Disrupting Under-employment
Vint Cerf, VP at Google and David Nordfors, CEO of IIIJ have a wonderful post on I4J called How to Disrupt Unemployment, imagining a world with:
“valuable jobs for every person, letting them do something that fits them like a tailored suit, creating the highest possible value and satisfaction for everyone involved.”
“This might be the greatest business opportunity ever” they proclaim, and we strongly agree.
Achieving this vision, is the mission of our company, and I want to describe some of the insights, challenges, and opportunities that we have uncovered in our year or so of research and development on that journey so far.
But first, one clarification: we think the problem is actually more about Underemployment (or Misemployment) than Unemployment.
Today, in the developed world, Unemployment is at relatively low levels (except some notable and desperate cases such as youth unemployment in Southern Europe). Most unemployment is frictional. We see the bigger driver of low productivity and low professional happiness coming from Under- or Mis-employment, where someone is, one way or another, in the wrong job. It is this condition that leads to the incredibly high level of worker disengagement that Gallup reported in its 2014 State of the American Workplace survey: 70% of workers disengaged.
Vint and David imagine a digital service, Jobly, that uses “smart technology to scan your skills, talents, passions, experiences, values, social network, and so on, tests the market for things you can do, and delivers opportunities to you from around the world to do those things.”
Below is a slide illustrating our sense that both the CV and the Job req have become stale, commoditised artefacts that do a poor job of facilitating matches between people and opportunities. Would it not be better if we could use Real-time signals from anywhere and everywhere to facilitate a much better match?
In this framing, we view the problem of how optimally to match a Person with an Opportunity foremost as a data problem where our success is determined by the quantity and quality of data that we can elicit about both the Person and the Opportunity, to then feed the algorithm that would match the two.
The practical challenge underlying this is how to get the most and best data. At scale, it requires overcoming the trust gap that has developed between ordinary people around the world, and purveyors of all the new tech products that spring up every day trying to serve them.
As the Economist recently put it: “If the perception takes root that enormous profits from exploiting data ... are crystallised in the fortunes of a few people living on a patch of ground near San Francisco, then there will be a backlash.”
We believe that most people in the world do not want to broadcast troves of data about themselves, for it to be hoovered up and returned to them in the form of targeted advertising. We believe people actually want less technology rather than more, less intrusion into their human lives, more self-determination and less by commercially-orientated algorithms.
So to gain access to the intimate data that would be required to achieve this vision, the application serving the purpose must first engender, and then sustain, extraordinarily high trust.
Practically speaking, this is why we have gone about collecting data about the Opportunity side of the equation first, rather than the Person side. We structure millions of datapoints on Industry sectors, Companies, and Jobs. Helpfully, we are seeing new data become publicly available with each passing month, for example the outstanding new Companies House repository of private company filings in the UK, easier access to Form D filings in the U.S., publicly available salaries for foreign workers on visas, and new APIs constantly making this all easier to access. Supporting this further, we are witnessing what seems like a secular trend towards transparency and disclosure across Industry in general, where smart, progressive companies recognize that they benefit by sharing more rather than less. Key executives write blogs, management disclose diversity statistics (even unflattering ones!) This expression helps companies to build relationships with customers, candidates and other stakeholders, and logically should enable better matching.
Individual/personal transparency has already increased vastly in the last decade, driven by social networking technology. 10 years ago the idea of posting a picture of your young child onto an internet site was seen as an ill-advised act. And look at Facebook today. We agree with Facebook’s philosophy that more transparency enhances the greater good, and are excited now to help drive the same increased transparency among companies.
So it’s getting easier to populate the Opportunity-side data-set. We can then use that data as content to attract, provide value for, and build a sustainable, trusting relationship with people / potential candidates, encouraging them to share the information with us that we would need to complete the match.
A second challenge that we encountered is a selection problem in the audience. Specifically, we learned that if we position our platform clearly for job-seeking (for example by including the word “Job” somewhere in our brand name), then the audience that we would attract would be predominantly job-seekers.
This is problematic because top companies, with many of the best opportunities, are often interested in “passive candidates” - people who already have a job, are at the top of their game, and likely to have many employment alternatives. This audience is not found trawling job sites and aggregators. And if our platform is thought of as one of those, then we are unlikely to attract these top end professionals.
For that reason, we build and position our products to appeal to and provide value for active professionals, for researching their sector, their competitors, or prospecting for customers. And if at some point in the future, they are looking for their next opportunity, they may recall that we have lots of quality jobs data, with lots of context, advanced search parameters, and they might spend some time with us looking for that opportunity. If we can attract these professionals, then our audience is of more interest to employers, thus helping us drive revenue, cover our costs, and become self-sustaining.
In many ways we are working to build exactly what Vint and David suggest. We’re calling it Craft.
We’d love to keep you posted on our progress, so if you’d be interested to receive occasional updates, please visit our homepage and click Learn More.
