After investing in equipment, manufacturing processes, software, and IT infrastructure, companies are now exchanging data every millisecond, from production lines all the way to the uppermost levels of the IT architecture. Paired with real-time monitoring technologies, data reinforces product traceability and secures the supply chain.
Companies can now use supply chain data for their business and operational strategies. They can leverage their original investments in track and trace infrastructure to collect, visualize, measure, and analyze data to improve quality, safety, and efficiency, as well as promote sustainability via, for example, creating a paperless supply chain. As communication of data is now fast and effective — flowing freely and securely among machines, lines, plants, and partners — it will take minimal effort to complete this first phase of investment and secure complete control over what is happening in real-time at each level of the supply chain.
BENEFITS OF TRACEABILITY:
The benefits of traceability (beyond mere regulatory compliance) stem from visibility created by uniquely identifying every product in the supply chain, from the manufacturer all the way to a specific patient. These benefits include reducing exposure to risk, managing, and reducing costs, and increasing accuracy. Now, every stakeholder has the opportunity to leverage visibility about what is moving where within their business and between themselves and their trading partners. The value traceability will deliver to a supply chain actor depends on their vision for what data can provide to their business.
The pharmaceutical industry had to reinvent itself during its serialization journey; many companies built up better communication — and integration — between IT and OT to help manage their transformation. Forward-looking companies also made organizational changes that could facilitate the second step in the digitalization path. Today, there is opportunity to continue collaboration between departments and secure the process by discovering, tracking, and solving any quality, process, production, and technical issues.
By connecting resources and production data, the new Industry 4.0 tools, such as Artificial Intelligence (AI), Internet of Things (IoT), and Machine Learning (ML), can be helpful in this process, as there will be an enormous amount of data to interpret for decision-making and analysis. Predictive applications in Industry 4.0 are also promising. We can predict if a product will be good long before it is released, and predictive maintenance procedures are becoming more popular as a means of guaranteeing equipment reliability.