Big Data in Pharma: Structure, Governance and Partnerships

STUDY OVERVIEW

The last decade has seen an explosion in the availability of data that can deliver valuable insights for the pharmaceutical sector– from Electronic Medical Records and clinical trial data to medical claims and patient behavior data. All these information types are part of the large and complex data sets that make up what’s called Big Data.

The pharma industry recognizes the huge potential that Big Data holds for providing insights that could have a major impact on clinical programs as well as commercial activities. Among the myriad challenges facing pharma as the sector strives to develop Big Data capabilities are where the Big Data team or function should sit in an organization, what governance system or policies should be in place and what type of organizations are best to partner with on projects. Best Practices, LLC undertook this study to probe these questions and current trends in the pharmaceutical sector around Big Data and the issues of structure, governance and partnerships.

KEY TOPICS

• Executive Summary
• Big Data Team Overview and Key Study Insights
• Quantitative Key Findings
• Qualitative Key Findings
• Defining Big Data
• Structure
• Governance and Capabilities
• Partnerships

• Do you have a centralized/dedicated group (Big Data team or function) to support Big Data projects?
• When do you expect your organization to establish a Big Data team or function?
• Large versus small pharma presence of centralized/dedicated Big Data team or function
• US versus global pharma presence of centralized/dedicated Big Data team or function
• Policies and procedures in place to govern Big Data activities
• Regions where you have Big Data capabilities and Big Data governance resides
• North American functions that utilize and/or lead Big Data projects
• Internal vs. external staffing for list of nine data capabilities
• Will your organization's data capabilities increase over the next 2 years and will resources be internally or externally increased?
• Which partners are most impactful/valuable on Big Data projects?

• Big Data Team/Function Part of Future: 53% of participants said they had a “centralized/dedicated” Big Data team or function, although centralization is certainly difficult to define in this case. Nearly all of the study participants will have a Big Data team or function by 2017. The structure and governance of a Big Data/Analytics team is certainly something organizations are wrestling with. 
• Big Data Policies and Rules Important for Future: Policies are proliferating on a variety of data issues. Our study  found that the absolute number of policies in place increased slightly at centralized organizations. Governance will be very important going forward as pharma needs a clear strategy for developing the function as well as bright lines surrounding the appropriate use and sharing of data between functions & organizations.

Industries Profiled:
Pharmaceutical; Health Care; Biotech; Chemical; Medical Device; Manufacturing; Consumer Products; Diagnostic; Biopharmaceutical; Clinical Research; Laboratories


Companies Profiled:
Merck; Merck Serono; Novartis; Boehringer Ingelheim; Genentech; Teva Pharmaceutical Industries Ltd; Pfizer; Baxter Healthcare; GlaxoSmithKline ; Bayer; Gilead Sciences; Janssen; Lundbeck; Sanofi; Esteve; Daiichi Sankyo; Purdue Pharma; AstraZeneca

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