Data Inflection Point

Sep 05, 2017
Volume 37, Issue 9

"Digital transformation” seem to be the buzzwords of this era for the life sciences industry and it’s no wonder, given the rise of digital information in healthcare.

Today we find ourselves in an industry that is increasingly complex; a data-rich environment that brings more and more information to the table, with a growing number of stakeholders and a need to draw insights—the right insights—from the multitude of data available to us. These insights drive market readiness decisions and often lie at the crux of a product market strategy. 

Just as the technological revolutions of customer relationship management (CRM) tools and big data have changed how life sciences companies do business, machine-guided, predictive insights from that data are the industry’s next big opportunity.

The future is here

According to Forbes, “Big data is transforming businesses across industry sectors—from industrial systems to financial services, from media to healthcare delivery, from drug discovery to government services, from national security to professional sports.” 

In her annual 2017 “state of technology” presentation, Mary Meeker, the visionary Internet maven of venture capital firm Kleiner Perkins Caufield & Byers, dedicated 31 pages to digital health and called this moment “the digital health inflection point.” We are now looking at an industrial revolution that is driving a need for more sophisticated technologies to manage the intricacies of data commerce.

Similarly, a Bain & Company report underlines the mastery of data and digital technologies as the distinguishing characteristic of the most competitive pharmaceutical companies in the next 10 years. 

Furthermore, big tech companies like Apple, Google, and Facebook are increasingly investing in healthcare. In fact, Bill Maris, a Google Ventures founder, left Google this year to raise a new investment fund of over $230 million that will focus solely on healthcare investments.

What’s holding us back

The healthcare industry has been slow to adopt emerging technologies, but the cautious pace is understandable.

Healthcare companies create and manage exponentially-increasing amounts of highly sensitive data, and must be compliant with the laws and regulations that surround it. “The healthcare industry has very stringent requirements around cryptographic security that dictates how and when the data needs to be encrypted, transmitted, and decrypted,” writes Meeta Dash of the Tokbox Blog. “The scope and complexity of healthcare regulation has made it incredibly difficult for organizations to adopt new technologies.”

Add to that the changing stakeholder landscape of healthcare, which has become ever-more complex. Traditionally, the industry catered to physicians—something that CRM software managed well. Field representative-generated data also helped to provide a more complete view of customers and markets for improved commercial and operational excellence. Yet, even as recently as 2016, according to an Econsultancy and Ogilvy CommonHealth report, up to 44% of biopharmaceutical companies said they were not prepared to use their CRM data in marketing campaigns. 

Now, there are more stakeholders than just the physician; payers, prescribers, providers, provider networks, and patients are as relevant as physicians, and physicians’ networks of influence are proving increasingly important in decision-making. 

Changes in regulations and culture are also redefining what is meant by “product value” for life sciences companies; new treatments are no longer rated in terms of efficacy and cost alone, but also in terms of how well they address customer needs.

As healthcare organizations around the world grapple with increasing price pressures, emphasis on value-based pricing models is becoming more pronounced and providers are under pressure to do more with less as well. Pay-for-performance or value-based pricing agreements with healthcare providers and insurers—much like the one struck between Novartis and Aetna/Cigna early last year for heart drug Entresto—are becoming more commonplace and, in turn, holding greater sway over physician choice. 

Additionally, segmented and sometimes siloed company divisions like market access or managed care are also quickly becoming essential sources (and consumers) of data for a more complete and holistic approach to “go-to-market” planning and execution. 

To keep up with this growing stakeholder network, life sciences companies require access to deeper and more diverse data sets. They also need more complete, integrated, and cross-enterprise technology solutions that can give them a broader view of the “customer,” with relationship and network analytics that provide a cohesive view of their market potential.  

The tipping point

The first step for the healthcare industry was to digitize its existing banks of data, replacing analog and paper-based systems with digital versions. The data generated within a given organization then became easier to organize, analyze, and share.

The next step was to collect more data sources—in other words, it was time to put the word “big” in front of “data,” and to access more channels of information. According to a McKinsey & Co. patient survey, nearly 70% of US consumers use an online channel to manage health and wellness, and patients can now access their own health records online and log important health data from their smartphones—simple actions that were previously unavailable. This democratization of healthcare information has returned incredible amounts of data to healthcare providers and the life sciences companies that work with them.

Patients are now connected instantly with disease-related information as well as online forums and communities. Meanwhile, apps and wearable technology are recording performance data based on lifestyle, selected symptoms, adherence, and overall well-being. 

The result is that patients are more engaged than ever before with their treatment pathway, and frequently approach their physician with ideas and suggestions, making them another important influencing factor for a brand.

 

Key opinion leaders and healthcare professionals are also using digital technologies that produce real-time insights into customer relations, opinions, and patient needs. At the same time, however, it’s still difficult to understand and set digital markers along the patient journey—including the increasingly complicated reimbursement journey—that align with a brand’s digital strategy.

These activities all generate high-value data that can be used as a part of a complete brand strategy, and that can be integrated into that strategy for improved customer access and engagement. Now, life sciences companies need to more effectively manage new and existing data sets; to gather, compile, and analyze them in order to better understand how to deliver value for their product portfolio.

Tapping into these data sources and the insights they harbor is vital for life sciences firms to inform and transform their business operations. In order to remain relevant and align with customer values, they must leverage real-time data to make more agile and confident business decisions and predict future trends. 

What’s next

This technological adaptation in healthcare reflects our rapidly accelerating ability to adopt new digital solutions. A decade ago, smartphones didn’t even exist and now more than half of the world’s population uses one. Similarly, in those 10 years, over 80% of the US population now has at least one social media profile. The pace at which new technologies are created and adopted is redoubling again and again. 

The next step is to take these massive datasets and put them to work. Having “big data” at our fingertips and knowing what to do with it is another story. Today, analysts still have to know which questions to ask of the data in order to gain any meaning from it. Shifting to machine-guided analytics means letting the data speak to us directly and suggest next-best steps. New technologies are less “human-guided” and more “machine-guided,” with predictive solutions increasing in importance. This is where life science companies’ go-to-market efforts can benefit most dramatically, leveraging data intelligence platforms to guide a data-driven, insights-driven approach to customer engagement through all channels, including personal and non-personal.  

The companies who are leading the way in digital transformation are equally focused on increasing their digital and analytic capabilities as well as on supporting these with strategy, culture, and organizational process. In order to be successful, a digital strategy must be embedded into all parts of the business, with customer engagement at the core, and the supporting technology being the means by which teams can holistically and cross-functionally execute to those initiatives.  

With a coordinated, cross-enterprise plan to bring currently fragmented and siloed approaches to digitalization together, life sciences companies will get the market, medical, and customer insights they need to transform commercial success with speed and confidence. The implementation of a digital strategy for a brand needs to be a team effort. It is a complex process, involving many moving parts and departments (both internally and externally) and a fundamental switch in mindset around data and the benefits that this will bring to the business. To be effective, it requires the buy-in of every member of internal staff who will be working with, or adjacent to, the new system—and aligned support from the right external partners.

A signal of our industry’s commitment to digital transformation is the increasing number of biopharma companies who now have senior leaders in place to lead these efforts—one in five of the top biopharma organizations, according to a McKinsey review of the top 25 global drugmakers. In fact, GlaxoSmithKline recently announced the appointment of a new senior position of chief digital and technology officer, recognizing the need to bring these initiatives to the highest level of senior management. 

According to a recent survey from Marketo, almost 70% of all US marketers are planning to use predictive analytics as their primary strategic marketing technology this year. The life sciences industry knows it needs to change and move in a similar direction. A 2015 survey from PwC revealed that 65% of senior sales, marketing, and strategy pharma executives expected to see increased digital interactions within their commercial approach in the near future. 

Healthcare companies have entered this new realm of analytics and insights, but so far have concentrated on clinical-centric initiatives. On the R&D side of healthcare, digital technologies are already being deployed to improve the development and adherence of treatments. The commercial and brand side of life sciences companies now has that same exciting opportunity to adopt new technologies to rapidly evolve and accelerate go-to-market—the likes of which we haven’t seen since the advent of CRM in the early 1990s.

Commercial teams, for example, can now get real-time alerts on anything from a formulary status change to a drop in prescribing patterns for their target customers. As life sciences brand teams begin to adopt these innovative technology solutions, they will see noteworthy improvements in customer and market engagement as well as improved collaboration between sales and marketing for optimized strategy planning and execution.

Medical affairs teams also benefit from this digital transformation, where data and insights-driven medical education programs improve product launch in an atmosphere that values scientific education over sales pitches.

Are you ready?

New digital technologies give everyone access to the art of data science. They transform advanced analytics into everyday insights so that commercial teams can stay one step ahead of customers and operate seamlessly with internal teams for improved brand success.

Now is the time for biopharma and medical device/diagnostic companies to take the next crucial step to adopting innovative technology platforms; platforms that manage and integrate multiple and diverse data sources, in varied and disparate formats, and that produce predictive analytics, powered by domain expertise, to produce relevant, real-time, and actionable insights.  

Welcome to the new inflection point in life sciences—the age of big data has now become the age of predictive insights. 

 

Lance Scott is President and CEO of Zephyr Health

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