When you’re searching the Internet for potential candidates, it’s quite common (and practical) to search for resumes of  people who are likely to be local to your opportunity. The two main ways of doing this are searching by area code and searching by zip code range.

While there are limitations of both approaches (not everyone includes a phone number or address), in this post I want to explore an interesting phenomenon that was brought to my attention not too long ago which clearly demonstrates that even when people DO provide a phone number or address, you may not be able to find them by searching for that information.

Yes, you read that right.

Recently I had a recruiter in my network ask me why he could find a specific resume online using Google, but when he added the area code (which was clearly on the resume) to the search string – the search result disappeared.

When he sent me the screen shots, I investigated – and sure enough, he was right.

What I find especially interesting is the fact that he found the resume at all, because he wasn’t using any location criteria in his search to try and find local people. If his initial searches tried to target local people using an area code or zip code range, he would have never found the resume in the first place.

Moreover – he would never know of it’s existence.

Click on the image below to watch a short video clip of the Google resume search phenomenon:

Fascinating and Frightening

Seeing something like this makes me wonder how many people have resumes and other information online that are indexed by search engines, but are never found due to the search criteria used.

My instincts tell me there are many – but the insidious nature of searching is that all searches “work.” In other words – you get results from your searches, which gives you a false sense of security (and perhaps accomplishment), but you’re not aware of available results that your searches simply didn’t return. You can’t be.

In fact, it never occurs to most people to even wonder about available results they have access to, but are never retrieved.

However, just because you don’t find something – does that mean it doesn’t exist?

Why Does Google Fail to “Find” the Search Result?

I have my ideas as to why that specific resume cannot be found when adding the area code to the search, but I am curious to know your thoughts.

Multiple Search Engines

Of course, you should always employ difference search engines, as they don’t all index the exact same pages/sites. And even of they did index the same pages/sites, it doesn’t necessarily mean that they would return the exact same results for any particular search.

For example, while Google, Bing and Yahoo can find the same result without the area code, only Bing and Yahoo find the result that Google fails to return when adding the area code to the search string.

Beware!

I bring this example to your attention because you should always be aware of the fact that you may have access to people that you simply cannot find using certain search criteria, and it’s not limited only to location searching. Searching by skill, title, company, industry, etc., can be similarly affected.

It’s often simply impractical to NOT search with some location criteria – few people have the time to sort through and review results from all over the world that they cannot use. And location-focused searching doesn’t just apply to resume search, but also for any kind of searching in which you are trying to find people that live relatively close to where the opportunity you are sourcing/recruiting for is located.

Hopefully this post makes you think twice about your strategy and tactics to try and identify local people and helps you uncover previously “unfindable” results.

Are you attending or thinking about attending SourceCon 2010 in San Diego in March?

I am going to be the keynote speaker for the event, and I will be presenting on Artificial Intelligence vs. Human Cognition when it comes to sourcing and matching resumes.

If you’re curious to know what kinds of things I’ll be addressing during the session, here is a sneak peek:

1. The intrinsic and often overlooked challenges associated with sourcing resumes
2. What artificially intelligent semantic search and match applications claim to do and how they actually work
3. The limits of artificial intelligence
4. What people can do that semantic search applications cannot
5. The 5 levels of semantic search
6. The 5 levels of secondary/e-sourcing
7. What I believe would be the ideal candidate sourcing/talent identification solution

If you’ve ever wondered about the fantastic claims that some of the semantic search application vendors on the market make as to how their solution can mimic a senior recruiter when finding candidates, then you will be very interested in hearing what I have to say about the reality of what they can do.

If you’re a sourcer and you’re concerned that your role/position might eventually be replaced by sourcing software, you will be encouraged by my analysis and supporting arguments that explain why the abilities of creative and investigative sourcers will always be in demand – tomorrow and 50 years from now.

I hope you will be able to attend SourceCon 2010 – I know I’m looking forward to it!

If you’re unable to attend, the good news is that the presentations will likely be streamed. Additionally, I plan on posting my expanded slide deck, including all talking points – so you won’t be stuck staring at some pretty pictures wondering what the heck I talked about.

When 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.

Many individuals and organizations treat the sourcing role and function of recruiting – searching for and identifying potential candidates – as an entry level position, and/or a simple and basic task that does not require much skill or experience. 

I agree.

I believe that it does not take much skill or experience to simply transcribe job titles and required skill keywords into LinkedIn, Monster, or an ATS and click “search.”

However, that oversimplified view of sourcing talent only describes the most basic level of talent identification, of which, I believe there are at least two.

Level 1 Sourcing

Level 1 Sourcing involves little more than taking titles and words from job descriptions and entering them into Internet search engines, social networks, job board resume databases, and applicant tracking systems to search for candidates.   

This is the proverbial “buzzword bingo,” and does not necessarily involve any real understanding (beyond surface level) of the roles, skills, responsibilities, or technologies involved in the hiring profiles or the candidates. These basic search terms produce search results that are then cursorily reviewed for keyword matching. 

Level 1 Sourcing involves a level of matching potential candidates to hiring profiles that is often superficial and generic – very little, if any, interpretive analysis is performed. This level of sourcing can in fact quite easily be performed by “junior” personnel/researchers – almost anyone can match keywords.

Not only can Level 1 Sourcing be performed by junior associates, it can (and often is) outsourced for $5 – $7 an hour.

However, don’t be fooled into thinking you are getting something fantastic for that $5 – $7 an hour – you’re getting exactly what you’ve paid for. Which is Level 1 Sourcing.

In my opinion, there is no need to outsource Level 1 Sourcing, because it does not require any deep understanding of the roles being sourced for, nor does it involve any true analysis or creativity. As such, Level 1 Sourcing is well suited for total automation. Why pay people to match keywords when matching applications can do it for you for considerably less than $5 per hour?

Many people are blissfully unaware of the fact that Level 1 Sourcers from any company will essentially find the same potential candidates as any other Level 1 Sourcer. It’s a simple equation: same keywords = same results. This is one of the reasons why Level 1 Sourcing provides no competitive advantage. 

Additionally, while Level 1 Sourcers can and will find SOME candidates, they will not and can not find ALL potentially qualified candidates available to them in the sources they are searching - that would be impossible, for many reasons that I’ve written about previously that are beyond the scope of this post. 

And finally, Level 1 Sourcers are typically unaware of the people that are in the ATS, job board resume database, or social network that they are searching that their queries did not return. In fact, to them, anyone that they don’t find simply doesn’t exist. 

Level 2 Sourcing

This is the good stuff. Level 2 Sourcing moves well beyond simple keyword matching and most certainly beyond a basic mastery of Boolean logic. 

Boolean logic is easy to learn – after all, there’s only 3 main operators! However, the “magic” of leveraging databases and information systems for talent identification does not lie in the Boolean search operators themselves, but in the following process: 

1. Analyzing, understanding, and interpreting job opening/position requirements - including elements which may or may not be explicitly mentioned in the position description or BQ’s
2. Taking that understanding and intelligently and creatively selecting titles, skills, technologies, companies, responsibilities, terms, etc., to include (or to purposefully exclude!) in a query employing appropriate Boolean operators and query modifiers
3. Analyzing the results of the initial search to assess relevance as well as scanning the results for additional and alternate relevant search terms, phrases, and companies 
4. Based upon the observed relevance of and intel gained from the search results, modifying the search string appropriately and running it again
5. Repeating steps 3 and 4 until an acceptably large volume of highly relevant results is achieved   

The “real” work of creating effective Boolean search strings lies in the interpretive analysis of the need, in determining what terms to include and exclude from searches and in what specific combination, in the analysis of the relevance of the initial search results, and in the adaptive process of learning from the results to creatively refine the Boolean search strings to find well qualified candidates – people who are highly likely to be (or know!) the right match for any particular hiring need. 

Unlike Level 1 Sourcing, Level 2 Sourcing involves and in fact requires a deeper understanding of the roles, skills, responsibilities, and technologies involved in the hiring profiles being sourced for. In this regard, Level 2 Sourcing goes well beyond explicit keyword matching and deep into implied experience and capability matching.

In addition to finding all of the candidates that Level 1 Sourcers can find, Level 2 Sourcers can also find the candidates that Level 1 Sourcers have access to, but can not and do not find. Interestingly, all Level 2 Sourcers will not find all of the same candidates, specifically due to their varying experience and creative and analytical ability.

And unlike Level 1 Sourcers, Level 2 Sourcers are acutely aware of the candidates they have not found, because they understand that every Boolean string and search strategy will find some candidates, and exclude others.

Level 2 Sourcing is Not a Junior Role and Cannot Be Automated

It is precisely because of the aforementioned reasons that Level 2 Sourcing cannot be performed by  junior level associates – it is not an entry level role, nor can it be outsourced for $5 – $7 an hour. Okay, it CAN be outsourced at those rates, but you won’t get Level 2 results. Remember, you get what you pay for.

Level 2 sourcing cannot be automated, regardless of what the vendor representatives of “artificial intelligence” resume parse/match applications may claim. This is because Level 2 sourcing requires “a posteriori” knowledge – which comes from experience, which comprises knowledge and skill gained through involvement and exposure. 

Applications do not accumulate experience or gain knowledge or skill, in the true sense of the terms.

AI matching applications essentially perform a form of pattern recognition to classify data through parsing resumes and employing a keyword/phrase taxonomy, which is built based on “a priori” knowledge/information extracted from the patterns and programmed into the matching logic. 

I recently spoke at the PDS Technology Conference and had the honor of seeing Dr. Michio Kaku present on the world of 2020 and beyond. Dr. Kaku believes that “Progress in artificial intelligence may come to a gradual halt around 2020. The two problems facing AI are pattern recognition and common sense.” 

I was happy to hear that Dr. Michio Kaku believes that the employment market of the future will be “dominated by jobs involving common sense (e.g. leadership, judgment, entertainment, art, analysis, creativity) and pattern recognition (e.g. vision and non-repetitive jobs).  Jobs like brokers, tellers, agents, low level accountants and jobs involving inventory and repetition will be eliminated.”

That’s great news for anyone performing Level 2 Sourcing, primarily because it requires creativity, interpretive analysis, judgment, and common sense (a natural understanding based upon experience) - four things that machines and applications are intrinsically incapable of.

Unlike AI matching applications, Level 2 Sourcers intrinsically understand that resumes and social media profiles are imperfect and incomplete representations of the people who created them, and that they often do not explicitly mention all of their skills and experience. As such, Level 2 Sourcers are not only able to find qualified candidates based on the words they use - many can also specifically search for and find people who have experience that they do not mention. In other words, some Level 2 Sourcers can find people based on what they don’t say. This is a skill that can only be developed over time from observation and experience.  

Final Thoughts

Level 1 Sourcing can be performed by entry level associates or be completely automated, as the level of matching produced is superficial and based primarily on explicit keyword and phrase matching. This can be quite sufficient for static and repetitive hiring needs for simple hiring profiles, where title searches will often suffice.

The value and the results provided by Level 1 and Level 2 Sourcing is vastly different - this is why some organizations see the sourcing function as a low level or junior role, simply outsource it for $5 – $7 and hour, or completely automate it. Interestingly, there are sourcers who make $50 to over $100 an hour, and they are worth every penny for the competitive advantage  and value they provide to the organizations they support.

Dr. Michio Kaku would classify Level 1 Sourcing as ”commodity based capital,” in that it is a product that is the same no matter who produces it - man, woman, or machine.

People who perform Level 2 Sourcing are true knowledge workers, whose value is intellectual capital – based in creativity, judgment, analysis, ”common sense” and “a posteriori” knowledge developed over time based upon experience – similar to senior Financial Analysts, Business Analysts, Data Analysts and Business Intelligence Analysts. Level 2 Sourcers produce a product that is quite different based on who produces it, and it cannot be reliably replicated by machines.

To be sure, one could easily break Level 2 Sourcing out to at least 3 different levels, because to lump everything more advanced and sophisticated than Level 1 Sourcing into one broad category is horribly limiting, but for the purposes of this article, it shall suffice.

Human Capital Data data is the sword of the 21st century – those who wield it well are the Sourcing Samurai.

In response to my recent post about the deficiencies in the search capability of many Applicant Tracking Systems, a few people commented to the fact that resumes stored in applicant tracking systems become stale and outdated over time, which may explain why ATS resume databases are often the candidate “source of last resort.”

While candidate records inevitably age over time and can become outdated, this definitely does not have to be the case.

A candidate record can only truly go “stale” if no one ever makes contact and updates the record with more current information from time to time – and it need not even be every 6 months.

Any recruiter worth their salt will attempt to maintain periodic contact with most candidates and update their information as appropriate, regardless of their job search status. This can also be automated to some extent with strong and effective CRM functionality – so even if the recruiter forgets to follow up with someone every 6 months, the CRM won’t.

Resumes Are Like Wine

While human capital data in the form of resumes and candidate profiles may get outdated, it never truly loses its value. Resumes and candidate records are like fine wine – they only get better with age.

Yes, I believe the value of human capital data actually increases over time.

If I find a resume of a 2 year Unix systems administrator today and permanently capture them into my ATS, over time that person will gain experience and expertise, and likely advance their career along the way. In 5 years I will have a 7 year Unix admin, a Unix systems engineer, perhaps a project manager or even a storage area network specialist – who knows? No matter their career path and progression, I will stay in touch with them and routinely update their information - regardless of their job search status.

The same is true of nearly every profession – accountants, attorneys, physicians, customer service reps, mechanical engineers, recent college grads, etc. – they will all gain experience and advance their careers over time. 

Limited Shelf Life

Did you know that some people who post their resume in online resume databases (job boards and such) sometimes pull their resume down shortly after they post it, rendering it unfindable? Sometimes in a matter of hours!

Social networking sites such as LinkedIn and Twitter can also suffer from a similar effect. Because they are based on UGC (User Generated Content), at any time any user can make their profile private and unsearchable (even via X-Ray searching in some cases!), or simply remove content that may aid you in searching for/identifying them based on their professional skills and experience.

However, if you’re always on the lookout for certain types of professionals, scouring every source available to you, and you permanently capture the information you find into your ATS/CRM, you may essentially be collecting rare vintages (yes, I’m going to continue with the wine analogy) that may no longer be in circulation in the near future. 

In other words, when you find and capture that resume or profile of the 2 year Unix admin (or accountant, or attorney, or recent grad, etc.) who pulls their resume or alters their social networking profile at some point in the future – you may have in your possession a candidate that may never be found by anyone else again.

This would allow you to specifically search for that particular candidate and reach out to them in a year or two’s time – when they are passively looking or not looking at all – and present them with a position that is well aligned with the next step in their career. At this point, you may literally be one of the few people who have quick and easy access to that candidate as their career progresses, regardless of their job search status.

ATS Databases are 70% Passive/Not Looking by Volume

I believe that a well stocked ATS candidate database is likely to consist of mostly (approximately 70%) candidates who are not looking or who are passively looking. That percentage is probably even higher when you consider only candidate records that have been entered/created over 3 months ago. So, if you’re one of those recruiting professionals who believe the hype that active candidates are bad and passive candidates are good, you should be excited about the prospect of building a private “passive” candidate database that you can mine to your heart’s content.

While I am most decidedly NOT one of those people who buys into the idea that passive candidates are the “best” candidates, I can tell you from experience that candidate closing and control is almost a non-issue when you are dealing primarily with people who are not actively looking, are not being called by every other recruiter in the known universe, and don’t have 5 interviews scheduled this week and 2 offers in hand.

So it IS nice to be able to purposefully target and dip into a large pool of well qualified candidates, who are not actively looking, and many of whom no one else has quick and easy access to. 

It’s not just nice; it’s also a significant competitive advantage.

Let Your Candidate Data Age Naturally

If you have a relatively large candidate database (10,000 to 1,000,000+), you needn’t worry about trying to maintain “relationships” with all of them – it’s actually impossible, unless your definition of “relationship” includes automated emails.

If you’re overly concerned with having ultra-fresh information on all of the candidates in your system at all times - don’t be. It isn’t really necessary.

I’ve called and made easy, frictionless hires with candidates who had records/resumes that had not been updated in 4 years. A seasoned sourcer or recruiter can easily make an educated guess at “career trajectory,” and when you make a call to someone whose resume is not on the Internet, not on LinkedIn, not in an online resume database – you essentially have a candidate no one else has practical, targeted access to – and closing/control is a non-issue when you call with the right opportunity, by design.

Final Thoughts

If you permanently capture data on your target professionals relatively early in their careers, you can cultivate their candidate records as their careers progress, allowing you quick and easy access to them as they evolve into more experienced passive or even non-job seekers – the virtually “ungettable” candidates that your competitors wish they had access to.  

If this approach to valuing and leveraging your candidate data doesn’t appeal to you, and you happen to be growing tired of having to store all of those old, stale resumes in your ATS/CRM – give me a ring – I’d be glad to take them off your hands.

Posting jobs in an attempt to attract qualified talent has many intrinsic flaws, and I feel that the 2 most significant limitations inherently involved with posting jobs  is that:

1. Job posting is a passive strategy that affords no control over candidate qualifications
2. Job ads only attract candidates who are actively looking

In comparison, proactively searching for qualified candidates is an active strategy which offers significant control over candidate qualifications and can be used to specifically target passive and non-job seekers.

In this post I will compare and contrast job posting and candidate search as means of identifying talent, and I hope to open your eyes to a new way of looking at the value/ROI of posting jobs.

Job Posting is a Passive Strategy

One of my favorite analogies for job posting is that it is just like setting a trap. The strategy is to set a trap in a place where you think your quarry might come across it and be ensnared.  This is very much a passive, hope-based strategy, and hope is actually not a strategy.

Job Posting Offers No Control Over Candidate Qualifications

If you are trying to snare a rabbit, you could just as easily end up snaring a raccoon, a skunk, an opossum – or basically any small indigenous animal that wanders by.

This is the same with job posting. If you post a job for a windows system engineer with a minimum of 5 years of experience, MCSE certification, and web hosting industry experience - literally ANYONE can respond, whether they have the appropriate experience, certification, or industry experience or not. As a passive strategy, you simply cannot control who responds – unqualified, underqualified, overqualified, out of area, etc.

This isn’t just my experience and opinion. A recent Atlanta Business Chronicle article cited a study of 501 hiring managers by Robert Half and CareerBuilder, which found that 44 percent of resumes presented to hiring managers are submitted by unqualified applicants. Additionally, the 2009 EDGE Report also found that 47 percent of hiring managers cited under-qualified applicants as their most common hiring challenge. 

Job Posting Attracts Active Job Seekers Only

Not only can you not control who responds to your job posting, the only people who are going to get “snared” by the trap you’ve set are people who are actively looking for a job.

According to data from the Bureau of Labor and Statistics, here is the breakdown of job seeker status:

• 32% passively looking
• 34% not looking
• 20% casually looking
• 14% actively looking

Now, unlike many people, I don’t think there is anything intrinsically wrong with active job seekers – they are not all desperate, unemployable people (can you believe people in the recruiting industry actually believe that?). However, the real issue at hand is that with job posting, you are essentially missing the other 86% of the workforce.

That means that when you post a job for an opening you need to fill in the next 2 weeks, you are realistically only tapping into 14% of the available workforce.  On top of that, many people who respond will not actually be qualified for the position.

That’s an issue!

One could argue that some of the people who are “casually looking” might stumble across your ad, but even if all of them did (which is highly unlikely), you are still missing 66% of the available workforce.

Your Ads and Postings are Invisible to Most People

Truly “passive” job seekers and certainly those who are not looking at all don’t even SEE ads for jobs right in front of their face, no matter how “targeted” and well placed your ads are.  Additionally, the reality is that most people tune out ads of any kind – on the Internet, on TV, billboards, etc.

When’s the last time you clicked on an ad or bought something/took action specifically because of a commercial or billboard you saw?

Even for those people who do “see” or “tune in” your ad/job posting – the reality is that most will not take action. Changing a job is a BIG deal – most casual, passive, and practically all inactive job seekers will not likely be inspired to take action and explore leaving their current position because they saw an online job ad. 

SEO Is Not Enough

I agree 100% with Marvin Smith that SEO is not enough. How could it be anyway? For SEO to work, you have to have someone searching for jobs and/or information about your company, and as we’ve already seen, that is going to be the active job seekers and perhaps some of the casual job seekers – which is only a small sample of the available talent, the clear minority.

Resume Search is an Active Strategy

Unlike job posting, which is a passive method of attracting talent (I would argue that it’s not even a method of identifying talent), searching for candidates in Applicant Tracking Systems, recruiting CRM’s, job board resume databases, and LinkedIn is an active method of talent identification. 

Instead of setting a trap and waiting for the right person to stumble across it (aka, “post and pray”), when you create and execute searches to find candidates, you are actively “hunting” for talent – targeting people with specific qualifications and experience, who live in specific areas – regardless of their job search status. 

Resume Search Affords Significant Control

When it comes to searching for candidates, I’m focusing specifically on resume search, because searching for resumes offers significant intrinsic advantages over non-resume candidate searches. Resumes (including complete LinkedIn profiles) are “deep” sources of data which enable sourcers and recruiters with a high degree of control over critical candidate variables, including skills/experience, industry, location, education, and to a lesser but still significant extent, desired opportunity and compensation. 

Sourcers and recruiters who are adept at leveraging deep human capital data (resumes and detailed social network profiles) create queries that control critical candidate qualification variables, allowing them to quickly identify people with highly specific experience, who live in specific locations who are likely to be interested in the role and compensation offered by the position the recruiter is working on. 

Resume Search Can Target Passive and Non Job Seekers

Unlike job posting and SEO which require some action on the part of candidates (actively looking at ads or running keyword searches) and are quite literally invisible to those who are not taking any action to look for a new job (the majority of all people), when you actively search for candidates, you can target people who are not actively looking.

How can you search for resumes of passive and non job seekers? Quite easily. 

Ready for a paradigm shift?

If someone responds to a job posting you posted recently and they enter their information into your ATS/recruiting CRM – they are most likely actively seeking a new job, although there is a chance you could also be collecting a casual job seeker.

Statistically, many people who respond to job postings are not actually qualified for the position they applied for. If they are not a match for any current openings, it is likely they will find a position with another company with a position they are actually qualified for.

But you still have their resume in your ATS.

Alternatively, their resume may still be posted in an online resume database somewhere (many people either don’t or forget to take them down after they take a new job). In fact, my own research has shown that approximately 75% of all resumes on the job boards are over 30 days old. So if you think that all of the resumes stored in online resume databases are of active job seekers, you are quite wrong. Statistically, the majority are likely to be not looking or passively looking. 

In about 3 months to 2 years’ time, those active job seekers turn into people who are likely to either to be not looking at all for a new position, or who may be satisfied with the new position they took, but open to better opportunities (passively looking).

Unlike job posting, when you are searching for resumes, you can actually specifically target people who are not likely to be actively looking.

An Alternative View of Job Posting

While most people see the primary value of job posting as a method of trying to attract the right person at the right time – I see it quite differently. 

If I post a job, I am not expecting results – experience and statistics show that most people who respond are not qualified for the position. Certainly, there have been times when the right person has responded to a job posting at the right time, but as an intrinsically passive strategy with no ”built-in” ability to control the experience and qualification of respondents, to rely on job posting would be folly. After posting a position, I will not wait and hope that the right people find my position. I am going to take control of the process and go out and actually FIND the right people.

So if the main value of posting jobs isn’t finding the right person at the right time, what could it be?

Another way to look at the value of job posting is that it can essentially become a method of cultivating your ATS/CRM into a wine cellar of sorts. All of those active job seekers who respond to your ads but who are not qualified (or simply not selected) for the specific position they applied to today may in fact be well qualified for other positions you have in the future. 

Active candidates who enter your ATS/CRM today (or post their resume online) become tomorrow’s casual, passive, and non-job seekers.
   

ATS Search Capability is Critical

In order to capitalize on your database of casual, passive, and non-job seekers – you need to have an appropriately capable candidate search interface coupled with the ability to run precise queries, enabling you to quickly target and access candidates of ANY job search status.

An ATS with poor/limited candidate search capability is like having a well stocked wine cellar that you can’t access because you don’t have the key to the door.  Or even if you had the key – you had no way of finding the exact bottle you were looking for.

Final Thoughts

Job posting is part of a balanced “diet” of recruiting methods, and it can produce results. I would never recommend to NOT post jobs – that would be ridiculous. However, if posting jobs is your primary method of trying to find the right candidates at the right time, I believe you are at a competitive disadvantage.

I would argue that the value of posting jobs does not primarily lie in the ability to find and attract the right candidate at the right time.  Job posting is essentially like trapping: set the snare and wait for the right person to stumble by - it is an inherently passive strategy with no control over what wanders in. Additionally, the only people who will search for or even “see” ads for jobs are those who are actively or casually looking.

I believe the less obvious but true value of job posting lies primarily in the collection of active candidates and the ability to cultivate them over time into more experienced/qualified candidates who will inevitably become passive/inactive job seekers.

Human capital data stored within your ATS/CRM increases in value over time, but it’s actually of NO value unless you have the ability and skill to retrieve and leverage that data.

It’s been a long time coming, but I have finally gotten around to creating a resources page that essentially contains a “best of” compilation of Boolean Black Belt articles. It contains 10 “How-To” posts ranging from how to search Linkedin, Twitter, Facebook, and Google for candidates, as well as articles on semantic search, Boolean, extended Boolean, and the top 15 common e-sourcing mistakes.

Here’s where to find it:

Enjoy!

In recent posts I’ve explained the Boolean Black Belt concept and exposed what I feel is the real “secret” behind learning how to master the art and science of leveraging information systems for talent identification and acquisition.

Now I would like to show you precisely WHY Boolean search is such a big deal in recruiting. There are 2 main factors: #1 candidate variable control and #2 speed of qualified candidate identification.

The goal of this article is to shed significant light on the science behind talent mining, how it can lead to higher productivity levels (more and better results with less effort), why I am so passionate about e-sourcing/e-recruiting, and why everyone in the HR, recruiting, and staffing industry should be as well.

Control is Power

Talent identification is arguably the most critical step in recruiting life cycle – you can’t acquire and hire someone you haven’t found and identified in the first place.

My experience has shown me that properly leveraging deep sources of talent/candidate data (ATS/CRM’s, resume databases, LinkedIn, etc.) can enable recruiters to more quickly identify a high volume of well matched and qualified candidates than ANY OTHER METHOD of candidate identification and acquisition (e.g., cold calling, referral recruiting, job posting).

The true power of Boolean search lies in the intrinsically high degree of control over critical candidate variables that using Boolean strings to search deep data sources such as resume databases, the Internet, and social media affords sourcers and recruiters. Applying that that high degree of control to large populations of candidates – tens of thousands (small internal ATS, niche resume database) to tens of millions (large ATS/CRM, Monster resume database, LinkedIn, etc.) enables adept e-sourcers/e-recruiters to perform feats of talent identification and acquisition most would think impossible.

Candidate Variables Defined

The match between a candidate and a specific job opening can be expressed as a combination of these 5 basic variables: Location, Skills (Experience/Education), Opportunity, Compensation, and Availability. There are certainly other factors at play when it comes to determining the right match between a candidate and a particular opportunity (e.g., cultural fit). However, these are the “big bucket” variables which render the rest pointless if they are not satisfied.

Control What You Can

Ultimately, the best match between an employer’s hiring need and a candidate is one where there is very close alignment between a candidate’s variables and those of the particular job opportunity.

Most job openings have a fixed set of variables – sourcers and recruiters don’t often have the opportunity to control or change the location of the position, the skills/experience/education required, the specific opportunity (the type of work involved in the position, the company/team culture, opportunities for growth/advancement, etc.), the compensation associated with the position, and when the position becomes available (open and ready to hire).

However, when it comes to searching deep sources of human capital data that support Boolean queries (such as your ATS/CRM, online resume databases, LinkedIn, etc.) to identify potential candidates for any particular job opening, sourcers and recruiters CAN exercise a significant degree of control over critical candidate matching variables.

Here’s a preview:

Controlling Candidate Variables Through Boolean Search

Location

When it comes to using resume databases (internal or online), sourcers and recruiters have nearly complete control over the location of the candidates identified – finding people in specific zip code ranges or by using a combination of area code and address search. A small percentage of the time, candidates with resumes not updated in the past 6-12 months may have moved from the address on their resume, but this is a fractional minority. Although using Boolean search strings to identify candidates in resume databases or online affords specific control over the location of candidates identified, there is less direct control over the commute tolerance/preference of the candidates – that can only be reliably determined by contacting each candidate. However, sourcers and recruiters can target people who live very close to the location of the job opportunity (5-15 miles), increasing the likelihood of solving the commute variable.

Skills/Experience/Education

Sourcers and recruiters can run Boolean strings when searching resume databases to precisely target specific experience, years of experience, education, certifications, environment/project, and industry experience. Those who are particularly adept at Boolean search can even achieve semantic search by crafting Boolean strings that go well beyond buzzword matching and target specific responsibilities, or in other words, what the candidates have actually done as well as what they have done it with. Although resumes are far from a perfect medium for accurately or wholly representing skills, experience, and capability, a well stocked resume database affords sourcers and recruiters the ability to run Boolean queries to quickly find candidates with highly specific experience closely matching the required skills and experience of the position being recruited for.

Desired Opportunity

Although sourcers and recruiters using Boolean search strings to mine talent from resume databases cannot precisely predict what candidates will want to do in their next career move, a resume or very detailed social media profile often affords significant insight into a possible “career trajectory.” In other words, a project manager over software development is likely to be interested in a similar role, or one that is a slight step up in responsibility. Similarly, a 3 year staff accountant is likely to be interested in a role as a staff accountant, or perhaps the next step up. Adept sourcers and recruiters can run Boolean strings to specifically target candidates who have experience similar to the work to be performed in the role being recruited for, increasing (but certainly not wholly controlling) the chances that candidates identified would be interested in the type of position they are recruiting for.

Compensation

As with the opportunity variable, sourcers and recruiters cannot precisely control the compensation requirements of candidates identified. However, resumes do enable recruiters to predict, to some extent, the desired compensation of candidates based on years of experience and market knowledge, and sourcers and recruiters can run Boolean search strings to target candidates with specific years of experience.

For example, in a given metro area, recruiters are likely to know what staff accountants with 3-5 years of experience (or software engineers with 3-5 years of Java programming, etc.) are being paid by most local employers, and from experience, what those types of candidates are looking for in terms of compensation when making a career move. Although this is certainly not precise control, it does allow some degree of control. Also, when reviewing resumes in a database, recruiters can make the educated decision not to call candidates with 10-12 years of accounting or Java programming (unless they want to ask for referrals), and specifically target and contact candidates with 3-5 years of experience instead.

Availability

When searching databases and online sources of candidates, there is no way to reliably predict or control whether or not people identified via Boolean search strings are available or open to make a career move at the time they are identified. However, when using online job board resume databases, searching for candidates with resumes posted within the past 30 days does increase the probability that the candidates identified are looking (actively or passively) to make a career move.

In Comparison: Cold Calling and Referral Recruiting

While cold calling and referral recruiting are tried and true methods of identifying talent, and I would never suggest that they be avoided – I’d like to expose the intrinsic ROI limitations they afford sourcers and recruiters, primarily the inability to control critical candidate variables.

Location

When it comes to cold calling into companies to source and identify potential candidates, there is very little control over where the candidates live. When calling into a company, you know where the candidates work, but the candidates could live anywhere within a 20, 30, 40, or even larger mile radius from that company location – in ANY direction. Because there is no way to know exactly where the people you are calling live prior to sourcing them, there is no way to significantly control the Location variable of the potential candidates, and each person identified will likely have a different commute tolerance/preference which is based specifically on where they currently live, not where they currently work.

As for referral recruiting, when we ask other people who they would recommend – we can neither control where the potential referred candidates work nor where they live, so there is even less location-specific control offered by referral recruiting over cold calling.

Opportunity

When cold calling into companies or referral recruiting to identify candidates, there is no way to predict or control what each person identified will be most interested in doing in their next career move.

Compensation

When cold calling into companies or referral recruiting to identify candidates, there is no way to control or predict what each person’s current compensation is, nor is there any way to predict their desired compensation. Even sourcing by title will not accurately or consistently predict the years of experience and specific responsibilities of each person identified prior to contacting them.

Experience/Capability

When cold calling into companies or seeking referrals in an effort to identify potential candidates, there is no way to predict or control each person’s capability to perform the responsibilities of the position being sourced for. Although you could ask for someone if they can recommend/refer to you a person with a specific title or experience, you simply can’t control actual experience of the people referred or identified, nor is there any way to control their career history, years of experience, education, or certifications.

The one aspect of experience/capability that can be controlled through cold calling is industry-related experience – if you call into a pharmaceutical company, you can be assured that everyone you identify has experience working in the pharmaceutical industry. However, the same cannot be said for referral recruiting, as there is no reliable way to control the specific industry of the people who are offered as referrals. Either the people you are seeking referrals from know of someone with the appropriate skills and experience and will recommend them to you or not. In either case, you are not the one in control – you are completely dependent upon each person you attempt to network with. 

Availability

There is no way to reliably predict or control whether or not people identified via cold calling and referral recruiting are available or open to make a career move at the time they are identified. Although you could ask people if they can recommend people who might be looking, whether or not they actually do know people who might be looking to make a change is not under your control, and the specific availability status of any referred candidate cannot be predicted or determined prior to actually speaking with the candidate.

Job Posting

For sourcers and recruiters – posting a job affords absolutely no control over critical candidate variables, as you are 100% at the mercy of other people finding and responding to the posting. Anyone with any experience in the HR/Recruiting/Staffing industry knows that very few people who apply to positions are well matched across the 5 critical candidate variables with regard to the position they apply for. When you post a job online, you simply cannot control who will respond, what their skills/experience/education will be, or even where they live.

While not truly representative of any degree of control, when people respond to a job posting – it is often because they are actively (or perhaps passively, depending on your definition) looking for a change of employment from their current employer or their unemployed status. After all – if someone is looking at job postings, they’re considering their options to a lesser or greater extent. So if your sourcing and recruiting strategy targets active candidates, this is the only bright spot when it comes to using job postings to identify potential candidates. However, just because someone responds to your job posting – it does not necessarily indicate that they are truly and unconditionally available to make a change. 

Candidate Variable Control: Comparison of Sourcing Methods

In review, let’s take another look at the comparison of Boolean search vs. cold calling, referral recruiting, and job posting as with regard to the degree of control over critical candidate matching variables for talent identification:

Using Boolean search strings to identify and mine talent from private and online sources of talent empowers recruiters with the ability to apply a significant degree of control over the location, skills, experience, education, opportunity, and compensation candidate variables – more than any other method of talent identification. 

Speed of Qualified Candidate Identification

The second piece of the puzzle that explains why Boolean search strings coupled with deep sources of candidate data (resumes and detailed social media profiles) is so powerful is the speed at which candidates who closely match the critical variables of a given position can be identified. 

E-Sourcing vis Boolean Search

Sourcers and recruiters who are competent at crafting Boolean search strings can find quickly find a large volume of candidates that are likely to closely match the 5 critical variables of the position they are seeking to fill. I’ve personally achieved, as well as trained other recruiters to achieve, anywhere from 20-60 well matched candidates identified per hour mining talent with Boolean search strings (20/hour for a very challenging position to 60/hour for positions/skills that are more common).

I’m talking about finding 20-60 people in 1 hour who have the skills, experience and education required for the position I’m recruiting for, live in a commutable radius for the location of the position, are highly likely to be attracted to the opportunity, and who are highly likely to be within the compensation range of the position. The only thing left to do is establish contact and a relationship with them, and attempt to solve the final variable – availability (whether they would accept an offer for the position if they interviewed well and felt it was a strong match).

Cold Calling/Referral Recruiting

While cold calling into companies can produce results, it is a slow and laborious process. Cold calling into companies can in some cases quickly yield a high volume of names, but the intrinsically low degree of control over critical candidate variables that cold calling affords sourcers and recruiters severely limits the speed of identifying candidates who closely match the position being recruited for. 

Referral recruiting, for many reasons can in produce some of the best candidates – most companies are proud to brag about the large percentage of referral hires they make. However, referral recruiting is also a slow and unpredictable process – not every person contacted will yield a referral, and even those that do are not statistically likely to closely match all 5 of the critical candidate variables. 

Job Posting

When it comes to posting jobs to identify potential candidates, it’s similar to setting a trap. It’s a 100% passive strategy - the only thing you are in control of is setting the trap. You cannot control what, if anything, actually wanders into your trap, or if anything ever does.

It’s the same with posting jobs – some jobs never get any responses. Others do get a large influx of candidate responses, but the probablity that any given person is a close match across the 5 critical candidate variables is intrinsically low.

Speed of Qualified Candidate Identification: Comparison of Sourcing Methods

Conclusion

I hope you now have a much deeper appreciation of the “method to the madness” behind leveraging Boolean search strings for sourcing and recruiting and understand why Boolean search is such a big deal in recruiting. There are tangible reasons why using Boolean strings to search private and online repositories of candidates can enable sourcers and recruiters to identify and recruit more well qualified candidates at a faster rate and a higher volume than any other method of candidate identification. Quality X Quantity X Quickness = Results.

Although cold calling and referral recruiting are proven and viable methods of candidate identification (and I would never recommend not performing them), there is no denying that they do not offer sourcers and recruiters a much (or any, in some cases!) control over critical candidate matching variables. They are also intrinsically slow methods of identifying precisely matched and qualified candidates.

Undeniably, talent mining via Boolean search strings affords sourcers and recruiters the ability to exert a high degree of direct control over the specific location of candidates, the skills, experience, and education of candidates, as well as the ability to specifically target candidates who are highly likely to be interested in the opportunity being recruited for, and the compensation offered by the opportunity.

Imagine being able to find a minimum of 20 people in less that 1 hour of research who have the skills, experience and education required for the position you’re recruiting for, live in a commutable radius for the location of the position, are highly likely to be attracted to the opportunity, and who are highly likely to be within the compensation range of the position. The only thing left to do is “smile and dial!” If this sounds crazy or impossible – trust me – there are people who can do this day in and day out.

LinkedIn, the Internet, job board resume databases, and most corporate ATS/CRM databases are huge repositories of candidates – many companies have hundreds of thousands to several million resumes stored in their internal resume database. The major online job boards all have 20M+ resumes each, and often have over 100,000 resumes in each major metro area. LinkedIn has over 40M profiles worldwide, and 20M in the U.S. alone.

Large databases afford sourcers and recruiters to benefit from the laws of statisitcs with regard to large sample sizes. If a recruiter or sourcer were looking to hire for a rare skillset or combination of skills and experience that represented only 1/2 of 1% of the available candidates, and they had access to a resume database of 100,000 local candidates – 1/2 of 1% of 100,000 is 500 people. Eye opening, isn’t it? If you ever find yourself thinking you’re working on an impossible position, always remember the candidates you’re looking for actually DO exist, in more numbers than you would perhaps like to believe. You just need to figure out how to find them!

E-sourcing/e-recruiting via Boolean search strings has the distinct advantages of speed, volume, and controlled accuracy of match across multiple and critical candidate variables which can enable recruiters to perform Just-In-Time delivery of well qualified candidates with less effort. The speed and match precision of searching for candidates with Boolean search strings effectively allows recruiters to produce more accurate results in less time, increasing productivity and reducing response time. Using proven Boolean search/e-sourcing best practices, the probability that any given call will produce the right match is intrinsically higher than any other method of recruiting (cold calling, referral recruiting, networking, user groups, etc.).

Everyone will have their own opinions about the pros and cons of cold calling, referral recruiting, and e-sourcing and which one is the superior method of talent identification – that debate will rage on indefinitely. However, there is no denying the objective and intrinsic advantages of precise control over critical candidate matching variables and high speed identification of accurately matched candidates that sourcers and recruiters adept at wielding Boolean search strings can achieve when coupled with a resume database of a decent size.

I define e-sourcing as proactively searching information systems (ATS/CRM, Internet, LinkedIn, Facebook, Twitter, etc.), to identify potential candidates. While there is much written on HOW to search the various talent sources available to recruiters today, there does not seem to be much written about their intrinsic value as sources of talent/human capital information. 

I believe that the value of any source of information is 50% based upon the actual information contained within, and 50% in the ability to extract out precisely and completely what the user needs. Information has no value if you are unable to access, search for, and find what you need and take action on it.

When it comes to leveraging information systems for talent identification and acquisition, it is critical to assess the depth of the talent/human capital data offered by the source as well as how “searchable” the source is.

Why?

Quite simply, the deeper the data offered by and the more searchable the the source is, the higher the ROI for your e-sourcing efforts. All electronic sources of talent are NOT created equal, and some offer sourcers and recruiters instrinsic advantages with regard to the ability to more quickly and precisely find more of the right people, yielding higher productivity.

I’ve created a graphic representation of a comparison of the data depth and searchability of the most common information systems used by sourcers and recruiters to find candidates.

Shallow Data Depth

The whole point of using information systems to search for candidates is to find people who have specific skills and experience, and typically people who live in a specific location. It’s not terribly difficult to find PEOPLE, but it can be very challenging to find the RIGHT people.

As you can see from the chart above, I’ve classified MySpace, Facebook, Twitter, and the Internet (non-resume results, such as press releases, company directories, etc.) as shallow sources of talent data.

This is because these sources either don’t offer much in the way of professional/occupational information (often a title and little else), and/or they have very little information as to the exact location of the potential candidates. In most cases, they contain very little information regarding critical candidate variables such as skills and responsibilities, quantity and quality of experience, career history and accomplishments, education, precise location, etc.

Many shallow sources of candidate information simply do not provide ANY information regarding some of these details. This is because the majority of people who use sites like Twitter, Facebook, and MySpace often don’t include professional/employment information on their profile. With little or no information to go on, it is extremely difficult to search for and identify candidates who have a high probability of at least meeting the minimum requirements for your opening, let alone exceeding them.

Low Searchability

While you can certainly search MySpace, Facebook, and the Internet – they have significant limitations with regard to their “searchability.” Facebook and MySpace are simply not designed to be highly searchable, at least not to find people you don’t know.

You may think I am crazy for saying that the Internet isn’t very “searchable,” but most search engines, including Google, don’t even support full Boolean logic. Also – the Internet itself is unstructured, which makes it intrinsically difficult to find exactly what you’re looking for without drowning in a sea of false positive results.

Sniffing out and following candidate leads based on shallow information and using sources that aren’t by design highly searchable comes with the territory of being a sourcer or recruiter, and the thrill of the hunt can be quite satisfying.

However, the angle of this article is ROI, or even more specifically ROTI (Return on Time Invested) – which is a good measure of productivity (Productivity + Work / Time). Trying to search shallow data sources with limited search capability can be an incredibly slow and time consuming process, as well as result in a significantly low return on time invested. I refer to this as “low yield” sourcing, and its cause is the shallow depth of information available and poor searchability of the sources – which cripples your ability to control or even identify critical candidate variables.

Deep Data But Low Searchability

In this quadrant we have many ATS/CRM solutions, as well as Internet resumes. In both cases, we’re dealing with resumes.

Resumes are definitely deep sources of talent data – and while they are not always complete or 100% accurate – most resumes do contain significant information about the people who wrote them. Even when poorly written, most resumes contain summaries of experience, objectives that can give you insight into the types of opportunities they are interested in, a work history giving you an idea of their capabilities based on their past responsibilities and experience, and of course an addresses – which can be critical in making an educated guess at whether or not they might be open to a particular commute.

While this deep level of talent data is wonderful – it’s of little use if your ability to search for and retrieve the data is limited. Unfortunately, many ATS/CRM solutions aren’t very searchable. In fact, some are laughably unsearchable, considering a major reason for storing human capital data is (you would think) to be able to retreive it to take action on it.

If you look closely at the chart above, you will notice it says “Most ATS’s.” That’s because there are some highly searchable ATS/CRM solutions on the market (Avature and Bullhorn come to mind), and I am also aware of some “home-grown” systems that are also highly searchable. So while there are some highly searchable ATS/CRM solutions available, too many are unacceptably low on the “searchability” scale.

When it comes to the Internet - while you can search the Internet and find resumes, only MS Live supports queries employing full Boolean logic. The irony there is that Live limits you to 10 search terms (unless that’s changed recently). It’s nice that Google gives you 32 search terms, but in some cases, this limits your ability to configure queries that are precise enough and/or remove all false positives.

And while finding some local resumes can be done using Internet search engines, it is difficult to be sure if you are actually finding ALL of, or even the best available, resumes. Because the Internet is unstructured, when you search for area codes, state abbreviations, and zip ranges (as you can with Google), you often get a number of false positive results. And if a person puts their resume online but does not list an address or a phone number – good luck trying to find them as a local candidate.

To be highly “searchable” – it should not be hard to find exactly what you’re looking for, and you should not have to suffer many irrelevant results.

Highly Searchable but Shallow Data

Here we have Twitter and LinkedIn.

I’ve written about this many times before – Twitter is an extremely shallow source of talent data. The operative word in the term microblog is “micro” – 140 characters for Tweets and 160 characters for a bio.  That’s not a whole lot to go on. While some Tweeps do Tweet about their professional life, many do not. Also, many people don’t give away much information in their micro-bio either. 

Unlike Twitter, which by design is a shallow source of talent data, LinkedIn is a deeper source of human capital data. However, while some LinkedIn profiles are as detailed as a traditional resume, there are still plenty of profiles with very little, if any, information on them. I have no doubt that over time more people will flesh out their profiles with more information and LinkedIn will move to the upper right quadrant of the chart.

Here’s where both Twitter and LinkedIn shine brightly – searchability.

Twitter employs tag searching (hashtags #), supports full Boolean logic, enables location searching via geocoding ( SQL near:DC within:25mi), and some third party applications (e.g., Twellow) allow you to search specific fields such as bios (@bio developer). Click here to learn more about searching Twitter for sourcing candidates.

LinkedIn supports full Boolean logic and can accept and run insanely long and complex queries, allows for Boolean searching of structured data (current/company, current/past title, school…), has configurable location searching, supports industry and group search, as well as “hand-coding” of searches with LinkedIn’s own advanced operators (ccompany:, ptitle:, joined:, etc).

Deep Data and Highly Searchable

Here’s the sweet spot for sourcing and recruiting – sources of talent data that offer significant depth of information AND are highly searchable. In this quadrant we have the job board resume databases and something I like to refer to as Talent Warehouse solutions.

The job major job board resume databases (Monster, Careerbuilder, Dice) all have…that’s right – resumes, which as we have already seen are deep sources of talent data. Resumes offer a work history including career progression, skills and experience (at least to some extent), environment/group/division/project information, education, and precise location. In many cases, resumes will detail specific responsibilities and responsibility level, as well as accomplishments and achievements.

In addition, all of the job board resume databases are also highly searchable, supporting full Boolean logic, useful query modifiers such as the asterisk for root-word searching, structured field searching (recent experience/titles, etc.), and configurable location searching. 

Sourcers and recruiters can run Boolean strings and structured queries when searching job board resume databases to precisely target specific experience, years of experience, education, certifications, environmental/project, and industry experience. Those who are particularly adept can even achieve semantic search by crafting Boolean strings that go well beyond buzzword matching and target specific responsibilities, or in other words, what the candidates have actually done as well as what they have done it with.

The combination of deep data and high searchability affords you the ability to search for and essentially control critical candidate qualification variables enabling “high yield” e-sourcing – a high volume of more accurately and appropriately matched results in less time.

Talent Warehouse

When you saw that large yellow bubble labeled “Talent Warehouse” in the upper right hand corner of the chart, I’m sure most of your were wondering, “What the heck is a Talent Warehouse?” 

Just as Business intelligence applications are typically supported by a data warehouse - which is the main repository of an organization’s historical data, also known as corporate memory (the total body of data, information and knowledge required to deliver the strategic aims and objectives of an organization) - a ”Talent Warehouse” serves as the main repository of an organization’s Human Capital data, and it would serve as the raw material for a Talent Support System (TSS) – a computerized system for helping to make Talent-related decisions, such as talent identification and acquisition.

The core of a Talent Warehouse is a relational resume database. We’ve already established that resumes are deep sources of human capital data – but you may have noticed that on the chart above, “Talent Warehouse” is actually higher on the scale of data depth than other sources of resumes. “What’s a deeper source of human capital data than a resume you ask?” 

A Talent Warehouse adds more depth to resumes through the use of comments/notes and tags – sourcers and recruiters can add additional information to candidate records and resumes based on phone screens, in-person interviews, references, tests and evaluations, etc. Imagine being able to search for candidates based on information contained in their resumes AS WELL AS information gleaned from the candidates through interviews. Imagine that! 

Although many Applicant Tracking Systems, HRMS/HRIS solutions and Recruiting CRM applications make lofty claims as to their capabilities and functionality, I don’t consider (m)any vendor solutions currently on the market to be a true Talent Intelligence/Talent Warehouse solution. Most are simply systems that track and organize applicants (ATS), and/or enable the management of “relationships” (CRM), and they often they lack a critical piece of the puzzle – searchability.

A true Talent Warehouse has a search interface that supports the searching of resumes as well as tags and notes using both standard and extended Boolean queries (including configurable proximity and variable term weighting) to enable effective semantic search as well include an Artificial Intelligence resume/job matching engine to cover all angles. This kind of search interface and engine can enable sourcers and recruiters to quickly and precisely find quantities of well qualified candidates.

In the hands of an adept Talent Miner, a Talent Warehouse can yield a high volume of results with a high percentage of candidates who have specific skills and experience, specific responsibilities, specific years of experience, specific environmental/project experience, and who live in a specific area. What this essentially affords a recruiter is the ability to leverage technology to find, contact, and establish and build relationships with more of the RIGHT PEOPLE, MORE QUICKLY, increasing productivity!

Conclusion

You can find and hire people by searching any electronic source of talent data – resume or otherwise. However, searching shallow and less searchable sources such as Twitter, Facebook, Myspace, blogs, the Internet and other similarly shallow sources of candidate data takes a higher amount of effort for a smaller return – a low ROI. This results in low yield sourcing and recruiting and ultimately lower productivity.

If you have deeper and more searchable sources of talent data, why would you go out of your way to (or allow your sourcing/recruiting team to) focus on low yield sourcing and recruiting?

Highly searchable and deeper sources of human capital data enable you find more appropriately qualified candidates more quickly, through your ability to search for, control, and quickly analyze and assess critical candidate variables such as specific roles/responsibilities, years of experience, skills/technologies, environment, education, and location. This results in a higher return on time invested and higher productivity.

While it may sound perfectly logical to start with the deepest and most searchable sources of talent data available to you, I assure you – not everyone actually does this. I continue to see and hear about sourcers and recruiters who are blinded by buzz of sources like Twitter and Facebook and who spend more time using them than their own ATS/CRM, or other deeper and/or more searchable sources available to them.

And If your private candidate database/ATS/CRM isn’t as searchable as it could be – consider doing something about it- because it should be.  

Make the conscious decision to focus the majority of your e-sourcing efforts on the highest ROI sources – those with deep data and those that are highly searchable.

Most recruiting and staffing organizations, ranging from executive search sole proprietorships to staffing agencies and Fortune 500 companies, have internal databases filled with information on thousands to literally tens of millions of applicants, candidates, and professionals. 

You would think that a private internal database of people that an organization has actively and passively, tactically and strategically collected over the years would be a prized posession and be viewed and leveraged as a significant resource and competitive advantage.

However, I recently read this post on Weddles and found out that a recent Online Sourcing Survey conducted by TalentDrive found that almost two-thirds (64%) of the employers represented by the survey’s participants did not know how many qualified candidates were in their own ATS databases.

Yes – you read that correctly. Most companies don’t even know how many people are in their Applicant Tracking Systems.

Surprised?

While that is an especially disturbing statistic and a sad reality, I’m actually not that surprised. Most Applicant Tracking Systems have horrible search interfaces and extremely limited search capability. Prospective candidates go in, but they don’t come back out. If you can’t easily search your internal database, how can you find the top talent hidden within, let alone determine the total candidate population?

How Searchable is YOUR ATS/CRM?

Deposits and Withdrawals

Having an ATS/CRM/candidate database that is not highly searchable is like putting your money into an insolvent financial institution - you can deposit money/assets in – but you can’t easily or reliably make withdrawals! Anything designed to store something should have strong retrieval capability – once you put it in, you should expect to be able to get it back out. Quickly and easily, no less. If you can easily enter prospective candidates into your ATS but you cannot easily retrieve the right ones at the right time – you’re essentially sitting on a giant Hidden Talent Pool.

Illiquid Human Capital

Everyone agrees that people are an organization’s most valuable asset. However, if you cannot quickly, easily, and precisely search for and retrieve highly qualified candidates from your private database, your ATS is essentially a source of illiquid (human) assets. In other words, you cannot easily convert the human capital data stored in your system into hires or placements.

The Black Hole

Just like light heading into a black hole, applicants and candidates often go into applicant tracking systems - but they don’t come back out. Presumably, there are only 2 main ways a person can end up in a company’s ATS: #1 They responded to a job posting #2 Someone ran a search (manual or automated) and found the candidate’s profile/resume and entered it into the database In both cases, someone – either a candidate or a sourcer/recruiter – has shown interest in a potential match at some point in time, and this should be worth something. People applying to jobs should be able to expect a response of some kind, and recruiters should be able to easily find well qualified candidates they found and entered into the system in the past.   

Sourcer/Recruiter Behavior

Can we blame sourcers and recruiters for NOT searching and leveraging their ATS/CRM if other sources they may have access to (such as LinkedIn and job board resume databases) are 10X more searchable? If trying to find appropriately qualified candidates in an ATS is as difficult and painful as pulling teeth, we should not be surprised when sourcers and recruiters search the Internet for candidates first, and the ATS last (if at all!).  A company’s private candidate database should, if anything, be MORE searchable and EASIER to use than publicly available systems and databases. As mentioned previously – people in your ATS have either shown specific interest in your company or were found elsewhere by a sourcer or recruiter and entered into the system. Both types of people should receive “priority handling.” 

Expect a Return on Investment

Many companies spend tens of thousands to hundreds of thousands of dollars on their Applicant Tracking/CRM systems, and they should expect a significant return on that money invested. I say that the value of a database lies not in the information contained within, but in the ability of a user to extract out precisely and completely what the user needs. If you can’t easily, quickly, and precisely retrieve talent out of your ATS – you didn’t get what you actually paid for. If you’ve been a corporate recruiter at some point in your career – did you ever have a 3rd party search firm/agency submit candidates to you that you already had in your ATS? Did you know that some companies will pay a fee or a premium (contract to hire) for candidates that 3rd party firms source and recruit that were in fact hiding in the company’s ATS? Without going into why companies would actually pay another firm for candidates they had buried in their ATS – the $64,000 question is why didn’t the corporate sourcers/recruiters find the candidate themselves? The answer is usually quite simple – because the company’s ATS isn’t very searchable. Perhaps it would be more accurate to call it the “20-30% of the first year’s salary” question. Ouch!

What Companies Can Do

To ensure that your private candidate database/ATS isn’t just one big fat black hole where candidates enter but they never come back out, here are a few things you can do:

Replace or upgrade your ATS/CRM

Yes, this will likely involve spending money. However, if people really are the greatest and most valuable asset of your organization – investing in a system that allows you to effectively capitalize on this asset is well worth the cost, nearly at any price! From a corporate perspective, moving to a system that makes it easy to find appropriately qualified candidates that you have already sourced can significantly reduce your cost-per-hire as well as your reliance on 3rd party search firms.  From a search firm/agency perspective, investing in replacing or upgrading your candidate database/tracking system can help increase your productivity (and likely profitability) by enabling you to more quickly and effectively capitalize on candidates you have already sourced, interviewed and qualified rather than having to try and source ”new” candidates from scratch for each job order/client request you receive. 

Integrate a New Search Interface/Engine Into Your ATS

Typically less expensive than switching out your whole ATS/CRM – there are several 3rd party search applications available ranging from highly configurable text search (Lucene, dtSearch, etc.) to conceptual/artificial intelligence search/match applications (Autonomy, BurningGlass, TalentSpring, Pure Discovery, Actonomy, etc.) that you can integrate into your existing ATS/CRM to significantly boost its “searchability.” Some of the aforementioned solutions are free (Lucene) and others are surprisingly affordable.

Train Your Sourcers and Recruiters (AND/OR Yourself)!

Sometimes an ATS/CRM is a black hole from which candidates never return because the sourcers and recruiters simply aren’t very proficient in how to effectively search information systems for talent identification (aka Talent Mining). If you already have a highly searchable ATS or CRM, invest in training your associates with the latest search best practices, tactics, and strategies. You don’t need a super-expensive “state of the art” search application to quickly find the right people. In fact – all you need is a search interface that supports full Boolean logic. I personally averaged 8 hires per month only after 3 months of experience as a recruiter – and my sole source of candidates was an old CPAS ATS developed by VCG. No Monster, no Linkedin, no cold calls – just a plain old resume database with about 80,000 records and a search interface that supported full Boolean logic. How’s that for ROI?

The Bottom Line

If your ATS/CRM is as easy to search as it is to put candidates in, you will be able to fill more of your company’s openings from talent you’ve already sourced. Any opening you can fill with candidates already in your internal system saves you the time, effort, and cost of advertising and searching for “new” candidates. Filling openings with candidates already in your ATS can afford you significant and measurable cost-per-hire and time-to-fill savings.  Additionally, having a highly searchable ATS/CRM can help you reduce your reliance on paid resources if you currently use them (such as Monster, a premium LinkedIn account, etc.). Is it easier to search public systems such as LinkedIn or Monster to find appropriately qualified candidates than it is to search your private ATS/CRM? It shouldn’t be.

How Many Candidates Are In Your ATS/Private Database?