We get a front row seat to how companies manage recalls, and there is a clear divide. The companies that manage recalls well are not always the biggest, or the ones with the most staff. They’re the ones that have invested in good data management practices. They’ve built a recall process that is driven by accurate, structured information, have systems in place to share the data quickly, and practice regularly to ensure it will work as intended when needed. They don’t just focus on what needs to be recalled – they’ve mastered how to run the recall itself.
By contrast, companies that struggle often focus heavily on the What – what products, what time frame, what distribution pattern – without enough attention on the How. Those details are essential, but they don’t get the job done on their own. A successful recall depends on how you manage the data: How do you notify partners? How do you confirm action? How do you track product removal across the supply chain? These steps require accurate, structured, and shareable data. And they require a system designed to support fast, documented action at scale.
Without that system, recalls become reactive. Data is incomplete, hard to access, inconsistent, or disorganized. Teams are forced to interpret unclear recall notices, make manual decisions, and often err on the side of over-pulling product just to be safe. That might seem like a cautious approach, but it leads to waste, confusion, and lost time.
When recalls are managed this way, it’s not because people aren’t capable. It’s because they don’t have the right tools or the right process. Product-centric thinking, without supporting data systems, isn't designed to keep pace with the complexity and speed required in today’s supply chains.
Data That Drives Action
At its core, a recall is a data-driven process. The moment action is required – whether it’s pulling product from shelves, contacting partners, or alerting customers – data must accurately reflect the product and its path through the supply chain. When that data is clear, consistent, and timely, action is precise. When it isn’t, confusion sets in and risk escalates.
That’s why a data-first approach is critical. It ensures that every stakeholder is able to send and receive accurate, usable information that can be acted on quickly. In a data-driven recall, the supply chain doesn’t need to wait for direction or clarification. Everyone knows what to do because the data is structured, accessible, and tied to the systems they already use.
This requires more than just having the right fields in a spreadsheet. It means data is standardized so systems can interpret it without manual formatting. It means your team knows where to find the information, and that the systems in place can communicate seamlessly with partners up and down the chain. It also means aligning on how data is stored and shared, from how lot codes are labeled to how distribution details are recorded and transmitted.
When It Works and When It Doesn’t
We’ve seen what it looks like when companies do this well. The recall is triggered and accurate product data flows immediately to every stakeholder. The distributor identifies affected inventory before it ever reaches stores. Retailers receive a data package that ties directly to their POS system. Consumers who purchased the affected item get a notification with clear next steps. The issue is contained, the public is informed, and the brand maintains trust.
We’ve also seen what happens when it doesn’t work. The recall notice is delivered as a PDF attachment or email. The store doesn’t track lot codes and has no easy way to match the information. Employees remove all similar product from the shelf, even if it’s unaffected. Some locations delay action while they try to verify the details. Customers are left confused, and still at risk. The process is slow, inefficient, and damaging.
Data Has to Be Shared
Good recall data isn’t useful if it can’t be shared. Yet, the industry still lacks a standardized way to capture, store, and distribute recall data. This leads to variability between suppliers, delays in interpretation, and unnecessary labor in reconciling data sets. Some companies send freeform recall notices that require manual formatting. Others use proprietary systems that don’t integrate well across partners.
To move forward, data sharing needs to be predictable. It should be clear what fields are required, what format they’re in, and how that information is transmitted. That allows your trading partners to respond quickly instead of reformatting and reinterpreting the recall before they can act.
This is especially important in an omni-channel, distributed supply chain, where the speed of a recall often depends on the clarity of the initial data. When data is consistent and timely, it allows everyone to do their job effectively.
Encouragingly, progress is being made. The data workgroup of the Alliance for Recall Ready Communities is currently partnering with GS1 to develop a standardized recall data set that can be shared seamlessly across systems and organizations. If you want to stay informed or get involved, you can sign up to receive updates at recallreadycommunities.org.
What You Can Do Today
Even without an industry-wide standard for recall data, you can still make changes today that will dramatically impact your recall effectiveness. Start by evaluating how your recall data is structured. Is it standardized? Is it integrated with your traceability system? Can it be pulled and shared in minutes?
If you’re still relying on manual emails, disjointed spreadsheets, or systems that require individual interpretation, it’s time to modernize. That doesn’t mean overhauling everything at once. Even small changes – like aligning formats with your partners or automating how recall data is generated – can make a big difference.
Mock recalls are also a great place to begin. But make sure they’re more than just traceability exercises. They should simulate the entire recall process, including how data moves across teams and trading partners. This is where gaps show up, and where you get the clearest picture of how ready your systems really are.
If you’re not sure where to begin or how your current recall process stacks up, talk to our team. We help companies identify practical ways to move from product-centric to data-driven recall management.
