Inmar Inc. | January 26, 2016

Thinking about big data, there have been a lot of calls to dive in, and it almost sounds like a business survival mandate if you believe some pundits. In many cases, that is certainly true — the masses of data accumulating between wearables, mobile devices, transactions, the Internet of things, etc., do show great competitive advantage to those who take it on.

For many, though, questions remain. What is big data, really, what can you do with it and how do we tackle it to greatest advantage? The challenge in healthcare is poignantly illustrated in a quote from Elaine Grant, writing online for the Harvard School of Public Health:

"Petabytes of raw information could provide clues for everything from preventing TB to shrinking health care costs—if we can figure out how to use them."

It's exciting to consider the competitive possibilities of capitalizing on massive amounts of data from new sources. However, when the time comes to take it on, it's easy to see that it is, indeed massive. So how do you approach big data and integrate new data sources into the mix?

It comes back to that old modicum about how to eat an elephant: One bite at a time.

More and more, we hear about the possibilities of big data, and yet there seem to be no clear answers about how to tackle it. That's ok — every entity has its own needs and uses for data, as well as its own unique set of sources and challenges with new efforts.

In the hustle for patient and customer information, market patterns, behavioral patterns, medication adherence and buying decisions can all improve health outcomes. We all see the great life-changing potential in this information.

The real challenge is developing the analytics to drive the intended results. With that in mind, we can't ignore the one big underlying theme of business: How to, at a minimum, be cost-effective in new data pursuits and at the maximum, generate return on the investment it will surely demand.

A recent study by data analytics firm Knowledgent Group shows that even among companies that are enthusiastically pursuing big data initiatives with obvious benefits, more than 60 percent say they have significant challenges to organizational adoption, including resources, data architecture and attaining the quality of data program they need. ("2015 Big Data Survey: Current Implementation Challenges," Knowledgent Group)

With all that said, jumping into a big-data initiative can look daunting, even overwhelming. With the many new sources of data comes the need for new ways to gather, integrate and utilize them. Already, in the brief history of big data, we're seeing the evolution from predictive analytics (what will happen?) to prescriptive analytics (what will we do when xyz happens?). These developments will require new talent, technology and capacity — be sure you can sustain managing the cost of adding these capabilities.

That brings us back to the idea of how to eat that elephant. There are some time-tested common-sense approaches that make sense and make those first bites more attainable. Keep these things in mind before you dive in:

Know what you can do

Are you set up to handle the volumes and types of data you want to utilize? If it takes too long to process large volumes of data, the information loses value — even hours or days may be too long to maintain relevancy in some cases. Assess your data processing capabilities and resources and know what's realistic before you take it on.

Start with realistic goals

Set up a vision and a plan that builds business strategies around clear objectives you know you can accomplish and fit your budget, and divide it into achievable initiatives. First, determine whether big data is even a realistic pursuit to begin with — clearly define what you need and what it will take to get you there. If it's a need for competitive survival, but a need without a budget, determine when it can be a reality and set about the tasks that make it possible to proceed.

Look within

Many companies have been gathering data for years but haven't used their existing data streams to their full potential. If you're considering a new, expensive big-data initiative, determine first how much potential data you may already have. Existing data streams may not be as enticing or sound as sexy as new data, but quite often, their quality and direct relevance to your business can bear more achievable value than a hasty move into an entirely new, expensive data exploration.

Collaborate and partner with experts to determine the validity of the data sets you have and what makes them unique to the ecosystem we call healthcare.

Big data calls us all. As we answer the dinner bell, even coming to the table planning on one bite at a time, we'll all need to loosen our belts a little before we start eating that elephant.

What are your challenges with big data? Share them with me and other readers by leaving a comment below.