DATA-DRIVEN MANUFACTURING THE DATA-DRIVEN
Data-driven manufacturing systems, like real-time analytics, integrated planning tools, and end-to-end traceability platforms, are becoming essential for long-term resilience.
R
ising consumer expectations for personalised products, increasing regulatory scrutiny, and growing pressure to improve sustainability
are all pushing manufacturers to reimagine how they operate. One of the most transformative responses to these pressures is the move toward data-driven manufacturing — a shift that is changing how products are made, tracked, and delivered around the world. At the centre of this are manufacturing
technology firms like Andea, which are helping food and confectionery manufacturers adapt by implementing data-focused systems that offer better traceability and efficiency.
A complex industry in transition Food and confectionery manufacturers operate in one of the most complex industrial sectors. Unlike other manufacturing industries, food production must contend with highly variable raw materials, constantly changing consumer preferences, and strict food safety regulations across multiple jurisdictions. Adding to the challenge is the need to localise products for different markets while simultaneously managing cost pressures and sustainability goals.
30 • KENNEDY’S CONFECTION • JULY 2025 Traditional production models often lack the
flexibility to adapt quickly to these variables. Siloed data, limited visibility across the supply chain, and manual tracking processes all hinder responsiveness. That’s why manufacturers are increasingly turning to digital transformation strategies and tools that emphasise real-time data, integration, and automation. Data-driven manufacturing refers to the
use of real-time data, advanced analytics, and automated decision-making to optimise production processes. This includes everything from predictive maintenance and demand forecasting to quality assurance and regulatory compliance. Manufacturing Operations Management (MOM) and Advanced Planning and Scheduling (APS) systems play a key role in this shift. When properly implemented, they can provide manufacturers with end-to-end visibility of their operations, enabling faster and more informed decision-making. Andea, a technology consulting firm that specializes in implementing these types of systems, has been involved in a number of food and confectionery manufacturing projects globally. Their work provides a useful
approach
case study in how data-driven tools are being applied in real industrial environments. One example is Andea’s ongoing
collaboration with Burger King SEE, the Southeastern Europe division of the fast- food chain. The project focused on improving the performance of the company’s existing systems while enabling integration with new data sources. According to Jacek Wałaszek, Business Intelligence Manager for Burger King SEE, the collaboration helped modernise their digital infrastructure and streamline how data is used across operations. “Implementing [Andea’s] recommendations has significantly improved the performance of our solution,” Jacek says. He noted that the process involved both strategic improvements and ongoing maintenance, with new capabilities added as the business evolved. While the specifics of the implementation
remain proprietary, the results point to a broader trend: food manufacturers and by extension, confectionery manufacturers, are looking beyond basic automation and seeking more integrated, responsive systems that use data to inform every part of the production lifecycle.
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