The pressure for supply chains to meet growing customer expectations is greater than ever before. Customers are now expecting highly digitised, streamlined services that are efficient, accurate, and sustainable. The best-in-class utilising AI are already seeing a 20% increase in customer satisfaction due to improved accuracy and efficiency in service delivery (McKinsey, 2023).
The challenge is, supply chain leaders are being pulled in different directions, not only facing pressure from the boardroom to cut costs but also being hamstrung by the maintenance of legacy systems. Sustaining these outdated systems isn’t just budget consuming, it also prevents meaningful innovation with new technologies like AI. For many, the shift from legacy to AI-driven solutions can seem overwhelming, particularly for those wary of the disruption it might cause. Yet, failing to evolve will not only lead to missed cost-saving opportunities but also risk alienating customers who demand more.
Supply chain leaders cannot afford to be stagnant. So, how can you transform from legacy systems to integrate AI, achieve quick wins, and meet the demands from both your boardroom and your customers?
Dr. Theodoros Lappas is Head of Data Science at Satalia and a globally recognised expert in AI. With over 20 years of experience in the field of data science, Ted has extensive expertise in delivering efficient solutions and value to organisations across various industries. Additionally, he is an Assistant Professor at the Athens University of Economics and Business. He also holds a PhD in Computer Science and Engineering from the University of California. His work has been widely recognised, with his publications being among the highest cited in relevant literature.
Dr. Panagiotis Repoussis leads WPP’s AI Research Lab at Satalia where he acts as tech lead and senior optimisation engineer for key projects in price optimisation, workforce allocation and port operations. With numerous influential papers to his name, he excels in the design, development, and application of computationally intelligent algorithms for robust decision-making in operational planning and resource scheduling. He also holds the position of Associate Professor at the School of Business at Athens University of Economics and Business.
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