"The kind of visualization that most people are moving toward is having dashboards of information where you can zoom in or zoom out--easily digestible to the business user," says Rao. "It's more hindsight analysis, basically backward looking. Most organizations are getting that. But now that we understand what happened or did not happen based on actions we took, we want to look into the future. That requires visualization that is much more dynamic."
Investing More in Gathering Data than Analyzing It
Companies are investing significant amounts in gathering data, Rao and Halter say, but perhaps not enough to integrate, merge and analyze it: 32 percent of organizations have invested more than $1 million in gathering, storing and retrieving internal data, but only 26 percent have invested more than $1 million in analysis of internal data.
Rao and Halter say respondents from the financial services, insurance and healthcare industries appear to be investing the most in data integration, and one-third of top performers likewise are investing more than $1 million in integrating third-party data.
Organizations may be hoarding data without analyzing it because IT and the business are locked into old ways of working with data.
"The traditional model of how business and IT work together traditionally no longer works in this field," says Oliver Halter, principal at PwC. "Business and IT always have had difficulties talking to each other. Traditionally, business creates requirements and IT executes. In the world of exploring data, that doesn't work so well anymore. The knee-jerk reaction of IT is, 'We're going to collect data and manage it, and you guys figure out what to do with that.'"
But the sophisticated analysis required to glean meaning from big data is often beyond business users.
"Those things are complicated and your typical business user doesn't know about it," Halter says. "I think what we're looking for is a new organizational approach, which means new talent and new ways of exploring that data."
They're Facing a Talent Gap
And that leads to the third big data barrier: the talent gap. As Rao and Halter note, it's no secret that companies often lack talent in the skills necessary to interpret big data. Only 44 percent of PwC's survey respondents said they have a sufficient pipeline of talent to undertake deep analysis of data, though top performers were more likely to feel they have a sufficient talent pipeline.
But Rao and Halter say that companies often overlook their existing talent: individuals in marketing analysis, actuarial groups and pricing/product development. These individuals can serve as a great starting point for talent to translate data into insight.
"Organizations that have been successful early have created new organizational models," Halter says. "They've created centers of excellence where business and IT come together. I have worked with clients where we literally created entirely new structures on the side of the IT organization. The teams have to be much more nimble, much more agile."
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