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Article Big Data Blog Life Sciences November 29, 2017 2 minute read

3 Key Big Data Challenges that Pharma Companies Needs to Solve to Keep Their Competitive Edge

The Life Sciences industry functions around data collected from different sources, for various purposes. As pharmaceutical and biotechnology markets are poised to exceed USD 1.2 trillion by 2022, it is only natural for organizations in the industry to want to invest in innovative and cutting-edge technologies to manage their biggest asset – massive volume of data from numerous sources.

With a great amount of data comes a great amount of challenges. Storing and recording data from various sources is one thing, leveraging it accurately for insights, is quite another.

Even today, when there are so many examples of big data analytics in pharmaceutical industry, very few pharmaceutical companies have been able to truly leverage their data for competitive advantage. The main challenges in doing so are:

  • Not having access to all levels of data
  • Not enough accuracy of derived analytics
  • Inability to deliver complex analytics fast in an easy-to-understand manner

Challenge 1. Disparity of Data Sources

The most prominent issue that all pharmaceutical companies face while preparing their data for analytics is the disparity of data. Most of the data is stored in silos and is accessed via different platforms, all using their individual data models and structures. Therefore, having access to all the data at any given point is extremely critical to running a viable analytics process.

Challenge 2. Ambiguity Around Accuracy

Another challenge faced by most of the organizations using analytics is the ambiguity around the accuracy of analytics reports, along with its time-based relevance. Due to data being stored in silos and collected from disparate sources, it is difficult to be sure if all the data was accessed or how fresh it was.

Challenge 3. Time-consuming Analytics Process

When so many data sources are used, it is difficult to harmonize all the data and run a set of analytics across the data set. Organizations that do not have a proper data analytics system in place, or even those who opt for a point solution, end up having to manually collate analytics reports and insights. Such a process is time-consuming and may fail to uncover insights that may have useful business implications.

It is obvious that the entire data capturing, handling, and analytics process needs to shift. In fact, the approach towards managing data is already changing. So much so, that the latest technology and approach are impacting the way organizations conduct their business.

When leveraged correctly, data yields insights that directly impact business growth. Any data analytics solution that can help organizations save money, increase the bottom line, and not cost an arm and a leg while doing so, would be sure to find its way on that organization’s wish list.

Saama can put you on the fast track to clinical trial process innovation.