Life Sciences Two People
NNIT Expectation Barometer 2023

Data enablement and digital business models

The potential of data enablement in life sciences

For companies in the life sciences industry, data is the most important asset to create better results throughout the value chain. By leveraging your data across the value chain, you can improve decision-making, efficiency, and quality and you can bring your products faster to market.

In the future, data is key to staying relevant and competitive – and ultimately bring better products to patients.   

But how do you bring data to live across different business units? How do you leverage  data to ensure cost savings, more efficiency and higher quality? And are you reaping the benefits of digitizing your business processes?

Realizing your full data potential requires the right mix of technologies, skills, structures, and priorities.

Where are you on the data journey?

That question we asked more than 100 respondents who participated in our survey, focusing on data enablement and the enormous potential of utilizing data across the life sciences industry to improve quality and competitiveness – and ultimately bring better products to patients.

The answers in this year’s survey provided some interesting results:

  • Only 50% of the respondents have already a data strategy in place in their organization.
  • The ability to enable data isolated within business units is rated above average for most.
  • However, leveraging data across or between business units seems more challenging to the majority.
  • Finally, nearly 50% of the respondents place heightened integration of AI at the top of their priority list.

In other words: The survey shows that lack of cross unit collaboration is the biggest barrier for leveraging data in business processes. Furthermore, there is a clear interest in utilizing AI, however using AI in life sciences raises profound questions and possibilities.

Based on the input we interviewed two NNIT experts who will give you their best advice within data enablement and AI:

In the first articles Ricco Larsen, Senior Vice President at NNIT, will, based on the survey results, give his top 3 best advice for digital leaders in life sciences in regards to building a solid data foundation.

In the second article Sam Laermans, Head of Digital Advisory at NNIT, will share his thoughts on the strengths and pitfalls of welcoming AI into the realm of life sciences and give his 3 best advice on what to consider before investing In AI.

Would you like to know more about how your organization can work with data enablement, digital business models and processes, and new agendas? Five NNIT experts share their best tips. 

Global cooperation between health authorities and increased focus on structured data reporting are just some of the regulatory trends impacting pharma companies. Christopher Lucas, Consulting Director US Research & development at NNIT Inc., explains how digital solutions can enhance regulatory data.

Read the article here

Reports of adverse events are increasing rapidly, placing a heavy burden on pharmacovigilance teams in the life sciences industry. Jesper Borgstrøm, Senior Business Consultant at NNIT, explains how advanced digital tools can help you process the growing influx of safety data to provide clarity and extract more value.

Read the article here

Both sponsors and research sites can benefit by increasing the use of digitalization and data enablement in clinical trials. According to Martin Lim, Managing Consultant at NNIT, streamlined patient recruitment, better data capture and reduced investigator burnout are just some of the advantages.

Read the article here

By analyzing their quality data, pharma companies can find the weak points in their value chain and optimize their processes. Charlotte Øbakke, Head of Quality, Europe at NNIT explains how digital tools and strong data models and be used to improve quality across your business.

Read the article her.

How much of the process-related data generated by your pharma production provides real value? According to Marco Glauner, Head of Manufacturing & Supply Chain Solutions Europe at NNIT, a fresh look at existing manufacturing, laboratory and serialization data can reveal multiple opportunities for improving your business. 

Read the article here.

About NNIT Expectation Barometer  

Every year, NNIT conducts an Expectation Barometer. It is an online survey where we focus on digitalization and take the pulse of different digital themes in organizations, spiced with in-depth interviews and case stories with selected digital leaders. 

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