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Home»Explore industries/sectors»Food Processing»Digital auditing cuts pet food quality assurance cycle time
Food Processing

Digital auditing cuts pet food quality assurance cycle time

By IslaApril 29, 20264 Mins Read
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Digital platforms used in food safety auditing reduced total audit cycle time by 25% and enabled earlier detection of critical deviations in pet food manufacturing, according to field data presented at Petfood Forum 2026 in Kansas City, Missouri, on April 28.

In her session, “Auditing the future: Digitalization and data analytics in pet food quality assurance,” Jennifer Lott, technical development director at SGS North America, drew on findings from more than 300 remote and hybrid audits conducted between 2021 and 2024 to make the case that digitalization is transforming how pet food manufacturers manage quality assurance — and that the shift is no longer optional.

“Food safety in pet food is no longer just about compliance; it is about trust, transparency and proactive risk management across the entire supply chain,” Lott said.

Her study tracked three key performance indicators: nonconformity closure rate, data capture accuracy and reviewer consistency. Across all three, digital tools outperformed traditional methods. Faster closure times mean a shorter window during which a known weakness exists in a system. Improved data accuracy leads to better decision-making. And greater reviewer consistency means leadership can trust that audit findings are comparable across sites, products and teams.

From snapshots to continuous assurance

Traditional auditing has relied on periodic on-site inspections and manual records review — what Lott describes as a “snapshot” of compliance at a single point in time. That model, she said, leaves gaps during which emerging issues can develop unnoticed, and introduces inconsistencies based on how individual auditors document findings.

Digital platforms address those limitations through standardized templates, real-time document exchange, remote verification and centralized evidence tracking. Dashboards and automated alerts replace manual email chains, giving quality teams faster access to what is open, overdue or already resolved.

“The value is not just speed,” she said. “It’s control and traceability.”

In two instances within the study data set, real-time analytics enabled early identification of consequential food safety issues: sanitation lapses and critical control point deviations that would have been slower to surface under traditional methods.

Predictive, not just reactive

Beyond faster detection, Lott said digital analytics position manufacturers to anticipate compliance failures before they occur. Trend data — repeated minor sanitation issues, recurring documentation gaps, incremental process deviations — can collectively signal a larger problem developing even when no single finding appears critical.

“Traditional auditing tends to respond to problems that have already been discovered,” she said. “Digital analytics allows teams to review patterns in both historical and real-time data to identify where the next problem is likely to emerge.”

That predictive capability also enables risk stratification, allowing quality teams to concentrate auditor time and resources where the probability or consequences of failure are greatest. “It’s not about cutting corners,” Lott said. “It’s about putting attention where it matters most.”

Challenges: security, data integrity and regulatory alignment

Lott identified three barriers organizations must address before digital audit systems can deliver their full value.

The first is cybersecurity. Audit platforms hold sensitive compliance records, supplier data and internal performance information, making robust access controls and secure data storage essential. “Digital audit systems must be secure by design,” she said.

The second is data integrity. Analytics are only as reliable as the data that feeds them. Incomplete records, inconsistent data entry or inadequate validation can produce misleading outputs. “Digitalization requires discipline,” Lott said, adding that governance around how data is entered and maintained is as important as the technology itself.

The third challenge is regulatory harmonization. Acceptance of remote verification, digital signatures and digital records varies across regulatory bodies and certification frameworks, creating uncertainty for organizations operating across multiple markets or standards.

Lott said none of these challenges should be treated as reasons to delay modernization. “They should be treated as design requirements — security, data governance and regulatory alignment — that need to be built into the program from the beginning,” she said.

Steps forward

Lott recommended a phased approach: assess current systems and gaps, pilot digital tools on specific use cases, build internal capacity and then scale. She cautioned against attempting to digitize all processes simultaneously.

Emerging technologies on the horizon include AI-based anomaly detection, blockchain traceability and IoT-connected sensors feeding live operational data into assurance systems. Not all are equally mature, she said, but together they point toward a more connected quality ecosystem.

“Successful digitalization is as much about people and process as it is about software,” Lott said. “The future of pet food quality assurance is becoming more continuous, more transparent and much more data driven. The tools are here. The opportunity is now.”



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