Every time InformationWeek writes about the emotional issues of IT employment, such as H-1B visas this week or career planning against offshoring in April, some readers zero in on the numbers and debate their relevance and veracity with a fire-spitting passion. And bless them for it.
Every time InformationWeek writes about the emotional issues of IT employment, such as H-1B visas this week or career planning against offshoring in April, some readers zero in on the numbers and debate their relevance and veracity with a fire-spitting passion. And bless them for it.A single number can turn public opinion. Witness recent research that claims China isn't producing nearly the 600,000-some engineers a year that's been widely reported. Numbers like those can take hold of a debate, leading to bad policy decisions and even bad career decisions.
In the H-1B debate, there's one single number that matters greatly. Lawmakers need to pick a number for how many visas to allow. Will 65,000 starve the U.S. talent appetite, or will the proposed 115,000 swallow the opportunity for U.S. workers? The number they pick will be wrong because there's no one perfect number, but they can't afford to get it too far in the wrong direction.
Which leads us in this debate to a place beyond numbers, to the realm of beliefs. And this I believe: We need a steady stream of immigrant and guest workers for a vibrant tech economy. And we need to err on the side of plenty. In an essay I spotted on Slashdot, writer/programmer Paul Graham weighs in on what makes Silicon Valley hard to replicate elsewhere. Immigration leads his list, as do a number of other issues related to dynamic, changing careers. The H-1B is one of many elements that makes the IT career uncertain. But the H-1B program, despite its shortcomings and problems, remains part of what we need for a thriving, job-producing U.S. tech economy.
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?