IBM takes on SAS for analytics domination, but neither is superior


IBM Global Services
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The Wall Street Journal is reporting that IBM plans to acquire SPSS for $1.2B all cash deal, which is roughly a 42% premium.

Watch out, SAS!

This match-up will be fun to watch… the massive public company, IBM, takes on the large private company, SAS — Abbreviation vs. Abbreviation. For those interested in the analytics that each is pushing the “abbreviation” comment has more to it than meets the eye. Each company is trying to help users make sense of their vast amounts of data through the use of statistics or business intelligence tools. Now, why is the “abbreviation” concept funny? Well by synthesizing data each company’s typical analytic process tries to make sense of the data by creating “buckets”, like an average or a customer segment. The consequence of “bucket-izing” or summarizing is data is lost for the greater good of manageability — International Business Machines becomes I.B.M and many much younger than I have no idea what IBM use to stand for.

O.k. so why are you still reading after such a failed joke? The main reason is that this is a big bet by IBM and SAS is already seeing the payoff as the market for these tools increases faster than the market for other technology solutions. Thee two companies largely now “own” this market and IBM with the acquisition hopes to offset a dying/shrinking annuity stream with a new growing one. The real fight for superiority in analytics is occurring in the new advances in econometrics and applications of mathematical models and hardware advances that make “abbreviation” or elimination of data a thing of the past. More simply, the power to treat a given customer the way they need to be treated and not like the generic segment they have been defined in.

More to come in follow-on posts as to the advances in analytics and implications, but until then check out Sentrana, a partner of CMG Partners and company with a superior science and technology. Read a Sentrana blog post debating the merits of IBM’s string computing claims.

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