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:
