The supply chain industry stands at a critical juncture, where the embrace of cutting-edge technology and data-driven decision-making has become indispensable for its very survival. The days of adhering to conventional models and processes are now unsustainable.Industry expert Lora Cecere, founder of Supply Chain Insights, emphasises that thriving in the contemporary landscape demands more than just a commitment to technological progress. Organisations must also fundamentally reconsider their approach to supply chain management.During a recent online event focused on practical AI applications in the supply chain and the delicate balance between value and risk management, Cecere and Jim Lee, the managing director at KPMG, discussed the impact of generative AI tools. These tools possess remarkable capabilities for human-like communication and sophisticated analysis, which have added complexity to the AI landscape. In today's fast-evolving business environment, it is becoming increasingly clear that the supply chain industry must leverage these emerging generative AI tools to maintain competitiveness.According to Lee, non-generative AI tools have played a pivotal role in advancing the supply chain. They have significantly enhanced predictive analytics and increased the responsiveness of supply chains by optimising essential functions like demand planning, inventory management, and logistics. "In supply chain planning, for instance, we've achieved a level where software processes are deeply embedded, indicating a mature stage, yet there remain numerous emerging AI use cases within the supply cha i n."He said room for improvement, especially in the field of transportation, existed. As an illustration, Lee shared a recent project he was involved in, demonstrating the potential of machine learning. He described how machine learning techniques could be utilised to predict carrier behaviour, such as whether they would accept or decline a tender. Cecere highlighted that the industry was currently experiencing a rapid evolution in technolog y, characterised by a hype cycle. She emphasised the need for companies to fully embrace Web 2.0 technologies such as machine learning and Nara AI. Moreover, she stressed the importance of moving away from the constraints of relational database frameworks, where the focus is on achieving perfection in data and answers. Instead, she advocated for a shift towards enhancing supply chain responsiveness within the dynamic and uncertain environment in which it operates.Drawing a comparison between technology adoption and automobile evolution, Cecere astutely pointed out that no one would buy a 1930 jalopy and install an electric vehicle engine in it today."However, in the supply chain, this is precisely what many companies do. They rush to adopt advanced technology without giving due consideration to the underlying models and the desired outcomes. It's high time we shed the misconception that efficiency alone equates to effectiveness in the supply chain. We must open ourselves to external signals that we currently overlook. This transformative shift in how we redefine work within the supply chain is undeniably more challenging at the moment than simply implementing new t e ch nolog ie s."
