Powering Commercial Effectiveness Through Big Data and Analytics

Powering Commercial Effectiveness Through Big Data and Analytics

  • September 2016 •
  • Report ID: 4275613 •
  • Format: PDF



Big Data is commercial dynamite for pharma – how can you unleash its power?
Big Data is here to stay. Not just a fad, it’s fundamentally changing the way pharma companies operate and providing a route to better commercial results. What are the key challenges and opportunities? What does best practice look like? Ultimately, how can the commercial benefits of Big Data be realised?
Powering Commercial Effectiveness Through Big Data and Analytics explores how Big Data is evolving beyond the patient experience and coming of age. Read it to hear from 11 experts at the forefront of pharma’s data revolution.
“Data alone has little value. It is the insight we glean from analysing it. Pharma has no chance of making money without making cases for change, defining burden or proving effectiveness in the real world. It simply cannot do these things without first connecting data for analysis.
Hassan Chaudhury, Chief Commercial Officer, Health iQ







Top Takeaways and Answering key questions:


Perfect partnerships: How important are partners in the long-term? Are the most productive collaborations internal and cross-functional or external and specialist?
The face of Big Data: What blend of skills and technological tools are needed? Does leveraging Big Data demand a departmental focus or a company-wide cultural shift?
Speed, agility, credibility: Are you responding fast enough to gain an advantage through Big Data insights? Is integration an issue? How robust are the patterns modelled and insights derived?
Balancing act: How should pharma seek to apportion investment for optimum impact? Should data architecture or data talent/analytics be the priority?
Where next? There is plenty that’s new and exciting. Wearables, social media, data-sharing, Internet of Things, real world data. What has commercial potential and what is simply ‘noise’?


Experts Interviewed for This Report


Brad Ashby: Director of Commercial Operations, Kaléo Pharmaceuticals
Blanca Rosales Baez: Executive Advisor – Business Development Big Data Analytics for Precision Medicine, Molecular Health GmbH
Peter Barschdorff: Vice President of Business Insights at Bayer: Market Research, Commercial Analytics and Commercial Reporting (Quotes attributed to him are his personal opinion and do not in any way represent Bayer Pharmaceuticals’ opinions or business practices)
Hassan Chaudhury: Chief Commercial Officer, Health iQ
David Latshaw II: Scientist at The Janssen Pharmaceutical Companies of Johnson & Johnson
Manish Mathur: Senior Director, Data Strategy and Management for Commercial Excellence, at Janssen Pharmaceuticals, of Johnson & Johnson (Views made in this report are his personal opinion and are not intended to represent the views of Johnson & Johnson)
Irina Osovskaya: Global Director of Mobile and Customer Experience Strategy at AstraZeneca
Anders Quitzau: Innovation Executive, Watson Advocate
Ian Talmage: Senior Vice President, Global Marketing at Bayer Pharmaceuticals
John Michael Veik: Large Enterprise Sales, IBM
Anonymous: The personal (non-Agency) opinion of a recent FDA employee
Content Highlights


Content Highlights

The growing power of Big Data over pharma’s commercial future
The commercial potential of Big Data and analytics
Key insights
A wealth of information available
Sub-segmenting patients based on genomics and personalised medicine
Segmenting physicians, key opinion leaders and payers
Deep learning about customer experience
Informing R&D, regulatory compliance and market access
SWOT analysis of Big Data techniques
Modelling and simulation: extracting business insight for commercial excellence from Big Data
Key insights
Appropriate modelling essential
Data types needed to improve aspects of commercial excellence
Real-world data
Data about a more accurate market share
Data sharing for better decision-making in the field
Data about the patient experience
Harmonising data from multiple sources
The tools to use: from knowing which data to use to actioning insights
From insight to competitive advantage: the human factor
From insight to customer-centricity to increased sales
Structural changes to accommodate Big Data
Key insights
Get your house in order
New capabilities and positions
A culture of data and innovation
Data-based training methods
Best future opportunities for the use of Big Data in commercial excellence
Key insights
The Internet of Things
Targeted customer messages
Precision medicine and personalised patient programmes
Payer orientation for improved market access
Improved physician engagement
Driving patient adherence
Overcoming the greatest challenges in Big Data
Key insights
Uniformity of data language
Data in disparate locations
Magnitude and credibility of data
Data privacy and security implications
The next five years of Big Data
Key insights
Machine learning and scaling data
Investments and partnerships in pharma
Security and compliance
Conclusion