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James Taylor

I will use this blog to discuss business challenges and how technologies like analytics, optimization and business rules can meet those challenges.

About the author >

James is the CEO of Decision Management Solutions and works with clients to automate and improve the decisions underpinning their business. James is the leading expert in decision management and a passionate advocate of decisioning technologies business rules, predictive analytics and data mining. James helps companies develop smarter and more agile processes and systems and has more than 20 years of experience developing software and solutions for clients. He has led decision management efforts for leading companies in insurance, banking, health management and telecommunications. James is a regular keynote speaker and trainer and he wrote Smart (Enough) Systems (Prentice Hall, 2007) with Neil Raden. James is a faculty member of the International Institute for Analytics.

August 2009 Archives

I was attending IBM's launch of its analytic appliances when it announced its intent to acquire SPSS. I did not get a chance to write much more at the time but I did not want to let the opportunity pass completely.I think the announcement represents a sea change in the decision management and analytics markets.

First it helps IBM deliver the predictive analytic element of its business analytics and optimization story. SPSS has many years of experience in productizing analytic R&D giving IBM a platform for bringing its own extensive analytic R&D effort to market. The potential for new capabilities based on IBM Research combined with new channels for PASW Modeler (Clementine as was) should be great for the analytics market as a whole.

SPSS has been a distant number 2 to SAS in the data mining/predictive analytics space for many years. While no-one, including me, expects acquisition by IBM to drive them past SAS it does represent a huge opportunity. The new channels for SPSS' products created by its acquisition by IBM include IBM's worldwide sales force, obviously, as well as its extensive network of partners. The focus of IBM on strategic relationships with customers will, I think, be particularly valuable to SPSS which has a history of selling direct to analysts/modelers. While this direct-to-user approach results in lots of customers, it does not establish SPSS as "strategic" or establish a broad commitment to using the SPSS modeling tools. IBM is more likely to drive this kind of adoption. Not only is this good for the SPSS product lines, it is good for data mining and predictive analytics more generally as I think it will raise the profile of modeling in companies.

Beyond analytics, though, the more interesting aspect is the potential for IBM to put together a complete decision management platform. Having the IBM platform support decision management as well as process management, event management and information management would be huge. And while acquiring all the pieces does not automatically give IBM such a platform they have historically worked to integrate their acquisitions fairly rapidly. I'll blog more about this over on JTonEDM later in the week.

And when we take the two announcements (analytic appliances and SPSS together) we have some interesting business implications. The Smart Analytics Systems represent another potentially powerful channel for SPSS. The Statistics modules were already going to be on some of these as part of the Cognos installs but the deployment products that SPSS has are ideally suited to this kind of appliance-based deployment. SPSS' decision management products - PASW Deploy for risk decisions, marketing campaign decisions and inbound communication decisions - package up models and rules for advanced decision making. Thanks to the simple interfaces decision services like this have these products are ideal for use in appliances. Putting these, and potentially other, decision-centric products on the Smart Analytics Systems will move them forward nicely.

Finally there is IBM's services business. Some months back IBM announced a new service line in Global Business Service - Business Analytics and Optimization. While Cognos and ILOG's optimization capabilities combined with various offerings from inside IBM R&D offered most of the software support this service line needs, the lack of an IBM branded data mining/predictive analytics offering was glaring. Adding SPSS now gives IBM's BAO service line all the tools it needs. Not only will that help BAO, it will drive SPSS into more IBM accounts.

As I said at the time, the importance of IBM's BAO service line should not be understated. Today high-end analytic solutions still require a significant amount of domain expertise and technical integration as well as multiple products. While I expect that to change, and the PASW Deploy products are an example of the kind of packaging that is required going forward, the ability of 4,000 IBM consultants to deliver more advanced analytics solutions is critical to increasing adoption and awareness around the world.

For more on this consider James Governor's post on IBM and SPSS, Forrester's report on the acquisition, Neil Raden's post on IBM's vision for analytics or Merv Adrian's post on IBM's move into predictive analytics.

Posted August 24, 2009 6:52 PM
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