On May 1, at Collaborate, our UK customer event, Anthony Plummer, Group CTO outlined our plans for harnessing AI and big data to transform supply chain management, before we then welcomed a panel of experts to discuss this topic further.
Embracing the ‘fourth industrial revolution’
Anthony began by highlighting the rapid evolution of AI and its significant impact on data utilisation. He pointed out that the current shift is not merely a technological upgrade but a profound change in how industries operate. By leveraging AI and big data, businesses can transition from reactive to proactive models, predicting future trends rather than just analysing past data.
Key points of focus
Anthony identified three key areas where AI and data are set to make substantial impacts to supply chains:
1. Improving supply chain visibility
Although supply chain visibility is not new, the integration of AI and predictive models allows for much more precise forecasting. Static dashboards are becoming obsolete; real-time, dynamic data is now essential for effective decision-making.
2. Inventory management
AI enables dynamic inventory management, allowing companies to respond in real-time to disruptions. Anthony illustrated this with examples of how delays in shipping can be mitigated by adjusting stock levels upstream, ensuring optimal inventory flow and minimising costs.
3. Cost reduction
Through AI and emerging technologies, companies can significantly reduce costs by minimising obsolete stock and optimising logistics. Anthony emphasised that this also ties into improved end customer satisfaction, as efficient supply chains better meet customer demands.
Addressing global disruptions
Anthony discussed the myriad disruptions facing global supply chains, from natural disasters to geopolitical events. He stressed the importance of data in navigating these challenges, advocating for strategies such as diversification of suppliers, increased automation, and comprehensive risk management. By leveraging AI, businesses can anticipate potential disruptions and devise more effective contingency plans.
Future directions: insights and predictive analytics
Anthony introduced the audience to several initiatives aimed at transforming supply chain processes at Ligentia:
We put containers on ships and load them in CFSs, do customs clearances, move them on trucks. But our job at the end of the day is managing your inventory. At the heart of what we do is making sure that your stock is in the right place at the right time and in the right levels… and it’s this live optimisation of inventory that we’re really keen to drive.
Collaboration and feedback
Anthony concluded by saying that collaboration is key to refining these technologies and strategies. As he handed over to the panel discussion, he left the audience with a clear message: the journey towards a data-driven future is just beginning, and it promises to be an exciting and transformative path for all involved.
His emphasis on proactive management, real-time data, and collaborative innovation sets the stage for a new era of efficiency and resilience in supply chain operations.
Meet our panellists
The panel brought together a number of industry experts and partners of Ligentia to explore how AI can revolutionise supply chain management. We were privileged to be joined by:
And the panel was moderated by Ligentia colleague and Automation Business Analyst, Ellie Allday. Thank you so much to the panellists for their contributions and their time.
Here’s a summary of the key points discussed by the panellists, highlighting their insights and practical examples, including timestamps from the video should you wish to watch the points in full.
AI’s role in predicting disruptions
Joseph emphasised the challenge of predicting disruptions, citing the unpredictability of events like the Suez Canal blockage and the COVID-19 pandemic. He argued that AI’s strength lies not in forecasting these disruptions but in predicting their impacts. AI can analyse vast data sources to assess how disruptions affect customers, suppliers, and specific products. This capability enables businesses to better understand and manage the ripple effects of disruptions, making supply chains more resilient. (play at 3.19)
The practical applications of AI in inventory management
Tom highlighted a practical application of AI in managing inventory during crises. He recounted an example involving a UK retailer facing skyrocketing container costs for importing Christmas trees. AI could have helped predict the necessary inventory adjustments, avoiding overstocking and financial loss. Such real-world scenarios demonstrate AI’s potential in enhancing decision-making processes by quickly analysing data and providing actionable insights (play at 4.51).
Addressing misconceptions and building trust in AI
Ellie discussed the common misconceptions about AI, particularly the fear that it will replace jobs. She stressed the importance of educating people about AI’s true role: augmenting human capabilities rather than replacing them. Ron likened AI to a toaster—people care about the results, not the inner workings. This analogy underscores the need for businesses to focus on AI’s outcomes and its alignment with their goals (play at 7.10).
Challenges in implementing AI
Anthony pointed out that stakeholder management is a significant challenge in AI implementation. He emphasised the importance of bringing everyone on board and assuring them that AI is there to support, not replace, their roles. Additionally, he noted that AI solutions need to be tailored to fit the specific needs of different customers, such as those in fast fashion versus food industries. Customization ensures that AI applications are relevant and effective across diverse business contexts (play at 18.32).
Process mining for efficiency
Joseph also explained the concept of process mining, which involves tracking log data to monitor and optimize processes. This technology has evolved to support real-time monitoring and predictive analytics, making it valuable for supply chain operations. By identifying inefficiencies and predicting future steps, process mining can significantly enhance supply chain efficiency, especially in shipping and warehousing processes (play at 20.10).
Collaborative approach to AI solutions
The panellists agreed on the importance of collaboration between technology providers and industry experts. Ron emphasised the need for a deep understanding of specific business problems to develop effective AI solutions. By combining expertise in technology with domain-specific knowledge, businesses can achieve significant leaps in innovation. This collaborative approach ensures that AI solutions are not just digitising old processes but creating entirely new ways of operating (play at 34.25).
Conclusion
The panel discussion shed light on the transformative potential of AI in supply chains, from predicting the impacts of disruptions to optimising inventory management and enhancing process efficiency. By addressing misconceptions and focusing on practical applications, businesses can build trust in AI and leverage its capabilities to create more resilient and efficient supply chains. The key takeaway is that AI, when implemented thoughtfully and collaboratively, can drive substantial improvements in supply chain management.
Watch the full panel recording
