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Medical Device Manufacturing Trends, Pt. 2: Digitize to Make Data Usable

Collect, connect, and contextualize medical device manufacturing data through advanced technologies to leverage digitization.

Digitization was already on the rise among manufacturers’ priorities, but the global disruption caused by the COVID-19 pandemic led many organizations to adopt digital solutions quicker than previously planned. The pandemic reportedly accelerated the digitization of manufacturing organizations’ internal operations and supply chain interactions by three to four years.1

In fact, according to a Fictiv survey of manufacturing professionals across medical device and other industries in 2021:2

  • 91% reported an increased investment in digital transformation efforts over the previous year.
  • 77% stated the increased year-over-year digital investment was significant or dramatic.
  • 95% agreed that digital transformation in manufacturing is essential to their company’s success.

“Few people will argue against digital transformation as one of the major drivers of growth and innovation,” Fictiv, which provides a virtual manufacturing platform, reported in its findings. “We have seen COVID-19 accelerate this trend by creating a wider acceptance and adoption of all things digital, both in operations and production.”

As the move toward digitizing manufacturing has accelerated following the COVID-19 outbreak, so has usage of the advanced technologies underlying digitization. Some of the most significant shifts include increases in cloud migration and use of advanced technologies – such as artificial intelligence (AI) and automation – in operations to leverage digitization and better collect, connect, and contextualize data.

Manufacturing Technologies to Make Data Usable

As enterprise data continues growing at a rapid pace – from manufacturing operations, quality, suppliers, and much more – the data is often unstructured, disconnected, and incomplete. If a company can’t quickly and intelligently analyze and leverage the massive amount of data being collected, that data offers little value.

Cloud technology, automation, and AI will play a major role in making this data usable for organizations in medical device manufacturing. Along with predictive analytics and other advanced analytics, these technologies provide greater insights into processes, products, and people. In turn, they enable medtech manufacturing leaders to make better decisions to improve operations and business.

3 Ways to Connect and Unlock Manufacturing Data

Below are three considerations that medical device manufacturing organizations should keep in mind as they look to invest in digital tools and technologies.

#1: Adopt a Cloud-First Approach to Digitizing Manufacturing

The cloud harmonizes different tech platforms, is scalable on demand, simplifies data management and access, and can actually increase data security with continuous security monitoring and incident response. The cloud breaks down silos and improves real-time communication and collaboration. Beyond connectivity advantages, a cloud-based manufacturing software solutions requires fewer capital investments and IT resources than traditional on-premise systems, reduces operational costs, and makes software updates seamless.

#2: Focus Manufacturing Automation Efforts on Offline Data Gaps

Manufacturers’ technology investments are often impeded by a digital manufacturing gap created by siloed information systems and paper-based, disconnected production processes. Integrating these disparate systems and paper-based processes with a manufacturing software solution with digital device history records (DHRs) can close this gap by creating productive connections between systems, processes, and people throughout the manufacturing process and across the entire enterprise for a holistic view of production data.

#3: Explore AI Opportunities to Improve Manufacturing Processes and Products

In product development, medical device manufacturing organizations are assessing the business value of using AI and machine learning (ML) technologies to identify process problems, product defects, and equipment maintenance issues before they result in costly delays. Top outcomes medtech and other life sciences companies are attempting to achieve with AI include enhancing existing products, creating new products and services, and making processes more efficient. Most reported having used AI successfully to make processes more efficient.3


Figuring out which areas to digitize can be difficult and different for every company, but medical device manufacturing organizations must understand how they can leverage the capabilities of new and existing digital tools and solutions to use untapped data, streamline processes, and improve operations.

“The time to act is now,” Deloitte says.4 “Acting proactively and leveraging the recent advancements in digital technologies are critical for the future success of medtech companies.”

  1. How COVID-19 Has Pushed Companies Over the Technology Tipping Point...,” McKinsey & Company, October 2020.
  2. 2021 State of Manufacturing Report,” Fictiv, April 2021.
  3. Scaling Up AI Across the Life Sciences Value Chain,” Deloitte, November 2020.
  4. The Digital Era in the MedTech Industry,” Stephen Laaper and Allan Krul, Deloitte, 2018.


David Butcher has covered business and technology trends in life sciences and industrial manufacturing for more than 15 years. Currently a content marketing specialist at MasterControl, he previously served as editor of Thomas Publishing’s Industry Market Trends and as assistant editor for Technology Marketing Corp.’s Customer Interaction Solutions. He holds a bachelor’s degree in journalism from the State University of New York, Purchase.

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