Advanced Documentation & Data Integrity for PCQI Compliance: Tools, Techniques, and Best Practices

The preventive controls qualified individual (PCQI) role, created under 21 CFR 117, carries significant responsibility — designing and implementing food safety plans, auditing processes and procedures, and validating and testing compliance regularly. But if you ask the average PCQI what they produce, you're likely to get an answer that has little to do with safe food: "I produce documents."

The documentation requirements introduced in 21 CFR 117 and related legislation and rules are significant, and for good reason: That audit trail is how PCQIs and regulators ensure compliance, verify that procedures are being followed, and trace food safety issues back to the source. These requirements aren't just auditing tools — they are risk management imperatives. But no matter how essential these requirements are, they still add significant overhead to a role that already feels stretched thin.

For PCQIs, finding relief from document overload means examining the requirements critically and identifying ways to increase efficiency while improving compliance and food safety. The advanced tools, techniques, and best practices discussed below will help PCQIs improve food safety documentation and data integrity compliance, making their facilities safer and more effective.

Reviewing PCQI Documentation and Data Compliance Requirements

Before we get into techniques to assist with document and data management, let's review the PCQI documentation requirements as present in the latest rules. (Note: Not all facilities will be subject to every requirement, and some may have other specialized document rules not covered here.)

PCQI Documentation Responsibilities

As mentioned above, this is not an exhaustive list: Some facilities may be subject to additional testing, verification, and audit documentation requirements. But even as a general list, it's extensive and can add up to thousands of documents produced annually at a significant cost in time, effort, and resources. Additionally, there are requirements for use and recordkeeping.

Tools for Food Safety Documentation and Data Management

Building an effective advanced food safety data plan begins with an efficient and compliant data stack. This means identifying, trialing and verifying, and learning a variety of software tools that cover every function in the documentation and data management process.

Turning to a food safety data stack for support can enable PCQIs to do more with less, while ensuring that food safety outcomes are kept front and center and compliance is built in.

NOTE: AIB International does not endorse any of the tools or companies mentioned in this article. All products not offered by AIB International are included as examples only. PCQIs and food safety professionals should independently evaluate all tools they are interested in for compliance and functionality against their own requirements before use.

Digital Storage Systems for Food Safety

Effective digital documentation storage (that meets recordkeeping requirements) is more complicated than it may seem. A proper storage system needs to be:

• Organized: Anyone looking at the file structure and document names should immediately understand what each folder and document contains, where to place a new document, and how to find a document they need without assistance.
• Searchable: The system should be easy to search, and searches should return relevant results.
• Durable: Data should be kept safe, with redundant copies and backups located in such a way that an incident (like a hardware fault or ransomware attack) can't damage every copy, and the entire system can be rebuilt from safe backups.
• Available: A copy of any current active document needs to be accessible at all times, at least within 24 hours per FDA requirements, but preferably no more than two hours.
• Secure: Access needs to be secured, with permissions granted to individuals and roles only as needed, and access (including changes) should be logged every time including who accessed what and when.
• Auditable: Changes must be tracked over time, with a record of who made any change, why and when it was made, and verification that the change was approved.

It's possible to build an in-house system that meets all of these requirements, but most companies don't have the resources to spend on building a full data management platform to do it. Moreover, it isn't required and is typically a waste of time given the availability of high-quality commercial systems.

Dedicated food safety management software (FSMS)

• Pros:
  • All-in-one solutions built specifically for food safety management
  • Integrate with common industry practices and tools
  • Built-in critical control point monitoring, validation logs, and supplier documentation templates and connectors
  • Searchable and validated audit trails and versioning
    
    
• Cons:
  • More expensive than non-specific solutions
  • Can lack flexibility to match individual facility/organization processes
  • Limited integrations and automations outside of the food production industry
    
    
• Examples:
  • Safefood 360°
  • SafetyChain
  • TraceGains
    
    

General-purpose cloud-based recordkeeping software

• Pros:
  • Flexible implementations, allowing storage of any kind of documents in any format
  • Larger and often more capable development teams, which usually result in better software, more security, and more frequent feature additions and updates
  • Stronger real-time collaboration, availability, durability, and remote access capabilities
  • Strong support from third-party developers, with a large variety of plug-ins, add-ons, and integrations
  • Often less expensive than dedicated solutions with broader capabilities that allow organization-wide use (outside of food safety) to amortize costs over more functions
    
    
• Cons:
  • Not built specifically for food safety
  • Can have more of a learning curve, with longer setup time to dial in for food safety needs
  • Might need add-ons and plug-ins (possibly from third party) to achieve all necessary functionality
    
    
• Examples:
  • Google Workspace
  • Microsoft SharePoint
  • Dropbox Business
    
    

Digital Food Safety Data Collection and Measurement Systems

Having the best document management system in the world can do little without receiving accurate and relevant data. Traditionally, many of the processes for collecting measurements relied on manual readings and entry. Apart from being time-intensive and inefficient, these systems are limited to point-in-time readings and prone to errors and tampering.

Modern PCQIs who want to achieve the best food safety outcomes in the most efficient manner must become food safety technology experts and integrate Internet-of-Things-(IOT)-enabled sensors. These devices can be integrated into existing facilities and equipment to automate continuous measurement.

• Pros:
  • Automated measurement and readings fed directly to data capture software
  • Can be integrated with recordkeeping/data management platform to remove the need for transcription and data entry
  • Continuous measurement, with some sensors able to update data down to fractions of seconds
  • Validated auditable records
  • Can be used in predictive analytics systems for food safety to identify red flags before a deviation occurs
  • Can be implemented relatively cost-effectively in stages
    
    
• Cons:
  • May require support from IT to install, calibrate, and integrate
  • More expensive than manual data collection
  • Devices must be evaluated for audit and compliance requirements
  • Ongoing maintenance, upkeep, and calibration costs
    
    
• Examples:
  • PTC ThingWorx
  • Siemens Industrial IOT
  • ABB Food and Beverage IOT

Miscellaneous Technology for Food Safety

Besides the core functions in the previous two sections, a variety of smaller or single-purpose tools can also help in a food safety data management stack. These component services typically plug into larger platforms using built-in connectors or APIs, or else allow you to integrate existing services.

Some potential tools, with examples, to consider include:

• E-signature tools for collecting auditable and compliant sign-off
  • DocuSign
  • PandaDoc
  • Adobe Acrobat Sign
    
    
• Access and authentication tools to control permissions and log access
  • MasterControl
  • Auth0
  • OAuth
    
    
• E-learning, training, and learning management systems (LMS) for storing and automating trainings
  • Absorb LMS
  • SAP SuccessFactors Learning
  • 360Learning
    
    
• No-code integration, automation, and API access tools to tie platforms together and reduce the need for manual intervention
  • Zapier
  • Make
  • Pipefy

Food Safety Documentation and Data Integrity Techniques

The right food safety data management stack only helps if you have processes to support it and tie it to specific desired outcomes. Ultimately, the role of a modern PCQI is that of a corporate risk mitigation and resiliency expert, with a focus on food safety for the entire organization, not just a technician. This means building processes that go beyond just "doing food safety" and instead are more broadly targeted at identifying and reducing risk.

Create strong data governance architectures

Data handling processes should be designed from the top down to comply with ISO 22000 and FDA CFR Part 11. That helps ensure that access is carefully managed and limited as much as possible based on roles and responsibilities.

• Least-privilege principles: Access should be granted with the fewest privileges and permissions possible. Read/write access should be defined by job function and tied to digital certificates or other cryptographically secure identity verification mechanisms.
• Classification segmentation: All data should be divided into classification categories and partitioned to ensure that retention and access rules are enforced based on those categories.
• Monitor and revoke: Regular permissions and access monitoring and auditing should be performed, and data access should be reviewed and revoked if needs change. Operate on the principle that any given user should not have access unless specifically necessary.
• Immutable logging: Technologies like Write Once Read Many (WORM) and blockchain can ensure that audit logging stays unchangeable and impossible to tamper with or remove.
• Standardized timestamps: Network time protocols and synchronized timestamps make tampering or otherwise falsifying time entries much more difficult, and can ensure that data integrity stays high across the system.

Design food safety data management for human fallibility

Most problems in data logs and quality control systems are not the result of intentional sabotage, but rather simple human error. Build embedded and automated controls to minimize human error when possible using computer logic and verification.

• Conditional validation: All manual entry fields should be tied to conditional validation logic to ensure that manual entries are accurate and fit expectations for values and datatypes, either by blocking incorrect input or allowing some deviation with confirmation.
• Automate approval workflows: Progression in documents and workflows that require sign-off or other review and approval should be blocked until the review is completed and approval is confirmed; any deviations or exceptions should be justified and the justification externally approved.
• Closed-loop notifications: In the event of deviations or exceptions, all relevant stakeholders should be notified automatically, and progress should be prevented until they confirm receipt and review. All notifications and approvals should be timestamped and signed with a secure credential, with logs kept separate from the main document.
• Validate proficiency: Ensure anyone who enters, modifies, or approves data and documents is proficient in not only food safety but data management policy as well. Tie credentialing to tested proficiency using LMSes or other similar verification tools.

Operate under the assumption that food safety technology fails

While technology is usually more reliable and robust than human operators, assume that your system will fail and design and audit appropriately. This means regular calibration and validation of end-to-end data, as well as building in self-testing and automatic data validation protocols.

• Leverage AI and statistical process controls (SPC): Use AI and SPC to design systems that monitor and analyze trends over time to flag small shifts that might signal big problems, and to help validate manually entered data against expected inputs.
• Build early-warning systems: Set control bands for every variable and document tracked, and use a robust automated notification and escalation system to gain advanced notice if something looks off.
• IQ, OQ, and PQ: Installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ) schedules should be developed and followed rigorously to ensure that every piece of the food safety data management system is operating as it should be. Train and validate anyone who operates the system to perform each qualification.
• Audit system changes: Build and follow a process to regularly audit system software, firmware, and hardware versions and update histories to ensure no unauthorized changes have been made. Create a strict update policy that outlines steps for testing and validating any version changes before they are rolled out to the live system.
• Automate backups across the system: Backing up isn't just for data. Design a plan for creating whole-system state backups, including: all of the data, hardware, and software state with current version and deployment details, as well as access controls/permissions. Automating this and maintaining version history allow for easy rollback in the event of a critical failure.

Food Safety Data Management Tips and Best Practices

In addition to the major changes outlined above, here are some quick changes you can implement to immediately improve documentation and data integrity practices across your food manufacturing organization:

• Review and align documentation records with PCQI and corporate risk management priorities: Regularly review the data you are generating through the lens of "Does this meet all the requirements of the food safety plan? Do I need this specific record or is this information covered elsewhere? Does this fit with global risk management priorities?" Sometimes, that means adding records, but often removing unnecessary data is just as important.
• Institute regular spot checks and audits: Data should be spot-checked daily or weekly to ensure accuracy and completeness. Quarterly internal audits should be used to verify the integrity of the system end-to-end and performed from the perspective of a food safety regulator, much like AIB International's Regulatory Readiness service.
• Monitor for bottlenecks and gaps: Use built-in auditing capabilities, external tools, and manual review to constantly identify gaps or bottlenecks in data management and address them when possible. It can be useful to keep a running list of improvements and optimizations to tackle as time allows. Solicit stakeholder feedback to add user-level data to the analysis.
• Train on the system, not the steps: Ensure consistent and continuous training on the entire document management system, not just specific steps that a stakeholder might need to follow. Providing broader context helps ensure retention and builds understanding for why team members need to do things a certain way, not just how to do them.
• Use a data organization system: Document organization and naming systems make document management systems work better by ensuring files are always where they should be and can be easily located or stored. Lightweight options like Johnny.Decimal can be a good starting point, while more tailored and robust systems like Functional File Plan (FFP) and ISO 22000 can be used for larger organizations with heavier documentation needs.

Good data management makes food safer

PCQIs who have made it this far may wonder, "Why should I care? My job is to ensure safe food, not manage IT." It's a valid concern — PCQIs are already under significant pressure from high turnover in food safety, high stress, and work overload. Additional responsibilities from a different domain can feel like a bridge too far.

But that's the incorrect mindset. Designing a robust automated food safety data management system actually reduces PCQIs’ workload, so they can spend less time shuffling documents and more time improving food safety outcomes. While these systems might require extra upfront design, implementation, and training time, they pay back in droves over the long term. A good food safety data management system helps PCQIs:

• Take back their time from managing documents and records.
• Ensure more accurate data with automations and IOT integration.
• Strengthen compliance and auditing requirements.
• Benefit from advanced technologies like predictive warnings for future problems.
• Build safer, healthier, more efficient food supply chains.