Big Data in Pharma: Information Type & Sources for Big Data Utilization Across Commercial Functions

STUDY OVERVIEW

The rapid evolution of Big Data is generating greater insights for commercial decisions within the biopharmaceutical industry. The inherent costs and challenges that come with harnessing large sets of information have caused the pharmaceutical sector to embrace Big Data analytics slower than other industries.

Identifying the most useful types of data and sources of data is an important initial step to realizing the huge potential that Big Data holds for commercial functions within pharma. It is also important to understand what internal and external groups value commercial Big Data analyses.

Best Practices, LLC undertook this study to probe current trends and best practices in commercial functions utilizing Big Data. The study offers key benchmarks around what types of data organizations are using most frequently as well as the data sources they find most useful. Also, the research examines which internal and external groups most value Big Data analyses and which are the most frequent requestors of such information.

KEY TOPICS

• Defining Big Data
• Data Types and Sources
• Data Producers, Dissemination & Requestors

• Value of listed types of transactional data sources
• Value of listed types of reported/survey data sources
• Value of listed types of online data sources
• Value of listed types of scientific/clinical data sources
• Value of listed types of machine-generated data
• Value of listed types of data producers
• The most impacted target audiences for data analysis
• Most common ways for disseminating real world data analysis
• Most common requestors of data analysis

• Commercial Payers and internal company sources were the only types of data producers a majority of partners rated as highly valuable. A majority of the commercial segment also rated health systems as highly valuable.
  
• Internal Commercial, Medical and Development functions were rated by a majority of respondents as the most impactful targets for data analysis presentations. A majority partners also said these internal groups were also the most frequent requestors of presentations.
  

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