The report, “Predictive Analytics: Improving Performance by Making the Future More Visible,” involved questions surrounding implementations and plans with predictive analytics from approximately 200 executives and IT managers. Industry distribution for participants consisted of services (53 percent), manufacturing (22 percent), finance, insurance and real estate (16 percent), and government, education and nonprofits (9 percent). More than two-thirds are actively using predictive analytics, some with developing use across the enterprise and other enterprises with predictive analytics in the planning stages.
What’s missing at many enterprises and how others have matured so quickly boils down to one main factor: training. Only 17 percent of those surveyed stated that users have been trained to produce their own analyses, and 58 percent indicated they don’t have the math background to produce analyses. Less than half of organizations provided any training on predictive analytics concepts and techniques, applications to business problems, and use of products, according to the report.
“Those organizations that did a better job with training in predictive analytic concepts had the highest levels of satisfaction,” said David Menninger, Ventana VP and research director.
Another sign of immaturity with predictive analytics is the lack of up-to-date management with models. Fifty-three percent reported they update their predictive analytics models, and just 29 percent update their models automatically. According to the survey, the 24 percent of organizations that are most satisfied with the returns and reports from their predictive analytics also update their models daily or often.
“I’m amazed that organizations do not manage their predictive analytic models more proactively,” Menninger said. “The processes to support predictive analytics need to be much more fully developed for organizations to get maximum benefit.”