Few sectors of the economy are as important, and as overlooked by consumers, as food safety in the food and beverage industry. Many consumers take for granted that their next meal is a mere trip to the supermarket away and that the food they buy from their local grocery store is well-preserved and safe to eat. It’s easy to forget that the fully stocked shelves of supermarkets around the country aren’t the product of chance or a happy accident, but are the work of thousands of supply chain workers.
Food supply chains are the business operations and procedures that get food to consumers. However, transporting and storing food isn’t the same as shipping and storing other products. Food supply chains come with a unique set of responsibilities and requirements.
Chief among them is the moral and legal obligation to uphold food safety and protect consumers. Guaranteeing food safety is a leading priority of food and beverage producers and supply chain workers, but oversights that lead to foodborne illness outbreaks unfortunately still occur. Often, these mistakes could have been avoided or mitigated had more comprehensive data assurance policies been in place.
Let’s explore the role of data in food supply chains and how data assurance can improve food safety.
The Role of Data in the Supply Chain and Cold Chain Storage
Food supply chains differ from supply chains for other products in that they often require products to be kept at sufficiently low temperatures to prevent food from deteriorating or spoiling. That means that each phase of its journey to consumers must be strictly temperature-controlled.
This temperature-controlled supply chain is known in the industry as cold chain storage. Cold chain storage is not limited to the food and beverage industry and is, in fact, used in other sectors of the economy essential to ensuring human wellbeing, including the healthcare and pharmaceutical industries. As you can see, cold chain storage has many different applications in protecting consumers’ health.
When it comes to the food and beverage industry, cold chain storage is a vital part of upholding food safety standards. So much so, in fact, that regulators require food and beverage companies to report temperature data of their food storage facilities. This way, regulators can make sure that food products are being kept at sufficiently low temperatures to uphold food safety standards.
Some food producers and farmers prefer to promote their produce seasonally to their local community in order to supply the freshest possible food as well as to cut back on their need for sophisticated cold chain infrastructure. But any company that is shipping food products over large distances must take steps to set up temperature controls for their supply chain and record and document those temperatures to meet regulatory requirements.
Before temperature data can be submitted to regulators it must be accurately collected and formatted, which is why data loggers are so important in the industry.
How Data Loggers Collect and Record Temperature Data
Data loggers are small electronic devices that collect and record environmental data such as temperature, humidity, or differential pressure. They are one of the primary tools that food and beverage companies use to collect and log temperature readings of food storage facilities, including those used during the transport of foodstuffs.
According to Dickson Data, data loggers use built-in temperature sensors to take temperature readings and use internal storage to log those temperature readings at regular time intervals around the clock, if necessary. Many data loggers can be individually programmed to record temperatures at specific intervals that align with regulatory requirements.
Data loggers have a few major advantages compared to analog temperature monitoring devices, such as thermometers, used in the past. Because data loggers are electronic, the readings taken by their sensors are more accurate than analog temperature readings. Moreover, since data loggers are automated, they significantly reduce human error as well as labor costs. Some data loggers can also be configured to detect if the door to a storage facility is left open and alert manufacturers.
Using data loggers to monitor and record storage conditions is important given that food safety violations can represent a serious threat to a company’s brand. This is especially true considering that crowdsourced food poisoning websites give consumers a direct view of any mistakes that a food retailer or distributor makes.
As you can see, the role of data loggers in collecting and recording temperature data to ensure food safety is robust. However, after data is logged, it must then be formatted and analyzed, which is where the importance of data assurance comes into the picture.
How Data Analysis Software Can Promote Data Assurance
While remote data loggers record temperature data, they can also be connected to computers using a physical cable or a Wifi connection and export their data to another device. Their environment data can be analyzed using powerful software to provide business intelligence insights that are extremely valuable to large corporations and regenerative farmers alike.
Data analysis software can detect patterns and draw conclusions from the data, as well as recognize potential errors or anomalies. The term data assurance refers to the practice of identifying and eliminating data anomalies and errors. This is done by profiling data to analyze potentially erroneous outliers in datasets, and then removing or replacing that erroneous data.
The term data cleaning refers to the process of correcting corrupted, inaccurate, or irrelevant bits of data. Data that is corrupted or inaccurate can then be removed from the dataset, or replaced with accurate data. Data wrangling tools and batch processing scripting can be used to perform these data cleaning functions automatically.
After data cleaning, datasets should be in line with similar datasets as outliers are identified and analyzed. For example, if there is a sudden spike in the temperature of particular food storage units, part of the data cleaning process would be to assess if the data that indicated those spikes is correct. If the data is accurate, the company can take action to assess the cause of the rise in temperature, and if the data is inaccurate, it can be removed from the dataset.
Data assurance can also help to detect if data is manipulated by malicious actors such as hackers, a danger that is faced by many companies that maintain important cold storage chains.
Too many foods and beverage companies neglect to implement effective data assurance and strategies, which can result in impeding food safety standards and creating public health risks.
In conclusion, we’ve seen how data loggers are used to monitor and record temperature data and comply with state and federal regulations. However, merely collecting and formatting data isn’t enough to protect consumers. Data assurance software can help companies more quickly identify risks to public health and control or prevent foodborne illness outbreaks.