Analytics is the accepted way to determine what business decisions are right for your organization, but now it is up to business teams and analytics teams to determine what types of solutions will best help them make these decisions, according to the second keynote at the Predictive Analytics conference, given by Thomas Davenport, a professor at Babson College and research director at the International Institute for Analytics.

The keynote was offered as a joint session to those attending the three concurrent conferences under the Data Driven Business Week umbrella, which also included eMetrics and Text Analytics World. Davenport said he enjoyed speaking to all three groups because he, as an analytics professional, looks at their adoption as a larger effort, comprised of professionals from all three conferences.

Davenport told conference attendees to embrace analytics, which he assumed most already had, given that they were attending the conference devoted to analytics. So instead of continuing to preach a respect for analytics, he changed the focus to taking these extraordinary results and making them everyday occurrences.

Davenport’s “Everyday Analytics” presentation discussed several successes in the industry and how to make them more commonplace. Predictable results in analytics require that team members create a set of solutions they are good at delivering reliable results with, he said.

It is by creating this list of solutions that teams can then begin to industrialize their process. Industrialized analytics are embedded, scalable and deliver consistent results.

“We can’t do it all. We have to help decision makers produce better decisions,” Davenport said, adding that analytics for the masses really hasn’t taken off and that it is up to analytics professionals to make gathering analytics easier, depending on their own industry and needs.

Process thinking (where developers associate a step-by-step process with how they go about their work on a daily basis to deliver results) is necessary in order to standardize the process of reading and delivering analytics, Davenport said. “Analytical solutions should be scalable, reliable, quick and well marketed,” he said.

Analytics are understood by the analytics industry at large, but since they are vitally important to making informed business decisions, Davenport said analysts (or “math people”) need to make it very easy for businesspeople to understand.