Can Careers Find the Right People?

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How do you find the best person for a job in the fastest way possible? The answer to this question is something of a holy grail for startups. A has shown, for example, that companies with effective recruitment strategies double the profit margins of their competition.

The flip side of this is many people don’t have the opportunity to be in fulfilling careers— instead merely clocking in and clocking out of their jobs for a paycheck. The result is a broken labor market that operates with a large output gap from the efficient case where everyone has the best job for them and companies with the best ideas are properly resourced. The most popular recruitment strategy involves storing applications from past job postings and sorting through them each time a position opens. This requires retaining and rereading thousands of resumes for each new hire, which is simply a waste of time and energy. It works sort of like an employee referral program but with some interesting new twists.

Our idea is to treat recruitment as a , which essentially calls for an optimized search to find the best candidate for the job.

Suppose, for example, that a startup company called Trike Drive is developing self-driving tricycles. They need to hire ten developers to implement a new deep-learning based vision controller, but they can’t exceed a fixed budget. They want to recruit a diverse group of the highest-quality candidates, avoid being buried in unsuitable resumes, and leverage an external network because they don’t have the critical mass to rely on internal referrals.

Their solution is to purchase NCNT in the form of 100 trikeCents, which they distribute to an initial group of graduating computer science majors at a research university nearby. Alice is a student who receives a devCent, and she reasons as follows:

1. Alice can apply to Trike Drive, and if she’s hired while holding a trikeCent, she gets a 10k NCNT bonus.
2. Alice could also send the trikeCent to Bob. If Bob gets hired while holding a trikeCent, he gets a 10k NCNT bonus while Alice gets a 5k NCN bonus as the direct referrer.
3. Bob could also send the trikeCent to Carol, and if Carol gets hired, she gets a 10k NCNT bonus, while Bob and Alice each get a 2.5k NCNT bonus.
4. If no one applies to Trike Drive holding Alice’s initial trikeCent, it expires and can be reseeded to another student. Once all ten positions are filled, all of the tokens expire.

nCent promotes better recruiting through external referrals

Recall that Trike Drive will hire at most ten developers, and each hire through the devCent program costs them no more than $15k of NCNT. This puts an upper bound (of $150k of NCNT) on the cost to run the program — which is quite competitive with traditional headhunting strategies. The expiration date of the tokens also limits the amount of time that the program can run — accelerating the recruiting process and allowing the company to discharge its financial responsibility for the program after a predetermined time.

Furthermore, if Alice knows Bob is not interested in trikes, but is fascinated with self-driving mopeds, she can exchange her trikeCent for mopedCent to give to Bob — all via distributed exchange and without Trike Drive and Moped Drive being in a trust relationship with each other!

The recruiting mechanisms in place today are absurdly inefficient. Fixing these inefficiencies could dramatically decrease unemployment, wasted time, energy, and money.

nCent is proud to announce our launch use case, , which enables companies to find the best candidate in record time. Indeed, this referral dynamic has already been successfully used to recruit all but one of our team internally at nCent!

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