Big Data in Food Processing

But all that data creates a challenge: it’s only as good as your ability to use it, and it is easy for processors to drown in data when they move from older systems to newer ones that report a constant stream of information for seemingly every metric. Having a plan in place to manage and learn from data without being overwhelmed is critical to successfully navigate this space and improve operations.

Effectively using data isn’t just a production benefit. It also helps streamline recall and audit processes, turning them from labor-intensive projects that monopolize multiple departments’ time to tasks that can be completed with the push of a few buttons.

Inventory management

The first step in transitioning to a data-driven operation is deciding what you want to achieve with your data and how you’re going to implement processes to meet that goal. This is generally a multi-stage process; for example, your first application of data may be for inventory management, followed by audit and recall management, and finally, full production data.

Inventory management is often a good place to start, especially for manufacturers with a wide range of products or who manufacture specialty products for a portfolio of brands. Take for instance a coffee company that produces coffee from whole beans for companies in different markets, including retail, food service, and hospitality. This variety can add up to a dizzying number of possible product and packaging combinations. Using traditional methods of inventory management to ensure that necessary ingredients and materials are readily available can prove to be labor-intensive and impractical.

Since implementing an enterprise resource planning (ERP) system, the company has seen drastic reductions in the time needed to complete inventory and has a much better understanding of its supply levels in real time. The ERP system is tied into the company’s entire manufacturing process. This fully integrated tool assists with processes such as inventory management, allowing operators to track items in the production schedule, and confirm that they have the required ingredients.

The system also reduces waste. This is not only great for the overall corporate footprint, but also a more efficient use of ingredients with relatively short shelf lives. By knowing its inventory levels in real time, the company more accurately and acutely controls ordering and delivery for the production process, avoiding the risk of waste.

Audit and recall management

Every processor understands the importance of good record-keeping for audit and recall purposes and strives to implement a system that keeps records neat and accurate. Out-of-date, imprecise, or incorrect records create a headache when needed for an audit or recall, requiring painstaking time and effort to wade through to collate the necessary data.

HB Specialty Foods, which makes bakery mixes and other specialty products, is an example of a processor finding a better way to maintain records. The company’s paper-reliant process consisted of 17 different forms customized for its various locations. Today, one dynamic form reports to a database, so pulling needed information now takes a matter of seconds rather than hours of digging through piles of paper forms.

A secondary benefit to improved record-keeping for safety and regulatory compliance is that it can help identify trends and potential areas for improvement. Instead of forms being filed away and only pulled out when needed, data can be reviewed and tracked over time, allowing for the identification of troubling trends or performance issues. This means potential problems can be addressed when they are beginning, rather than when they get out of hand.

Maximizing the benefits of production data

When you tie together all the elements of production into a data-driven infrastructure, you’re free to explore its ability to power improvement and efficiency at every stage, from demand planning to packaging formats. But to enjoy the full range of production data’s benefits, processors must have a framework in place to collect the data, evaluate it, and apply it to concrete initiatives that achieve planned operational goals.

The best way to do this is to build from the bottom up. An effective onboarding strategy begins by bringing in all the stakeholders and asking the question, “What do the people on the production line need to work most efficiently?” The data that is most helpful to them on a day-to-day basis will be different from the data that is most helpful in long-term planning and analysis. Both perspectives and sets of data are needed. Understanding which data best speaks to your audience—and why—is what allows you to use that data effectively.

Clif Bar has adopted this model to improve its short-term production efficiency and long-term business strategy. Human-machine interface (HMI) panels throughout the company’s facilities display real-time production data so operators and managers can immediately gauge production status in relation to benchmarks; reports are also available via tablet and a web-based interface that support the programmable logic controller (PLC) processing the hard data. With convenient tools that present straightforward information using relevant metrics, team members can evaluate areas of need and adapt in real time to meet goals for production volume and quality. These insights allow the company to track and compare improvements from shift to shift or hour by hour.

Big data, big advantages

Food processors large and small now have the ability to collect data from every step of their processes. This previously unprecedented access to information offers tremendous insights into current operations and potential improvements. In this data-centric climate, companies are empowered to boost their operational efficiency, identify real-time production trends, and understanding the needs and pain points concerning inventory, equipment, and personnel on the production floor.

Even so, a hasty investment in networked equipment that’s implemented without identifying goals or allocating appropriate skilled labor to manage it is a recipe for disappointment. Understanding and applying the data received is what distinguishes good intention from effective execution. Having processes in place to not only collect, but also manage and utilize data properly will prove your new technology as a versatile tool and an asset rather than a crutch. When you plan for these processes and communicate their implementation to all levels of your business, you set the table for enhanced workflows, faster problem-solving, and increased productivity.