The explosion in popularity of new business intelligence platforms and data warehouse technologies throughout the 1990s was well documented. But while companies in a broad range of industries including financial services, high-tech and retail were quick to embrace the newfound ability to analyze past business performance, most universities, hospitals and pharmaceutical companies remained quietly on the sidelines.
Two decades later, another major wave of technological innovation is sweeping over the IT landscape in the form of modern big data analytics solutions. Only this time, the script has been flipped.
The same schools, hospitals and pharmaceutical companies that were last on the scene during the business intelligence boom are now among the earliest and most aggressive adopters of modern data analytics technologies. Right from the start, organizations in these three critical sectors were -- and still remain -- eager to embrace the big data revolution, quickly understanding the many ways they stood to benefit by connecting to and analyzing all forms of data, including new data types such as text, video and social media.
What changed? What turned these habitual late-movers into the most enthusiastic of early adopters? As with any significant shift in behavior, there are a number of contributing factors, but let’s take a look at three of the most critical.
1. The Customer Has Changed
Nothing changes the behavior of an organization more quickly than a change in the behavior of its customers. In the case of universities and hospitals, the behavioral patterns of the students and patients they serve have changed dramatically.
Students today -- at all levels -- are conscientious adopters of technology and fervent users of social media. They go through their entire academic careers without ever hand-writing a report or setting foot in a physical library. Students don’t want digital connectivity in the classroom -- they flat out expect it. They are the epitome of the data-driven consumer. To understand them, schools realized they must understand both the data they create and the data they consume.
The same can be said of hospital patients. Hospitals were among the first to come head-on with an internet savvy clientele -- the WebMD effect, so to speak. Patients that used to come to doctors for answers were suddenly coming to them to confirm what their web research had already convinced them was true. To better understand and communicate with patients, hospitals had no choice but to better understand the digital world driving their behaviors.
As for pharmaceutical companies, just try getting a modern trial participant to provide feedback by way of a written form or a phone interview. That’s a study going nowhere fast. The ability to capture and analyze digital information has become a necessity for companies whose livelihoods depend on receiving feedback.
2. The Digitization of Data Made it Worthwhile
Universities, hospitals and pharmaceutical companies weren't late to the business intelligence game in the ‘90s on account of laziness. They were late-movers because there was no perceived business value to be gained. All of their data was maintained through paperwork. Their digital footprints were miniscule. The organizations simply didn’t stand to benefit enough to make immediate investment in these new business intelligence technologies worth their while -- or their money. And even if they thought it was worth their while, there was the issue of security. Aside from classified government documents, there may be no more sensitive forms of information in the world than student data, patient data and trial data. The concerns around security were in many cases too daunting to move past.
Everything has changed. Not only has digital security evolved to the point where organizations that follow best practices and use modern security solutions can feel safe, but the abundance of digital data has created business opportunities that simply cannot be ignored. Schools can learn what their students think simply by reading Twitter, patient records can be transferred across the world in seconds, and drug companies can get feedback from trial participants in real time leveraging internet-connected devices.
What the availability of all this information translates into for these organizations is opportunity. It’s the opportunity to learn which classes appeal to students before building out the semester schedule. It’s the opportunity to understand how a patient might react to a treatment before ever prescribing it. It’s the opportunity to move clinical trials ahead faster and more efficiently than ever before. Against this backdrop, it’s easy to see why these organizations have been so eager to leverage big data analytics.
3. The Data Is More Diverse than Ever
One of the biggest misconceptions about big data is the notion that data volume is the primary driver of complexity. It certainly can be, but more often than not, the diversity of data is a far bigger challenge. The more diverse the data sets an organization deals with, the more critical the need for a modern big data solution becomes. Perhaps more so than any other group of organizations, universities, hospitals and pharmaceutical companies deal with an incredibly diverse and complex universe of data.
Universities deal with various forms of student data, enrollment data, HR data and tuition data. Hospitals deal with demographic data, patient histories, treatment data and facility data. Drug companies have to process scientific data, study data, participant data and trial data. And that’s just scratching the surface for each.
Now factor in different data types (structured, unstructured, social, text, machine, etc.), as well as different data locations (on premises, cloud, remote office, branch campus, etc.), and what’s left is a level of complexity that demands attention. To their credit, educational institutions, hospitals and pharmaceutical companies have been proactive about leveraging the new wave of big data and analytics solutions to manage this growing data complexity.
Needs Trump Hype
If there’s a key learning to be had from this dramatic shift, it’s that hype and industry excitement itself is not enough to justify jumping onboard any particular industry bandwagon. For schools, hospitals and drug companies, the business justification just wasn’t there back during initial explosion of BI technology. In the era of big data, however, the justifications have been clear, and in turn, so too has their commitment to embracing the opportunity. Other businesses, regardless of industry or vertical, would be wise to make similar choices.