Why Life Science Organizations Fail To Implement Effective Data Strategies

In the rapidly evolving landscape of life sciences, where innovation is paramount, numerous organizations have foundered in their efforts to establish effective data strategies. Despite recognizing the potential of big data and analytics to revolutionize drug development, personalized medicine, and patient care, a surprising number of life science entities struggle to harness their data's full power. The reasons for these failures to implement effective data strategies offer a cautionary tale for organizations across all sectors.

One notable example can be traced back to a report published by NewVantage Partners, which surveyed executives from major pharmaceutical companies and healthcare organizations. The report highlighted that a staggering 90.6% of respondents admitted they faced challenges in becoming data-driven. Additionally, 92.2% stated they continued to struggle with cultural challenges to organizational alignment and business adoption.

The causes are multiple.  To dive deeper in this topic we had a very open discussion with our guest Noel Gomez Co-founder of Datacoves. He brings a wealth of experience and expertise in data management and strategy within the life sciences industry. With over 15 years of experience helping large organizations, Noel has worked with companies such as Pfizer, GSK, J&J, Amgen, and Kenvue, to name a few. He has implementation and change management experience working with both technical and business clients in their digital transformation initiatives. Noel is well-equipped to help us understand the challenges life science organizations face in implementing effective data strategies.