Big data might be here, but businesses are not always thinking big enough, according a recent report by Information Week.
Armed with survey results gathered in September 2012, Mike Healey of InformationWeek crunched the numbers and came up with an assessment: business leaders are not yet utilizing their own numbers well enough.
"There’s no question there’s more data available than ever, especially information from the Web and the new wave of smart mobile devices," he wrote. "Our beef, though, is that most businesses aren’t good at using the data they have now."
Let's look at some of the key findings about the data that businesses have and at what a company's decision-makers can do to leverage that information for greater success.
Thinking 'Big Data': Going Deep in the Database Milieu
A key lesson businesses need to learn from the concept of big data — that is, the implementation of cross-system analysis in search of new trends and uses — is that the data they're accumulating every day can't be best put to work for them if it's relegated to the finance department.
Unfortunately, data and analysis too often stay in their silos. Healey's survey finds that just one-third of the respondents analyze their data in a cross-departmental fashion.
Furthermore, the report tells us, quality-checks on data require today's analysts to think in other-than-linear terms. Look at it this way, just because a set of business-to-business geolocation results seems to point to Boston as the source of recent incoming commerce, the nature of the Internet means that that the business could actually be originating somewhere else entirely. Who's checking that? Cross-functional teams should apply veracity "stress tests" to the data used, Healey says.
The takeaway: big data may be an attractive idea, but what we'll refer to as deep data — meaning, data into which departments have first dug down and vetted for false assumptions — that's what will be key to keeping accuracy in the big-data equation.
Thinking 'Big Data' Again: Going Lateral in the Database Milieu
Stick with the same old centralized model of data analysis, and you'll miss the benefits that big data can bring. That's at the root of all this big-data talk. But one of the underpinnings of big data is that it’s not exactly about quantity, it's about the "geography" that you cover within your extant data. Focusing only on how many phone calls or e-mails it takes to satisfy a customer is one thing, but analyzing how phone, e-mail, customer-relationship management, and web analytics intertwine, then looping that information into a whole picture — that's another. Maybe you discover that one e-mail does the trick of two calls, or that moving your FAQ to a higher-level page cuts down on both. Therein lay the big-data picture.
And what about all the information about your products that is available online? As your customers tweet, and post to Facebook, and use forums — is that dataset impacting customer processes with your internal staff? The point is that while bad information can lead to unrealistic expectations, good information can drive resolutions without a phone call to your CRM.
If you're not analyzing these things, you're not thinking in terms of big data, and you're probably missing out on an opportunity to make your systems work with greater elegance.
Tools and Skills: People and Tech
One of the obstacles to using data better, as Healey identifies it, is that businesses seem to love spending money on stuff. But when it comes to staff? Not so much. The phenomenon may be twofold.
First, Healey suggests that a mere 33% of respondents saying that training and development are on their agenda is simply too low to absorb the workload and learning curve that should come with putting big data to use. Second, a recent McKinsey & Co. study projects that big-data staffing will face a 140,000–190,000 employee shortfall by 2018.
The answer, however, may not be to hire up the next wave of fresh faces who say that they can cover that gap. "You already have talent within your organization," Healey says. "You, and possibly they, just don’t know it. Consider that 39% of [survey] respondent organizations have department-level analysts as the primary users of their information. This can be a huge opportunity. Break these people out of their department silos and start moving them toward a more holistic view of the data."
Finally, it's about getting something done with what you analyze. Maybe not. Only 9% of the respondents in Healey's survey said they were "extremely effective" in utilizing the data that they gathered.
The trick, as Healey found it: "this group overwhelmingly considered data core to organizational strategy and had higher levels of integration of almost every data type we asked about. And even though budget was still the primary barrier to successful use of big data for this group, they showed higher levels of planned investment in tools and staff."
Find that balance, and big-data may be more of an open door than a tightly barred window.