For pharmaceutical companies data governance is a critical piece of the data management puzzle.
Pharmaceutical and life sciences companies face many of the same digital transformation pressures as other industries, such as financial services and healthcare that we have explored previously. In response, they are turning to technologies like advanced analytics platforms and cloud-based resources to help better inform their decision-making and create new efficiencies and better processes.
Among the conditions that set digital transformation in pharmaceuticals and life sciences apart from other sectors are the regulatory environment and the high incidence of mergers and acquisitions (M&A).
Protecting sensitive data in these industries is a matter of survival, in terms of the potential penalties for failing to comply with any number of industry and government regulations and because of the near-priceless value of data around research and development (R&D).
The high costs and huge potential of R&D is one of the driving factors of M&A activity in the pharmaceutical and life sciences space. With roughly $156 billion in M&A deals in healthcare in the first quarter of 2018 alone – many involving drug companies – the market is the hottest it’s been in more than a decade. Much of the M&A activity is being driven by companies looking to buy competitors, acquire R&D, and offset losses from expiring drug patents.
With M&A activity comes the challenge of integrating two formerly separate companies into one. That means integrating technology platforms, business processes, and, of course, the data each organization brings to the deal.
As in virtual every other industry, data is quickly becoming one of the most valuable assets within pharmaceutical and life science companies. In its 2018 Global Life Sciences Outlook, Deloitte speaks to the importance of “data integrity,” which it defines as data that is complete, consistent and accurate throughout the data lifecycle.
Data integrity helps manage risk in pharmaceutical and life sciences by making it easier to comply with a complex web of regulations that touch many different parts of these organizations, from finance to the supply chain and beyond. Linking these cross-functional teams to data they can trust eases the burden of compliance by supplying team members with what many industries now refer to as “a single version of truth” – which is to say, data with integrity.
Data integrity also helps deliver insights for important initiatives in the pharmaceutical and life sciences industries like value-based pricing and market access.
Developing data integrity and taking advantage of it to reduce risk and identify opportunities in pharmaceuticals and life sciences isn’t possible without a holistic approach to data governance that permeates every part of these companies, including business processes and enterprise architecture.
Data governance gives businesses the visibility they need to understand where there data is, where it came from, its value, its quality and how it can be used by people and software applications. This type of understanding of your data is, of course, essential to compliance. In fact, according to a 2017 survey by erwin, Inc. and UBM, 60 percent of organizations said compliance is driving their data governance initiatives.
For pharmaceutical companies, data governance helps organizations contemplating M&A, not only by helping them understand the data they are acquiring, but also by informing decisions around complex IT infrastructures and applications that need to be integrated. Decisions about application rationalization and business processes are easier to make when they are viewed through the lens of a pervasive data governance strategy.
For pharmaceutical companies, data governance can be leveraged to hone data integrity and move toward what Deloitte refers to as end-to-end evidence management (E2E), which unifies the data in pharmaceuticals and life sciences from R&D to clinical trials and through commercialization.
Once implemented, Deloitte predicts E2E will help organizations maximize the value of their data by:
If that list of benefits sounds familiar, it’s because it matches up nicely with the goals of digital transformation at many organizations – more efficient processes, better collaboration, improved visibility and better cost management. And it’s all built on a foundation of data and data governance.
To learn more, download our free whitepaper on the Regulatory Rationale for Integrating Data Management & Data Governance.