Food safety and commercial microbiological labs process hundreds or thousands of tests daily to ensure the safety and quality of food and beverage products before they reach consumers. Labs face a variety of challenges, prompting managers to seek methods and technologies to increase testing capacity and improve workflows, aiming to make labs more efficient and proactive using data insights. 

Currently, many lab processes are manual, repetitive, and low value-add, but necessary to perform a test. For example, sorting, counting, and recording test results requires hours of work and can introduce inconsistency and human error. The repetitive nature of these processes can also lead to technician burnout, which introduces yet another challenge: recruiting and training new staff members. Rotating technicians may increase the potential for more errors, and these outdated processes can limit how many tests a lab can process each day.

So, how can labs evolve, reduce risk, and increase output to support faster growth? 

Automation—a tool to reduce risk and increase output 

Automation can help support higher throughput and growth by allowing labs to streamline processes, reduce human error, and increase total lab capacity. While automation isn’t new to labs, as some systems have been around since the 1990s, technology has continued to evolve and not all labs have followed pace. The adoption rate for automation among food safety labs is still low. Enhanced technologies with both automation and aspects of artificial intelligence (AI) present a tremendous opportunity for food safety lab managers to help reduce repetitive tasks and boost productivity levels. 

In food safety labs, automation can help at all stages of testing. First, liquid handlers or automatic pipetting tools can dispense exact amounts to create consistent samples for testing. Automated systems can make multiple samples and dilutions for testing simultaneously, leading to significant efficiencies versus manual pipetting. In addition, the precision and accuracy of automated systems can be higher due to the reduction in potential errors found in manual pipetting.  

Second, advanced technology can now be used to identify, count, and record microorganism colonies for quality indicator tests. Automation and AI capabilities continue to provide opportunities to optimize technicians’ time, reducing manual counting and logging of results. Both examples reduce hands-on time while improving consistency. Even more advanced capabilities allow intelligent software systems to interpret and analyze data so technicians can make actionable decisions faster.  

Reaping the benefits of automation

For labs looking to improve productivity, the first place to start is to assess where repetitive labor and time-intensive work occur regularly. Upfront costs for technology investment and access to trained technical staff should also be considered. One reason why the adoption of automation in food safety labs has been slow may be because managers have been willing to put up with the hidden costs of inefficient, repetitive processes versus an immediate capital expense investment. But with increasing labor costs, managers are now more open to assessing opportunities for improvement and finding ways to reduce or eliminate many of these hidden costs. 

Once an assessment is complete, lab managers can apply automated systems to reduce or remove repetitive workloads. Instead of investing in a fully automated solution, a lab manager may choose to invest in more capable instrumentation to help improve lab efficiency without making significant changes to workflows. One common example of this is semi-automated dilution dispensing. By working with an automation platform expert, lab managers can calculate the expected return on investment, which helps determine what solution and level of investment is right for their own lab. 

Automation is a must in food safety and the foundation for the future  

For high-volume commercial labs, investment in automation is a must to achieve today’s high-pressure testing goals. After labs implement workflow optimization and simplify sample processing through ready-to-use solutions, the next step is to invest in automation that can exponentially increase throughput and reduce human error. This will allow labs to move from individualized testing operations to centers of excellence where data is at the forefront of decision-making.  

Even more importantly, automation is the basis for future innovation that will continue to occur, creating the foundation needed for machine learning and predictive analytics to be integrated into the modern lab. Automation is here to stay. Modern high-volume commercial food safety labs can be designed to run like well-oiled machines and help the food industry generate insights and manage risk through advanced data analytics, with the ultimate goal of protecting consumers.