Job Application Math

By Macrane on June 17, 2012

By the time we reach college age, it is no longer a secret that the numbers are often stacked against us in application situations.  Heavy competition comes not only from people better than us, but also from people with whom we stand shoulder to shoulder statistically.  This thorny bit of truth extends well past college applications into entry level jobs.

One of my duties as an intern at a small company this summer has been to sort through applications for a newly vacated position.  Generously titled “Operations and Communications Assistant,” my responsibilities range from answering phones and ordering paper clips to writing press releases.  After hours of scanning the hopefuls’ résumés and cover letters, I have found that the odds in the ever-challenging job search world are not in the applicant’s favor, even in the well-qualified.

Safe and secure in my internship, I can’t help but wonder at the applicants’ plight.  To date, we have received more than 180 applications for this position.  With such a large applicant pool, a stray factor like an aesthetically less appealing résumé or vaguely worded cover letter is a one-way ticket to the discard pile, if only to reduce the large number of qualified applicants.  After trawling through each application, scanning for keywords and evaluating experience, I assembled a pile of about 40 applicants who are excellently suited for the job.

That’s forty people who beautifully encapsulate the traits listed in the job description:  They are effective communicators, they have media experience, they have administrative experience, they write pretty.  But forty is thirty-nine more than will get the job.  Albeit, this is before interviews, salary negotiations, and the other stepping stones of the application process.  But the odds are still sufficiently stacked against the applicant that I decided to use a little simple math to model the situation.

Given that this is a probability model, a chance of 1 is a (mathematical, not actual) guarantee that a given person will be selected for the position.  If all of the applicants were equally qualified, then the odds of any one getting the job would be:

1/180 = chance

But applicants are not made equal.  Some kind of weight (w) must be assigned to each applicant to denote their experience and suitability.  So the chances of any one applicant become:

(1/180)w = chance

Let’s say that w can carry a value between 1 and 4, with a 4 being given to the most qualified applicants and a 1 to the least qualified.  That still leaves forty applicants with a chance of 4/180, or 1/45 in this imaginary mathematical scenario.

Taking this in another direction, how many jobs would one of these qualified people need to apply to in order to be mathematically guaranteed a spot?  Assuming in this mathematical scenario that each job and each pool of applicants was identical, the number n of positions one would have to apply for would be:

n * 4(1/180) = 1

Or, of course, n = 45.

None of this math holds water in the real world.  It is just an imaginary scenario which I think adequately illustrates the difficulties and frustrations of entry-level positions for which there are many, many qualified contenders.  This is true of the small company at which I work, and it is no doubt true at a much larger scale with companies like McDonalds, which last year received one million job applications (and accepted tens of thousands).  For the dozens of excellently qualified applicants whom my company will not end up hiring (and the 100+ less qualified applicants), persistence will be almost as important in their job search as experience.  It’s a dispiriting fact, but it’s in the numbers.

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