How AI is Transforming Supplier Risk Management in Retail & CPG

In addition, external factors such as the pandemic, geopolitical conflict and climate change have profoundly elevated the level of scrutiny that companies place on their suppliers and global supply chains. With billions of dollars on the line, better management of supplier risks is critical. However, comprehensive supplier risk management has remained out of reach for most organizations – an excellent idea but either too expensive or incomplete.

Enter Artificial Intelligence (AI): New technology is revolutionizing supplier selection and risk management, offering new, proactive ways to tackle the challenges of a 21^st century supply chain.

A survey by Deloitte¹ revealed that 70 percent of CPOs indicated an increase in procurement-related risks and supply chain disruptions. The same study identified AI-led supplier management as the foremost procurement strategy to unlock value. Moreover, a recent McKinsey survey² on Generative AI (Gen AI) reported that respondents experienced revenue increases exceeding 5 percent in supply chain and inventory management.

AI can automate large parts of supplier evaluation and qualification by analyzing supplier profiles, compliance data and certifications, financial data and performance metrics. AI-based analytics platforms can integrate various information about suppliers and, crucially, keep track of changing circumstances to ensure risk evaluations remain continuous rather than happening at a single point in time. This helps companies identify reliable and high-quality suppliers more efficiently and respond nimbly to any changes in supplier risk profiles.

Koch Industries⁵ uses an AI-powered tool to optimize its supplier base by analyzing granular data at the Stock-keeping Unit (SKU) level, unlike traditional procurement methods focusing on high-level purchasing categories and aggregate spending. This tool ingests comprehensive datasets, including supplier information, purchase orders, invoices and previous unsuccessful quotes, to offer detailed insights into qualified suppliers and identify backup options within the existing supplier network, thereby minimizing the need for lengthy Request for Quotes (RFQs).

One of AI's most significant impacts on supplier risk management is its ability to conduct continuous risk assessment and monitoring. AI can track supplier performance, market conditions and any external factors impacting the supply chain in real-time. Next-gen, AI-led risk monitoring platforms surpass traditional methods, incorporating recent incidents, operational intricacies, financial stability and cybersecurity considerations into a comprehensive evaluation of suppliers’ risk profiles.

By utilizing predictive analytics, AI identifies potential risks, such as geopolitical issues or natural disasters, and provides early warnings to companies. For example, a supplier's exposure to conflict zones like Ukraine or Russia can disrupt supply chains, as seen with commodity shortages. AI’s real-time monitoring and early warning systems help mitigate such risks effectively.

In another example, WNS collaborated with a leader in frozen foods, leveraging an AI-driven 360-degree and continuous risk intelligence platform to enhance supply chain management. This advanced technology streamlined the supplier network, identified potential risks and allowed the company to proactively adapt to market demands. The platform's comprehensive approach ensured a robust and responsive supply chain, capable of addressing various challenges while maintaining optimal performance.

AI-enabled chatbots and virtual assistants can more efficiently manage routine supplier inquiries, streamline communication and resolve issues. This automation frees up human resources to concentrate on strategic supplier relationships and value-added activities. While self-service portals have long assisted category and risk managers with supplier data on demand, adding AI chatbots allows for more specific and granular analysis, enhancing the overall supplier management process.

Walmart⁶ uses AI-powered chatbots to automate negotiations with "tail-end" suppliers, which account for around 20 percent of its expenditures on low-value items. This AI-driven approach streamlines the procurement process, making it more efficient by handling negotiations that would typically require significant time and effort from human employees.

AI algorithms can optimize supply chain networks by considering factors like supplier capabilities, lead times, transportation costs and demand fluctuations. By simulating different scenarios and analyzing historical data, AI helps companies make better-informed decisions about supplier selection and inventory management. For instance, in 2021, Home Depot leased its container ship to navigate pandemic-induced shipping disruptions, ensuring timely product delivery for the holiday season. This type of strategic decision-making, supported by AI-driven scenario analysis, can significantly enhance supply chain resilience.

Home Depot⁷ is now leveraging cloud-based Google AI technologies, such as ML, computer vision and Gen AI, to enhance its inventory management operations and improve overall supply chain efficiency.

Looking Ahead

AI is enabling retail and CPG companies to make better data-driven decisions, select the right suppliers, mitigate risks, maintain efficient supplier relationships and enhance the resilience of their supply chains. As AI evolves, its integration with human expertise will be pivotal in driving the future of supplier risk management in these industries.

The nature of work within supplier management will undergo rapid transformation alongside technological advancements. Manual work will be dramatically reduced; rich, real-time insights into supplier capabilities and risk will become more accessible. These insights will need to be analyzed and acted upon. AI will elevate what supplier management can achieve, transforming the expectations and responsibilities of supplier management professionals.