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Cloud Computing Debate: Booz Allen Hamilton Comments on Recent McKinsey & Co. Report

By annie shum | April 22, 2009

http://cloudcomputing.sys-con.com/node/927844/print
(In a recent discussion document titled “Clearing the air on cloud computing”, Will Forrest of McKinsey & Co. offered his view on cloud computing. Unedited comments on the report from Mike Cameron and Rod Fontecilla, Booz Allen Hamilton Principals are provided below, published at their request.)

The recent McKinsey report on cloud computing “Clearing the air on cloud computing” has caused a bit of a stir, primarily since it purports to demonstrate that cloud computing can be twice as expensive as traditional data centers in some applications. Since this report makes a claim to an analysis of cloud economics, we would like to weigh in with a couple of comments regarding the report.

The McKinsey report, as presented, seeks to be the “other voice” and offer a contrarian view of cloud computing. The first thing we noted was the statement, on slide 7, that “Cloud computing can divert IT departments’ attention from technologies that can actually deliver sizeable benefits; e.g., aggressive virtualization.” This view seems to be an underlying motif in subsequent discussions, yet it is a premise that is not substantiated.

We are also somewhat taken aback by a management consulting firm is proposing an “industry standard definition” for cloud computing, having rejected, for various reasons, the definitions used by the IT vendors and data center owners that are currently creating cloud computing in the industry, as well as by centers of academic excellence (e.g., the computer science department at Berkeley). We are surprised that McKinsey rejected a definition of cloud computing (slide 11) because the definition doesn’t provide “definitive economic implications.” Webster’s dictionary defines “bicycle” without making any economic implications.

Definitions say what something is. Economic implications are a value judgment. We do not understand how a definition, absent a value judgment. It is also an assertion by McKinsey that the definition fails because it does “not distinguish cloud services from clouds.” Interestingly, on slide 17, a cloud service is defined as having two of the three key requirements of a cloud. This leaves McKinsey’s definition of cloud services to mean “not quite a cloud.” The report does not attempt to define what cloud services are, stating only that “it could run on top of a cloud.”

They state that cloud offerings “are most attractive” to small and medium sized business, and “there are significant hurdles to the adoption of cloud services by large enterprises.” That would come as quite a shock to Target, Eli Lily, the New York Stock Exchange, the American Stock Exchange, NSADAQ, Toyota, E*Trade, Computer Associates, and a host other large enterprises that have been in the cloud for a couple of years.

The “significant hurdles” to cloud adoption by large organizations appear to be McKinsey’s opinions but not supported by hard data. For example, “business perceptions of increased IT flexibility and effectiveness will have to be properly managed.” What perceptions? Managed by whom?

We are trying to figure out how McKinsey got to the numbers they cite, on slide 24, in their comparison of CPU costs per month in the data center versus in the cloud. Taking the $14K/server cited on slide 23, and dividing that out over a three year refresh cycle, costing it out by month, and dividing by 8 to reflect the cost of each processing core, I got to $48/month. But that price does not reflect any power, facilities, or labor, so the “Total Cost of Assets” MUST be higher than the figure cited by McKinsey, unless they changed assumptions between examples. They also make an assumption of an Amazon large instance (discounted by 25% for reasons that are not provided) and calculate a cost per month of $270.

Where this example appears to break down is that, for the data center, they are calculating the cost per core, while for Amazon they are calculating the cost of a Large EC2 instance, which is four cores. On a single-core basis, an EC2 Small instance is only $72 month, running non-stop. Assuming the same 10% utilization used in other examples, the comparison should be $48/month for the data center and $7.20 month for EC2.

Their assertion that moving a data center to the cloud provides a 10-15% savings in labor seems to be well off the mark. In the discussions with cloud providers, we learned that labor went from being one of the largest components of cost to an insignificant component of cost, largely because of virtualization (reduced hardware baseline plus ease of provisioning logical, rather than physical, devices) and elasticity (automated resource management).

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