The Way We Work

Editor’s Note: This post originally appeared on John Horton‘s personal blog, Online Labor. You can also follow John on Twitter.

On most ecommerce sites, information about the supply side of the marketplace is digitized and publicly available, while information about the demand side is generally not. For example, Amazon, Expedia, iTunes, Etsy, etc., all collect and display detailed data about the items for sale, but there is generally little to no information about the consumers with the demands.

If we look at the labor market, the reverse is true—it’s the demand side that’s digitized. On online job boards like CareerBuilder,, Indeed, SimplyHired, etc., job posts have detailed descriptions about the nature of the work, skills required, location and approximate salary, but the job seekers—the sellers—generally do not create profiles that describe themselves.

It might seem like the reasons for this difference are fundamental, but I think that’s unlikely. If you look at certain labor markets, the supply side is being digitized—primarily through LinkedIn (in a big way) and sites like oDesk (in a comparatively smaller, but more comprehensive way). On these sites, workers create permanent, searchable profiles for employers that contain rich, employment-relevant data about themselves.

With the rise of LinkedIn, we are witnessing an unprecedented, voluntary data collection and digitization of the supply side of the labor market. On LinkedIn, individuals can create public profiles and list their education, professional credentials, associations, skills, current and past work experiences and, critically, their other professional connections (indicated by approved links to other LinkedIn users).

As of July 24th, 2012, approximately 19% of U.S.-based Internet users had a LinkedIn profile [*see note below for interesting background for this figure]. According to LinkedIn, as of March 12, 2012, more than 160 million people have created profiles, and in many industries a LinkedIn profile is expected of all applicants. In fact, I talked to oDesk’s corporate recruiter, asking her how many of the candidates for in-house oDesk positions had LinkedIn profiles. She responded:

“I’d say it is close to 100% (and certainly 100% for viable candidates). I can’t think of an example of someone who I have screened who didn’t have a profile on LinkedIn.”

This “supply digitization” is going to be very impactful, because once the supply side of the labor market is digitized, platforms can begin making data-driven, highly contextualized recommendations to both sides of the market. In other words, the more detailed digital data these platforms have, the better they are able to recommend highly relevant jobs to job-seekers and equally relevant candidates to employers.

In addition, the platform’s recommendations can potentially have the advantage of being informed by a holistic view of the marketplace. That’s because, in computer-mediated marketplaces, essentially every piece of data that goes into—or is generated by—the marketplace is by necessity captured in an electronic database, and this mountain of data can be used to inform recommendations.

Of course, job boards do try to make recommendations by suggesting job openings to workers, but these recommendations are limited to whatever search terms and perhaps geographic and/or salary constraints a job-seeker enters in a relatively brief search session. The platform cannot condition its recommendations on a worker’s employment history, educational background, skills, current employment status, professional connections, certifications, personality, test scores and other match-relevant factors, nevermind try to balance recommendations to navigate the twin shoals of market thinness and market congestion.

Unfortunately, a lot of this work on recommendations will likely happen within companies in a state of semi-secrecy, but hopefully enough will be made public that others can contribute, such as with the Netflix algorithm prize.

It’s a little sad that so far society has expended more machine-learning research effort in trying to predict movie tastes rather than job fit, despite the enormous economic and even humanitarian consequences of improving the labor market. However, I predict this will change, and I expect a lot more work to be done on this topic from computer scientists and market designers in the coming years.

*Origin of the “19% of the U.S. population has a LinkedIn profile” number

In writing this blog post, I wanted to get an accurate number for what fraction of the U.S. population has a LinkedIn profile. This number was proving to be hard to come by, so I decided to try a relatively new service launched by Google called Google Consumer Surveys. For 10 cents an answer, you can pose questions to a supposedly representative sample of U.S.-based Internet users. You also get some of the respondent’s basic demographics, such as inferred age, gender and income. I launched a one-question survey and got 1,511 responses in less than a day. The screenshot below shows the main results, but it also includes some neat tools for looking at the data in different ways. I made the survey public—check it out here. I’m quite pleased with the service and plan to use it again.


John Horton

Staff Economist

John Horton is the former Staff Economist at oDesk, with expertise in labor economics and online work. His work focuses on data analysis and experimentation concerning the promotion of efficient matching in the marketplace. John received a PhD in Public Policy at Harvard University for his thesis “Online Labor Markets.” He also graduated from the United States Military Academy at West Point with a B.S.… read more