Over the last decade, there has been a fierce increase in the freelance economy in the United States. Millions of people are now working on platforms ranging from Uber and Lyft to Taskrabbit and Fiverr, accepting usually short-term tasks that can be accomplished efficiently and repeatedly. Although these casual jobs were the subject of painstaking scrutiny of their pay structures and workplace safety, their effects were mostly limited to those who did not work in the liberal professions.
Times are changing rapidly, however, and markets are entering more and more into white collar territory with better product design.
Take for example Clora, who works with the highly specialized talent needed to produce and launch a new life science product. Or Paro, which connects businesses to accountants and other finance professionals to manage the financial department of a company. Or Catalant (formerly HourlyNerd), which works with independent consultants who can solve a range of complex issues such as market size or product marketing.
This may be an exaggeration, but it's only a matter of time before rent-a-CEO options also exist.
Part of this transformation of white-collar work certainly comes from businesses and workers who want more flexible work arrangements. However, I would also argue that the renewed focus on product design has been critical to effectively creating a market for online talent.
Different tasks often have very different requirements and workflows, and the product must match the type of talent that he hopes to attract. These new markets understand that professional work is often ambiguous and difficult to judge quality, and have developed key product features to handle these challenges.
This is very different from the early years of the mainstream internet, where online job markets were designed as open spaces, with both sides of the market competing for transactions to occur . A client can post a potential job on Craigslist, or a worker can post his availability to be hired. These were marketplaces built around serendipity, with almost no indication of which platform to bill on, how to charge, or how to find the best talent for a particular project.
Over time, it became clear that some tasks were much more popular than others, and they were just as repeatable. Uber takes a passenger from an origin to a destination, and Taskrabbit allows you to hire someone to install IKEA furniture. You do not need to use paragraphs to describe what you are looking to do, and you should not have to negotiate a price every time you want to get in a car or install a bed frame Malm.
This regularization has become the product itself – as a result, the freedom market for all has become a restricted menu of options with standardized pricing and rating systems. More importantly, the identities of the workers themselves are often protected from the client on these platforms. You buy the quality mark of the company, not the guarantee of the workers that they can do the job.
Today there is a market for almost all simple and easy-to-define tasks. The challenge has been how to design markets to handle more complex forms of work and evaluate the quality of this work, especially in cases where quality may be in the eye of the viewer.
One answer was to focus on hyper-specific (but lucrative) verticals. Clora and Paro are good examples of this trend. The strength of Clora is to know the hiring model for the pharmaceutical and life sciences industry. They understand what talent is needed and, more importantly, how to evaluate that talent. By focusing on accounting, Paro has a relatively objective standard on what a quality job looks like, which facilitates the assessment.
The key to each of these platforms is that prices, ratings, quality and product offerings are not standardized in the same way as previously produced marketplaces. Each of these platforms recognizes that, say, the launch of a cancer drug is going to be very different from a treatment for male pattern baldness. There is no secret algorithm capable of detecting these nuanced differences without human judgment entering the equation.
So, to compensate for this variability, these markets put much more judgment on the quality of work on the shoulders of the professionals themselves. Unlike Uber, there is no GPS telling anyone to move from this job to this job. As such, these newer markets are somewhat hybrid between the first generation of Craigslist free-to-all marketplaces and the second generation of products like Uber that we have seen more recently.
B12, a company I've recently profiled, is trying to build a unified infrastructure to handle exactly that kind of ambiguous task. Its open-source Orchestra platform is designed to manage not only the non-linear work patterns that occur in these contexts, but also how to judge the quality of the platform (its answer is to have the professionals evaluate it by means of a code). other professionals). It's a bold idea, although I still believe we'll see a lot of verticalized markets as sales and marketing in these areas are difficult.
When we really evaluate what is happening around work, especially professional, there can be incredible complications that make machine learning and algorithms difficult to perform. Product designers must include ambiguity, complexity and social human factors in the labor markets to properly attack these industries. Fortunately, we see a new generation of startups doing just that, and that will not only give opportunities for founders and VCs to make a lot of money, but potentially millions of additional workers.
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