Today’s supply chains face an increasing number of threats from natural hazards to geopolitical conflicts to cyberattacks. Let’s look at some of the key considerations companies need to think about as they seek to consider the role of AI-driven supply chain risk management to not only protect and enhance their bottom lines, but also develop stronger relationships with suppliers and customers.
GET THE INSIGHTS
FOR MORE CONTEXT
Supply chain risk management was not always as complicated as it is today. The earliest form of the discipline began as a way of monitoring the financial health of first-tier suppliers in an organization’s network. By keeping tabs on the financial performance of those they did business with, organizations had a decent grasp of when and how they would need to adjust their relationships and practices.
Over time, the discipline evolved to incorporate factors such as natural disasters or geopolitical tensions. Added criteria like this sharpened risk profiles; organizations now have a deeper and more nuanced understanding of the forces impacting their supply chain, as well as insight into how to adapt.
In the 20-teens, non-physical considerations such as environmental impacts and human rights issues entered the picture. Now it’s not just a matter of financial performance, but a question of all the company’s business practices — are they ethical? Are they in line with what’s best for the planet? Finally, the supply chain disruptions caused by the COVID-19 pandemic were a tremendous wake-up call to organizations, sending deep supply chain visibility from a nice-to-have to a need-to-have.
With all these added layers of complexity, organizations require more sophisticated approaches to supply chain resilience. Hence, the growing role of AI-driven supply chain risk management.
WHAT YOU NEED TO KNOW
Supply Chain Intelligence: The Value of Premium Data Sources
As AI continues to play an increasing role in supply chain risk management, high-quality data is becoming ever more important. Layering in third-party premium data adds fidelity and accuracy to risk alerts. Data quality matters both in terms of identifying immediate supply chain threats in real-time, but also looking back in time to clarify how exactly a certain threat arose.
These third-party premium data sources can provide organizations with deeper insights due to dedicated analyst teams, domain expertise and robust methodologies. For instance, every single premium data vendor has a dedicated team of analysts, dozens if not hundreds of experts, focused on gathering, verifying and improving the quality of that data. They have deep domain expertise and models and methodologies that have been developed over the course of years which can result in much better insights, as well as greater noise cancellation.
Conversely, public data sources are often available for free, but sometimes they aren’t as up-to-date and lack the kind of highly evolved processes to get to the best quality insights. In many cases, they are no different than what you’d find in your Google News feed. Furthermore, these data sources may also lack the sector specificity that can be so consequential in helping an organization understand the landscape in which it is operating — and ultimately how that affects its supply chain operations.
Take premium financial data, for instance. An organization can look, say, 12 months or more into the future and see an insolvency coming well in advance. Getting these early warnings well in advance of an incident allows a team to course correct, and, in this case, perhaps look for an alternate supplier or make other strategic adjustments. In other words, premium data means far fewer surprises.
Mapping the Terrain: Adding N-tier Visibility
We’ve touched on the need for premium data sources in supply chain intelligence. But how deeply does that data reach into a given supply chain? AI is at its most powerful when it can work within the complete structure of the supply chain, including sub-tier visibility.
Complete sub-tier visibility includes everything beyond an organization’s first tier of direct suppliers. Sub-tier visibility helps you identify critical dependencies and risks. For instance, in one project, Sphera uncovered that three of our client’s alternative suppliers relied on a single tier-2 supplier for a critical material, creating a dependency that could stifle our client’s production flow of goods should that specific supplier become unable to fulfill its role. Understanding such bottlenecks allows a business to proactively address risks and avoid disruptions.
Sub-tier visibility isn’t just about regulatory compliance. It allows companies to plan better, forecast risks and develop scenarios to mitigate those risks. It also helps companies build more comprehensive supplier profiles, understand where their supply chain weaknesses are, and identify opportunities for improvement. A holistic picture of your supply chain empowers data-driven decisions that lead to better outcomes.
The Human Touch: The Need for Expert Validation
In the context of supply chain management, the AI pros are as powerful as the cons are dangerous. AI can serve as an unprecedented boon to supply chain leaders. By rapidly and automatically assessing factors ranging from regulatory shifts to weather events to geopolitical issues, these tools can predict disruptions and equip supply chain leaders with information to side-step potential risks and maintain business continuity.
However, AI can also backfire and end up overloading leaders with irrelevant or worse, inaccurate information regarding their supply chains. This is why AI works best when it’s paired with human expertise. Furthermore, experts add a layer of noise cancellation to the alert process. In many cases AI will alert you to hundreds of issues, but with added human validation, you are only alerted to true risks to your supply chain.
When experts vet recommendations surfaced by AI, that’s when the technology achieves its fullest potential, fast, accurate, and capable of providing unprecedented supply chain visibility.
Working Together: Supplier Collaboration Software
Gone are the days of suppliers existing as a mere means to an end for an organization. Nowadays, they’re part of the rich, complex and ever-evolving operational ecosystem. As we alluded earlier in this article, supply chain risk management used to be about merely monitoring the fiscal performance of your suppliers. Things are vastly different now, and monitoring is no longer enough: direct supplier collaboration is vital to a healthy and resilient supply chain. Supplier collaboration software can make this possible, facilitating a dialogue between an organization and its suppliers, as well as assessments that can help gauge risk in an accurate and direct manner.
To put it another way, it’s not just about applying pressure to suppliers to improve; it’s about making suppliers part of the solution. Being involved in the process provides them with advantages too: being more transparent can give them a competitive advantage, attract more business and strengthen supplier relationships. Plus, many businesses introduce incentives to suppliers like longer contracts, higher volumes of goods purchased, or the opportunity to work collaboratively on product development.
Ultimately, this is a win-win arrangement for everyone involved.
HOW SPHERA CAN HELP
By integrating Supply Chain Sustainability (SCS) and Supply Chain Risk Management (SCRM) into one platform, Sphera’s Supply Chain Transparency (SCT) product line provides organizations with end-to-end visibility across the entire supply chain to effectively manage supply chain risk, sustainability and regulatory compliance.
Our advanced AI technology, premium data sources, N-tier mapping capabilities, team of risk assessment experts, supplier collaboration features and more come together to deliver AI-driven supply chain risk management for the modern organization.
Learn more about Sphera Supply Chain Transparency now.
