Building Resilient Supply Chains of the Future with AI
The practice of outsourcing manufacturing to regions that have skilled labor and lower operational costs has been the norm for as long as we can remember. More recently though, the global supply chain has been adversely affected by myriad black swan events—geopolitical conflicts, natural disasters, the pandemic, labor shortages, and more—which has made it highly risky to continue this practice. As more vulnerabilities are uncovered, supply chains need to rethink their strategies and approach towards planning and forecasting in a way that ensures agility and resilience.
The good news is that new-age technologies like artificial intelligence (AI) have been providing a unique opportunity for relocating production closer to markets, reducing dependencies, and being competitively cost-efficient. Traditionally, most supply chain operations have been carried out using spreadsheet-based analytics, which are now being replaced with AI models. For example, AI-driven forecasting has been advantageous, decreasing occurrences of errors significantly. Such errors would usually result in the loss of sales and product unavailability, impacting the entire supply chain ecosystem.
Simplifying Supply Chain Operations with AI
Admittedly, this new wave of supply chain transformation will take time. Enterprises need to proactively understand the capabilities of AI and advanced digital technologies that can bolster detection, analysis, prediction, and prescription across supply change management systems. This will also ensure improvement in planning and execution as traditional roles within the supply chain organizations are restructured. With machines performing the time-consuming tasks of analyzing, human workers will have more time in hand to take strategic decisions—leading to the formation of self-sufficient, intelligent, and resilient supply chains.
Within supply chain management, core enterprise resource planning (ERP) functions are complex with far too many systems and processes being introduced to navigate evolving requirements and disruptive events. However, the idea of having AI-driven ERP functions in place is to simplify the decision-making process across the supply chain by providing the decision-maker with the right information at the right time. This is what lies at the heart of an agile supply chain, helping operators with the correct data in the desired format that ensures faster, more efficient, and simplified operations.
For businesses, this means not just implementing AI but also establishing a well-defined operational and governance model that is synchronized with AI’s capabilities. Digital algorithms and AI can then be effectively utilized to detect issues before they occur and determine, well in advance, through various simulations, the potential consequences to prepare for.
Realizing the Vision of ‘Intelligent’ Supply Chains
Technology like AI is as good or as bad as its user. To utilize AI’s full potential, one must ensure buy-in from all the stakeholders within the organization and understand the requirements of managing these engines with the right balance of technical skills and high-quality data models. Organizations must also consider developing in-house expertise around this technology, specifically generative AI (GenAI) as foundation models trained with massive datasets from different sources will be leveraged during deployment. This would mean not only broadening the OT and IT budgets but also introducing more learning and training programs to upskill or train the workforce.
The advantages of AI are far-reaching to ignore in the current scenario. In many ways, AI can help remediate technical debt by refactoring outdated code that essentially frees up resources to be used in other areas of supply chain operations. AI and machine learning (ML) can improve visibility with their ability to study diverse datasets of suppliers and consumers, opening new avenues and opportunities. Most importantly, AI can help generate actionable insights around consumer trends, which will go a long way for suppliers and distributors to optimize their inventories. We are amid a paradigm shift –from a reactive, complex system towards simplification, agility, intelligence, and resilience—as enterprises continue to integrate AI and ML in supply chains.
