Long-Term Unemployment and What We Need to Do About It
Date: Monday , April 02, 2012
Risesmart is a provider of next-generation outplacement solutions. The company leverages a cloud-based technology platform, proven methodologies and one-on-one support to help employers with their workforce strategies, and displaced employees with their career strategies. The company has raised a total of $13.85 million since its 2007 founding from NVP, Storm Ventures and angel investors.
At long last there is some encouraging news on employment, but the American economy is far from well. Long-term unemployment is at historically high levels and will be a drag on a recovery unless action is taken to reduce it. Fortunately, we have at our disposal the tool that can help solve this problem as it has so many others: technology. It is time we turned the power of technology toward addressing this longstanding problem.
Long-term unemployment is often lost in the employment figures that spring forth monthly from the U.S. Bureau of Labor Statistics. That agency and the news media most often focus on the official unemployment rate, new jobless claims, and the number of new jobs created. But dig deeper and there is reason for concern. The current eight percent unemployment figure does not include the 8.1 million people defined by the government as “employed part time for economic reasons” or the 2.6 million more who want a job but haven’t looked for one in a month. The U.S. government’s measure of all those impacted by unemployment (the BLS’s U-6) is actually about 15 percent of the workforce.
Still, the most worrisome element of the current economy is long-term unemployment. The Americans out of work for more than six months – some 5.4 million of them -- account for more than 40 percent of the total number of unemployed. The average duration of unemployment stands at 40 weeks, by far the highest figures seen in data that stretches back to 1948. US Federal Reserve Chairman Ben Bernanke, for one, has voiced concern about this. He recently testified before Congress that if the situation persists, more of the long-term unemployed will lose job skills and struggle to regain them. That will have the effect of reducing the country’s supply of skilled workers.
Causes and Remedies
It is easy – but simplistic -- to claim that the unemployment situation will improve with the economy, and that we should merely weather the storm. Slack demand may be the most obvious cause of unemployment, but it is not the only one. Erosion of skills, as cited by Bernanke, is a cause, as are mismatches (functional and geographic) between employers and employees. The labeling of certain workers as less desirable is third.
Worker skills are improved with training, of course, and mismatches between employers and employees can be addressed in several ways. But all those solutions have something in common: the use of technology. Skills training employ any number of technologies, and government efforts to facilitate worker mobility would do likewise. But what of job search? What can be done to improve the databases workers currently use to look for work?
These days someone using a popular job-search database might type in “marketing executive” and get a few useful responses before seeing listings for an executive with oversight of the marketing department, an administrative assistant in the marketing department, and so on. These listings are static; they cannot be improved upon. What if technology could be employed to help these listings “learn” to give more useful responses? With this semantic element in place, the databases could be self-improving, and over time more and more effective.
These kinds of semantic technologies are available. They can be deployed to improve a debilitating situation with national implications. All we need to do is resolve to address the situation and make it rewarding for the private sector to do so.
Precedents for Action
Americans have repeatedly used technology to solve national problems. Steamboats moved people faster than horses; trains, then planes did it faster still. Technology helped build an economy built on steel, then oil, then manufacturing, then services. It helped wipe out diseases and win a world war. Currently technology is being employed against a serious national problem: the high cost of health care.
It has spawned a new and growing industry: medical banking, in which banks have become involved in the processing of health-care-related transactions. The U.S. government has helped hasten change through legislation, the Patient Protection and Affordable Care Act. Under the law, health plans must adopt electronic processing protocols by summer 2013, and a series of other provisions will take effect through 2018. So it's no surprise that the banking industry is investing more than $100 million a year in technologies to process claims and other transactions for providers of health services. They are moving quickly for the best possible reason, they see a profitable business. Government merely provides the leadership that helps pave the way.
The case for action seems clear. In long-term unemployment we have a potentially debilitating national problem. And while markets ultimately provide the jobs that improve economies, we have some powerful tools available to us to help hasten – and sustain – a recovery.
Technology can be employed against two elements of unemployment by improving worker training and better matching employers and potential employees. Semantic matching technologies will not only be better than current platforms now in common use, they will improve over time and become steadily more effective.
Could we go further still? American economists say that 4 percent to 5 percent of the workforce is always looking for new work because of market forces that move jobs between different industries and locations. They call this frictional unemployment.
Could technology help us devise systems to reduce this "friction" and change the rules of unemployment forever?