LinkedIn also helps recruiters scour their own companies for talent: firms are often poor at spotting what is right under their noses. Marie-Bernard Delom, who has the task of identifying high-fliers at Orange, a French telecoms company, is using LinkedIn for that reason. She has commissioned software that combines LinkedIn profiles with internal data. Companies can also see how they measure up against others trying to hire the same people. They can do so using LinkedIn in combination with other sites such as Glassdoor, where people anonymously rate the places where they work or have been interviewed. Mr Shapero calls this a “sales and marketing process”, in which companies treat their reputations as employers like brands. They can track how many staff have quit to join the competition, as well as how many are coming the other way. LinkedIn members can “follow” companies they do not work for, another loose indicator of potential interest in a job: both Novartis and Infosys boast 500,000. American tech giants have many more.
As LinkedIn attracts more members in more countries and industries, its data will become richer. Put another way, the lines in Mr Weiner’s graph will become more numerous—and more useful. He thinks that if you trace the connections between workers, companies and colleges, and if you map people’s jobs, qualifications and skills and plot these against employers’ demands, you will end up with a step-change improvement in information about labour markets: big data for the world of work.
The world’s labour exchangeAnd that, in principle, should help labour markets work more smoothly, potentially reducing Europe’s youth unemployment rate, for example; or matching some of America’s 20m underemployed with its 4.7m vacancies; or helping the millions of Chinese expected to migrate from the countryside to cities to find work. Such hopes are remarkably ambitious. They amount to a gargantuan exercise in eradicating the mismatch between the skills people have and those employers want, or between the places jobs are on offer and those where people live. As Mr Blue concedes, “there are real barriers that we haven’t even begun to face yet.” LinkedIn is only starting to reach beyond professionals, for example. Eventually it may have even to think, as Amazon, Facebook and Google are doing, about providing internet access in remote parts of the world; but that is far ahead. Still, LinkedIn is starting to do more than just find and fill professional jobs. Undergraduates can see how many of their predecessors have ended up in given companies or professions, to help them plot their own paths. (Those who graduated years ago can do the same for their classmates, and laugh or weep accordingly.) Some companies have begun to use LinkedIn’s data to help them decide where to open new offices and factories. By looking at the skills on offer—at least among the network’s members—and demand for them in different parts of the United States, LinkedIn’s data scientists can identify “hidden gems” where there are plenty of potentially suitable employees but little competition for their services. Perhaps most significant, LinkedIn has started to feel its way beyond professionals. Since early June the number of jobs on its site has jumped from 350,000 to about 1m. As well as openings for software engineers at IBM can be found jobs as delivery drivers for Pizza Hut or on the tills at Home Depot—which until now no one would have expected to find there. This is because LinkedIn has added jobs from employers’ websites or human-resources databases to its existing paid advertisements. Unlike paid ads, the new ones are seen only by members who are actively seeking jobs. The idea is being tested only in America so far. But if delivery drivers and checkout clerks start to look for and find jobs on the site, LinkedIn will have taken a step towards becoming a much broader job shop. It is hard to know what its eventual effect might be. Even if Mr Weiner’s grand vision were realised, it could not cure global unemployment on its own, though richer data ought to make a difference. In explaining high unemployment rates in Western economies, many economists would put more weight on weak aggregate demand than on a mismatch of location or skills. It is even difficult to quantify the impact of LinkedIn on labour markets so far. In theory, making it easier for people to find better jobs could affect the rate of job turnover within firms: recruiters say they have noticed little impact, and that other factors (such as the economic cycle)—seem to matter more. But no one really knows. As LinkedIn’s data pool deepens, its value to researchers as well as its members and corporate customers will increase. Pian Shu, an economist at Harvard Business School, points out that you could compare the career paths of those who graduate in recessions with those who graduate in booms: do the former, as you might suppose, fare worse? Aiding academic research is not LinkedIn’s priority. But its interest to economists is a sign of how pervasive it has become. “I’m on there until midnight a lot,” says Mr Han, of his quest to find the right people for Kenandy. “I’m hooked.” (The Economist)[eap_ad_3]
