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Best Practices for Easing Traceability through Technology

Dayna Nicholas, Director of Quality & Regulatory Affairs, Land O'Frost
Dayna Nicholas, Director of Quality & Regulatory Affairs, Land O'Frost

Dayna Nicholas, Director of Quality & Regulatory Affairs, Land O'Frost

"Traceability" refers to the process of tracking individual products throughout their lifecycle, from sourcing through production and to final distribution. It is a foundational aspect of food quality and safety that also has deep impacts on operational efficiency. 

For example, consider a scenario in which foreign material is discovered in a product at the plant's packaging end—or is discovered after distribution, prompting a recall. The producing plant's management team must act quickly to pinpoint the problem's source, identify its scope, and ensure remediation. Determining accurate information quickly is vital for communication to the corporate Crisis Command Team.

Locating all potentially affected products and preventing future contamination requires reliable data. Not only is the speed of the essence, but accuracy as well. No company wants to go before the media to announce a recall—let alone be forced to expand the recall later because of incorrect data. Slow reaction times and inaccuracies erode consumers' trust in the brand.  

As supply and distribution chains become more complex, integrated technologies can ease traceability. However, managers should not assume that data is accurate just because they have Enterprise Resource Planning (ERP) technology and a Quality Management System (QMS). Technology can improve traceability, but only if steps are taken to validate the data and verify traceability protocols. 

Why technology is only the first step

There are two components to any traceability effort: technology and humans. Most QMS and ERP technologies are populated by data that is either keyed or scanned in by individuals. Even with the best systems in place, it's human nature to try to find operational shortcuts. Unfortunately, shortcuts can impact data quality. 

For example, Land O'Frost team members are instructed to scan barcodes on vats of raw material just before loading the materials onto the transfer conveyor. Scanning populates the ERP showing the exact time material was used. Yet if five vats come to the floor at the same time, a team member could scan all of the vats at once. The system would then show that multiple vats were used at the exact same time when in reality, they were used over a period of several hours. If only one of those vats was suspect during a recall, the recall would have to be expanded to include all five, greatly expanding scope.  

 Effective traceability requires managers to blend data-driven insights with human compassion and respect. Once data is validated, it can help bring entire teams together over process improvement goals

Fortunately, operational shortcuts sometimes leave ERP data clues. In this example, an audit would show that the five tickets were scanned in just a few seconds, alerting us to a potential workflow issue. 

Traceability best practices

Effective traceability requires managers to blend data-driven insights with human compassion and respect. Once data is validated, it can help bring entire teams together over process improvement goals. Here are some best practices to achieve solutions-oriented traceability processes:

Create cross-functional teams to identify places within technology systems where traceability breaks down. No technology can do everything, so companies need to look comprehensively at the intersection of process, system capabilities, and system limitations. A cross-functional team composed of experts from IT, operations, traffic, and food safety/quality should regularly brainstorm techniques to ensure good data is entered into the ERP and other systems so that reliable traces can be accomplished quickly.

Turn common operational issues into traceability tests. Use problems identified during the normal course of operations—such as the foreign contamination example—as an opportunity to call together supervisors and superintendents to test traceability protocols. Ask each person to do just a portion of the trace. That way, without undue burden, they can use the tracing exercise to reinforce appropriate processes within their departments and keep their tracing skills sharp.

Conduct traceability training and mock recalls. The time to test traceability protocols is not during a recall incident. Instead, once a year, set up a working traceability training session where IT staff show users easier methods to enter, access, and use ERP data. Training sessions paired with periodic mock recalls allow managers to work together with IT experts to find better ways to safeguard tracing accuracy. 

Divide and conquer. Asking one person to handle a trace during an actual recall is a set-up for failure. What if the recalled product both was shipped and remains in inventory, for example? Tracing it all would be a massive undertaking. So, appoint a team to generate a faster and more accurate traceability effort.  

Use data to build a foundation of trust and respect. Quality managers can foster continuous improvement by taking a collaborative approach to determining whether protocol breaches identified by ERP data represent "people" failures or "process" failures. In the bar code scanning example, honest and open conversations with team members on the floor might reveal that they lack the right tools at the right places. Thus, data and discussion could lead to a simple resolution: placing scanners closer to the locations where the materials are used. 

Technology is not perfect, but by easing traceability it can help a management team identify and solve challenges. Using data-driven insights to encourage teamwork and build trust can inspire a dedication to excellence that makes quality, safety, and consumer responsiveness possible.

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