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2016 Annual Influencers Outlook: The Data-driven Revolution is Upon Us

To read all the excellent articles, please access the full issue of Verix Influencers Outlook 2016 here.

Special thanks to Annie Reiss, VP Marketing at Verix, for the opportunity to contribute. And to her team for a beautifully crafted e-zine.

Ramon has been developing and launching big data databases, enterprise apps, development tools and master data management platforms for over 20 years.

Formerly VP product marketing at Veeva Systems, Ramon is currently the Chief Marketing Officer at Reltio, a provider of a modern data management Platform as a Service and data-driven applications.

Ramon is now using Reltio’s own data-driven applications in-house for more effective sales, marketing, and a myopic focus on customer experience and satisfaction.

So, naturally, we asked him to contribute his thoughts on the continuing effects of big data on pharma. What we received is an important account on what big data will be able to deliver, and what it won’t be able to replace. 

2015 saw a significant increase in the number of companies deploying Big Data Analytics tools, emboldened by their peers seeing success from the maturing offerings of established vendors in the life sciences industry. Given the opportunity there have also been no shortage of new vendors, all offering some flavor of the latest in NoSQL, Deep Learning and in-memory processing. The landscape continues to expand leading to evaluation paralysis, or Franken-research IT projects that are destined for an unhappy ending. In this evolving journey, you can hear business teams continuing to ask the grating, but very reasonable question- Are we there yet?

High quality profile data : oxygen and water

The industry has concluded that if data is the new lifeblood of life sciences, then reliable, high quality profile data is like oxygen and water, an essential foundation before any analytics and insights can be drawn. With the increasing popularity of the cloud, smaller companies, many pre-commercial, can now benefit from continuously clean data that not only contains accurate profile information, but deep affiliation, hierarchy and relationship details. 

Gaining this level of insight used to be purely an IT discipline called master data management (MDM) costing millions in hardware, on-premises software and consulting services. Today “modern” data management in the cloud can easily combine and clean master data across internal and external sources, correlate those profiles with transactions, big data or small, and maintain those relationships to provide a core repository from which predictive analytics can be obtained.

Next wave of data mania

2015 was the year of mega mergers, with industry giants in life sciences joining forces to gain access to promising drug pipelines. Only time will tell if each M&A will be classified as a success. Even though cost savings can be realized through consolidation of operations, reduced sales reps, and other staff- the industry continues to search for new ways to generate growth. Data holds the key to streamlining processes, optimizing collaboration, improving customer satisfaction and meeting compliance reporting goals, but it also unlocks the formula for competitive advantage. The rise of high paying job titles such as data scientists, and in the c-suite chief data officers (CDOs), are gaining in significance and popularity in other industries. Life sciences companies are already starting to face this same wave of data mania.

If anything the ‘big data-hype’ has just begun. It’s true that the term “big data” unjustly makes people think primarily of size (volume of the data), but it’s the variety, velocity and even veracity (quality) of the data that has life sciences companies taking notice. Rather than focusing on the size of the data, they are rightly focusing on the size of the problems that they can solve. 

Being “data-driven” is a business term that has also been hyped to the max over the last few years with many experts encouraging companies to use analytics and visualization to gain the insights they need to succeed. As previously discussed, data mania is reaching a fever pitch with the BI and Analytics market forecast by some to be $18B+, with the separate sized data management market at $65B+. That’s a lot of money being invested by business teams and IT, often in uncoordinated efforts. 

Unquestionably there are successes that can be tied to the investments, but the ROI of software has always been arbitrary. Without a closed loop to correlate back actions to the insights provided, it’s a continued guessing game at best.  

What it really means to be ‘data-driven’

While the hype and noise shows no signs of abating, buyers of technology are focusing on time to value and differentiating capabilities. Business users in particular who experience the ease of use of products such as LinkedIn and Facebook as consumers, are asking tough questions of their IT counterparts: “Are we there yet?” questions are now morphing into “Why can’t I get it and why does it take so long?”, and “Why can’t my application deliver recommended actions to me like LinkedIn, and why does it make me search for something it already should know?” This powerful voice of the user is putting pressure on IT, already faced with shrinking budgets and legacy systems to maintain, not to mention continuing issues with data quality and security. 

2016 will see a revolution in what it really means to be data-driven, and the ones that will thrive will be those that can have the platform and technologies that can deliver and share information on demand, anytime, anywhere across the enterprise.

Don’t eulogize person-to-person interaction just yet…

Increased M&A always results in many losing their jobs due to consolidation of roles, and the reduced need for physical interaction and presence when dealing with customers, whether they be HCPs or larger entities such as IDNs. An interesting twist is that the reduced contact or coverage means potentially less information provided back to the home office where predictive insights are being generated. 

Licensed third party data, social site chatter and even sensor related data doesn’t yet completely replace the unique insights that can be gathered from person-to-person interaction. The name, address, phone number and license number of a physician is fundamental, but which HCP is a key influencer within their peer network, on which committee, and how that group makes decisions, are “soft” data facts that have the makings of true competitive advantage. Take the enriched insights which consumers rely on in the form of Yelp business reviews, or endorsements through LinkedIn. These types of social collaboration and curation form the basis for the next generation of insights for the enterprise. 

If pharma can harness the workforce they have to gather information at source through data-driven applications then they can truly extend and see the added value of their teams out in the field, rather than just as an operating cost line item.”