Now, facing the existential crisis of the cloud, it's trying to do the same thing with Watson, its supercomputer. Watson, IBM hopes, will generate the software and services revenue it needs to remain relevant in the cloud era.
The company plans to invest $1 billion in a new Watson unit. There is reason for optimism. That's because Watson isn't just another way to play Jeopardy. It's also another way to do cloud analytics.
Cloud analytics is the big software challenge of our time. Cloud analytics takes the huge fire hose of data created by the Internet and turns it into intelligence, into answers to questions that may not have been asked yet.Cloud analytics is the difference between the National Security Agency collecting all that data on what everyone is doing online and actually doing something about terrorism. It's the difference between reacting to what customers may be doing and being pro-active, getting things to them before they ask. The primary method for analyzing big data sets has been Hadoop, which was developed at Yahoo (YHOO), refined by Google (GOOG) and built through an open-source process. It's okay. If you ask Hadoop to analyze data along certain parameters, it will do that. But if you ask Hadoop a question in English that relates to a big data set, you won't get an answer back in English, or even in real-time. With Watson, IBM says, you will. IBM has already created vertical market applications for Watson in health care, in finance and in visualization. Now it wants to build applications in other areas and sell the results. It will sell systems designed to analyze clients' cloud data, it will sell results and it will sell services that lead to asking data questions Watson can answer. The most interesting bit is where IBM will do this. It has chosen an address near New York University in the heart of Manhattan for the unit which will employ 2,000 people. IBM moved its headquarters from Manhattan to suburban Armonk, N.Y., 50 years ago, in 1964. The move to near NYU is symbolic as well as practical. The center of economic activity is moving from the office park to the university campus, creating a new explosion of growth around research centers in cities large and small. IBM is on top of it. The question remains whether there is enough business in Watson, or in any form of cloud analytics, to make up for losses in cloud hardware and services that IBM is suffering as a result of Amazon (AMZN) dominating the cloud rental sector and Google dominating cloud presence. IBM had revenue of $104.5 billion in 2012, which was down from 2011's peak of $106.9 billion. For the first three quarters of 2013, it had revenue of $72 billion. It has to beat 2012's fourth quarter to even match 2012 totals when it reports a few weeks from now. That illustrates the size of the hole cloud has blown in IBM's income statement. The company spent most of the last decade moving operations closer to customers, reducing its U.S. headcount and increasing it in places such as India and China. That not only kept costs in line, but brought IBM to where the software business was. But location doesn't count for that much in cloud. A single server farm can serve a vast geography, and through ties to other server farms, capacity moves itself to where it's needed. IBM doesn't need engineers who can help companies answer questions so much as it needs salesmen who can help customers ask better questions. As the old enterprise business withers away, with server racks located inside customer offices, and moves toward larger cloud systems housed in shared facilities, IBM has to reinvent itself again and find a way to bring in more business from the new markets than it's losing in the old. Watson can help with that. A branded system in cloud analytics could become a $1 billion business in a few years. But IBM needs 100 Watsons to keep the doors open, and the enterprise pool may be draining faster than even Watson and cloud analytics can fill it. IBM is in a race against time, and its survival is at stake. Does Watson have a solution for that problem? At the time of publication, the author owned shares in Google and Yahoo. Follow @DanaBlankenhorn This article represents the opinion of a contributor and not necessarily that of TheStreet or its editorial staff.
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