Analytic Insights Remain Trapped in Complexity and Bottlenecks, Teradata Survey Says

By Ken Briodagh October 26, 2018

Business and IT decision-makers are increasingly frustrated by the complexity, bottlenecks and uncertainty of today’s enterprise analytics, according to a recent survey of senior leaders at enterprise-sized organizations from around the world. The results were announced at the recent Teradata (News - Alert) Analytics Universe conference in Las Vegas.

The survey, conducted by independent technology market research firm Vanson Bourne on behalf of Teradata, a data intelligence company, found significant roadblocks for enterprises looking to use intelligence across the organization. Many senior leaders agree that, while they are buying analytics, those investments aren’t necessarily resulting in the answers they are seeking. They cited three foundational challenges to making analytics more pervasive in their organization:

  1. Analytics technology is too complex: Just under three quarters (74 percent) of senior leaders said their organization’s analytics technology is complex, with 42 percent of those saying analytics is not easy for their employees to use and understand.
  2. Users don’t have access to all the data they need: 79 percent of respondents said they need access to more company data to do their job effectively.
  3. “Unicorn” data scientists are a bottleneck: Only 25 percent said that, within their global enterprise, business decision-makers have the skills to access and use intelligence from analytics without the need for data scientists.

“The largest and most well-known companies in the world have collectively invested billions of dollars in analytics, but all that time and money spent has been met with mediocre results,” said Martyn Etherington, CMO, Teradata. “Companies want pervasive data intelligence, encompassing all the data, all the time, to find answers to their toughest challenges. They are not achieving this today, thus the frustration with analytics is palpable.”

Overly Complex Analytics Technology
The explosion of technologies for collecting, storing and analyzing data in recent years has added a significant level of complexity. The primary reason, according to the survey results, is that generally technology vendors don’t spend enough time making their products easy for all employees to use and understand; this problem is further exasperated by the recent surge and adoption of open source tools.

Limited Access to Data
The survey further found that users need access to more data to do their jobs effectively. Decision-makers and users understand that more data often leads to better decisions, but too often, a lack of access to all the necessary data is a significant limiting factor for analytics success. According to the survey, decision-makers are missing nearly a third of the information they need to make informed decisions, on average.

Not Enough Data Scientists
Finally, “unicorn” data scientists remain a bottleneck, preventing pervasive intelligence across the organization. Respondents see this as an issue and connect the problem to the challenge of using complex technologies. To combat it, the vast majority say that they are investing, or plan to invest, in easier-to-use technology, as well as in training to enhance the skills of users.

The global survey was conducted in August and September 2018 among 260 senior business and IT decision makers in the Americas, Europe and Asia Pacific. Respondents’ organizations had 1,000 employees or more, were from any public or private sector, and had global annual revenues of $250 million or more (with 69 percent of respondents from companies with at least $1B in global annual revenue). Interviews were conducted online or via telephone using a rigorous multi-level screening process to ensure that only suitable candidates were given the opportunity to participate.


Ken Briodagh is a writer and editor with more than a decade of experience under his belt. He is in love with technology and if he had his druthers would beta test everything from shoe phones to flying cars.

Edited by Ken Briodagh


Original Page