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5 Digital Supply Chain Management Tools That Will Transform Life Sciences Organizations


Digital transformation initiatives were already underway among life sciences manufacturers before COVID-19 struck, but the volatility resulting from the global pandemic in 2020 brought to light the importance of digital supply chain tools. In fact, according to a McKinsey survey of global executives, companies digitized many activities 20-25 times faster as a result of COVID-19.

For life sciences organizations, integrating digital supply chain tools has enormous implications.

Business Impact of Digital Supply Chain Tools

For forward-looking companies that are taking steps toward digital transformation in manufacturing, research is beginning to show a clearer business impact of digital supply chain management.

“At organizations that experimented with new digital technologies during the COVID-19 crisis, and among those that invested more capital expenditures in digital technology than their peers did, executives are twice as likely to report outsize revenue growth than executives at other companies,” according to McKinsey.

Not only have digitally mature companies outperformed their competition during the global pandemic, but they are expected to continue accelerating ahead of their peers. Boston Consulting Group (BCG) research shows that more than 80% of companies plan to accelerate their digital transformation efforts — and with good reason.

“Digital leaders achieve earnings growth that is 1.8 times higher than digital laggards — and more than double the growth in total enterprise value. In the short term, digital technologies and ways of working offer productivity improvements and better customer experiences. In the medium term, digital opens up new growth opportunities and business model innovation,” according to the consulting firm. “Successful transformations also set companies up for sustained success; they won’t have to digitally transform again as they master continuous innovation.”

Research compiled in MasterControl’s “The State of Digital Maturity in Pharma and Medtech Manufacturing” report shows that the need to improve connectivity is the driving force for 41% of life sciences manufacturers’ efforts to pursue digital transformation in manufacturing. Companies that don’t embrace digital supply chain management and other modern approaches won’t just lag in digital maturity – they’ll fall behind competitors who are enhancing efficiency and visibility by using innovative new tools.

Integrating Digital Supply Chain Tools

Several technologies have emerged to help life sciences companies excel in an increasingly digital economy. Here is what five of these technologies mean for the life sciences supply chain:

  1. Automation - Automating operations and systems can streamline work along the supply chain. For many life sciences companies, capturing and managing supplier data often involves dealing with data manually using a paper-based or partially electronic system, and then not updating the data regularly. digital supply chain tools and supplier management automation can be leveraged to collect and process real-time information automatically, thereby eliminating the slow, time-consuming effort of manually gathering, entering, and updating data.
  2. Internet of Things (IoT) - The IoT, the network of physical devices and systems that communicate and exchange data, holds real potential for optimizing supply chain operations, especially for collecting data from across many data sources and measuring performance in real time. IoT devices provide real-time visibility of operations throughout the manufacturing process. Manufacturers can embed IoT sensors in most items moving through their supply chain, gaining unprecedented visibility and traceability of parts for assembly, finished goods, and more.
  3. Advanced Analytics - As IoT data continues growing at a rapid pace, the data is often unstructured, disorganized, and incomplete. The massive amount of supply chain data collected is of little use if a company can’t quickly and intelligently analyze and leverage it. Advanced analytics can play a major role in making digital supply chain management data usable, providing greater insights into processes, products, and people and, in turn, enabling supply chain leaders to make better decisions to improve operations and business.
  4. Artificial intelligence (AI) - AI and machine learning technologies, which learn over time as they are exposed to more data, have great potential to transform supply chain processes. They enable companies to collect data from a variety of areas and apply self-improving analysis. AI can be used throughout the supply chain to find patterns, forecast future scenarios, identify and correct data errors, surface risks, elevate IoT insights, and improve material planning, order scheduling, and logistics.
  5. Blockchain - Blockchain is essentially a digital, decentralized, distributed, and immutable ledger, and it has the potential to be very disruptive. Once information is entered into the blockchain, the distributed ledger becomes locked and tamper-proof. Smart contracts, traceability, authentication, and other highly decentralized digital supply chain management functions are considered key candidates for blockchain, although most supply chain blockchain projects are still pilot projects.

The promise of digital transformation in the supply chain is a more complete understanding of every element of the supply chain, helping companies to improve planning, decision-making, and responding to issues. When data is digitized and connected to other data points across the enterprise by the IoT, and analyzed by AI algorithms, the data becomes more visible, usable, and valuable.

A Digital Path Forward

Integrating digital supply chain tools can bring substantial opportunities when the right digital technologies are applied and in the right way. Yet large-scale change is hard, so as life science manufacturers look for ways to boost the business impact of digital supply chain tools, they can start their digitization efforts with a "small automation" approach, focusing on quickly implementing flexible, adaptable technologies that fill existing gaps created by their enterprise systems.



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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