companies in many industries have found they can create value by applying digital and analytics technologies to new business models and product offerings. Now, agriculture players, from farmers to end customers, are discovering that these technologies can play a role in optimizing the fiendishly complex agriculture supply chain.
Using the torrent of data they are capturing, leading agriculture players are following the lead of companies in other industries by building digital twins of their physical supply chains. These virtual replicas enable companies to run simulations and optimizations, leading to significant potential savings on the cost of moving crops through the system.
In this article, we discuss why agriculture supply chains are so complicated and how companies can use digital and analytics technologies to optimize them. Players that employ techniques such as digital twins could achieve a competitive advantage in a challenging market.
Supply-chain processes are inherently complex across industries, with multiple functions interacting with different, potentially conflicting objectives and numerous dependencies between material and information flows. The agriculture supply chain is further complicated by fragmented inbound and outbound networks. The typical agriculture supply chain involves three steps: from farmers to intermediate silos, from silos to transformation plants, and from transformation plants to clients. Each step requires multiple decisions.