supply to individual buyers. The internet marketplace that Aggrigator envisions will attempt to disrupt this market construct.
So far so good, you say. Yet another internet marketplace, Uber, is looking to disrupt a traditional marketplace by providing an online platform with the network effect. There is, however, one critical piece of insight that Rego has had that seems lost on many online aggregators. He recognizes that the goods he deals in are perishable, and as a result, exhibit significantly different price behaviour based both on the quantity of the produce demanded and how close the produce is to rotting. And so, he allows both buyers and sellers to adjust their bid versus ask prices based on both quantity as well as time, using a proprietary algorithm. The algorithm aggregates both demand and supply, combined with perishability, in real time, to change the model of price discovery in the market.
Most aggregators, including ride hailing services such as Uber do not allow for this. They rely only on the demand side of the equation, for example the demand for rides around rush hour to price-discriminate among buyers by applying “surge pricing” rules during certain times of day. In addition to the other troubles that Uber is having with recalcitrant founders and with regulators such as London’s city government agencies, price discrimination or “price fixing” is also illegal in many countries, and as such, its surge pricing practices come under strict regulatory scrutiny.
But the truth is that these rides are also perishable commodities. They lose value after rush hour, and a driver who is competing with many other drivers on the same route may realize that he or she is better off bidding a lower price than the “surge” price, if allowed to do so, in order to win the maximum number of rides before the rush hour perishes. There are taxi apps such as the Germany-based Blacklane that allow drivers to bid in a reverse auction process, but this bidding is opaque to the customer, who sees a constant price. Lower bids from drivers only benefit Blacklane.
Several other goods and services that have a “use by” time or date such as flight tickets or hotel nights, are perishable. An algorithm that allows for both sides of these markets—demand and supply—to dynamically adjust without friction as goods or services traded increase in perishability would disrupt today’s disruptors. If Rego’s algorithm indeed works, I will be looking to invest.
Siddharth Pai is a world-renowned technology consultant who has personally led over $20 billion in complex, first-of-a-kind outsourcing transactions.
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