For any industry, the ability to connect data points, maximize equipment efficiency, and extract performance insights are well-documented advantages of implementing “Industrial Internet of Things” (IIoT) into the supply chain. Transparency created by an integrated network of “smart” devices fosters improved data insights, opportunities for predictive analytics, and increased efficiency. However, life sciences companies should also consider IIoT as a way to improve quality compliance.
One of the most popular and debated solutions has been the incorporation of IIoT. Integrating IIoT into the supply chain for purposes related to speed has become especially enticing and beneficial for quality managers. Utilizing IIoT can provide quality with the necessary data and documentation to identify root causes and execute corrective and/or preventive actions in a timely manner.
IIoT Solutions have Huge Upside to Enhance Quality Compliance
According to warning letters issued by the FDA in 2016, trends have shown an increased focus on data integrity and the consistency with which records are taken along the supply chain. Life sciences companies can use IIoT solutions like electronic documentation platforms, smart labeling, and GPS to minimize supply chain bottlenecks and enhance quality compliance by minimizing deviations caused by human error or process failures. Moreover, as serialization becomes even more critical for global supply chains, IIoT automation can ensure each transfer is tracked and recorded to improve expiry management and defense against drug counterfeiting.
Leveraging IIoT solutions can also elevate the perception of quality as a more strategic business function as opposed to being perceived as a reactive function or cost-center. Instead of putting out fires as they occur, quality managers can use IIoT and predictive analytics to develop preventive measures for problems that could happen in the future. For example, some pharmaceutical companies have employed predictive analytics to reduce cost per dose, increase productivity, and avoid purchasing additional manufacturing capacity. By improving foresight, companies can more accurately predict and prevent drug shortages as well as help position the supply chain to facilitate innovation and adapt to evolving trends in personalized goods. In this way, implementing IIoT can boost a company’s ability to improve therapeutic outcomes for patients.
…But Concerns Still Remain
While IIoT solutions modernize supply chain capabilities, they also have their own associated risks. Overwhelming influxes of data require complex infrastructure and platforms to help manage and make decisions. As connected systems extract data at higher volumes, leadership must develop new ways to store, interact with, and interpret the data. After all, the ultimate value of data collection is the insights it generates.
The key to incorporating IIoT is moderation. Quality and supply chain managers must identify specific areas of improvement and assess whether corresponding IIoT solutions align with their businesses. Sometimes, selecting an IIoT strategy without caution can result in massive volumes of perplexing data and increased inefficiency.
With regards to supply chain transparency, incorporating IIoT solutions is a two-sided coin. Connecting a network of smart devices increases accessibility but also heightens the threat of cybersecurity. For life sciences companies, protecting records and product information is of utmost importance. As the rate of cyber breaches continues to climb, network security and the protection of cloud-based storage systems will become additional areas for quality and supply chain to address.
Where Can You Go From Here
Coordinating a switch to a full-on or hybrid IIoT supply chain is an elaborate process. Every company deals with different situations and issues regarding quality and supply chain and, as a result, requires a specific IIoT strategy. In order to commit to IIoT as a quality solution, you need to weigh all benefits, risks as well as verify which areas of the supply chain are most conducive and profitable for implementation.
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Co-author and contributions by Adam Kershner.