C-Level Executives Seeing Big Results From Big Data

An overwhelming majority of executives from companies that have brought big data projects to production are pleased with the results, according to new research by Accenture Digital. However, they also cite security as the major challenge they face.

“One thing we’ve seen in the past year is that people are not really talking about what is big data anymore,” says Vince Dell’Anno, managing director and global information management lead, Accenture Analytics, part of Accenture Digital. “They’ve done their experimentation. They’ve got some understanding of it. What they’re talking about now is what happens when they need to scale to support, 1,000 or 2,000 or 5,000 users. That’s where challenges like security and integration come into play.”

Between February and early April 2014, Accenture screened more than 4,300 CIOs, COOs, CMOs, CFOs, chief data officers (CDOs), chief analytics officers (CAOs) and other senior technology, data and analytics leaders from companies in 19 countries and across seven industries. Of that number, 36 percent said their company had not completed and weren’t currently pursuing a big data installation and four percent said their organizations were in the process of implementing their first big data project. Of the remaining 2,600 respondents that had applied big data to their businesses, Accenture focused on a sample of 1,007 executives.

Accenture found that 92 percent of the executives were satisfied with the results from their big data projects, and 89 percent rated big data as “very important” or “extremely important” to their businesses’ digital transformation. Eighty-two percent also said big data provides a significant source of value to their companies.

“The survey results we got back up what we see on the ground,” Dell’Anno says. “Big data is being used across all the industries that we’re in.”

“Businesses are at a transition point where instead of just talking about the potential results that can be achieved from big data, they are realizing actual benefits including increasing revenues, a growing base of loyal customers and more efficient operations,” adds Narendra Mulani, senior managing director of Accenture Analytics. “They’re recognizing that big data is one of the cornerstones of digital transformation.”

Dell’Anno says that the financial services and communications industries have been among the most aggressive adopters of big data, but he also notes the insurance industry has seen big uptake in the past year and even utilities are beginning to take advantage of new capabilities provided by the Internet of Things.

“Today, even the most basic items like water pipes can generate and provide data,” adds Mulani. “While the Internet of Things is giving rise to massive sources and quantities of data, new big data technologies are emerging that help uncover crucial business insights from the data. Companies not implementing big data solutions are missing an opportunity to turn their data into an asset that drives business and a competitive advantage.”

Finding New Sources of Revenue Is Major Big Data Focus

Finding new sources of revenue is the area that businesses focusing on the most when it comes to big data projects and it’s also where businesses are seeing the most extensive tangible business outcomes. Accenture found that 94 percent of executives said their companies use big data moderately or extensively to identify new sources of revenue. Additionally, 90 percent of companies use big data moderately or extensively to retain and acquire customers and 89 percent to develop new products and services.

Fifty-six percent of executives reported that their companies are experiencing extensive tangible business outcomes from big data in finding new sources of revenue. Additionally, 50 percent point to new product and service development, 51 percent to enhancing customer experience and 47 percent to winning and keeping customers.

Peering into the future, 63 percent of executives said they believe that in the next five years big data will have the biggest effect on their customer relationships. Fifty-eight percent mentioned product development and 56 percent said operations.

With companies putting big data projects into production, 51 percent of executives cite security as the greatest challenge facing their organizations when implementing big data. Executives also cited budget (47 percent), lack of talent to implement big data (41 percent) and to run big data and analytics on an ongoing basis (37 percent) and integration with existing systems (35 percent).

“We’ve seen organizations overcome big data implementation challenges by remaining flexible and recognizing that no single solution fits every situation,” Dell’Anno says. “If a particular approach doesn’t work, organizations try another one, learning as they grow. They also start small and stay realistic in their expectations. Rather than attempting to do everything at once, they focus resources around providing value in one are, and then let the results cascade from there.”

Accenture also found that large companies (with more than $10 billion in annual revenue) are taking a different approach to big data than their small and mid-sized brethren (with less than $500 million in annual revenue).

First, executives from large companies are more likely to see big data as extremely important. The study found that 67 percent of executives from large companies see big data as extremely important compared with 43 percent of respondents from small companies.

Also, Accenture found that executives from large companies have a broader perception of what big data includes as compared with respondents from smaller companies. In particular, large companies are more likely to use more data sources in their big data efforts — social network data (54 percent vs. 29 percent); visualization data (50 percent vs. 29 percent) and unstructured data (49 percent vs. 36 percent).

The C-suite of large companies are also more likely to support big data projects. Accenture found that 62 percent of executives from large companies report extensive C-suite understanding and support of big data initiatives compared with 42 percent of respondents from small companies.

That said, Dell’Anno notes that smaller companies actually have a number of advantages when it comes to implementing big data intiatives.

“Bigger companies have larger budgets, but are stymied by organizational constraints — how they’re organized, processes they’ve developed over time,” he says. “Those things end up being gates rather than money or technology.”

Smaller organizations, on the other hand, tend to be more nimble and have the option of turning to services like Amazon Web Services to stand up data discovery and analytics in a rapid and cost effective way.

“It’s really an even playing field,” Dell’Anno says. “The competition is going to be for talent. It’s not just being able to hire people, but are you working on a problem that’s really going to be meaningful and engaging for them.”

Recommendations for Big Data Success

To get the most out of your big data projects and to overcome the challenges that big data brings, Accenture offers these key recommendations:

• Explore the entire big data ecosystem and be nimble. Data sources and big data technologies are in a constant state of flux. Companies need to learn to stay alert and be nimble to seize opportunities arising from evolving technologies.
• Start small then grow. Rather than attempting to do everything at once, companies should focus resources around proving value from big data in one business area first via a pilot program or proof of concept.
• Focus on building skills. With talent still one of the biggest big data challenges, organizations need to build the big data skills of existing employees through training and development. Fifty-four percent of executives said their companies have already developed internal technical training opportunities for their employees. Most organizations also tap outside expertise — only five percent of respondents said their company only relies on internal resources for big data implementations.

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