1) "Traditional business intelligence applications (reporting, ad-hoc querying, OLAP) are great at answering questions like "what happened," "why it happened," etc., but they do not help you with answer to questions like "what may happen," said Forrester analyst Boris Evelson in his insightful breakdown of the deal's implications. Question: would your CEO be happy or unhappy if your company could begin to anticipate what's around the corner and be as prepared as possible for it? Would your CEO be happy or unhappy if customers started saying things like, "You guys have really stepped it up -- you've begun to anticipate my needs and that's enormously valuable to me."
2) As Forrester's Evelson and also his colleague James Kobielus articulate in detail, the IBM purchase of SPSS is rocking the not only the world of predictive analytics and data mining, but also the broader and more-established world of BI. And both analysts predict that other players in the important but more-passive world of BI will have to get much more aggressive on the predictive-analytics front. So over the next several months, we're going to see lots of new combinations of companies and products and technologies -- check out the analyses from Evelson and Kobielus for comprehensive lists of the hunters and the hunted.
3) In particular, SAP was called out as becoming more exposed by IBM's acquisition of SPSS, which is (well, that will shortly become "was") an SAP partner. Here's how Kobelius sized up the situation: "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." Ouch! But SAP didn't get to be the world's biggest provider of integrated global enterprise apps by being a pouter, and it is sure to take some very swift and aggressive action to head off this incursion by IBM deep into what could have been one of its core growth markets. There's a little bit of time for SAP and others to make their moves because the IBM-SPSS deal is not expected to be complete until the end of the year. On the flip side, the end of the year is only five months away.
4) That means Oracle will have to enhance its predictive-analytics capabilities. And so will Microsoft, and MicroStrategy, and Information Builders, and every other BI-specialist company that doesn't want to get branded as backward-looking instead of forward-looking.
5) And then there's the wild-card in this deck: SAS. It's been talking sophisticated predictive analytics for quite some time and delivering world-class products and is a powerhouse in some of the exact industries IBM/SPSS is targeting, including retail and telecom providers. And SAS is a privately held company so it doesn't have to factor into its plans the pressure from financial analysts that will surely play a part in the actions of the others. SAS might decide it's time for it to raise its profile accordingly and take a much more vocal role in this emergent and fascinating market in order to take its place among the big dogs in this romp.
6) IBM's creation of its own Business Analytics and Optimization Consulting group will serve as a megaphone for not just its own capabilities but also for this dynamic but not widely understood market sector. It's going to take a while before some people understand the distinctions between predictive analytics and, say, demand forecasting.
7) Wireless and mobile enterprise apps will become more urgent than ever before in a world driven by what's coming and what's likely. Companies who buy predictive analytics software are going to be the same ones who allow their own customers to engage with them on whatever terms those customers want -- and that is increasingly mobile. So I think we're going to see this deal trigger an acceleration in the development of more and better mobile solutions for a wide range of enterprise apps, and won't that be nice for CIOs who so far have had to cobble together a mish-mash of various incomplete and limited solutions.
8) And most important of all, once CIOs get a real taste of what predictive analytics can do, they're not going to be willing to settle for the same-old same-old in other product categories. As they begin to get a sense of the power and potential they can harness by being able to anticipate -- to predict and analyze -- future customer behavior, they're going to expect other IT companies to show and tell how their products can help with this forward-looking view out the windshield instead of the traditional scenery of the rear-view mirror. They will force IT vendors of all stripes to explain to them how those vendors' products will help generate growth, help enhance customer intimacy, and help their companies shorten the lag time between customers wanting/needing something and customers getting something.