Monthly Archives: July 2012

Digitization of the supply side of the labor market

Note: This blog post also contains a short review of Google’s new Consumer Surveys service. See the end of the blog post for details. 

On most electronic commerce sites, information about the supply side is digitized and publicly available while information about the demand side is generally not: Amazon, Expedia, iTunes, Etsy etc., all collect and display detailed data about the items for sale, but there is generally little or no information about the consumers with the demands. If we look at the labor market, the reverse us true, in that it is the demand side that’s digitized. On online job boards like CareerBuilder,, Indeed, SimplyHired etc., vacancies are described via detailed textual 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 to the marketplace. 

While we might think that there are some fundamental reason for this difference, I don’t think this is the case for the simple reason that in the case of labor markets, the supply side is being digitized, primarily though LinkedIn (in a big way) and through sites like oDesk (in a comparatively smaller, but more comprehensive way). On these sites, workers create permanent, searchable profiles for employers that containe 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 yesterday (July 24th, 2012), approximately 19% of the US-based Internet using population had a LinkedIn profile [* see note below for interesting background for this 19% figure]. According to LinkedIn, as of March 12, 2012, over 160 million people have created profiles, and in many industries, a LinkedIn profile is expected of all applicants. I talked recently to oDesk’s corporate recruiter, asking her how many candidates 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. 

I think this supply digitization is likely to prove consequential, 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. The recommendations made by a platform can have the advantage of being potentially informed by the platform’s holistic perspective on the marketplace. In computer-mediated marketplaces, by necessity essentially every piece of data that goes into or is generated by the marketplace is captured in an electronic database that could conceivably used to make recommendations. 

Of course, job board do try to make recommendations by suggesting vacancies to workers, but they are limited to conditioning those recommendations on 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, I think a lot of this work on recommendations will happen within companies in a state of semi-secrecy, but hopefully enough will be made public that others can contribute, ala the Netflix challenge. It’s a little sad that to date society has expended more machine learning research effort trying to predict taste in moves rather than fit for jobs, despite the enormous welfare consequences of the labor market. However, I predict this will change and expect a lot more work on this topic from computer scientists and market designers in the coming years. 

[*] The Origin of “19% of the US Population has a LinkedIn profile” Number

In writing this blog post, I wanted to get an accurate number for what fraction of the US population has a LinkedIn profile. This number was proving 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 US-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 1511 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.  

Shrimponomics, Complements & BPOs

Most relevant image available from doing a
Google Image search for “Shrimp using a computer”

A few years ago, there was a Freakonomics post about how people reason about economic situations and phenomena. The phenomenon in question was shrimp consumption: the amount of shrimp people eat in the US per capita  tripled between 1982 and 2007. When asked to explain this rise, non-economists mainly give demand reasons (changes in preferences), while economists are more likely to also give supply reasons (improved fishing efficiency, rise of aquaculture etc.). 

If I had to offer an explanation for this focus on demand explanations, my guess it that demand explanations come more easily to us because it is the side of the market that is more familiar to us : most of us have eaten shrimp & bought shrimp—very few of us have worked in commercial fishing. So when asked “why are people consuming more shrimp?” we start with “why might I consume more shrimp?” and although price is certainly a reason (and a path of thought that would help lead to a demand explanation), it’s not as salient or even as interesting as things like changing tastes, health trends, exciting new shrimp-based dishes etc.     
So this blog post isn’t about shrimp and it isn’t about supply & demand. It’s about complements and substitutes. I think there is a similar psychological tendency to focus on goods-as-substitutes than goods-as-complements.  At the individual level where we are making choices, we are usually thinking in terms of substitutes: do I want coffee or tea? Should I take a vacation to Las Vegas or Hawaii? Mac or PC? It’s a bit more subtle to think about “if I had X, would it make Y more useful to me” which is at the heart of all complementarity stories. 

This is a long-winded introduction to my real topic, which is that in my last blog post, I made the argument that online work could disrupt the BPO industry by serving as a substitute for what BPOs offer. A point I didn’t think of—but in retrospect seems pretty obvious—is how just as easily complementarity could be the dominate effect. After my blog post, my CTO at oDesk, Odysseas, emailed me with his thoughts:  

The primary benefit of BPOs is not that of labor cost arbitrage. Thats typically the motive/benefit for offshore staff augmentation firms – but BPOs are business process outsourcers. BPO is ADP [Automated Data Processing] that outsources your payroll or a business that outsource your HR process etc… We often tend to think of BPOs as an offshore firm that does a little bit of everything having as sole pivot point its lower cost of labor – thats true, but its an abuse of the term and I would agree there that the particular type of business is going to be affected in the years to come from online labor.

This part is basically my substitutes story—now the complements part:

However, the more interesting effect would be the effect of online labor to the real BPOs..
There BPOs will not be negatively affected – the opposite. The availability of online labor would allow BPOs to become more flexible lower their overall fixed costs force them to become more automated and streamline (their virtual nature will require that), allowing them to lower even the cost per customer, allowing them to focus on smaller projects, smaller customers allowing to address smaller/different market segments.  They will become less relying on an enterprise sales force customer acquisition model which is dramatically affecting their cost structure.
We are seing examples of what the new BPOs will become in companies that outsource the process of testing (uTest) of seo writing (Mediapiston) etc.

He’s of course exactly right—and he’s a CS PhD, not an economist, so shame on me :). If you think of true BPOs in the sense that Odysseas is talking about, then the complementarity story becomes more important. These true BPOs would be big buyers in the inputs market and would benefit greatly from a liquid, efficient market for labor.