The data generation and collection strategies at the center of life sciences organizations and their manufacturing processes have evolved dramatically, especially in recent years. These organizations now collect and store huge volumes of data across their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos.
These advances have coincided with the proliferation of connected sensors and increasingly inexpensive storage, leading to an Industrial Internet of Things (IIoT) ecosystem projected to generate more than 4 trillion gigabytes of data per year by 2020, according to IDC Research.
New, advanced data analytics have a huge positive impact on the growing volumes of data in many sectors, from retail to financial. So why aren’t all these new analytics widely leveraged in the life sciences industry? With so much data and the promise of so many new technologies, why is it so difficult to gain the same benefits as other sectors? Why do so many life sciences organizations still feel like they have too much data and not enough insight?