Supply chains across nearly all industries are at some point on the “digital transformation” spectrum. The food supply chain in particular, has one of the greatest opportunities to digitize. By moving away from manual and highly insular processes and connecting the various constituents on a single digital “network,” all parties can significantly improve customer service levels and secure and speed up the food supply chain from farm to table. A cloud-based network infrastructure enables all parties to communicate across all marketing and sales channels, calculate the potential business value, model all cross-functional and multi-echelon network process flows and identify the underlying data.
New technologies such as artificial intelligence (AI) and digital consumer-driven supply chains address critical problems that have plagued food manufacturing and delivery for decades, including the lack of collaboration, data latency and lost revenue. By providing a single version of the truth across customers, carriers and suppliers, each digital network is able to run real-time autonomous algorithms that execute and match demand to the supply of goods and services.
Leveraging digitization to drive value
The advent of digitization has also enabled a new category of technology known as digital twins. Gartner defines a digital supply chain twin as “…a digital representation of the relationships between all the relevant entities of an end-to-end supply chain — such as products, customers, markets, distribution centers and warehouses, plants, finance, attributes and weather.” The push to create the digital twin has never been more important, as an article in MIT Sloan Management Review points out, “digitalization and sustainability are two of the most powerful market influences in today’s corporate landscape.”
So, how can companies in the food supply chain digitize the industry while maintaining sustainability? Having the ability to rapidly communicate with partners will help to resolve complex issues quickly as problems arise.
Like most companies, members of the food supply chain still try to manage problems through manual processes such as emails, phone calls and even faxes. All these manual processes lead to delays in the exchange of information, which makes it difficult to resolve time-sensitive disruptions, as in the case of a spike in demand, which leads to a stock-out. Problems within the food supply chain can be complicated to solve, because there are three or more parties involved in the transaction, and even more in the workflow across multiple tiers in the supply chain. As a result, these problems must be identified and resolved in real time, rather than the next day when it is too late to avoid a significant and possibly brand-altering issue.
Faults in the food supply chain
Typically, the way demand is communicated today takes an exorbitant amount of time. Point of sale data is put into memory where it runs overnight. The next day, the information is extracted and placed in a spreadsheet that is sent from the restaurant or grocer to the distribution center. The data is then aggregated into another spreadsheet or format usually taking another day, which is then communicated to the next tier, such as the co-packer. Finally, this demand signal makes its way to the end supplier; the farmer. The delay in the sharing of information results in a total lag time of four days.
This delay in communicating the demand signal requires suppliers who are further away from demand to hold higher levels of safety stock in order to provide higher service levels. This creates a cascading effect known as the “bullwhip effect,” where uncertainty and variances are amplified up the supply chain, leading to increased precautions, such as high levels of safety stock.
As one gets further away from the demand, higher inventories are required, which means food tends to be less fresh and needs to be frozen. The result? Food waste increases and the financial and environmental costs begin to take their toll.
The United Nations estimates that of the roughly one-third of the food produced in the world for human consumption every year -- approximately 1.3 billion tons — gets lost or wasted. To solve the complex problems facing the food supply chain, many trading partners are now creating a single, collaborative network across the supply chain. With a secure permissions-based framework, these digital networks enable partners to share their data in real time to create a single version of the truth and leverage AI and machine learning to holistically optimize the end-to-end supply chain.
Matching supply to demand across tiers
In order for AI and machine learning to make an impact on high inventory levels across the supply chain, intelligent agents need to run across the connected network of participants to translate demand into the appropriate units and amounts from the point of consumer demand all the way to the end supplier.
For example, the restaurant sees they will need five cases of steak. The distributor sees two pallets are needed to meet demand. While the co-packer also sees demand through their perspective, they also know they will need to provide that distribution center with two pallets, giving the co-packer time to collaborate with their raw material supplier, transportation department and labor schedule. This demand is translated all the way to the farmer, who now understands precisely what demand looks like today and into the future with greater accuracy than ever before.
Creating value for all
Translating and communicating real-time demand down multiple tiers and across the food supply chain also affords each partner more lead time, which means more options, allowing supply chain teams to get creative. With more lead time, food can be put on a rail, minimizing costs and carbon footprint. Every partner at every step in the supply chain has a clear understanding of what demand is, so partners can optimize to meet consumer demand, ensure high service levels, and lower unnecessary inventories. The instantaneous communication of data based on permissions and with the help of AI, brings down demand variability and allows all trading partners to collaborate more effectively, reducing supply variability for all.
For instance, restaurants and grocers can automate replenishment by using intelligent agents to place orders with greater accuracy, which optimizes inventory levels at the store to meet consumer demand. This frees up managers to focus on improving quality and the customer experience. While improving service, they are also reducing inventories, eliminating expedites and inter-store transfers, reducing waste, as well as increasing revenue due to higher service levels.
The distribution center benefits by lowering transportation costs, eliminating expedites, carrying less inventory, and reclaiming space for a richer variety of products. It also improves efficiency and increases distribution centers throughput by prioritizing shipments based on demand. Suppliers also enjoy reduced transportation costs and fewer expedites as they too get more accurate forecasts and orders and can therefore better plan raw materials and labor.
Driving digital transformation
Key to the wide adoption of a digital ecosystem is the digitalization of the entire supply chain, so that all partners can act as their own “hub” and use networks services to deliver value for their customers. Each of the food supply chain participants can act as a seller, buyer, distribution center or retailer, all at the same time. A true supply chain network “understands” and coordinates the roles and relationships and can look outside the four walls of the enterprise to share data holistically across every tier in the food network for everyone’s benefit, including the most important one--the customers. While digitalization cannot happen all at once, businesses should get started now so they do not leave profits on the table.
