Online shopping has become a daily routine in our lives. It is no longer surprising to buy the goods before going to bed and receive the package as soon as you wake up. A real surprise is the logistics system behind it. How do companies predict what consumers will order, prepare inventory, and send deliveries?
All these delivery processes are possible with the utilization of data. A great deal of data is accumulated from various sources every day, including destination, product information, and delivery schedules. Through this data, companies predict delivery areas, order times, and product quantities. Based on the results, decisions are made on warehouses that store products. This is called a ‘smart warehouse’ and it allows companies to easily monitor or maintain the availability of stocks.
Other than the low availability of stocks, the bottleneck is one of the factors that hinder fast delivery.
Therefore, suppliers use big data for route optimization. Big data collects and analyzes information on weather and traffic to assign the shortest route to delivery vehicles. By using these data, suppliers can save a great amount of transportation costs and improve interoperability. In response, consumers can receive the goods they ordered at the expected arrival time.
E-commerce has grown as social distancing and non-face-to-face life have become standard practice. Consequently, logistics accounts for a large proportion of consumer satisfaction and supplier’s responsibility. As punctuality and transparency has become important, companies are focusing on the combination of data technology and logistics services. This is not a temporary trend but is recognized as a major field of the market that will continue to be developed onwards. According to the research, the supply chain big data analysis market was estimated at $3.55B in 2020 and it is expected to grow to $9.28B by 2026.
Most logistics companies already employ data-driven logistics strategies. Coupang is a Korean company that succeeded in enhancing delivery efficiency by using data. Coupang analyzes data on consumers’ purchasing patterns to figure out the product sales depending on the region. Following that, Coupang AI analyzes and arranges the location of all products in real-time so that they can be delivered with the best time and space efficiency. Rocket delivery, which completes delivery in just a day, is based on this kind of big data application process.
Logistics startups that utilize AI and big data technologies are also expanding steadily. According to the Korea Transportation Institute’s “2019 Logistics Startup Business Survey,” the number of logistics startups in 2018 was 151, more than tripled from 40 in 2015. Currently, it is estimated that there are more than 200 companies in logistics startups.
Techtaka, one of the logistics IT startups, has contracted with several distributors to expand its activities in the logistics market. Techtaka is operating a logistics platform called ‘ARGO’ that integrates and provides all IT systems necessary for e-commerce logistics. “ARGO” connects multiple IT systems to a single platform and automatically connects data at all stages from product registration to order and delivery.
In addition to domestic delivery, cross-border e-commerce, which buys and sells goods worldwide, is growing very rapidly. However, the process of transporting cargo overseas is very complicated and difficult. To solve the difficulties of international logistics, cross-border e-commerce logistics platforms that effectively combine various sales channels, delivery companies, and means of transportation are emerging. The platform links channels and processes based on data. Then, the integrated data is refined and the status of sales, orders, inventory, delivery, and costs is reported to the dashboard. Ultimately, it will learn the accumulated data and develop into a model that optimizes inventory and delivery based on demand forecasts.
Big data has become an indispensable element not only in business but also in everyday life. Data will continue to accumulate and will analyze itself more precisely through machine learning. This means that more remarkable logistics advancement could soon emerge. Sooner or later, we can enjoy a more convenient logistics service that will surpass the overnight delivery.
K-UNIV Reporter
Choi Yuna
