Article Published: October 26, 2016
Article Published: October 26, 2016
You understand the principles of balance, forward motion, kinetics, traction and resistance. The mechanical construction of the bicycle has been reviewed and internalized mentally. You could pass any written test on the subject.
But until you climb onto one and start to pedal, you have only knowledge. You don’t truly know how to ride a bike without real-life, participatory and practical application of that knowledge.
So it is with the emerging field of predictive analytics. Understanding trends and opportunities through the strategic mining of data can be a powerful source of knowledge, with important value to an enterprise. But if all you have is knowledge, and are left to your own devices to apply it in a practical sense, you may crash and scrape your bottom line’s knees just as badly as someone who just read a book on bike riding.
Greentree-based Othot – short for “Original Thought” – has emerged with a cloud-based software service that provides that essential follow-through, helping not only to reveal trends through predictive analysis, but also to provide tactical action steps to apply that knowledge through prescriptive analysis.
Andy Hannah, Othot CEO, had worked with the International Institute for Analytics to interact with large companies using data analytics and began to wonder how medium-sized organizations use this valuable approach, as well.
“Our idea behind Othot is to democratize predictive analytics, determining how to make it easy for companies to adopt,” Hannah explained. “We take the cost and complexity out of analytics.”
Hannah described a core driver behind the Othot approach as making sure its users determine what high-impact question it needs to ask to make sure the right data gets collected and analyzed. Such questions could include: Will a prospect turn into a customer? Will customers churn? Will customers turn into high-value relationships, such as customers buying the car, a service package, warranty, after-market products, tires, and even the next car? For colleges and universities, a high-value relationship means enrolling students who remain for their entire academic careers, who become active and supportive alumni, and who serve as ambassadors for the school throughout their careers.
The higher education community represents the strongest adopters so far of the clear, intuitive, easy-to-use Othot package, which requires no capital investment or lengthy training commitment.
“How do you focus on 100,000 applicants to enroll 1,000?” posed Hannah. “How do you identify students with a higher probability of coming to your school? Students with a 30-to-60 percent chance of enrolling—this is the real battleground. They have enough potential to end up as enrolled students to deserve marketing attention.”
John Abbatico, Othot’s Chief Product and Chief Technical Officer added, “Othot’s machine learning engines determine the triggers for each individual school that figure most strongly in getting those students to commit—such as proximity of their home to the school, whether they attend an on-campus event, SAT scores, and more—and make these recommendations to the school for action. It is both a predictive and prescriptive approach, and a very distinct one in the marketplace.”
One university client of Othot admitted 20,000 students and enrolled only 2,000. The Othot software predicted, within a margin of 15, the students who would be enrolled and was 90 percent accurate in identifying not just the number of students, but the actual individuals.
“Othot helps clients use their money more effectively, yielding better results, including gaining happier customers,” Hannah concluded. “That’s engineering data in the right way. Plus, Pittsburgh is a great place to build this business. Pitt and CMU have been tremendous partners and sources of talent.”