Developing Supply Chain Resilience Capabilities with AI

Data lies at the centre of AI. But ‘having data’ in itself is not enough to build a resilient supply chain. AI needs massive amounts of data and even bringing data together from different sources poses challenges because of a lack of standardization and governance structures like policies, procedures and protocol.

Dr. María Jesús Sáenz’s wrote this whitepaper to bring some direction to procurement leaders and changemakers. Her whitepaper is a fantastic contribution that brings some much-needed clarity and evidence around AI to the procurement industry.

Dr. María Jesús Sáenz’s thought leadership comes at a time of great uncertainty in the world. In a post-covid era, AI tools have taken the world by storm, but many organizations are still struggling to find ways to use it most effectively. That’s why I’m so excited that we are able to partner with María and publish her expert opinion.

There are a few key points that I want to highlight from the report around the opportunities and use cases for AI, what we can learn from disruption and how AI-powered tools can make data accessible and actionable.

My favorite insight from this whitepaper it that organizations can leverage AI-tools for predictive capabilities and develop mitigation strategies before disruptions occur. This enables forward-thinking leaders to make supply chain resilience an innate capability.

Opportunity and use case

Like María, I see a big opportunity with AI in its ability to aggregate data, analyze it and produce actionable insights. AI-enabled tools can accurately collect the different features (economic, sustainability, global, geographic, etc.) of each of the supply chain actors - suppliers, manufacturers, customers, logistics service providers, etc. - that can shape the risk profile of each node and the holistic supply chain as a whole. This greatly reduces risk of disruption and develops supply chain resilience.

What we can learn from disruption

To say that the last few years have been disruptive is probably an understatement. So, what can we learn from it and be prepared for future events?

AI can play a crucial role in identifying the root causes of disruptions and expediting recovery by providing insights that empower supply chain managers and executives to better understand the variety of disruptions and their context.

AI enables informed choices about the best suppliers and facility locations and, especially during crises, facilitates optimal predictions, distribution strategies, and inventory levels based on extensive data modeling.

While this can help you prepare for an event, it can also help to respond to it. Identifying the source of disruptions early is key to a fast operational recovery.

How AI-powered tools can make data accessible and actionable

AI-enabled tools can aggregate, analyze and offer actionable insights into supplier performance, market conditions and other relevant data that could impact your suppliers.

The predictive capabilities of AI can support quantifying critical key performance indicators to develop supply chain resilience, such as time to recovery, time to survive or value at risk, which measure the potential and real economic losses given a potential disruptive scenario.

A central theme of the whitepaper is the power of predictive capabilities of AI to help organizations identify and mitigate potential supply chain risks based on real-time evidence. With AI-enabled tools, we can aggregate and analyze supplier data, save time and effort on data management and get to market faster by finding new and innovative suppliers quickly and efficiently.

I hope that you get as much value from this whitepaper as I did. Download and read the full document here.