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Survey Results
Data Silos: A Prominent Barrier in Strategic Initiatives
A significant 50% of participants rated data silos as a 9 out of 10 when considering them as obstacles to achieving strategic goals. The challenge of data silos in the life sciences industry is evident. Fragmented datasets and disconnected systems can limit innovation. The emphasis on removing data silos speaks to the growing need for platforms that enable unified data access.
Internal Silos and Their Impact on Insights and Innovations
An overwhelming 100% of respondents believed that breaking down internal data barriers would lead to enhanced insights and innovations. This unanimous sentiment underscores the universal understanding that collaboration and free-flowing data are vital for driving forward the industry's research and development.
Quality and Completeness of Data Sets: A Call for Improvement
The feedback on data quality was revealing. With no respondents rating their datasets above 6 out of 10, there's a clear call for better data quality and integrity within the industry. Ensuring data quality, management, and integration becomes critical in addressing these concerns, helping organisations to derive meaningful insights from their datasets.
Dataset Size and Robustness in R&D Leveraging
While the majority (75%) did not view the size or robustness of their datasets as R&D limitations, it's essential to recognize that having ample data isn't synonymous with having actionable data. The industry's challenge lies not just in collecting, but effectively utilising and interpreting this data. Platforms and tools that can streamline, curate, and make sense of vast datasets are becoming indispensable.
Investment Trends in Data Management Platforms
Reflecting the industry's pivot towards enhanced data management, 100% of participants indicated interest in investing in data management platforms. This trend points to a recognition within the life sciences sector that, to remain competitive and innovative, organisations must prioritise state-of-the-art data management and integration tools that align with their R&D objectives.
Scattered Data: The Search for Integrated Information
Half of the respondents (50%) identified the challenge of scattered data as a significant hindrance. This feedback highlights an industry-wide struggle: the need to swiftly locate and access relevant data. The life sciences domain, with its vast and growing datasets, requires platforms and tools that not only store data but make it effortlessly discoverable. An integrated, centralised system can curate and consolidate data, ensuring that professionals spend less time searching and more time deriving meaningful insights.
Data Cleaning: The Unsung Hero of Analytics
33% of participants pointed to data cleaning as a primary challenge. Before any meaningful analysis can occur, this data must be cleaned and standardised. Adopting automated tools and hiring dedicated data stewards can streamline this tedious yet essential task, ensuring that datasets are accurate, consistent, and ready for analysis.
Carbon Footprint and Sustainability: An Overlooked Priority
Interestingly, none of the respondents identified carbon footprint reduction as a current challenge or focus. As global emphasis on sustainability grows, the life sciences industry should also pivot towards environmentally-conscious practices, aligning with broader global goals.
Sponsored by
We are a global player in life-science R&D informatics, providing customers with cutting-edge multi-omics data management and integration software. We develop innovative off-the-shelf and custom solutions for clients in pharma, biotech, agriscience, consumer goods, and research centers. Omics Data Manager (ODM), our flagship product, helps organisations create a FAIR catalogue of multi-omics investigations (studies, samples, omics data), with powerful tools for curating rich and standardised metadata in bulk, as well as optimised RESTful APIs for scalable cross-study, cross-omics integrative search.
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