The importance of analytics to IBM was made quite apparent with the announcement to spend over $1b to acquire SPSS (NASD:SPSS) who after 40 years was one of the key providers of predictive analytic technologies. Recently SPSS had communicated a simplified position of their technology portfolio that covers data collection, statistics, modeling and deployment of analytics. While SPSS had specialized over the decades in providing data mining tools to specialized and trained professionals, they also had been working to make their technology more consumable by a range of customer and operational professionals. In the market discussion about analytics, SPSS providing predictive analytics that is becoming a necessity for corporations who want better insight into future performance and potential outcomes.
IBM has been methodically expanding their information management software portfolio over the last five years and who had in recent years acquired Cognos to advance their position with BI and performance management. IBM recently communicated their continued growth of the IBM Cognos product line and the adoption of their tools and applications. For IBM who has been busy investing into delivering a deeper level of sophistication in their analytics through their global services called Business Analytics and Optimization (BAO) has been focused on providing solutions to organizations specific needs. But beyond this is the mission of IBM to focus on delivering information where and when it is needed through what is called Information Applications that span line of business and vertical industries. This new form of applications leverages the core portfolio of products in what IBM calls InfoSphere that provides integration to management of information including content and data on any platform and part of their information agenda that I have been watching grow significantly for more than 5 years.
With SPSS, IBM now can empower new classes of analytic solutions with SPSS that go well beyond the traditional BI applications that focus only on historical data. These solutions were also well advanced by SPSS who had introduced focused solutions leveraging predictive analytics and text mining technology to address the needs of organizations in assessing customer experience through feedback management and analyzing customer interactions stored in text that my colleague Richard Snow examined recently. Now for IBM the opportunity is quite large to address new classes of applications from information to predictive analytics that can utilize the technologies from SPSS. This provides IBM a competitive advantage that Oracle, SAP and others including SAS Institute will have to determine how to respond but IBM will have to invest further into specific LOB areas like customer to compete with other dedicated providers.
For organizations looking to see how the technologies from IBM and SPSS work together, there are plenty of working examples since the organizations were working together through an existing business partnership. There is plenty of time to work out the organizational and product details that will be critical for short term success but for now this is a key milestone in the history of the software industry. SPSS has great depth and a rich history that will be further monetized and improved upon by IBM broader global reach and deeper consulting services organization. I find it hard to find anything but positive aspects of this acquisition by IBM that will significantly improve their market efforts. IBM will have to demonstrate their ability to apply the technology to the specific business needs of organizations and integrate the technology further into the IBM InfoSphere and IBM Cognos technology to simplify the administration and management and advance the application of predictive analytics to be more easily used by a larger audience of business professionals.