Last year was a period of heavy investment in big data technologies by organizations. According to a 2014 survey from Gartner, 73% of respondents claimed to have invested in big data. What’s more, the number of organizations stating that they had no plans for big data fell from 31% in 2013 to 24% in 2014.
Now that companies have sophisticated technologies in place for gathering data, their focus is on finding ways in which they can mine data to gain an understanding of its meaning. After all, it’s not enough to simply gather data; rather, organizations must learn how to convert that data into relevant insights that can be applied across their entire organization.
Although gathering this intelligence from big data is a priority for businesses in 2015, it’s turning out to be a real challenge. According to PwC’s Digital IQ Survey, 62% of respondents believe big data can give them a competitive advantage; however, 58% also agreed that moving from data to insight is a major hurdle.
So, why is it so difficult for organizations to effectively gather data insight? Perhaps they’re struggling to overcome the challenges that come with big data, such as lack of company buy-in and sparse IT talent. Below are four common hurdles companies face when trying to extract valuable insight from large sets of data, and how to solve them:
1. Focus on Quantity over Quality
Just because you can gather certain data points, doesn’t necessarily mean you should, as some information simply isn’t important. Organizations often make the mistake of investing in ways to gather more data, rather than ways to integrate and analyze it. Because of this, businesses end up with large piles of data for which they have no way to derive knowledge. Before you go about collecting more data, make sure you first have a way to properly analyze it—which brings us to our next point.
2. Large Data Analysis Talent Gap
Extracting insight from large, complex data sets takes a certain amount of experience and skills that typical IT departments don’t encompass. According to the PwC report, only 44% of survey respondents said they have sufficient talent to undertake the deep analysis of data. To overcome this hurdle, companies must nurture existing talent or seek outside help to take over data analytics.
3. No Well-Defined Goals in Place
When you don’t have a well-defined goal, big data can become overwhelming. Before diving into a pile of data, ask yourself what you want to get out of your data investment. Whether it’s growing a specific market segment or reducing business inefficiencies, having a specific goal in place will narrow your focus to more effectively solve the problem.
4. Lack of C-Suite Buy-In
In order for big data—or any investment for that matter—to make a real impact across the entire organization, upper management needs to be involved. Yet many executives don’t effectively communicate the benefits of big data, keeping departments in the dark about its potential. Before investments are made and goals are set, make sure to get buy-in from the C-suite.
This year, the focus for businesses is turning complex data sets into meaningful insights that can help improve decision making and business strategies. To successfully accomplish this difficult task, however, business will have to overcome the hurdles of these common big data insight challenges. Make this year the one data insight works for you.