The PCQI role was first introduced in 2015 to align with the Food Safety Modernization Act (FSMA) passed by Congress in 2011. Over a decade later, the world is very different: New threats like COVID-19 and Avian Influenza have emerged, existing threats have intensified, climate change has advanced and may be accelerating, and supply chains are longer and more complex than ever. Maintaining food safety is a more challenging goal than it was; keeping up requires a proactive approach to anticipate and prevent problems long before they manifest.
Fortunately, new technologies and use patterns can make PCQIs and food safety professionals more effective and efficient. Innovations in real-time data (RTD) processing and predictive analytics, Internet of Things (IoT) monitoring and connected systems, and new approaches to traceability like blockchain and real-time cloud data stores are having transformational effects across industries and roles. Adding them to the PCQI technology toolkit can do the same for food safety.
But doing so requires PCQIs to take the initiative: Food safety regulations move slowly, and are years behind the state of the art before they're even passed. To meet expanding food safety challenges and roles, PCQIs must become experts in emerging tech and figure out best practices outside of the context of regulatory guidance. This guide can help set the foundation.
Real-Time Data, Predictive Analytics, and Artificial Intelligence
Using data and analytics to make food safety decisions is not new. One of the mandates in the FSMA was to reorient food safety and GMP rules toward a more data-driven approach, based on best practices already in place at top food safety programs, to improve risk identification, prevention, and overall compliance.
What's changed is the amount of data, the insights drawn from it, and the technologies used to unlock those insights.
PCQI Technology Definitions
- Real-time data: Data that can be accessed as soon as it is collected, often with minimal processing between creation and storage. Often stored in cloud systems for availability, and with processing and analysis done either via a separate system or in real time as the data is requested by users.
- Predictive analytics: Using historical data to make inferences about future events. Modern systems can collect a lot of data from multiple sources to build incredibly detailed predictions with high levels of certainty.
- Artificial intelligence: Specifically, large language models and similar systems use large quantities of data to train themselves to recognize patterns, making them extremely powerful for analysis and insights.
Best Practices and Benefits for PCQIs
Advances across all of these technologies have been so significant that any one of them could use a standalone book of best practices and applications. However, some applications are easy to implement, making a big difference in a short amount of time:
- Enhanced preventive control verification and validation: Combining historical data with AI-powered predictive analytics gives PCQIs a powerful tool to ask questions about the future: What level of testing is sufficient to meet deviation goals? What's the next likely thing to break or fail, given historical patterns? What is the probability of contamination by source? Previously, this level of analysis would have required extensive knowledge of statistical analysis, but modern tools make it accessible.
- Evidence-supported audit documentation: An always-on, real-time data program can track hundreds of variables on a second-by-second basis and store them in a time-stamped, secured, validated way. This data can be used to supplement and inform audits, solving the problem of human error in measurement and recording as well as data falsification, making audits much more accurate and improving food safety plan integrity and audit documentation. These systems also support regulatory compliance by generating secure, searchable records with audit trails, often required under FSMA.
- Faster CAPA response: Predictive analytics powered by real-time data can warn about potential deviations much earlier than manual monitoring or simple sensor-based alerts — sometimes, they can even provide a warning before the deviation happens. Knowing that a failure has just occurred or is about to occur shortly gives food safety professionals a much wider response window, minimizing potential damage. Additionally, advanced systems may also suggest probable root causes based on historical deviation patterns, aiding not just response but also long-term prevention.
IoT and Connected Monitoring
Advanced analytics and data processing don't mean much if data isn’t coming in quickly, reliably, and in large quantities. Connected monitoring with the Internet of Things solves this problem. IoT devices are often small, relatively inexpensive, and can be added to a wide range of equipment and environments.
PCQI Technology Definitions
- Internet of Things: A group of technologies that deal with connectivity, interoperability, and power used to build hardware that is always on, always connected, and can transmit data to a destination often, even if there aren't established networks. These technologies are used to build sensors and controls that can be added to existing equipment with minimal modifications for smart, real-time data collection and activation.
Best Practices and Benefits for PCQIs
Much modern production equipment has built-in sensors and networking, but many facilities operate using equipment built (or at least designed) before Wi-Fi was common. IoT devices give PCQIs the power to turn this equipment smart without extensive renovations or massive budgets.
- Multiply monitoring capability: Not only do IoT devices give you the power to monitor thousands of variables — from temperature to air quality to voltages and weights — but they also allow you to do so remotely. Rather than checking refrigerator temperatures manually, for example, an IoT sensor could monitor temperatures every second, transmit those values to the food safety office or a cloud repository, and send out an alert the minute values exceed target ranges.
- Power real-time and predictive analytics: With predictive modelling, facilities can catch deviations before they even register as such. By feeding data to predictive analytics engines, IoT sensors can help PCQIs recognize and prevent dangerous trends early. Extending the refrigeration example, a temperature sensor in cold storage might send an alert if it notices that the temperature has been consistently going up by half a degree per hour for the last 12 hours; even if the value is still in range, that kind of trend analysis is a red flag that something may be wrong and should be looked at immediately.
- Validation and logging: Combined with secure storage, IoT sensors can help PCQIs comply with documentation and logging requirements without manually logging every value. When the right encryption standards and timestamping are integrated into this data collection, the resulting readings comply with document retention and data quality requirements (much more successfully than manual auditing does).
Smart Traceability With Blockchain, Cloud Storage, and Integrated Data Platforms
While blockchain technology is most strongly associated with cryptocurrency and the world of alternative finance, the underlying ideas are far broader than dodgy investments and joke coins. At its heart, blockchain, secure cloud storage, and integrated data platforms all do the same thing: create permanent, secure records that are accessible from anywhere and can connect to virtually anything.
PCQI Technology Definitions
- Blockchain: A digital ledger that creates immutable records distributed across multiple computer systems and is accessible to anyone with the proper authorization from anywhere.
- Cloud storage: Like blockchain, these are distributed (stored across multiple computers) and accessible from anywhere with an internet connection. Unlike blockchain, the data isn't always immutable, but the format and structure of the stored contents are much more flexible.
- Integrated data platforms: User-friendly software that connects data storage to tools that can use that data in simple, streamlined ways.
Best Practices and Benefits for PCQIs
When combined with traceability initiatives, these tools can dramatically improve visibility into how food reaches customers, from raw ingredients to finished packages. As outbreak threats increase and the FDA focuses more heavily on identifying and controlling source infections, these tools are a powerful addition to the PCQI technology toolbox.
- Secure, verifiable vendor records: Programs like the Foreign Supplier Verification Program (FSVP) have strict rules on collecting, verifying, and maintaining vendor records. Cloud solutions are a perfect fit, as they allow these records to be instantly sent and maintained indefinitely without worrying about physical storage. What's more, they can track and maintain changes to the documents in real time and keep a log of all modifications, giving PCQIs instant access to the most current reports and visibility into how vendors have performed over time.
- Better recall-readiness: When IBM launched its Food Trust program with Golden State Foods, they brought recall-readiness into the future. The system combines blockchain and IoT to build real-time, trusted, persistent records of every single step a piece of food makes on its journey from farm to table. This allows for a previously unimaginable ability to instantly trace contamination, and drastically simplifies the recall process.
PCQI 2.0
Taking advantage of these technologies means a new kind of PCQI: part food safety expert, part technology guru, part data analyst. And PCQIs have to do this largely on their own; while the FSPCA is slowly updating content to include training on digital records management and data validation, they are still far behind the state of the art.
Fortunately, new technologies make it much easier than ever before to combine these skills. Many are plug-and-play, and most outsource the deep analytical work to algorithms and data centers. PCQIs don't have to worry about how they will measure, analyze, and communicate; just what they want to measure, analyze, and communicate. To ensure data integrity and system security, PCQIs must also work closely with IT and cybersecurity teams to align their tools with IT protocols and regulatory frameworks, creating safe, reliable, and compliant implementations.
The payoff, however, is much better food safety with much less of the kinds of work that people tend to be bad at: measuring and recording data accurately and consistently. Teams that prepare their food safety personnel to harness these technologies will outperform on audits, have fewer food safety incidents, and anticipate and react better to events. For food safety pros, the only question is: Is my PCQI program keeping up?
Contact AIB International to learn how our consultants can prepare your food safety training programs for the 21st century and beyond.
