Massimo Crudeli
Discover today’s top Artificial Intelligence use cases for improving efficiency and avoiding drug and device shortages.
According to a June 2023 MGMA Stat poll, more than three-quarters (76%) of medical groups surveyed reported negative impacts from drug and drug supply shortages. One practice leader called the problem “a pandemic all its own.”
Shortages of medicines related to a wide variety of conditions, from respiratory and gastrointestinal disorders to cardiovascular and cancer concerns, are impacting patients worldwide. The same is true of medical devices, such as those used in anesthesiology, radiology, dialysis, cardiovascular care, and other specialties.
Recent news stories have kept these shortages in the public consciousness, relating the difficulties and dangers of strained supplies of everything from ADHD medications to oncology drugs. As these disruptions filter down to patients, providers are often forced to make uncomfortable decisions that can sometimes mean the difference between life and death.
These alarming shortages are occurring for a variety of reasons, including increased demand, parts discontinuation, bankruptcy, compliance requirements, rising inflation, the energy crisis, supply chain complexity, manufacturing capacity issues, geopolitical events, natural disasters, race-to-the-bottom pricing strategies, and more. In a complex global economy with many variables, quite a bit can go wrong.
Technology Helps Life Sciences Organizations Improve Supply Chain Resiliency
While certain scenarios may be outside the control of pharmaceutical companies, biotech firms, and medical device manufacturers, life sciences organizations can—and should—be much more proactive when it comes to supply chain resiliency and operational efficiency. The FDA has offered supply chain resiliency guidance, as has the European Medicines Agency (EMA).
Mike Walker, Executive Director, Global Life Sciences Strategy at Microsoft, wrote in a June 2023 Forbes article that “the importance of a well-functioning supply chain has never been more evident than in recent years. A pandemic, geopolitical conflict, increased costs, and uncertain availability have had fundamental implications for pharmaceutical organizations.”
To solve the problem, Walker encourages life sciences organizations to digitalize their operations and embrace technologies such as Artificial Intelligence (AI) to optimize data. “The pharma industry is feeling the pressure of competition from startups and cloud-native disrupters,” he writes. Too many manufacturing sites are using on-premises solutions, which, according to Walker, “tend to be an inhibitor to growth.”
By organizing data with a cloud-based Enterprise Resource Planning (ERP) system, organizations can start using AI to streamline workflows, solve problems proactively, and mitigate risk. “An AI-driven approach to planning ensures visibility of supply chain activity but also allows for the prediction of future events,” according to Walker. “This all starts with creating a data strategy that directly addresses data availability, access, and quality and leveraging technology to eliminate unstructured and manual data entry.”
While AI can automate many mundane tasks, its real power lies in extracting insights from disparate data sources that are beyond human perception. With human oversight, these insights can be used to solve problems and drive growth.
By organizing data with a cloud-based Enterprise Resource Planning
(ERP) system, organizations can start using AI to streamline workflows, solve problems proactively, and mitigate risk.
Walker asserts that generative AI can help pharmaceutical companies forecast demand more accurately, improve inventory management, reduce lead times, and optimize production processes.
His vision of the future of life sciences manufacturing also includes business composability, digital twins, augmented reality, virtual reality, and mixed reality technologies, and lights-out factories that can reduce costs by 15%–30%, manpower by 50%–70%, power consumption by 40%, and product deviation by 50%.
Laying the Right Foundation for AI-Powered Supply Chain Management
The new Microsoft Dynamics 365 Copilot is enabling businesses across all industries to benefit from the latest AI advances. With AI capabilities available in limited preview in the Microsoft Supply Chain Center, companies that use the Microsoft Dynamics 365 ERP system can try Microsoft’s AI-powered Supply Chain Center to:
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Predict and mitigate risks by tracking events that may impact your supply chain
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Orchestrate actions across your supply chain with end-to-end visibility
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Reduce supply and demand mismatches by running simulations using AI and real-time analytics
Microsoft Dynamics 365 is a powerful ERP for modern business organizations. And it becomes purpose-built for life sciences companies when used with native solutions from STAEDEAN —such as STAEDEAN Life Sciences Supply Chain Management—that address the specific data collection parameters, regulatory requirements, and compliance issues faced by pharmaceutical companies, biotech firms, and medical device manufacturers.
Many life sciences organizations are using outdated ERP systems.
Talk to STAEDEAN about digitalizing your company today for
greater efficiency and cost savings.
Top AI Use Cases for Supply Chain Management
Once you have your data centralized, Microsoft Copilot can start delivering greater supply chain resiliency and operational efficiency for your business. Here are just some of the ways you can start benefiting from intelligent process automation, natural language understanding, and other AI capabilities today:
1. Avoid Supply Chain Disruptions
Microsoft Copilot monitors the news and flags weather, financial, geopolitical, and other issues that may impact key supply chain processes. Predictive insights surface affected orders across materials, inventory, carriers, and distribution networks, and automated, contextual emails open a channel for real-time collaboration between you and your partners.
2. Supercharge Procurement Productivity
Procurement professionals spend lots of time manually reviewing purchase order change responses. Copilot can quickly identify high-impact and low-impact changes and take rapid action to address risk.
3. Elevate Forecast Accuracy
Microsoft Copilot brings a greater foundation of trust to system-generated forecasts using natural language querying. Now demand planners can breeze through their demand plan analyses, reducing the time needed for fine-tuning and adjusting from days to minutes.
4. Mitigate Order Delivery Risks
With conversational AI, procurement teams can instantly gather and analyze performance data for monthly supplier reviews and help struggling vendors meet their delivery requirements. Additionally, AI can significantly accelerate new supplier onboarding by bypassing or accelerating internal legal review.
5. Gain Instant Inventory Insights
Through root-cause analysis and recommendations, Microsoft Copilot’s AI can help you reduce stockouts and improve customer satisfaction and loyalty. Users can swiftly ascertain stock levels and solve problems by typing inquiries in natural language, like chatting with a friend. Gone are the days of navigating through cumbersome menus and remembering product IDs or location details.
As a Microsoft ERP partner for life sciences, STAEDEAN helps pharmaceutical companies, biotech firms, medical device manufacturers, and Contract and Development Manufacturing Organizations (CDMOs) throughout the U.S., Europe, and Australia innovate and run more efficiently.
We’re excited to help life sciences organizations begin and continue their AI journeys and embrace new standards that will define the future of Good Manufacturing Practice (GMP). If the advances delivered by Microsoft Copilot are any indication, AI is poised to revolutionize the way life sciences companies develop and manufacture drugs and devices.
Do you want to start your AI journey and prepare your life sciences business for the future?
Massimo Crudeli