Digital tools in food, beverage lay the groundwork for AI-driven success

The adoption of system software and digital tools is accelerating in the food and beverage industry. Companies are investing in digital tools to accelerate product development, and these system integration projects are succeeding due to agile-based approaches. The result is providing digital foundations for food companies that will eventually drive artificial intelligence (AI) strategies.

Food and beverage company boards are asking for AI strategies in 2024. At the IFT FIRST conference, Michael Warter, SVP and chief information officer at Ruiz Foods Products Inc., revealed that his board wants a Generative AI strategy sooner rather than later.

“The first challenge is getting people to understand what artificial intelligence (AI) is in its various facets,” Warter said. “To me, it’s understanding your processes and data so you can build effective models for AI.”

Over the last five years, food and beverage companies have adopted digital tools and system software to accelerate product development. Platforms like Enterprise Resource Planning (ERP) and Product Lifecycle Management (PLM) software have succeeded due to nimble, agile-based project approaches. The objective of these digital platforms is structured and clean data within the enterprise that will drive more efficiency with compliance, traceability and supply chains.

“The reality is that companies can adopt digital tools incrementally, realizing value at each step,” Wes Frierson, VP of product lifecycle solutions at FoodChain ID, said. “This phased approach not only spreads out the investment but also eases the transition, helping to mitigate change management challenges.”

Ruiz Foods touched on its recent PLM projects at the IFT FIRST conference. During a panel session, the company cited its ERP cloud project and its move away from on-premises hosting to reduce operational costs. With the help of Infor and Doppio Group, Ruiz Foods devised a plan to transition gradually to the cloud instead of moving everything simultaneously. “We were able to find a way to step into the cloud without having to do it all at once,” Warter explained.

While AI seeps into every conversation in 2024, food and beverage companies are moving fast to establish structured data throughout their enterprises via digital platforms. PLM software is essential for visibility into ingredient suppliers, compliance data, traceability and efficiencies during product development.

“Digital tools not only streamline processes but also enhance collaboration and provide greater visibility across the organization and your supply chain,” Frierson said. “This increased transparency is particularly crucial in ingredient supply chains, where relevant data insights can significantly reduce risks associated with compliance, quality control and supplier reliability.”

Like Ruiz Foods’ reliance on its integration partner, FoodChain ID delivers solutions to clients to accelerate product development and increase traceability. The company’s Recipes & Specifications platform manages data and process automation across the New Product Development (NPD) lifecycle. The platform offers digital supply chain collaboration, specification management, advanced recipe development, integrated compliance and labeling tools.

According to a FoodChain ID survey, customers’ development data had to be manually reentered on an average of seven different systems during the standard development process. “Before adopting our solution, we commonly see customers gathering information from their suppliers over email, then trying to organize and leverage that information throughout the product development process using traditional tools like Excel or Genesis,” Frierson explained.

In addition to the recipe platform, FoodChain ID also has a formulation for PLM solution that plugs into existing PLM platforms, like Oracle PLM or Siemens Teamcenter. This solution includes embedded advisor technology that delivers real-time, contextual information in the product development stage.

“For example, it might suggest substituting an ingredient, flagging a potentially problematic supplier, or warning that a key requirement for a targeted claim is not being met,” Frierson said.

A phased project approach to digital transformations is winning and helping food companies meet challenging drivers moving toward AI-based strategies.