Inside the critical role traceability plays in food fraud prevention 

According to the US Food and Drug Administration (FDA), when someone intentionally leaves out, takes out, or substitutes a valuable ingredient or part of a food, it is known as economically motivated adulteration (EMA). One of the most recognizable forms of EMA – and one of the most challenging to prevent – is food fraud.  

One of the challenges when assessing food fraud prevention is frequency – product counterfeiting and food fraud are relatively rare events, which make it hard to predict when such an event might occur in the future. Deep data dives are a preferred course of action in food fraud prevention, and for good reason. The more insight gained from a situation or problem, the more effective a company can be at addressing an issue. But how can companies apply data and key learnings to prevent food fraud when it remains relatively rare in the world today? Typically, a quantitative or statistical model would be employed but with rare events, there will be little to no previous data from which to extrapolate future expectations quantitatively. This quantitative and analytical limitation has led to a focus on prevention and reducing vulnerabilities. Prevention includes a multi-layered approach of activities such as supplier approvals, product authenticity testing, and traceability.   

One step that companies can take to address the toughest food fraud challenges – including concealment, counterfeit, and mislabeling – is to establish an enhanced traceability system as part of a broad food safety management system. Food traceability, in its most basic form, provides information about a product’s history and origin, but its true impact runs much deeper.  

Data dive 

Traceability, data analytics, and systems such as artificial intelligence or machine learning help food fraud prevention, but the key is understanding how the data in hand relates to the specific problem in order to drive informed decision making. But before a deep dive into the data can be conducted, the data must be collected. And that requires traceability.  

Traceability refers to the ability to follow a food product as it moves from its origin through each step of the supply chain (i.e., farm to fork). The ability to do this

requires a foundation of data capture and sharing throughout the product’s life cycle. The foundation of traceability system development begins with the identification of Key Data Elements (KDEs) and Critical Tracking Events (CTEs), which together provide a structured approach to capturing and maintaining product movement and identity throughout the supply chain. CTEs represent key events in a product’s life cycle where data must be collected to track activities such as movement or transformation, while KDEs are the specific data points recorded at each CTE to maintain product identity. Together, these elements form the foundation of an event-based traceability framework.   

For example, in spice processing, “blending” could be classified as a Transformation CTE. At this stage, the relevant KDEs would include information about the Who (entity that owns the event), What (inputs and outputs), When (date and time), Where (location), and Why (transformation). This process of defining CTEs and capturing KDEs extends throughout the supply chain, from harvesting and comingling to processing, packaging, distribution, and ultimately, sale to the consumer. Designed to adapt to varying supply chain lengths and product complexities, the event-based framework ensures traceability remains effective across diverse scenarios.  

Implementing this level of traceability in supply chains – particularly those most susceptible to fraud – enhances the ability of supply chain owners or regulators to identify and respond to potential risks more effectively. By systematically capturing KDEs at each CTE, traceability systems create a detailed and structured record of product movement and transformation. When fraud or contamination is detected, this granular data enables a more precise evaluation of where issues are likely to have originated, allowing for targeted audits and root cause analysis. Instead of broad, resource-intensive inspections, regulators and businesses can focus efforts on specific points in the supply chain where discrepancies arise, improving response times and strengthening overall supply chain integrity. By strengthening visibility and accountability, event-based traceability frameworks play a critical role in safeguarding supply chains against fraud, improving regulatory enforcement, and maintaining consumer trust.  

In the world of food fraud, traceability is most effective as part of a multi-layered approach that involves traceability, tracking, authenticating the product and packages, and reviewing the documents for authenticity. Implementing multiple simple and varied countermeasures can hinder individuals who attempt to bypass them.   

For a list of the sources used in the article, please contact the editor.  

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Blake Harris is Technical Director of IFT’s Global Food Traceability Center. With more than a decade of experience in supply chain-related functions at private sector and NGO organizations, Blake’s focus centers on enhancing data digitization in food systems, which involves collaborative efforts with a diverse range of stakeholders from industry and government to non-governmental sectors.  

John Spink, PhD, is Director of the Food Fraud Prevention Think Tank, as well as Lead Instructor of the Food Fraud Prevention Academy, which provides free online training. He is also an Assistant Professor in the Department of Supply Chain Management (SCM) at the Eli Broad College of Business at Michigan State University (MSU). John is the author of the first textbook on the topic with the 2019 publication “Food Fraud Prevention – Development, Management, and Implementation.”