Have you tried DAMM?

In the Reputation Economy, computers are increasingly making important decisions for us – for instance, who to hire or fire. This trend is called “decisions almost made by machine,” or DAMM.

As the term suggests, these decisions are made with minimal human oversight. Consider hiring: Many companies now use computers to screen job applicants. After all, recruiters are slow and expensive; computers, on the other hand, can make thousands of decisions each second, and they don’t need lunch breaks or paychecks.

Consider that the Mars One Organization received over 200,000 applications from hopefuls who wanted to join a mission to Mars. If a human being has to spend five minutes evaluating each application, they would have to spend nine years working full-time in order to process the applications.

Savvy job applicants will anticipate these automated screening procedures and prepare their materials in a computer-friendly way. If you make it easy for a computer to recognize and categorize your accomplishments, you can increase the chances of a favorable outcome.

Most of these automated systems look for keywords based on the employer’s requirements. So if a vacancy notice calls for a CPA it’s a good bet that someone programed the screening software to scan applications for the word accounting.

And keep in mind: DAMM can also vault you forward in your career. This was the case for Arnel Pineda, a small-time singer based in the Philippines, who loved uploading covers of Journey’s hit songs to Youtube. His performances received thousands of thumbs-up votes, and so he started appearing higher in the results when people searched, say, “Journey cover.” And this automated ranking system eventually propelled him to stardom: Pineda ended up become Journey’s new front man for the world tour.

When it comes to the power of reputation to shape your career – well, don’t stop believing.

Hiring valuable talent is a challenge, since there’s no way for companies to know exactly how applicants will perform in a role. After all, the conventional approach to hiring, which relies on gut instinct and resume evaluation, followed by a personality-based interview, simply isn’t that effective.

This was proven by a study that asked a group of MBA students to choose between two candidates on the basis of traditional face-to-face interviews. The results were grim: These well-trained future managers selected the higher-performing candidate a discouraging 56 percent of the time.

So in order to close the gap between seeming aptitude and actual performance, hiring managers are increasingly relying on real-world tests that simulate the actual job: Candidates are asked to complete certain challenges designed to weed out low-performing candidates.

In the publishing industry, for example, aspiring editorial assistants are asked to demonstrate their ability by editing a manuscript.

Another method companies use to address this gap is the acqui-hire: A company acquires a successful start-up and hires its founders and staffers. This approach is most commonly used by behemoth tech companies, like Google or Facebook, who are looking to hire top engineers and software designers.

And in the near future, improved computer reputation screening will also provide a way for companies to better evaluate future hires based on their past-performance data.

This approach resembles what football recruiters currently do to hire NFL players: An applicant’s resume or work history is broken down and analyzed in the same way that NFL recruiters evaluate college football careers on the basis of yards, tackles, receptions and other statistics.

In other words, using available data, computers will scan a list of applicants to find the ones with standout stats. Accordingly, the top performers will be the most valuable players of the employment world.

Although more and more people are going to college, employers have difficulty finding job applicants with relevant skills and training.

Why the discrepancy? Well, part of the reason students enroll in college is to signal to employers that they’re likely to be high performers.

However, mounting evidence shows that the traditional, one-size-fits-all four-year model of on-campus education is a poor fit for many students. Some students learn fast; others take longer to master the same material.

Additionally, college simply isn’t an effective way to gauge skills, which is why the Reputation Economy is poised to replace traditional signals with new signals that communicate actual learning more clearly.

This will completely change the way students and job applicants are evaluated. Companies will make decisions based on criteria that actually matter. And the central question will be whether this person will be a good employee in this particular job, at this particular company.

So what would an alternative system look like? Well, consider mathematician Sal Khan, who started uploading math lessons on YouTube in 2006. His audience quickly grew, so Khan quit his job as a hedge fund analyst to start his own company. His mission? To make the prestigious schools he attended obsolete, to replace a Harvard diploma with an education anyone could achieve anywhere.

Today, Khan Academy is one of the largest non-profit online schools, with videos on everything from biology to art to economics. This model differs from traditional education in many respects: There aren’t mandatory curriculums or semesters; students can advance as quickly as they like; and instead of hour-long lectures, lessons are delivered in short, fifteen-minute units.

As similar approaches become more common, it won’t matter whether students learn online, in the classroom or through an apprenticeship. If the learning is measurable and demonstrates the student’s ability to succeed in a particular job, they’ll be ready to step into today’s Reputation Economy.

Everything you do online today will be recorded, stored and analyzed to determine your reputation score, which will be updated instantly and used to predict your behavior. This will have huge consequences for your career, your business and every other area of your life.

Check out my related post: Can companies from different industries learn from one another?


Interesting reads:

https://hbr.org/2018/01/as-ai-meets-the-reputation-economy-were-all-being-silently-judged

https://www.goodreads.com/book/show/17262185-the-reputation-economy

 

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