With digital opportunities sweeping the supply chain landscape, preparedness and line-of-sight will be paramount to the success of food companies. Rapidly evolving technologies such as generative AI, data analytics, automation, block chain are shaking up the “smart” supply chain.
A quick look at the 2024 “Top Food Chain Technology” list by Food Chain Digest (the official magazine of Food Shippers of America) gives you a rare review of some of these sophisticated technology platforms. In reflecting on this list, here are some of the big trends, benefits and actions food shippers can find in the current digital shake-up:
GenAI is a subset of Artificial Intelligence (AI) that has the potential to revolutionize food chain management, procurement, transportation and logistics. Software engines powered by GenAI can process much larger data sets than previous forms of machine learning and can analyze an almost infinitely complex set of variables. GenAI can also learn —and teach itself — about the nuances of any given food company’s supply chain ecosystem, allowing it to refine and sharpen its analysis over time.
The list of opportunities for GenAI is extensive. It can help to ensure procurement and regulatory compliance, streamline manufacturing production workflows, and enable logistics communication by using virtual assistants to handle routine inquiries and provide quick responses.
While use of AI is an enterprise-wide consideration, food companies should avoid dissipating effort across several single point disconnected AI implementations. Core supply chain and business processes should be strategically rethought and redesigned to effectively leverage GenAI.
Food shippers would be wise to build a clear business case for each application planned in this area, and should illustrate how AI improves productivity of supply chain employees, inventory, assets, and the estimated financial impact to operations. Food shippers also should re-evaluate current supply chain analytics processes and platforms to assess an AI upgrade to improve these.
Data is one of the core challenges facing food chain management. Each day, millions of data records are generated across supply chains from multiple systems – and the proliferation of digital technologies, IoT devices, and advanced tracking have compounded the problem. The wealth of data has created greater data silos within the organization which has resulted in disconnected data sets, along with duplication and misinterpretation of data.
Consequently, availability and quality of data as well as cadence and consistency now are critical considerations for supply chain managers. They must efficiently manage complexities within their data landscape to be able to make informed and intelligent supply chain decisions.
Many food shippers are adopting a use case-driven approach to proactively address data quality issues. As a result, they can prioritize data quality improvements where they matter most, thereby gradually refining and improving their data sets.
Lack of visibility across the layered tiers of supply chains has major implications for food companies, particularly in meeting regulatory requirements and mitigating risks. Breaking the barrier of visibility beyond Tier 1 enables food companies to view across their extended supply chain into partners, increase more meaningful insights into root causes of problems, anticipate new risks, and enhance the ability to meet ESG goals through improved traceability and transparency.
Successful food shippers are moving toward a more collective and data-driven approach by using technology solutions and partnerships. By doing so, they can extend visibility of product flows to develop more comprehensive views of their supply chain ecosystem. They’re also creating cross-functional teams to provider a more clear picture of key use cases, the scope of visibility, and surfacing downstream food chain problems.
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