Boolean Search Conquers Impossible Google Position

Posted at February 3, 2010

Google Gang Sign by Silona creative commonsWhen I run recruiter training classes, I often ask for the trainees to bring me example positions they are having trouble working on to use for live sourcing training.

During one such class (a little over 2 years ago), I had a recruiter bring me an opening for a challenging position at Google that had been open for a while. He had been working this position for a couple of weeks and had failed to produce a single candidate that Google was interested in interviewing. 

Many Had Already Tried and Failed…

As I asked him for a little background on the position, I found out it had been open for 4 months. 

That’s almost always a bad sign to a recruiter, as it had no doubt been thoroughly beaten up by countless other recruiters/vendors to Google. However, he assured me this was not a “black hole” requirement and that Google would indeed interview and hire candidates.

Now, the position this recruiter was working on was a network performance test engineer, which poses some unique searching challenges because most of the Boolean search strings that recruiters will employ will result in many false positives – resumes of candidates that contain all of the search terms, but who are not primarily responsible for the performance testing of networks. A simple game of “buzzword bingo” would not work for this position.

This was also independently verified by Google, as they commented that most of the candidates they were receiving were not appropriately qualified – most were QA/test engineers who had performance tested software and network applications, but not networks and network hardware specifically.

Give Me Four Hours to Chop Down a Tree…

When I first accepted the challenge of helping this recruiter, my initial searches did pull many false positives. However, after about 20 minutes of manipulating search strings and observing the corresponding changes in the results, I came up with a handful of Boolean queries that resulted in fewer false positives and a larger percentage of resumes of people who were primarily responsible for the performance testing of networks.

Once I gave these searches to the recruiter and he put them to use, in 2 weeks he called to let me know Google had already hired one of his candidates he had found using the Boolean search strings, and he had an interview request for another.

Where Did He Find the Candidates No One Else Could Find?

So where do you think he found these candidates that no one else had been able to find and submit to Google for the network performance testing positions?

Cold calling? Referral recruiting? Blogs? User groups? LinkedIn? Twitter? Facebook?

Nope – he found them on (drumroll please)…………..Monster.

Yes – this recruiter was able to use a resume database that presumably quite a few (if not all) other vendors to Google (and likely Google’s contract recruiters as well) had access to and most likely used to try and find candidates for these positions for several months.

Interestingly enough, the candidates this recruiter was able to find were not new candidates who just posted their resume – their resumes were over 3 months old, which tells me that they had been in Monster’s resume database ever since Google released their network performance testing positions.

I specifically point this out because I love to continuously disprove the commonly held belief that if many recruiters have access to the same resume database that they will be able to find the same candidates, the best candidates, and all of the appropriately qualified candidates.

Holding onto that belief is as foolish as thinking that if 10 people go fishing in the same lake, that they will all catch the same fish, as well as the biggest fish in the lake.

Job Board Resume Databases Do Have High Quality Talent

This is also a good example of how, contrary to popular belief, you actually CAN find extremely good candidates (Google is notoriously elitist, which I respect) on the job boards. I continue to see well-respected recruiting and staffing thought leaders comment on how the job boards have mostly “mediocre” and declining levels of talent.

This may be subjectively true, but certainly not objectively true. Besides, when’s the last time they ran a search and hired someone from a job board? Nothing bothers me more than people talking about something they have little-to-no direct experience with. 

All Boolean Search Strings “Work”

I am 100% positive MANY recuriters searched Monster in an attempt to find candidates for the network performance testing positions at Google. But there’s a funny thing about Talent Mining – you’re only aware of the candidates you actually find, and conversely, you are not aware of the candidates you didn’t find.

However, that does not mean the candidates you want and need aren’t in the database you’re searching. It just means you weren’t capable of finding them. When most recruiters search any particular database, including their own ATS or LinkedIn, and don’t find the people they’re looking for, they assume the candidates don’t exist.

But they’re there. Trust me.

The Power of Talent Mining with Boolean Search Strings

Here’s the search string that produced one of the candidates who was hired at Google:

Test* and (qa or quality) and (perl or tcl*) and (cisco or rout*) and (lab* or case* or plan* or script*) and (ixia or smartbit* or “smart bit”) and (L2* or LACP or STP or RSTP or VRRP or UDLD) and protocol* and (bgp* or eigrp or rip or ospf or mpls)

Interestingly, most of the search terms in the string above were not in the job description or required skills.

So it took me about 20 minutes of experimenting and refining search strings to come up with that search, from which a recruiter was able to make a hire from less than 10 phone calls on a position that had been worked for 4 months by countless other recruiters who had access to the exact same database.

How’s that for ROI?

That’s the power of effective e-talent discovery.

Hidden Talent Pools, Human Capital Data, Monster, Resume Sourcing, Sourcing and Recruiting, Talent Mining

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