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Predictive analytics is being embraced at an increasing rate by organizations that need to gain actionable and forward-looking insight from their data. Why? Companies realize that simply looking in the rearview mirror to obtain insight and make decisions is not enough to remain competitive. Companies want to better understand what actions their customers might take. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. Some examples include customer churn analysis, predicting insurance fraud and finding patterns in health related data.
Recently, Hurwitz & Associates published its inaugural "Victory Index for Predictive Analytics." The Victory Index is a market research assessment tool developed by Hurwitz & Associates that analyzes vendors across four dimensions: vision, viability, validity and value. In the course of our research, we surfaced a number of trends in the predictive analytics market that have important implications for companies considering deploying the technology. Five of these trends are discussed in this article.
1 | Providing Solutions Across the User Spectrum
Whereas the traditional user of predictive analytics was a statistician or other quantitative analyst, a change is occurring in user type. There is a shift toward business analysts as users and consumers of these products and services, and businesses want to expand the field of users even further. In fact, many organizations believe that anyone with knowledge of the business should be able to make use of predictive techniques. Vendors have responded to this demand in different ways. Some are providing more user-friendly graphical user interfaces and automating the process of building predictive analytics models. Some vendors provide tools with shortcuts, for example, suggesting the right predictive model for a user based on the data at hand.
Ease of use is a huge trend in predictive analytics today. However, since predictive models can be complex (and some remain best left to statisticians to build) some vendors are providing technologies for sharing the results of the models via interactive mashups and other Web interfaces. These strategies can help nontechnical users build and make...