Although metadata collection may seem contradictory to the idea of simple record keeping, it’s important to gather all relevant information that could potentially influence test results and the outcome of food safety interventions. For example, when determining the effectiveness of various antimicrobials within a company, it is important to collect biomapping data across all processes and operations. Once collected, trends can be determined within each processing operation and across the entire company to determine the effectiveness of interventions to reduce pathogens. Based on trends data, you can make informed decisions to foster improved food safety.
3. Keep Your Eye on Trends
With such an abundance of food safety data, managers often become hyper-focused on specific parameters and miss important trends. Look beyond daily data to identify trends based on location, season, and production cycle. Understanding trends revealed by data can separate meaningful information from “noise” in order to determine the most effective interventions.
It is critical to note any changes in system approaches when analyzing trends. For example, a revision in sample collection procedure or a simple change in process equipment can affect food safety data. These updates should be noted to allow for easier trend identification. The answer to “what changed” is easier to find with good record keeping and notes from processing employees, providing important information for future food safety decisions.
Therefore, when monitoring trends, it’s important for the plant manager to maintain a time log of changes in the system. To make accurate decisions based on data, consider any changes in laboratory methods, chemical use, or any other variables that may affect test results. Be sure you are identifying true trends in addition to simple changes in process. Realize that even the smallest of changes—even changes that are not specific to your food safety processes—can impact food safety interventions.
A history of your operation provides another clue to identifying trends within your data. Building a history of your operation takes time; however, knowing how weather and other seasonality factors affect production demands and food safety concerns will allow you to analyze data more effectively based on time of year. It is never too early or too late to start collecting data and building a food safety history.
Predictive analysis and predictive modeling are emerging as helpful tools to predict food safety outcomes based on statistics. These tools use machine learning to provide insights into patterns than may not be immediately apparent through simple statistical process control (SPC) data analyses. Most data analysis has always relied on standard and simple SPC; however, with increasingly complex food safety systems and the proliferation of data, the typical box statistics are no longer able to provide in-depth trend analysis.
Those wanting more predictive modeling and analysis over their entire food safety systems may want to consider contracting with third-party trained statisticians for complex analyses. Prior to enlisting these third-party statisticians, it is important to ask questions regarding the use of the data and the safety of the data control. Third-party statisticians for metadata analysis can be useful for handling complex systems and helping to answer complicated food safety questions and meet objectives.
Whether using SPC or a third-party statistician, be sure to step back and take your own experiences and knowledge of your operation into consideration as well. Combining your expertise with predictive analytics tools can help you understand and manage data trends that lead to better decision making.
4. Don’t Forget Quality Considerations
It’s important to understand how food safety interventions may affect product quality. In addition to pathogen testing, measurements of color, shelf life, and other food quality parameters can reveal your products’ overall acceptability in the marketplace.
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