How to Transform Medical Device Supply Chain with MDM

Oct 20, 2021
Life Sciences | 5 min READ
    
Medical Devices Supply Chain
The healthcare supply chain is under enormous pressure. Particularly, the supply chain in medical device industry is getting more complex by day as companies are on an expansion spree to align their product portfolios with the rapidly changing ecosystem. While the pandemic is a major cause of disruption in the industry, it is not the only one. Factors such as sudden unforeseen events like climate change or natural disasters, macroeconomic policy changes, political scenarios, malicious cyber threats, and financially fragile suppliers are equally responsible for bringing down the operations for medical devices in the supply chain.
John Danese
John Danese

Industry Director

Life Sciences

Birlasoft

 
Top it all; companies have to adhere to specific guidelines and regulations related to processing, packaging, data governance, and more that creates more challenges if not monitored closely and carefully.
Usually, the supply chain management in the medical device industry creates and manages a massive amount of data—another area of concern that comes in the way of seamless operations of the entire industry. On a practical note, this data has been managed in silos curbing its ability to generate value. The realization that this data can drive value across the supply chain is essential to keep the operations going.
Hence, strengthening the supply chain is very much the need of the hour now. Identifying these pressure points and redefining the entire system making it data-driven, will make the supply chain more resilient in function. On this note, let's look at the potential supply chain issues in detail:
Stay Ahead
Visit our Life Sciences & Healthcare page
MDM and Medical Device Supply Chain Issues
Industry's current supply chain will not be able to overcome these challenges forever. Companies must develop new capabilities, especially a robust data management system and new ways of operating, stepping up the speed, flexibility, efficiency, and reliability of the entire system. Better data handling and management is a prerequisite to achieving a value-driven supply chain, and MDM transformation is a priority.
AI and Machine Learning Use Cases in Insurance
Inefficient Supply Chain
Inefficiency in the MedTech supply chain weighs heavy on production costs and inventory management, ultimately failing to adhere to the regulatory compliance and guidelines, pushing the company toward higher costs and squeezed margins. Proper cloud-hosted master data management and its integration with the existing framework would help navigate these challenges easier and faster.
Delays in Product Launch
Companies want to expand their product portfolio to aligning it to the changing market needs and environment. As modern, smart, connected device production gets more complex, enhanced scrutiny and quality checks must be in place. Product lifecycles lengthen. But, we expect the same infrastructure and the processes to guide us through. Failing to evolve the data system and identifying the clear points in which the product doesn't conform to specifications often delays the launch of the products. Revisiting the entire process manually to find the loophole takes ample time, incurring a loss of resources.
High Volume of Lost Sales
The problem becomes stickier when demand is high. A product failing to launch at the right time due to wrong reasons that go undetected leads to lost sales revenue and opens the door for competitors to gain first-in-market advantages. Businesses lose out on the market share. With the rise in demand, quality and compliance issues also surge, leading to higher production costs.
Medical device supply chains could cut manufacturing lead times and allow manufacturers to carry significantly smaller inventories with proper management of master data.
How is AI Transforming the Semiconductor Industry: Top Use Cases and Benefits
Potential Indicators: Need for MDM Transformation
Enabling effective management of master data and its faster exchanges as per the global standards, the medical device supply chain can strategize better to deliver performance at a lower cost. A smart move is to identify redundancies, inconsistent workflow, error-prone areas, high-cost touchpoints and bringing coherence to the entire supply chain, a digitized transformation of master data management.
AI and Machine Learning Use Cases in Insurance
Inability to Collate Product Information for Supply Chain Management
A poor master data management leads to half-baked product information for the supply chain. For instance, without clear data visibility and availability, it is hard to understand the quantity of stock inventory, faulty checks, unclear deliveries, no demand forecasting, and ambiguity in almost every production process. Eventually, this leads to chaos and a supply chain collapse.
An Exponential Increase in Product Data and Digital Assets
Cloud is the future to host and manage master data. For a medical device manufacturer, it brings in great advantages. Digital maintenance of product data helps easily identify the ineffective process flows, enabling targeted actions and quick resolution without hindering the operations as a whole. It is easy to put compliance checks and identify potential points of failure that bring down the efficiency of the supply chain.
Foundational Support for Data Transformation
A well-managed master data approach is the basis of data transformation and migration. In the case of future mergers & acquisitions, this proves to be beneficial, providing clarity of what product data is current and accurate and establishing consistency in the content, format, review and approval processes of the data. This way, companies can build resilience and mitigate risks while data is migrating to the new enterprise data master data management framework.
Examples of MDM-led Supply Chain Transformation in Medical Devices Industry
MDM-led supply chain leaves no gaps in strengthening the overall architecture. Companies can take targeted actions and make informed decisions in times of vulnerabilities. For example:
  • Taking financial challenges head-on, like - poor credit history, corporate liquidity, changing industry value.
  • Having good protocols in place and a better cybersecurity posture for potentially identified threats.
  • Regulations enabled beforehand for anticipated changes.
  • Set the structure by concentrating on the parts of the value chain exposed to climate changes, trade regulations, conflict, or epidemics and making it easier to shift manufacturing and supply chain operations to alternate sites.
  • Visibility of suppliers, planning of inventory, delivery schedules, performance, sourcing risks, and more operational challenges could be addressed easily with careful study of the records.
  • Organizational restructure and its impact, product complexity, any concerns related to the organization's reputation could be tracked and monitored.
Master Data Management in Healthcare
To summarize, master data management will help solve medical device supply chain issues and evolve to the next normal. Better equipping the companies with the facts and figures to predict disruptions in advance and act accordingly, building resilient and compliant supply chains.
 
 
Was this article helpful?