From recommending additional purchases based on the items that customers place in online shopping carts to pinpointing hospital patients who have a greater risk of readmission, the use of predictive analytics tools and techniques is enabling organizations to tap their collections of data to predict future business outcomes — if the process is managed properly.
Using predictive analytics tools lets organizations look ahead in an effort to optimize business strategies. But there has to be a purpose to the analytics efforts, and a solid plan behind them.
Predictive analytics has become an increasingly hot topic in analytics circles as more people realize that predictive modeling of customer behavior and business scenarios is “the big way to get big value out of data,” said Mike Gualtieri, an analyst at Forrester Research Inc. As a result, predictive analytics deployments are gaining momentum, according to Gualtieri, who said that he has seen an increase in adoption levels from about 20% in 2012 to “the mid- to high-30% range” now.
That’s still relatively low — which creates even bigger potential business benefits for organizations that have invested in predictive analytics software. If a company’s competitors aren’t doing predictive analytics, it has “a great opportunity to get ahead,” Gualtieri said.
Predictive analytics projects can also provide those benefits across various industries, said Eric King, president and founder of The Modeling Agency LLC, an analytics consulting and training services firm based in Pittsburgh. “Everyone is overwhelmed with data and starving for information,” King noted.
But that doesn’t mean it’s just a matter of rolling out the technology and letting analytics teams play around with data. When predictive analytics is done well, the business benefits can be substantial — but there are “some mainly strategic pitfalls” to watch out for, King said. “Many companies are doing analytics to do analytics, and they aren’t pursuing analytics that are measurable, purposeful, accountable and understandable by leadership.”
Data scientists don’t know it all
Plan ahead on predictive analytics
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