Recent food recalls should serve as a constant reminder of the importance of environmental monitoring programs (EMP). A robust, well-thought EMP with a strong focus on finding pathogens “before they find us” helps ensure that safe food is produced and protects the brands of food producers. With the explosion of digital solutions and artificial intelligence, food processors now have access to tools that will help them be even more proactive and productive.
In today's world of data and digital transformation, the food industry must harness the value from those new tools. It's also important to “avoid mistakes” by making the wrong investments. bioMérieux’s suite of innovative solutions for Augmented Diagnostics includes the specialization in digitalizing EMP. Here are a few key tips to ensure a successful implementation.
The Value of Digitalization
While digitization is simply converting information into a digital format (think Excel), digitalization is developing and implementing processes that change workflows and improve existing manual systems. For EMP, digitalization means completely automating the scheduling and CAPA processes, results mapping, and trend analysis.
Digitalizing an EMP brings enormous benefits. Besides time savings through automating processes, one key value is the speed at which actionable information is made available. Personnel are notified immediately if something is out of spec, prompting urgent action and simplifying decision making, start CAPA or get to root cause. Another benefit is the ability to easily dashboard, benchmark different sets of data, see trends earlier, and catch potential problems before it’s too late. Finally, having everything digitalized makes it easier to pull data for auditing, root cause analysis, or just ensure that the EMP is properly executed.
The Promise of Predictive Analytics
With the explosion of big data analytics, machine learning and artificial intelligence, the food industry is seen as the next sector to fully embrace those new tools. However, it is important to understand the food industry’s dynamics to properly leverage those tools. Two aspects of the food industry make applying big data analytics to food safety and quality challenging. First, even though manufacturers generate tons of data, only out-of-spec results can really be leveraged for analysis. And, generally, out-of-spec data is rare, making a big data approach difficult. Second, food manufacturing plants are constantly changing environments with myriad interactions and moving pieces which, again, makes analytics more challenging as many tools make assumptions based on static sets of data.
To address that challenge, connecting data to expert analysis is paramount in order to draw meaningful and actionable insights out of them. For food safety and quality, this means associating data analytics with expertise in food safety and quality, microbiology/chemistry and food processes.
Tools Do Not Replace Behaviors
It’s well-known that tools only regurgitate whatever input they were fed. At bioMérieux, we believe it’s all unoptimized data without a comprehensive, risk-based EM plan, as well as the people, tools and training to execute it properly. It would be very risky to make critical food safety-related decisions based on the insights provided by a digital tool that was fed poor data. Before implementing any digital solutions or predictive analytics, it would be wise to analyze your current plans and make the necessary adjustments to be confident that the analytics are based on sound data.
The emergence of digital tools dedicated to EM programs create opportunities for food safety and quality leaders to accelerate time-to-decision, be more proactive and have a more robust EM program. But those are just tools, and it’s the expertise, sound strategies and precise execution from bioMérieux, your trusted partner in augmented diagnostics, that make data meaningful and actionable for food producers worldwide.
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