A new report from big data analytics and marketing applications company Teradata has revealed companies are making significant investment in big data analytics and are seeing a significant return.
The global report surveyed more than 300 senior data and IT decision makers in leading companies, and studies the impact of big data initiatives on organisational culture and practices, citing challenges and confirming the business value of big data investments.
According to the report, across all categories of investment, about 90% of organisations report medium to high levels of investment, and about a third call their investments “very significant.” Additionally, about two-thirds of respondents report that big data and analytics initiatives have had a significant, measurable impact on revenues.
“It’s exciting to see that companies using big data technologies are realising the impact that’s been promised for some time,” says Chris Twogood, vice president of Product and Services Marketing at Teradata.
“Companies aren’t just committed to investing in big data analytics; most companies are seeing a material impact as a result of that investment,” he says. “One out of five survey respondents (21%) agreed that big data analytics is the single most important path to competitive advantage, while 38% called it a top five issue.”
Twogood says that deploying big data analytics through an analytical ecosystem including a data warehouse, along with open source technology, provides the integration across multiple disparate systems that further enhance competitive advantage.
Among the six industries surveyed, executives saw different value potential in big data; retail respondents held it in highest regard, indicating that in retail, big data and analytics is the key to competitive advantage.
Twogood says the survey shows that big data is shaping the future and driving opportunities for innovation in three key areas: creating new business models (54%); discovering new product offers (52%); and monetising data to external companies (40%).
According to the report, the leading-edge organisations, ones that placed a higher level of importance on big data and analytics, indicated that C-suite sponsorship was critical.
More specifically, in organisations where big data is viewed as the single most important way to gain competitive advantage, over half are led by CEOs who personally focus on big data initiatives.
In organisations where big data is viewed as a top-five issue that gets significant time and attention from top leadership, the sponsor is typically one level below top leadership.
The survey also reveals that many obstacles remain, especially with regard to culture, strategy and operations.
Over half of the survey respondents noted that adopting a data-driven culture is the single biggest barrier, suggesting that the idea of a data-driven approach is not universally accepted today.
Rewarding the use of data and fostering experimentation and creativity with data were also highlighted in the report as significant cultural challenges.
“Despite the progress we see reported, as companies make the most of big data resources, there remains plenty of room for improvement,” says Matt Ariker, chief operating officer of Consumer Marketing at McKinsey.
“The cultural challenges can handicap every facet of a big data initiative,” he says.
“But the good news is that the reverse is true as well: improving how a company fosters a culture and mindset that rewards the use of data experimentation can help a data and analytics initiative gain momentum and impact.”
Companies that are gaining the most traction with their big data initiatives are looking well beyond transactional data – they’re exploring many data types.
he most-cited was location data (used to identify an electronic device's physical location), collected by over half of the respondents, followed by text data (unstructured data like email messages, slides, Word documents, and instant messages).
In addition to exploring these new data types, leading companies are selectively combining structured and multi-structured data sets in an analytic ecosystem, enabling the discovery of analytic insights that drive new innovations.