Future analytical software needs conceptually skilled business users

Wednesday 13th February 2008
Examples of the analytical software space syntax that works as a information retrieval software for urban structures. Courtesy: www.span-arch.com/

Analytical software for business optimisation is the next technolog spend, argues Steve Lohr's blog for the New York Times. Fly in the ointment is a shortage of not just skilled workers to make the software, but of business people with the math and conceptual ability to use it.

Forrester Research has lowered its 2008 estimates for the growth in spending on technology goods and services, down to 2.6% from 4.6 % in the US. Globally, it says, growth will be 6%, down from a previous estimate of 9%.
The Forrester report is squarely in line with what other research houses and CIO’s have been saying. But a conversation with the report’s author, Andrew Bartels, was more intriguing.

Forrester’s economic models, Bartels says, show that technology spending tends to fit into alternating 8-year patterns, going back to the 1960s. For roughly 8 years, technology spending closely mirrors the growth of the economy.  Then come 8- years when investment is substantially higher than GDP growth. These recurring 16-year cycles have  tracked the spending and absorption of new waves of technology, from the mainframe to the Internet.

In 2009, according to Forrester’s model, another 8-year swing should begin. A big part of the next wave,  Bartels predicts, will be a move beyond using technology to automate business operations like financial reporting, marketing and procurement. “The next phase is using technology, especially analytics software, to optimize business results instead of just automating business processes,” Bartels said.

This smarter software, or  business intelligence software has been the biggest software deals in the last year,
with big enterprise vendors buying up business intelligence companies: SAP (Business Objects, $6.8bn), I.B.M. (Cognos, $4.9bn) and Oracle (Hyperion, $3.3bn).

Fueling this is the data explosion in digital form that might be used to make better business decisions. Not just structured information in corporate databases, but in e-mail, reports, Web sites, electronic whiteboards, wikis, social networks, video and voice files.

Bringing that information usefully, into the corporate world is a huge challenge not simply one of technical integration or technology engineered switches.  Knowledge encapsulated in software is  frozen, rigid.
Human decision-making is a fluid, on-the-fly process.

SAS is not in play in the recent takeover whirl because it is private and is owned by Jim Goodnight, who has the lowest profile among the nation’s software billionaires. He is not selling.

SAS is a specialist in heavy-duty analytics, used by companies and government agencies to do everything from detecting credit-card fraud in fractions of a second to determining sizes and styles of jeans to sell best in the various stores of national retail chain.

Demand for his company’s software is brisk and growing,  but Goodnight is worried about the shortage of not just skilled workers to make the software, but of business people with the math and conceptual ability to use it.

SAS, among other initiatives, is supporting an interdisciplinary Institute for Advanced Analytics at North Carolina State University which will issue masters degrees in analytics, the first group of students receiving their degrees this May.

If there is any doubt that human judgment is the central ingredient in making decisions, no matter how fancy the tech tools, look no further than the subprime mess on Wall Street, writes Lohr. It is a huge failure of the quantitative wizards, or quants, using computing tools. 

“It was the quants, and they were using our software,” Goodnight observed.  “But they didn’t understand the underlying vehicle when computing the risk.”

Source and full article: http://bits.blogs.nytimes.com

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