Now more than ever, a product’s “history” (details of how it was made, where it has been, how it was sourced, etc.) is being scrutinized as closely as the price tag. Consumers and companies are demanding ethically sourced, sustainable products; in fact, both are increasingly changing their purchasing preferences to reflect these factors. An EY study revealed that 42% of consumers are willing to spend more for products produced sustainably. Regulatory authorities are increasingly requiring companies to disclose sourcing practices. For example, final rules released by the Internal Revenue Service on May 3, 2024, on the clean vehicle provisions of the Inflation Reduction Act, incentivize companies (and consumers to whom the credits can be reimbursed) that pass the “traced qualifying value-added test.” Supply chains today are global, complex and ever changing. With supply chain disruptions becoming increasingly common, companies are often exposed to significant operational and reputational risks.
Supplier traceability is defined as the ability to identify and track the entire movement of raw materials. From cultivators and extractors to material processing, traceability allows companies to follow material around the globe from company to company and gain the transparency that is increasingly becoming a requirement. Companies have been interested in traceability programs, with interest surging strongly post-pandemic; however, historically, traceability has not been feasible. Slow global adoption of digitization has meant that data collection, storage and transmission are performed manually, with varying global standards. Additionally, available technology solutions were often impractical; bespoke platforms required broad stakeholder consensus and were expensive to implement, requiring multiple years to complete. There are also significant ongoing requirements, including heavy supplier dependency to effectively maintain the data (including Tier 2+ suppliers), as well as intercompany cybersecurity and administration constraints.
What are the different maturity levels of supplier traceability?
Supplier traceability maturity levels encapsulate the evolution of a company’s ability to oversee and manage its supply chain with increasing sophistication and foresight.
Level 1: Monitoring. The focus is on establishing automated systems for 24/7 risk monitoring and alerting. This stage involves the stratification and prioritization of risk alerts to manage the vast amount of data efficiently. Companies at this level benefit from visualization tools that map out networks and risk impacts, providing a clear overview of potential vulnerabilities.
Level 2: Predicting. Companies leverage advanced analytics to forecast performance and potential disruptions. This predictive capability extends beyond the typical 30-60-90-day outlook, offering a more strategic view of the supply chain. “What-if” scenario planning becomes a critical tool, enabling companies to anticipate and prepare for various contingencies.
Level 3: Mitigating. The maturity level is characterized by well-defined governance processes that address both known and unknown risks. This stage is about moving from reactive to proactive, with strategic actions designed to protect the long-term supply. Companies at this level have established robust frameworks for mitigating risks, verifying that they can maintain supply chain integrity and continuity even in the face of unforeseen events.
![](https://www.scmr.com/images/2024_article/EY_supplier_levels.jpg)
The EY Supply Chain and Operations Platform addresses the key problems that the industry is facing in getting to the monitoring traceability maturity level. The platform empowers supply chain teams with unparalleled visibility, decision intelligence and better cross-functional optimization to create business value. As a unified artificial intelligence (AI)-driven solution, it realizes the power of end-to-end curation of data across enterprise systems, planning systems and custom applications to drive actions.
![](https://www.scmr.com/images/2024_article/EY_image_2.jpg)
How can recent technological developments help accelerate the maturity journey?
Recent developments in technology, such as the rise of AI and enterprise data quality, are helping organizations gain insight into supply chains more feasibly than ever. Data is more accessible than before, from publicly available information on social media platforms, to government agencies, to companies specializing in specific raw materials. However, data sources have proven one-dimensional, with some focusing on disruption risk while others assess working conditions and sanctions, necessitating the use of multiple data sources. Often, companies, through only a handful of cost-effective data vendors, can access thousands of data sources to perform holistic risk assessments. Effectively analyzing and consolidating that information, from thousands of possible data sources, has previously proven challenging for companies to derive signals from noise.
AI is becoming increasingly effective at defining action-oriented insights and, eventually, using machine learning models, in predicting disruptions over time while also working to assess drivers of disruption more accurately. While not as precise as direct supplier integration, AI solutions can be implemented today and sidestep many of the existing traceability challenges, including supplier dependency, cybersecurity risk and challenging multiyear implementations. For example, leading market tools provide a multidimensional overview of the constant stream of threats from the increasingly complex ecosystems risks, allowing organizations to continuously assess strategic, economic and operational-related threats and implement mitigation strategies.
Who should lead the company’s traceability journey?
To lead the company’s traceability journey, chief supply chain officers (CSCOs), chief procurement officers (CPOs) and enterprise risk leaders should harness the power of AI. AI can not only predict disruptions and risks in the supply chain but also support strategic decision-making. The aforementioned business leadership can drive this transformation by implementing robust governance frameworks, enabling them to redesign their organizations with enhanced due diligence during vendor assessments and improved risk management processes.
By identifying key risk drivers, companies can utilize third-party data providers to train machine learning models, generating specific insights tailored to their supply chains. AI-driven predictive capabilities are highly effective in forecasting supplier risks before they occur and providing a comprehensive evaluation of supply chains across various risk factors.
Conclusion
As traceability programs become a business requirement, the appropriate platform combining publicly available data and AI tools can enable companies to move beyond base-level traceability. Technological advancements are enabling corporations to identify root causes of risk in their supply chains and, over time, begin to predict where and when disruptions will happen. Supply chain, procurement and enterprise risk organizations can collaborate to use this information proactively as they seek to reduce supplier risk, redesigning their supplier base to reflect desired risk profiles more appropriately. Now is the time for companies to act by leveraging AI-driven predictive insights and implementing effective governance to mitigate supplier risk proactively.
The views reflected in this article are the views of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.
About the authors:
Venkat Maddila is a trusted executive advisor specializing in the definition and execution of supply chain strategy, M&A and has experience working globally with industrial clients.
Travis Wolf is a partner/principal in EY’s Supply Chain practice, focused on helping our clients achieve a resilient and flexible supply chain through the power of process and digital transformation.
Carl B. March is a manufacturing transformation leader at EY. He works with manufacturers to architect, accelerate, execute and scale their most ambitious manufacturing transformation visions.
Anthony Mubarak is a partner/principal in EY’s Supply Chain practice, focused on separating their supply chains on global carve-outs and helping clients design their end-to-end supply chain and transformation roadmaps.
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![As traceability programs become a business requirement, the appropriate platform combining publicly available data and AI tools can enable companies to move beyond base-level traceability.](https://www.scmr.com/images/2024_article/GettyImages-traceability_2.jpg)
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