According to Forrester Research’s customer experience index, even improving patient experience by one or two points can have an enormous impact on patient satisfaction and a health care organization’s bottom line. It’s the proverbial win-win.

We've all been there. To that land of customer enchantment and delight where a recording tells us our calls are important. In fact, we’re so important that we're typically put on hold and pushed to a self-serve website to solve our own problems. If we want to talk to a human being, there’s little satisfaction in knowing our calls will be handled in the order they were received.

Today’s demand for big data talent reflects a recurring theme that happens whenever a new valuable technology becomes available. Companies face the conundrum of figuring out how to quickly capitalize on the latest technology to gain business advantage during a time when a limited supply of skilled talent exists in the marketplace.

Internally, the tug of war begins because marketing, operations and customer service all push to leverage these technologies as quickly as possible, while IT tries to figure out how to get it done. The business ends up with two options: develop the expertise internally or partner with an outside resource.

Do you ever feel like you’re drinking marketing data from a fire hose when what you really need to improve customer experience is a narrow straw?

Consumerism has significant implications for understanding data analytics, including the need to better understand the healthcare customer before they ever become a patient.

Buy (don’t build) healthcare data insights to improve data investment ROI

Healthcare organizations have been investing heavily in big data analytics, software, hardware, staff, and services to get insights into quality and cost. These insights will be critical as healthcare facilities take on more and more risk in a value-based care model. About 40 percent of healthcare providers are expanding IT budgets, a recent IDC Health Insights report revealed. The report noted that analytics is the top reason for the increase.

Healthcare organizations (HCOs) have been, and continue to be, invested heavily in IT to improve outcomes and lower costs. While much of this investment continues to support the implementation and optimization of mandated electronic medical record (EMR) systems, the post-EMR implementation world is on the horizon, and all of those EMR systems will be generating tremendous amounts of data. According to PwC’s 2016 Annual Global CEO Survey, 95% of healthcare CEOs are already looking beyond EMR and say they are exploring better ways to harness and use big data.

Data is exceptionally valuable for companies making decisions concerning reducing costs and increasing revenues. Though it’s seemingly simple to run a data report, getting to the right actionable insight can offer both opportunities and missteps.

I’ve yet to see the statistic that a new app is born every five minutes, but I’m sure it exists somewhere. At last count, there were 265,000 health-related apps on the iTunes and Android stores. Certainly the FitBit and its heart monitor predecessors paved the way for new health apps ranging from blood sugar monitors for diabetics, to weight loss, to support communities for any number of health afflictions.

2016 Big Data Analytics Leadership Equation

It’s the old 80/20 rule, or, in health care’s case, the 85/15 rule. Roughly 15 percent of patients drive 85 percent or more of costs for health care and insurance providers. Managing these patients effectively can significantly improve bottom-line results — and there is plenty of room for improvement.

Analytics have become “big” and “intelligent” over the years, but companies still struggle to squeeze the full value of their data analytics to meaningfully direct their go-forward strategies. While we see this trend continuing into 2016, there are some bright spots as technological advances enable companies to wade their way through the murky data lakes toward clearer waters.

Recently, we here at Capto had the opportunity to “eat our own dog food” at one of our clients, a Fortune 100 company. In the middle of a Capto-designed Business Intelligence (BI) Analytics Acceleration Program—part of our Synaptic methodology—our client’s big-data analytics leader accepted a position in another area. The VP in charge of BI asked us to step in and fill the leadership void in the analytics team.