5 Changes Life Science Companies are Making in their Digital Strategy

June 04, 2021

By Monstarlab

Part of our Health & Life Science Series

According to experts, life science companies are past jumpstarting digital transformation and are well into adapting their new systems [1]. However these companies are discovering that complacency is not an option as they settle into their new dynamics. As the sector’s enterprises are met with new challenges and many changes, competitive companies have turned to the following technological innovations for their impacts on boosting operational productivity, accelerating growth, and revolutionising customer experience. 

In this article, you will learn:

  • What timely adjustments in strategy life science companies are making in their digital transformation efforts
  • What new uses of existing technologies the sector is leveraging
  • The impact of these changes on the sector’s stakeholders

Artificial Intelligence beyond having a ready-made reply

Although chatbots, Natural Language Processing, and the broader Conversational Business Intelligence have catalysed customer-centric operations and have changed the customer experience altogether, there are far bigger roles and responsibilities that Artificial Intelligence (AI) could cover and conquer when used correctly – something that the life sciences’ industry leaders have already realised.

Top IT Use Cases:

  1. Data Governance
  2. Knowledge, Content Management & Information Portal
  3. Data Visualisation & Democratisation

According to the latest report on the top technology use cases, the majority of the players in life sciences have already employed AI in working directly with their largest asset – data [2]. Companies are replacing outdated data collection methods, automating rule-based processes, and even making data management decisions.  With 27% of organisations in a global survey reporting more than a 10% labor cost reduction, 23% reporting the same savings in operations, and 19% the same in marketing and sales, enterprises are reaping the rewards of AI in their digitisation [3].

Scaled Cloud Integrations

Multitudes of life science firms have already integrated the Cloud in their businesses. However, much of their initial efforts have proven unsustainable because of inaccurate data quantity and quality measurement, as well as unprepared and overwhelmed in-house resources.

Companies in the sector have been reported to leverage expertise from third-party partners, seeking secure large-scale data government success. As quantified by the same group, 53% measure data management success with agility and marketing speed, 26% with improved customer satisfaction, and 26% with increased adoption rates – indicating their positive experience with these outcomes [4]

Novel Custom Software Development

As software development has been considered the underlying enabler of digital transformation since its boom by transformation partners [5], custom software development as part of transformative strategies no longer sounds exciting. However, recent innovations on life science softwares will tell you that that doesn’t stand true for them.

With this year’s surge of novel and distinctively-purposed software such as interactive patient-care applications, precision research software, nano to macro modeling and interpretation tools, and collaborative therapeutic or medical procedure applications, the public sees more of the logic behind custom software development’s claim to fame. Along with the consumers, corporations are also enjoying and riding on this novelty to both enhance customer experience and operational efficiencies, and are paving the way for the rest of the sensible businesses to follow.

Robotics Process Automation 

Robotic Process Automation or RPA has also become a notable and increasingly visible solution sought by advancing enterprises. From a life science point of view, RPA can help across the GxP landscape including Good Manufacturing Practices, Good Clinical Practices and Good Laboratory Practices by automating processes through rules-based systems, according to a 2019 report on life science [6].

Some of the manual processes RPA can be applied to include

  • Streamlining the product labeling process in manufacturing
  • Maintaining official records required by predicate rules, subject to inspection under FDA requirements
  • Identifying high-risk abnormalities in images through large-scale interpretation and processing of clinical trials data, such as radiology reports

While the stakes for integrating RPA are often low, non-invasive, and quick in adapting to existing systems, the reward can be high when life science companies unlock the value behind the technology. In fact,  a minor sampling conducted recently found that implementing RPA for data validation processes can eliminate manual errors by 80 to 99% and ensure data consistency and accuracy in reporting [7].

Blockchain in Supply Chain

With almost daily developments, the rapid pace of progress in therapeutic and medical technologies are challenging life science supply chains. From drug delivery to tracing sold miscellaneous products, the need for secure, speedy, and accurate distribution from the manufacturing end equally increases along with such developments.  With Blockchain technology, the sector is quickly catching pace.

Within life sciences alone, a projected $3 billion opportunity by 2025 could be credited to Blockchain due to its ability to manage supply chain provenance, serialised track and trace, and specialty logistics with minimal intervention. This calculated, speedy, and uncomplicated approach to the supply chain has been widely popular and highly trusted among transforming businesses [8]

Although these trends and changes have made their rounds in improving and innovating business in the life sciences, the real key to success in digitisation remains to be how these technologies are being utilised and maximised. 

Key Takeaways

  • The life sciences, growing into the digital business ecology, needs to situate and act upon their goals beyond their initial strategy and in tune with the current technological atmosphere
  • The massive amounts of valuable data ingested and created by enterprises in the sector proves best approached with minimum human intervention and more adaptive technologies that coordinate processing from end to end (AI collecting and interpreting data, the cloud storing and distributing it, RPA automating following processes, and Blockchain encrypting and continuously recording and tracking transactional data) 
  • This adaptive and coordinated digital approach boosts transaction and operation speeds, reduces manual errors significantly, and increases productivity for enterprises at varying levels.


[1] AIT News Desk, “Axtria CEO Talks Life Sciences Commercial Excellence In Ask Jassi Video Series”, 2020
[2] Axtria, “Emerging Technology Trends In the Life Sciences Industry”, 2020
[3] Statista, “Cost decreases from adopting artificial intelligence (AI) in organizations worldwide as of 2019, by function”, 2019
[4] Accenture, “Life Sciences Companies See the Cloud as a Path to Product Innovation”, 2018
[5] Intland Software, “How Digital Transformation Impacts Software Development”, 2019
[6] Deloitte, “Life sciences IT quality Validating cognitive solutions”, 2019
[7] Deloitte, “RPA and CA in medtech Increasing efficiency, reducing costs”, 2018
[8] Accenture, “Transforming life sciences with blockchain”, 2018

Other references:

AI Multiple, “15 RPA Benefits Compiled from Top Sources”, 2020
Deloitte, “2020 Global Life Sciences Outlook”, 2020

Read more insights and see more of our work on health & life science

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