James G. Kobielus By James Kobielus

IBM dropped a big bombshell at the start of any already action-packed day for the analyst community. At this moment, I’m sitting, along with several dozen of my peers from Forrester and other firms, at the IBM Smart Analytics System launch event in Hawthorne NY. I’ll blog on IBM’s other announcements in a separate items.

The bombshell was IBM’s announcement that it’s acquiring SPSS, a long-established, leading provider of predictive analytics (PA), data mining (DM), statistical analysis, and text mining tools. The acquisition, subject to the usual shareholder approvals and regulatory reviews, is expected to close later this year. But, even in advance of that near-certain consummation, IBM’s bold move has already sent shockwaves throughout the analytics market.

Most important, IBM has acquired the second largest vendor of PA/DM solutions, dwarfed only by privately held SAS Institute. In this segment, IBM’s proposed acquisition is having the same impact that its Cognos buy had on the business intelligence (BI) market two years ago. In many discussions with Forrester customers, SPSS is often mentioned as a key solution provider for predictive modeling and statistical analysis against structured, semi-structured, and unstructured content.

For IBM’s competitive standing in the data management market, this acquisition represents one of the last missing pieces of its Information On Demand (IOD) portfolio. By acquiring SPSS, IBM has acquired a substantial PA/DM brand with a very loyal set of longtime customers who have build their customer churn, supply chain optimization, and other predictive models on its best-of-breed platform. SPSS recently underlined its feature-comprehensive value proposition through re-branding around the “Predictive Analytics Software” (PASW) family name. But longtime customers didn’t need to be reminded, of course, that what used to be known as “Clementine” defines a functional high-bar in this solution segment.

IBM would probably be the first to admit that it took its focus off the PA/DM market over the past several years as it build out the BI, data warehousing (DW), and other pieces of its IOD portfolio. IBM had never really exited the PA/DM market, but casual observers might have thought otherwise. However, the vendor three years ago chose to de-emphasize its Intelligent Miner tools–which support mining of structured data–as stand-alone offerings. It essentially buried these solutions, moving them into its InfoSphere Balanced Warehouse family, where they are now offered as features of its Enterprise Edition DW software, rather than as stand-alone tools that would be enhanced and evolved independently.

IBM and SPSS’s respective customer bases should rest assured that overlaps among their respective product portfolios are not extensive. Once the acquisition closes, IBM is almost certain to build out its SPSS brand and, over the coming 1-2 years, phase out the Intelligent Miner technology within its InfoSphere portfolio. One tricky issue is which text analytics solution family–SPSS’ or IBM’s OmniFind solutions–will prevail as the parent converges these offerings in its IOD portfolio. Another issue is how IBM will integrate the SPSS offerings into its still-evolving in-database analytics roadmap for InfoSphere Balanced Warehouse. Hopefully, IBM will maintain and extend SPSS’ already extensive in-database analytics integration with a broad range of vendor DWs, including such Big Blue rivals as Oracle, Microsoft, Sybase, and Teradata.

Who loses from IBM’s acquisition of SPSS? Fundamentally, one can’t help think that SAP missed the boat by not seizing the opportunity to acquire partner SPSS, whose Clementine technology it OEMs, has integrated with its BI technology, and sells as SAP BusinessObjects Predictive Workbench. PA/DM is an increasingly key component of a full-fledged BI solution stack. However, the remaining field of vendors with stand-alone, horizontally applicable PA/DM vendors consists primarily of vendors who are large but proudly and stubbornly independent (especially, SAS Institute); high-quality but much less widely adopted (e.g., KXEN, ThinkAnalytics); or specialized on customer, financial, scientific, or other specialized analytics (e.g., Unica, Fair Isaac, Accelrys).

Some IBM rivals in the BI space already have strong PA/DM tools, most notably Oracle (Oracle Data Miner) and TIBCO/Spotfire (the Insightful tools). Among BI vendors, Microsoft, MicroStrategy, and Information Builders have PA/DM capabilities, but they are not to a SAS or SPSS level of sophistication. These and other BI vendors should also be scouting for strategic acquisitions.

What do you think? Will IBM’s acquisition of SPSS lead to further merger and acquisition activity in this space as other leading BI players strengthen their PA/DM solutions?