Digital supply chains: how data management is changing along the supply chain of the food & beverage industry

Supply chain is an articulated system made up of people, companies and processes, involving a range of activities including product planning, raw material procurement, processing and packaging, storage, warehouse management and distribution to the end consumer.

Supply chain is a focal point of the food & beverage industry as it has to guarantee food quality and safety through precise tracking of products and their raw materials, upstream and downstream of each process along the supply chain, in compliance with industry regulations.

The importance of data traceability in the supply chain of the food & beverage industry

Supply chain in the food & beverage industry needs to track and manage data and information from the start of the line to the end of the line and in distribution warehouses to the end consumer, so that raw materials, individual products and packaged batches can be tracked down effectively and quickly.

To achieve these goals, there needs to be a continuous exchange of data and information in real time between the manufacturing processes, suppliers and actors in each activity of the supply chain, including the warehouse and distribution logistics.

Manual inspections and paper records of data create grey areas in the supply chain, causing errors and delays to the detriment of production efficiency, product reliability and traceability.

Digital transformation of the supply chain

A critical issue that penalises a traditional supply chain is managing each process step separately. Isolated processes and the lack of information exchange produce inefficiencies with the risk of harmful waste and disruptions along the supply chain.

The technologies introduced by digital transformation in the Industry 4.0 paradigm have enabled the development of integrated solutions to automate manufacturing processes and supply chain activities, including warehouses and logistics, to generate data to be shared and exchanged in interconnected and interoperable environments. This approach includes technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Blockchain and many others.

Hence, the concept of a “digital supply chain” born, which develops its operational models through integrated data management tracked by automated processes at each stage of the supply chain, in a globally interconnected system that also includes suppliers and distribution logistics.

To support the digital supply chain, a centralised platform is needed that integrates management software such as ERP (Enterprise Resource Planning) focused on resource and supply chain planning and WMS (Warehouse Management System) to manage and track data from storage operations, warehouse flows and shipments, providing real-time information with maximum visibility for their sharing.

A “digital” Supply Chain Management (SCM) capable of tracking and sharing data automatically (without manual intervention), raises the standards of efficiency, quality and transparency of the supply chain in the food & beverage industry, allowing traceability of products and raw materials in compliance with industry regulations. Furthermore, with a digital supply chain, planning errors, interruptions and excess stock in the warehouse are reduced, optimising time to market, costs and productivity.

Potential of data: digital supply chain towards proactive autonomous planning

A critical issue that can cause delays and inefficiencies in a traditional supply chain is the need for human intervention in the decision-making process to manage planning and connections between suppliers and between isolated supply chain activities.

Considering an increasingly volatile and rapidly changing market, in addition to the risks of disruptions from suppliers and internal assets, the traditional planning approach managed only by human staff may prove poorly responsive and therefore risky for a resilient supply chain.

A data processing system collected in an integrated digital supply chain has the potential to approach decision-making phases in real time through autonomous planning, capable of addressing critical issues quickly, flexibly and reactively in the event of disruptions or sudden changes in demand.

Autonomous planning in a resilient digital supply chain is developed on an automated technology platform. It is based on in-depth analysis of continuously collected data at each stage of the supply chain, sharing information to proactively process supply chain decision-making in real time with appropriate algorithms.

In this context, Chief Supply Chain Officers are called upon to develop innovative operating models, spreading a new professional culture among the human capital employed in the supply chain towards a management supported by data analysis, software applications and proactive digital technologies, going beyond traditional schemes.

Digital supply chain towards hyperautomation

Hyperautomation is a combination of several digital technologies, including Robotic Process Automation (RPA), Machine Learning (ML), Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Blockchain and many others.

Modern digital supply chains approach hyperautomation technologies with the aim of implementing the capacity to process heterogeneous data in ever-increasing quantities, improving the efficiency and reliability of autonomous planning.

In particular, through the analysis of data (cause/effect) collected over time and in different contexts that influence digital supply chain planning in different ways, the algorithms of artificial intelligence systems in combination with machine learning systems acquire an “experience” with which they create reference models to elaborate autonomous decision-making processes in real time that are increasingly reliable.

Following this trend, through the analysis of shared data in the digital supply chain, it will be possible to make forecasts on demand variability, estimate risks and digitally simulate the effects of planning along the supply chain, assuming different contexts and criticalities.

Future scenarios in the food & beverage industry foresee a development of digital supply chains with autonomous planning systems in response to the increasing amount of variables and data to be managed in real time. The centrality and supervision of humans, who will have to drive digital innovation and take care of process reliability, remains fundamental.