Three Indicators of Data Maturity Leadership in Life Science

Data Maturity Leadership in Life Science
Data Maturity in Life Science
Earlier this year Informatica’s CEO introduced the concept of Data 3.0: A level of organizational maturity where data is the new control point, and will shape how applications are developed and deployed. At conferences and in private discussions I have been party to, the theme of ‘Data Powering Business’ is gaining strength. Many Life Science organizations are starting down the path to ensure high quality data is a corporate priority, and available to all.

The trend towards Data 3.0 in Life Sciences is in part being driven by the transformation of health care from treatment of individual ailments to collaboratively managing health. In this new model for improving quality of life in the twin reality of increasing lifespans and rising chronic disease, manufacturers of medicines will also deliver services ‘beyond the pill’. Collaboration and new services (many of them will be digitally enabled) gives rise not only to new data, but multi-purpose data. That is, data that is not ‘owned’ by any one department, but can be used to drive process improvement and business value across many traditional silos.

In future life science companies who rely on data (and not applications) to give them competitive advantage will reap rewards in terms of agility and innovation. The future is always uncertain, but in the corporate world, the growth of data in terms of volume, variety and importance is a certainty.

Fortunately many life science companies have realized that their core differentiator is the ready availability of high quality data. Once data is flowing throughout the organization, specific applications can be selected (or developed) to deliver competitive advantage. With the availability of high quality data, these applications should be deployed more quickly, and have a higher probability of success in terms of accurate results based on accurate inputs.

So far, I have mentioned ‘the future’ in this blog. But the data-driven future is actually not far off, and is more likely to be measured in months rather than decades. Looking across Informatica’s customer base, I see three traits of data driven life science companies:

  1. Their leaders have openly stated that data is vital to their future.

I interpret this as a statement of intent: If senior leaders tell the world data is a differentiator, then the value of data is well understood. Investment in this asset will not be far behind.

Philips CEO, Frans van Houten stated in an interview to a Dutch newspaper that ‘Data and communications play an increasingly important role in health care.’

Philips was a 2014 finalist in for an Informatica Innovation Award, awarded to organisations who are transforming their businesses by unleashing the full potential of their data. Their quest for enterprise level high quality data has started in 2012.

A commitment to digital innovation is also a commitment to data. Ipsen’s executive committee has charged their CIO & Digital Officer, Malika Mir, to rapidly deliver digital transformation: “The critical question for us is how digital technologies can help Ipsen understand the patient experience better.” It is through data that Ipsen will understand the existing patient experience, and how they can improve this experience to encourage compliance to treatments for improved patient results.

  1. They have a platform approach to data management.

Having a corporate data platform with common tools and capabilities is a clear indicative of a Data 3.0 maturity level: The primary focus is on data availability, with all new and existing applications and innovations benefiting from this high quality data. Data platforms often have names, helping to raise the profile of data internally and externally. It also provides a useful reference framework to promote internally to people who are used to applications with names.

Contract Research Organisations in particular have a high focus on the data platform approach. Quintiles relies on Infosario for improved decision making: “Quintiles’ Infosario clinical data management platform gives researchers and drug developers the knowledge needed to improve decision-making and ultimately increases the probability of success at every step in a product’s lifecycle.”

ICON’s information platform ICONIK enables more informed, data-driven decisions regarding the clinical trial process, including the effective use of monitoring resources, patient treatment and safety and site performance.

  1. They deliver value from integrating disparate data sets 

Hospitals are leaders here in terms of reaping the rewards of the ease of integrating data to improve research and patient health with an eye to improving the cost and effectiveness of chronic disease.

UPMC has a foundational architecture in place, allowing researchers to electronically integrate—for the first time ever– clinical and genomic information on 140 patients previously treated for breast cancer.

Similarly, MD Anderson Cancer Center  securely houses clinical and genomics data in one centralized location. Patient samples are already being collected and analyzed to determine genetic signatures of disease.

What is most interesting to me, is that the examples above are not outliers. They are definitely leaders, and are have clear returns on their investments in data. From my perspective, I can see a large group of fast followers. Many companies are leveraging data to break out of organizational silos to deliver both medicines and health care innovations faster.

As a positive by-product of tearing down organizational barriers in data, the life science industry is becoming more transparent. The availability of high quality data within Life Science is of interest to all of us: Data will underpin a world of faster development of new medicines, enable innovative treatments, and crucially – increase trust in the entire industry through open dissemination of information. This is a data-driven future I look forward to.