Nikolai, a fruit importer based in Moscow, Russia, is urgently looking for 100 metric tons (MT) of tomatoes to distribute to his wholesale clients as his supplier in Mexico was hit with a hurricane and supply was cut. Yet, this is proving difficult as prices have skyrocketed as other areas in Central America have also suffered from the impacts of the hurricane.
On the other side of the pond, Mr. Cho, a farmer of tomatoes in Gyeongbuk, South Korea, is considering dumping his tomato crops due to an unexpected oversupply that caused prices to plummet. Nikolai and Mr. Cho both have what each other wants, but trading between the two is almost impossible due to the lack of information available. How can the two businesses be brought together in a trusted environment in order to facilitate a profitable business relationship?
This is typically what information asymmetry looks like to the average buyer and supplier in the food industry. Without a balanced view of the available data, connecting a potential buyer with a new supplier is incredibly challenging. And if the standard supply chain is disrupted it creates an effect that can see the whole chain collapse. That is why companies who can harness the data and then provide a service that creates a trusted connection can prove invaluable to securing the food supply chain globally.
Why solve information asymmetry in the food trading industry?
A solution to information asymmetry will help strengthen the global supply chain while helping prevent a domino effect of asymmetry. For example, a product ranges from grade one to grade ten in terms of its quality. In a stable state, the first-grade buyers (normally the biggest buyer with the highest need) and first-grade suppliers (the ones with the more reliable high-quality product) match, second-grade buyers are matched with second-grade suppliers and so on. If there was a sudden problem with a first-grade supplier, the first-grade buyer will need to source products from the second-grade supplier. The second-grade buyer, whose matched supplier can no longer supply them, will need to source from a third-grade supplier.
As this cycle continues, the supply chain becomes unstable and is at risk of collapsing, whether temporarily or long-term. This is what happened when meat processing plants in the United States were temporarily shut down due to the spread of Covid-19. Plants were hit as thousands of workers tested positive for the virus. Pork processing plants were particularly affected with three of the major factories forced to close. Compared to the year before, beef processing went down 27% while pork processing went down almost 20%, according to the USDA, as reported by CNN.
When products are under-produced in one region due to issues such as climate change or the current global pandemic, there is a tendency to over-produce in other regions, maintaining the total global volume, but local supply can still be dramatically affected. Although the total volume remains relatively static, the makeup of this total volume can vary significantly, and the challenge of trading revolves around the information available. How do the buyers and suppliers know each other exists and at what prices are their products being traded? Information asymmetry in the food trading industry can be incredibly severe and can create considerable swings in product value as a result.
Agricultural products, especially fruits and vegetables, have considerable variations in variety, quality and production. With language and foreign exchange barriers always present, it can be difficult to compare global prices and data. The first challenge is to establish an objective criterion for comparing prices. For example, apples have hundreds of varieties and suppliers scattered around the world in tens of thousands of units. To objectively compare the prices you need to start by categorizing the variety and quality grades of each product and then collect price data. This is facilitated by local knowledge, partnerships with governments and trade associations. The digital transformation of the food and agriculture industry has also had a positive impact, enabling trading platforms to analyze thousands of new sources through machine learning. Platforms such as Tridge also use analog information provided directly from the suppliers that deal directly with us. This data is then all cross-compared to ensure that it is as accurate and reliable as possible before it is uploaded to a platform to enable buyers and suppliers to have better visibility of the product availability and supply.
Another major hurdle is trust. The food and agriculture industry is accustomed to doing business in a face-to-face manner where trust is built over years of trading. As with every industry, there are unscrupulous individuals who will try to manipulate the system for their own gain. However, problems outside of the control of the supplier can also result in products not getting to the consumer. More recently, and as an indirect result of the challenges of Covid-19, many in the industry have seen logistics problems with global shipping being subjected to significant delays. Problems such as these can result in produce rotting by the time it arrives at its destination through no fault of either the buyer or supplier. Any provider attempting to correct asymmetry in the industry is tasked with safeguarding against common issues.
Covid-19 brought about the perfect storm for the food and agriculture industry: no business travel permitted, shipments facing weeks of delays due to container shortages, lack of available workforce to harvest products or to process the raw products to the finished packaged goods. Each of these led to a serious global challenge around food security. Digital transformation can help overcome this by enabling the fulfillment of orders in much the same way that Amazon works. Trading platforms can become the eyes and ears of the buyers and bring significantly smaller suppliers to a global stage to create a new buying economy where supply and demand are both satisfied.
Hoshik Shin