December 13 2017 | 0 Comments | 112 reads Average Rating: 3

Pushing the Data Analytics Envelope: From Understanding to Predicting to Taking Action

by John Pagliuca and Mark Feeney in Life Sciences

When Stranger Things fans finished watching all of the available episodes of the much-talked about series, they opened up their Netflix account and were told to watch Twin Peaks or Freaks and Geeks. And, most likely, they happily obliged.

How does the online streaming media service know how to direct its members? Netflix knows what summaries users are reading, how long they spend surfing titles, what TV shows and movies they ultimately watch and for how long – and uses this information to better understand its audience. This approach enables Netflix to know what users want before the actual users knew what they want. In fact, 75 percent of users select programming based on Netflix’s recommendations. Perhaps most importantly, the more sophisticated insights have made it possible for Netflix to acquire and develop superior content and create an enhanced user experience. As a result, Netflix has grown its membership to 110 million and its sales to more than $11 billion in 2017.

Netflix is not the only organization leveraging more sophisticated data analytics. Indeed, professional baseball teams use advanced analytics to predict where balls will be hit, which players will be better in certain situations and exactly how pitchers should pitch. And, online retailers, such as Amazon, leverage data analysis to anticipate purchases that will be made for specific products and to determine how to stock their warehouses.

What all of these organizations have in common is that they are moving beyond the common use of analytics. They are not only using descriptive analytics to gain the hindsight to understand what happened and diagnostic analytics to gain the insight to understand why something happened but they are also leveraging predictive analytics to gain the foresight to understand what will happen and prescriptive analytics to gain the where-with-all to accurately anticipate what needs to happen to produce a desired outcome.

Healthcare organizations can do the same by bringing together various data types – claims, eligibility, lab, fitness, socio-economic and more – to holistically understand patients and then applying prescriptive analytics to enable them to take the actions that will produce the most desirable outcomes.

Case in point: A healthcare organization in Florida identified that there were pockets of patients who were not complying with their prescribed medication regimens. By analyzing various sets of data, the healthcare organization determined that these patients were not picking up their medications from the pharmacy because the driving route required them to take several left-hand turns – something that older drivers often avoid. Taking the analysis up to the prescriptive level, though, enabled the organization to develop a variety of strategies designed to overcome this driving hurdle. More specifically, the organization determined that it could produce greater medication adherence by partnering with other businesses to offer a transportation service to the affected population of patients; providing a mail-order prescription service; or using an online mapping service that could develop driving routes that don’t require left turns.

Here, we’ve provided a brief illustration of the benefits of predictive and prescriptive analytics. For a more in-depth discussion about how healthcare organizations can move up the analytics continuum and produce optimal outcomes, check out our Webinar entitled “Gaining a Competitive Advantage through Predictive and Prescriptive Analytics.”

Download Slideshare | Watch On-demand Webinar | Check Upcoming Webinars

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Author
John Pagliuca
Vice President, Life Sciences

John is responsible for leading the commercialization efforts of SCIO’s SaaS solution suite and advanced analytics within the US Life Science vertical. He has more than 15 years of sales, marketing and technology experience, with particular expertise in quantitative analytics and SaaS solutions for Life Sciences.

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Author
Mark Feeney
Life Sciences Consultant

Mark holds a Master’s Degree in Analytical Geography from Binghamton University and has spent 20 years in the Life Science industry.

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