Big data projects can far surpass the hype by nurturing context and connections, according an analysis of numerous case studies by Nucleus Research.
The analysis report, “The Big Returns from Big Data,” involved input and anecdotes from 58 big data implementation case studies across a range of industries and verticals. Nucleus reported staggering ROI figures for enterprises that successfully fanned out big data tools and access across internal and external data sets. Maturity of big data implementations was key to returns, according to the report. Extensive additions of predictive analytics and connections of internal data sets to those massive, real-time sources such as social media, brought in, on average, 241 percent ROI for enterprises involved in the Nucleus review.
Examples of those returns included: a 942 percent ROI for a manufacturer that was able to scour large, disparate data sets from vendors for purchasing and cost information; 1,822 percent ROI from reduced labor costs by a resort that integrated shift scheduling processes with data from the National Weather Service; and an 863 percent ROI by a metropolitan police force that was able to combine various crime databases alongside predictive analytics and its department assets.
On the other side of those enterprises reviewed in case studies, 12 failed to fully pay back their implementation investment. From that group, Nucleus found that 7 stopped or became hung up at the automation phase with their large and unstructured data sets, while the other 5 “were only slightly more advanced and were using big data to support operational tasks,” says Nucleus Principal Analyst Hyoun Park.
“Companies that failed to achieve high levels of ROI typically had not taken advantage of the collaborative, contextual and predictive benefits of big data. Instead, they were simply automating big data processing for standard reports and workflows,” Park says. “None of these companies [that failed to see ROI] had spread the use of big data to an enterprise-wide level or done any significant work to align the collection of big data with specific revenue-producing activities.”
Over the next 6 to 12 months, Park says the two main challenges with big data projects will be mastering visualization of data sets for more widespread use and contextualization of data within enterprise parameters and governance. These forces combined will mark the next tier of ROI and success with the growing expectations from big data, says Park.
“Enterprises that successfully use big data will figure out how to turn millions of inputs into a few easily digestible figures that can be shared socially and made available either in the board room or on a laptop, smartphone, or tablet,” the analyst says.
This story first appeared on the website of
