InformationWeek's 2012 U.S. IT Salary Survey shows IT pros doing OK in a slow-growing economy, with staffers typically making $90,000 and managers $116,000. Most wanted: People who blend business analysis and IT skills.
An Unforgiving Market
The rise of the business analyst has a flip side: the decline of some U.S. programming jobs and app and system support jobs over the past decade because of automation and offshore outsourcing. One IT pro in the Midwest (who asked that his name and company not be used) says he faced that reality a couple years ago when the bank he worked for was acquired by one of the giants. He supported the credit card unit's autodialing software, which is used to call people who are late on their payments, and the acquiring bank was a big user of offshore outsourcing. "It seemed like the writing was on the wall, that my role was going to be outsourced," he says.
He worked his relationships in the credit card business unit, and now instead of supporting the technology, he's an analyst helping business managers sift through call data to assess how well call agents are doing and how they could be more effective. He bought books on SQL and SAS analytics to learn those skills, and he's taking a course to bone up on PowerPoint, since he's doing more presentations. He earned a 4% raise with the new job, and he sees more potential for advancement. Back in his old division, staffing is down from 12 people to two.
Brown-Forman's analytics needs have changed as the company goes increasingly global. In the U.S., where the law requires distillers to sell through a distributor, its dashboards are more focused on production and the distributor channel, Duncan says. In other markets, Brown-Forman has been buying distributors, so its dashboards need more of a retail focus. Duncan needs to know data warehousing and BI technology well enough to design the data cubes, but he also must understand the business needs well enough to tease out from executives what would be the most valuable analyses. "A lot of people don't know what they need until they see it," he says. "Sometimes that's a very iterative process."
Procter & Gamble plans to quadruple the number of analytics people it employs and sit them with the nearly 60,000 employees who now use the company's data "cockpits." Web-based companies such as AOL, ComScore, and eHarmony are using clickstream and mobile big data analyses to identify the most promising potential customer, marketing partner, or soul mate.
This growing faith in data-driven decision-making is creating a talent shortage. Stacy Blanchard, talent organization lead at Accenture Analytics, a 2-1/2-year-old unit of the management consulting and technology services firm, says the big push among clients is to find people who can tell the CEO what's going to happen next--not what happened last week or last month. (Accenture Analytics alone employs more than 20,000 people.)
"They're typically statisticians who are deep into data modeling, they're close to the technology, and they know the right algorithms to use with the data available," Blanchard says. These next-gen analytics specialists are more receptive to open source tools and cloud computing than their predecessors. "They want to be sure that they're using the latest, greatest technology and have access to certifications and training," she says.
In the U.S. alone, McKinsey predicts that demand for big data and deep analytics experts will exceed the supply by 140,000 to 190,000 positions by 2018 if current trends continue. What's more, U.S. companies will need 1.5 million more managers and business analysts who can ask the right questions and consume the results of big data analysis, according to the McKinsey report "Big Data." Companies can't count on college grads or immigrants to fill that gap, McKinsey concludes: "It will be necessary to retrain a significant amount of the talent in place."
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?