Product inspections, swab sampling, Hazard Analysis and Critical Control Points (HACCP) certifications, freshness tests, hygiene audits, and more—there is no shortage of testing within meat and poultry production systems. Regulatory and customer audits demand accurate and complete testing on a multitude of parameters, all designed to help the industry meet consumer expectations and comply with regulatory standards for food safety.
With all this testing, managing and analyzing the resulting data can be a full-time job. One of the last things a plant manager wants to think about is gathering more data, but using testing analytics more strategically can lead to better management of food safety, product quality, and overall operations, paying dividends in regulatory compliance, customer satisfaction, and consumer trust.
Here are four best practices that can help you make better use of food safety data.
1. Understand the Why
When it comes to food safety validation, it’s important to understand what data you need and why you need to collect it. By setting data collection goals, you can ensure your testing generates the most relevant data, leading to better food safety intervention decisions.
Start by defining three to five questions you need to answer to improve food safety. Often, these questions align with the food safety concerns that may keep you up at night. Getting a handle on these questions can help you collect the data needed to address those concerns.
For example, you might ask: “How can we reduce total pathogen loads so antimicrobials can do a better job of meeting food safety performance standards?”
Gathering pathogen data at each step from preharvest to postharvest can help identify the points where pathogen loads spike and interventions could be added or improved. You may want to start by measuring the types and levels of pathogens that are present on animals entering your establishment. Animal-borne pathogen data may be helpful information as you assess needs for preharvest interventions to bolster your plant’s multi-hurdle food safety solutions.
2. Fine-Tune Your Record Keeping
Data overload is a pitfall of any testing system. The meat and poultry industry as a whole collects millions of data points each year to meet HACCP or other audit requirements and to evaluate effectiveness of food safety interventions.
Once collected, it’s important to keep data organized so that it can be useful in analyses and decision making. Even more important, data must be quickly accessible in case of a potential recall or food-borne disease outbreak. As food safety recalls have evolved over the past few years, accurate data and record keeping may mean the difference between a short-term, localized issue and a nationwide recall involving millions of pounds of product.
Keeping data organized and analyzing it effectively are two of the biggest challenges the industry faces every day, week, and year. Most operations can improve the way they input and store data to more easily observe or evaluate trends.
Some companies create their own customized internal record-keeping systems or purchase online systems. The best record management system is one that meets your needs. Most often, simpler is better.
Establishing data spreadsheets across complexes within a company is also important to allow observation of trends across different geographic locations as well as different management styles. Having uniform data collection and record keeping among complexes is critical for future trend and metadata analysis.
Once data has been organized in an online record-keeping system, analysis and interpretation become important. When keeping and analyzing records, metadata can be just as important as outcome measurement. This is where trend analysis and decision making can occur. Metadata analysis can be difficult but very important, especially when determining current trends and future predictive modeling.
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.
For example, a food safety intervention may affect your product’s water-holding capacity. Without conducting product quality testing, you may be unaware of negative effects on yield and the consumer’s eating experiences.
Food safety is a basic expectation from consumers, but quality also matters, both for initial and repeat purchases. Quality is directly tied with product branding and drives consumer purchasing decisions. If a food safety intervention affects product appearance or taste, sales may suffer accordingly. In addition, even a small decrease in yield from a food safety intervention can result in millions of dollars lost per year.
Data collection, record keeping, and analyses can be overwhelming tasks. To ease the burden and achieve effective food safety systems, it is important to define the goals for data collection, develop systems to collect data relevant to these goals and objectives, and then determine the proper process for analysis to answer the questions. Analyses may be completed in-house if the questions are relatively simple and straightforward. More complicated situations may require a third-party statistician trained in statistical methods to help answer relevant food safety questions and model data for predictive analysis.
When done correctly, data analyses and modeling are effective tools to improve food safety. The data and the answers are in your hands. Using information properly can provide the insights and interventions to help you sleep better at night.
Dr. Alvarado is the food safety technical services manager at Arm & Hammer Animal and Food Production. Reach her at [email protected].
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