By Thaddeus Wolfram
An identity crisis of sorts is striking the pharmaceutical industry. Many of its biggest players are rethinking their core competencies in reaction to health care reform and the changing landscape of health care delivery. But their reaction is also spurred by the sweeping data revolution.
Pharma companies have discovered that data analytics can be used to improve everything from clinical trial decision-making to marketing practices, and from inventory control to regulatory compliance. This means entrepreneurs who are poised to help pharma make the most of data analytics have a unique opportunity. But to fully take advantage of it, entrepreneurs need to understand the strategic struggle taking place inside pharma.
In strategy sessions across the industry, executives are grappling with important questions: Does data analytics need to become a core competency? Should it be on par with the science of R&D and the commercial interface with customers and patients? Further still, is analytics so important to the future success of these other competencies that it warrants an even greater consideration?
Those questions are leading to some soul-searching by pharma executives. They’re taking a hard look at current and future product lines and their available resources. They’re examining key assets and the resources required for effective data analytics, such as supportive enterprise architecture and the right mix of data scientists.
The sweet spot
If advanced data analytics is deemed strategically critical to the company’s future, the company will likely strive to make analytics a core competency and develop the capabilities internally. Where analytics is considered important but not critical enough to become core, the alternative is to partner with an experienced data analytics expert. This is the sweet spot for entrepreneurs who specialize in data analytics.
To determine if outside help is necessary, consider:
- The gap between what the company is doing now compared to what it would like to achieve
- The capabilities, skill sets and technological requirements necessary to realize value from data
How far data analytics might deviate from a company’s current business model in these situations, a pharmaceutical company could benefit most from outside help. But there are some situations where a pharma company may not want to work with an outside party – for example, when the data itself contains the seeds of competitive advantage.