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
Report Features
- Unique insights from experts in Big Data and analytics from companies such as AstraZeneca, Bayer, Janssen and J&J
- Graph showing the number of Chief Data Officers by background
- Graph illustrating lung cancer classification complexity
- SWOT analysis of Big Data and analytics in commercial effectiveness
- Graph detailing advanced analytics through the commercial life cycle
- Case Study: The convergence of healthcare, Big Data technology and customer interface Case Study: The convergence of healthcare, Big Data technology and customer interface
- Case Study: Understanding the payer landscape with a third party
- Case Study: Increasing diagnosis rates to increase market share
- Case Study: Developing salesforce commitment to use of analytics
- Case Study: Long-term collaborations with technology giants
- Case Study: Piloting the IoT for the future
- Case Study: A third party for drug non-adherence measures
- Best Practice: Connecting the dots in social media
- Best practice: Essential organisational lessons for big pharma
- Best practice: Adopting Big Data into the organisation
- At-a-glance summaries of all the key takeaways.
Key Benefits:
- Understand the importance and value of Big Data to pharma’s future
- Know how Big Data and analytics can drive commercial excellence across the organisation
- Create a progressive operating environment that allows the power of Big Data to be released
- Use Big Data outcomes to radically improve patient, payer and physician engagement
- Apply Big Data analysis to drive competitive advantage and customer-centricity
- Understand the challenges of harmonising data from multiple source to create meaningful insights
- Assess the technical and operational developments that will drive the Big Data agenda over the next 5 years.
Top Takeaways and 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
Key Quotes
“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
“An often overlooked aspect of Big Data is how it relates to the manufacturing process itself. Over the past 5–10 years, there has been a concerted effort in creating systems that record real-time process data, house batch information and analytical test data. The issue with these data storage systems is that they are segregated and often do not have a common format, which leads to a wealth of ‘dark data’ that we put so much effort into collecting, but not utilising to its full potential.”
Dave Latshaw II
Scientist, Janssen Pharmaceuticals
“In the past, there was a lot of emphasis placed on relationships. But as the number of channels continues to grow, in addition to relationships, you also need to take a very important note of the insights that you’re able to gather from multiple channels. Sales people are not going to sit and fiddle with all sorts of IT tools. Without having a really good analytical ability, you cannot get through to people in the field in a way where they can make decisions very quickly.”
Irina Osovskaya
Global Director of Mobile and Customer Experience Strategy, AstraZeneca
Who Would Benefit from This Report?
- Data analysts charged with designing and delivering Big Data projects
- Medical affairs professional harnessing Big Data insights for medical communications
- HEOR teams building evidence of product value
- Commercial teams needing Big Data outcomes to support commercial propositions
- Regulatory professionals needing to ensure compliance with data privacy regulations
- Company leaders needing to resource and support Big Data initiatives.
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
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