Here is the expanded slide deck from my SourceCon 2010 Keynote: Resume Sourcing and Matching – Artificial Intelligence vs. Human Cognition. It contains all of the talking points as text so you are not left guessing as to what I spoke to during the live presentation.

You’ll learn about the intrinsic and often overlooked challenges associated with sourcing resumes (it’s deceptively complex), what artificially intelligent semantic search and match applications claim to do and how they actually work, the limits of artificial intelligence, what people can do that semantic search applications cannot, the 5 levels of semantic search,  the 5 levels of talent mining, and what I think is the ideal candidate sourcing solution.

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 recently wrote an article that definitively defined the “Boolean Black Belt” concept. In this post, I explain how to become one. The good news is that you don’t have to be born with the “Boolean gene” (no one is). The bad news (for some) is that it requires a great deal of what is known as “deliberate practice.”  

The Talent Excuse

As I have worked with and trained many recruiters over the span of my career, I’ve often had people “explain away” my ability to leverage technology (ATS/CRM, Internet, Social Media, Job Board databases, etc.) for talent identification and acquisition with the excuse that I have a “talent” for it. In my first few years in recruiting, I accepted that at face value. I never really wondered where my ability came from - I assumed I actually did have a “talent” for talent mining.

Talent is Overrated

Over the years I’ve come to understand and appreciate that I don’t necessarily have an innate ”talent” for leveraging sources of human capital data - no one is born with an e-recruiting gene. What I actually have is 2 factors that I believe have contributed significantly to my skills and ability. 

#1 I have a combination of personality traits that have likely facilitated my learning of the art and science of talent mining: I’m competitive (I hate to lose), analytical, detail oriented, don’t give up easily (okay, maybe not at all), and I really enjoy figuring things out. Nothing really special there – certainly not a rare combination of traits, and I’m sure many people share them. However, personality traits are not something most people have a choice in.  

#2 Lots of “deliberate practice.” This is something anyone can choose to do, and it’s what really separates world-class performers from everyone else. 

Not All Practice is Created Equal

Back in October 2008, I read an article in Fortune magazine titled “Why Talent is Overrated,” by Geoff Colvin. It completely changed my understanding of my own so-called “talents” and how I came to achieve them. If you haven’t read the article or the book that Geoff wrote (Talent Is Overrated: What Really Separates World-Class Performers from Everybody Else) – I strongly urge you to do so. They are fascinating reads that will give you significant insight as to exactly why some people are so much better than others at what they do. 

In both the article and the book, Geoff Colvin articulates the concept of “deliberate practice” very well - it is a unique kind of activity, characterized by several elements that when combined, form a powerful whole greater than the sum of their parts. As I read Geoff’s content, I realized that I owe a great deal of my e-recruiting skill and ability to ”deliberate practice” and I firmly believe anyone for the most part can replicate the conditions under which I learned the art and science of e-recruiting.

I will only briefly summarize all of the critical elements that define and differentiate “deliberate practice” from what most people think of when it comes to practice, because Geoff Colvin does such a fantastic job of going into significant detail when explaining the concept. Trust me – at least read the article, if not the book.

#1 Deliberate Practice Improves Performance by Design

Deliberate practice is specifically designed to improve performance by continually stretching you just beyond your current ability. Unfortunately, when most people “practice,” they are just doing what they’ve always done – which does nothing to improve performance. Unlike many professional athletes, most business professionals (including sourcers and recruiters) do not go to work every day specifically trying to get better at what they do. It’s something many people may talk about, but very few people actually do.

Geoff Colvin cuts to the root of the matter, pointing out that “Most fundamentally, what we generally do at work is directly opposed to the first principle: It isn’t designed by anyone to make us better at anything. Usually it isn’t designed at all: We are just given an objective that’s necessary to meeting the employer’s goals and then expected to get on with it.”

If you are looking to master talent mining – you must specifically design your approach at work to improve your performance – not simply meet goals and objectives. You will need to specifically practice what you are not currently good at, always seeking that which is just beyond your ability. Do you passionately attack positions that you’ve never worked before, that you don’t have a pipeline for, that are difficult for you to understand, or that require a rare combination of skills that is difficult to find? Or do you post the job, hope for the right people to respond, and move on to something you’re more comfortable with? When you finally do find a candidate, are you relieved at your success and acheivement, or do you ask yourself whether or not this is the BEST candidate you could find?

#2 Deliberate Practice Requires High Repetition

Properly conducted, deliberate practice involves a high amount of repetition, and it is critical to choose an activity that is just beyond your current ability. When it comes to deliberate practice, Colvin points out that volume matters, explaining that ”Top performers repeat their practice activities to stultifying extent.”

If you seek to become a Boolean Black Belt, you will need to practice the entire process of analyzing and interpreting job requirements, translating the requirements into Boolean search strings that are highly likely to find the right/best people, analyzing the results for relevance, and continuously refining the search strings based on the observed relevance and intel gained from each successive search - A LOT. When it comes to deliberate practice, volume of repetition is key.

#3 Deliberate Practice Involves Continuous Feedback

When performing deliberate practice, feedback on results is ideally continuously available. When applying this concept to practicing talent mining, the continuous feedback should be painfully obvious – with every search you run, you are either finding a large volume of highly relevant results (well matched/qualified candidates), or not (lots of results, many false positives, and few highly relevant results). 

As Colvin points out, the aspect of continuous feedback may seem obvious, but not necessarily so when results require interpretation – in many cases a coach, teacher, or mentor is a critical factor in providing feedback. You may think your search results are highly relevant, or perhaps represent the best candidates a particular source you are searching can offer – but until a highly proficient mentor reviews and assesses the results objectively, you may actually be in a dangerous state of ignorant bliss. You don’t know what you don’t know, and you can’t find what your Boolean search strings are incapable of returning. 

#4 Deliberate Practice is Mentally Challenging

Deliberate practice requires a high degree of mental focus and concentration, differentiating it from simple and mindless repetition. Specifically focusing on the analysis of the relevance of your search results, questioning whether or not you in fact found all of the best candidates that a particular source has to offer, and continually seeking ways to not only improve the relevance of the results, but also to increase the quantity of high quality results requires significant focus and concentration. Talent mining is 90% thought process and strategy, 10% Boolean operators and syntax.

#5 Deliberate Practice is Hard Work

As Colvin so aptly points out, “Doing things we know how to do well is enjoyable, and that’s exactly the opposite of what deliberate practice demands.” Deliberate practice requires you to specifically target what you’re not good at, which can be an uncomfortable and perhaps painful, if not enlightening, process – which explains why most people actually shy away from deliberate practice. If it were easy and fun to become truly great at something – everyone would be so. That explains why there are so few true top performers/masters in every endeavor. 

Most sourcers and recruiters can run Boolean search strings to find candidates in ATS/CRM applications, on the Internet, social media sites, and job board resume datbases – so it seems easy. But just because you can do something, it doesn’t actually mean you’re actually any good at it, or that you’re getting ALL of the BEST results possible. This goes back to point #3 – many people are not capable of objectively judging the quantity and quality of their search results and also rarely have access to a basis of comparison. If you are not even aware that you could be getting more and better results more quickly, talent mining seems simple and the idea that you need perform hard work to practice to improve your skills and abilities may seem preposterous.

Being satisfied with your current level of ability at anything is a sure sign that either #1 you’re actually not as good as you think you are, or #2 you don’t prioritize or commit to improving your skills – or perhaps both!

#6 Deliberate Practice Focuses on the Process, Not the End Result

To become a top performer, you need to set goals that specifically focus on improving your skills and ability. Colvin explains that ”…the poorest performers don’t set goals at all; they just slog through their work. Mediocre performers set goals that are general and are often focused on simply achieving a good outcome – win the order; get the new project proposal done. The best performers set goals that are not about the outcome but rather about the process of reaching the outcome.”

When I read that, especially that last sentence, I literally had an epiphany – looking back at my career in recruiting, I was never really focused on achieving placements, which appears to be the obvious goal of recruiting. I was always specifically focused on finding the best possible candidates for the positions I focused on each day in the least amount of time. As a result, over time, I got really good at quickly finding a large volume of highly qualified and well matched candidates – which resulted in a record number of placements.

It is a deceptively simple difference – focusing on the process of achieving the outcome rather than the outcome itself – but it does define the vast majority of top performers in every field.

#7 Deliberate Practice Requires Metacognition

Research has shown that top performers monitor what is happening in their own minds and ask questions of themselves. This process is known as metacognition. John H. Flavell, an American developmental psychologist, explains that metacognition “refers to one’s knowledge concerning one’s own cognitive processes or anything related to them, e.g., the learning-relevant properties of information or data.” Colvin points out that top performers perform metacognition ”much more systematically than others do; it’s an established part of their routine.”

To become an expert at leveraging information systems for talent identification and acquisition, metacognition plays a critical role in the process of anaylzing and interpreting job requirements and determining what terms to include in your Boolean search string as well as which ones to specifically exclude. This involves challenging your assumptions as well as the information in the job description and requirements, and pausing to reflect and observe your own thought processes: Do I really understand this position? How many different titles could candidates performing this role have? How many different ways can this type of experience be described in a resume, and how can I effectively search for all of them? Would ALL candidates with this type of experience ALWAYS explicitly mention the required technology and/or skills in their resume? Am I learning from every result/resume I review?

#8 Deliberate Practice Involves Continuous Improvement

Feedback on your e-recruiting efforts can come in many forms – from your phone screen and/or interview with the candidates you found through your searches (were they well qualified and interested in potential opportunities?), to the client’s/manager’s/team’s interview with the candidates you’ve sourced and screened (did both the candidate AND the hiring authorities feel it was a great match?), all the way to a successful hire that “sticks” (the ultimate feedback loop).

The final key to deliberate practice is how you respond after you’ve completed your work and evaluated the result. Average performers shy away from asking themslves the difficult questions. If some of the candidates you’ve sourced with your Boolean search strings ended up not being interested in your opportunity (regardless of whether or not they were actually available) – you should try and figure out how you can be more accurate with your searches the next time around. Don’t assume that it’s “normal” for some candidates to not be interested in your opportunity – if they’re not, your searches weren’t accurate and you’re calling the wrong people.

Even if your e-recruiting efforts have resulted in a hire – instead of congratulating yourself on a job well done, ask if you could have found an even better candidate more quickly. Top perfomers strive to figure out how to perform better the next time, regardless of the result, as they judge themselves differently than most people do – to a higher standard. 

Conclusion

I have never received any formal (or informal, for that matter) training in secondary sourcing/Boolean searching, nor have I ever used a cheat sheet. While training and materials can certainly help get you going in the right direction, if you want to be world-class at leveraging information systems for talent identification and acquisition – quite simply it takes a lot of “deliberate practice.” You can’t pick and choose from the list of the core principles of deliberate practice detailed above – it requires all of them combined.

Many people say they want to be the best at what they do and to achieve great results, but most aren’t willing to commit to the time, effort, and deliberate practice it requires. Being great at anything is hard work – there is no substitute, and there is no “easy button.” And that’s precisely why there are so few top performers in every field.

I’ve been blogging for a little over 6 months now, and I realized I’ve never come out and actually defined the term ”Boolean Black Belt.” The concept seems pretty self explanatory, but there has been at least 1 person who’s taken the opportunity to point out (and gain some traffic in the process – it’s all good) that it could be perceived as a bit of an oxymoron to be an “expert” in something as simple as 3 Boolean operators.

So what is a “Boolean Black Belt” anyway?

Black Belt

I use the term ”Black Belt” in reference to the widely known way of describing an expert in martial arts, where the black belt is commonly the highest belt color used and denotes a high degree of competence. That’s the easy part; the “Boolean” part isn’t so simple to define.

Boolean

I’d like to take the opportunity to clear up some misconceptions about, and disambiguate my use of “Boolean” in “Boolean Black Belt,” and pretty much any article in which I refer to Boolean.

When I refer to “Boolean,” I am not refering only to the basic Boolean operators of AND, OR, and NOT. I’m actually referring to the entire process of:

1. Analyzing, understanding, and interpreting job opening/position requirements 
2. Taking that understanding and intelligently selecting titles, skills, technologies, companies, responsibilities, terms, etc. to include (or purposefully exclude!) in a query employing appropriate Boolean operators and query modifiers
3. Reviewing 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. Repeat steps 3 and 4 until an acceptably large volume of highly relevant results is achieved 

Instead of trying to put all of that into a domain name and a concise catch phrase, hopefully you can appreciate why I chose to summarize that entire process as ”Boolean.”

Beyond Boolean Logic

Admittedly, the basic Boolean operators are easy to learn – after all, there’s only 3 of them! However, anyone who’s adept at leveraging databases and information systems for talent identification knows that the “magic” does not lie in the operators themselves, but in all of the steps detailed above.

The “real” work of creating effective Boolean search strings lies in the interpretive analysis of the need, 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 the adaptive process of learning from the results to further refine the Booleans to find a large quantity of highly relevant results – people who are highly likely to be (or know!) the right match for your hiring needs. 

(Effective) E-Sourcing Ain’t Easy

While learning about the concepts of basic Boolean logic is easy, there is nothing inherently easy about creating Boolean search strings for talent identification. To say that searching databases and information systems to identify talent is “easy” because it’s defined only by 3 simple Boolean operators is to admit that you have little to no understanding or appreciation of e-sourcing. 

That would be like saying that a challenging math-based brain teaser is simple because you understand addition, subtraction, division, and multiplication.

For example, this classic puzzle should be easy for anyone who understands basic math, right?

“My grandson is about as many days as my son is weeks, and my grandson is as many months as I am in years. My grandson, my son and I together are 100 years. Can you tell me my age in years?”

After all, it only requires 3 basic and simple mathematical operations: addition, multiplication, and division. If that one is too “easy” for you, give this brain teaser a try – it too only requires basic math to solve.

It should be obvious that the real challenge of math-based problems comes from being able to understand the puzzle in the first place, and then determining precisely what types of equations and operations are required to solve the problem. The analysis and understanding is primary, the mathematical operators secondary, as they are useless without the proper understanding of the required and specific application of them. It’s the same thing with Boolean search strings.

Extended Boolean

Beyond the 3 “standard” Boolean operators, there lies extended Boolean, which includes proximity operators and variable term weighting. While not every search engine supports extended Boolean, those that do afford users the ability to dramatically increase the relevance of search results, effectively enabling user-defined semantic search. I’ve written 7 articles on how people do not need a semantic search engine in order to actually achieve semantic search.

Semantic Search

Semantic search can be defined as search techniques that leverage the actual meaning in words and phrases and can return results that more closely match the “meaning”  or intent of the search rather than simply returning results that match the words of the search. The whole goal of searching databases, the Internet, social media, or other information systems is ostensibly to find people who have a high likelihood of being (or knowing!) a potential match for a hiring need that you have now, or will have in the future.

The more skill and ability you have in being able to craft and execute Boolean and extended Boolean search strings that find more of the right people more quickly, the more effective you can be as a Sourcer or Recruiter. By “effective” I mean: filling more positions with high quality talent while reducing time-to-fill. More. Faster. Better. 

Whenever I refer to “Boolean” in articles or even in the name of this blog, I’m actually referring to extended Boolean and user-defined semantic search as well as the basic Boolean operators. 

Query Modifiers

Boolean search strings are often comprised of more than just search terms and Boolean operators. There are also query modifiers, and depending on the search engine, they can include: *, ” “, -, ~, ( ), w/, and many more.  Anyone hoping or claiming to have a high degree of competence with e-sourcing not only has to have a solid command of the basic Boolean operators, but also how to leverage the available and appropriate query modifiers.  

Conclusion

I use the term “Boolean Black Belt” to describe someone with a high degree of competence in the entire process of interpreting and understanding a specific talent need, determining what terms to include and/or exclude from searches and in what specific combination, crafting search strings making effective and appropriate use of Boolean operators, query modifiers, search terms, and semantic search techniques, the analysis of the relevance of the initial search results, and the adaptive process of learning from the results to further refine the Booleans to find a large quantity of highly relevant results – people who are highly likely to be (or know!) the right match for their hiring need. 

When most people in sourcing and recruiting roles refer to “Boolean,” they are not simply referring to AND, OR, and NOT. To say that mastering the use of Boolean search strings is limited to the understanding of the functions of 3 Boolean operators would be ridiculous. 

Most people would agree that Barack Obama is an excellent orator, yet he does not use words most people do not understand. For the most part, he uses common words that everyone is familiar with. But his ability as an orator cannot be defined by or limited to the common words he uses - it lies in how he organizes his thoughts and how he arranges and delivers his sentences to convey his indended meaning.

Most sculptors, golfers, jiu jitsu practitioners, and orators use the same tools, clubs, moves, and words. However, mastery does not come from the specific tools, clubs, movements, or words - it’s in the appropriate and effective APPLICATION of them, typically in response to a challenge or to achieve a specific goal. 

Knowing what golf clubs are and how to swing them does not make you a world-class golfer. Having a good vocabulary does not make you an excellent public speaker. Knowing how to punch and kick will not ensure you can win any martial arts/MMA competitions. Owning a hammer and chisel does not make you a world-renowned sculptor.

Similarly, having a command of 3 Boolean operators does not ensure that you can understand the positions you are sourcing or recruiting for and effectively leverage electronic sources of human capital data (databases, ATS/CRM’s, social media, the Internet, job boards, etc.) to find more of the best candidates available for your hiring needs more quickly.

Nor does it define a Boolean Black Belt.

Boolean Contest – come one, come all!

Irina Shamaeva and I were chatting a few weeks back and she asked me if I thought a contest focused on Booolean strings would be a good idea. You can imagine my reaction – “Of course!” She thought offering prizes of ResumeFinder or ResumeGrabber would be a great idea, and Chandra Bodapati, CEO of eGrabber, was gracious enough to offer his fantastic products FREE to the winners!

Here are the Official Rules of the Worldwide Boolean Strings Contest – 2008, sponsored by eGrabber

The contest starts on Tuesday December 9, 2008 and ends on Sunday December 21, 2008.
To participate, you need to complete three steps.

1) Post one new discussion item either on the “Boolean Strings” group on RecruitingBlogs or the “Boolean Strings” group on LinkedIn.
(Your post can be a tip, a question or a reply to somebody else’s question. Post between 12/9/08 and 12/21/08.)

2) Download and try ResumeFinder and/or ResumeGrabber.
(This step is optional but you get one bonus point for this.)

3) Answer questions in this Quiz.
(This is a multiple choice quiz on your mastery of Boolean Strings.)

The contest will have multiple winners! One person for every 25 participants will get the tool of his/her choice, ResumeFinder (a $349 value) or ResumeGrabber (a $495 value).
Plus, eGrabber will offer one month subscription to ResumeFinder to everybody who participates in the Contest! Check the box at the end of the quiz and you will receive a ResumeFinder product key.

The winners will be announced on Tuesday December 23. The top winner will get the title “Boolean Strings Master – 2008″. If you have any questions or comments please email us at contest@booleanstrings.com

Good luck, and good Boolean!

When it comes to golf, what’s more important – the clubs or the golfer?

It should be obvious that it is not the clubs, but the technique and skill of the person wielding the clubs.  Tiger Woods could play better than most people even with 20 year old clubs found at a yard sale. 

If you own a set of golf clubs but can’t play 18 holes in under 100 strokes, it’s more likely due to your skill and ability level rather than the brand and price of your clubs. Simply owning a set of clubs (even the best available) does not make you a great golfer.

Likewise, just because you have access to the Internet, an internal database/ATS, social networks, and perhaps a job board to two (which all “speak” Boolean, by the way!) – it does not automatically mean you are adept at leveraging those information systems to quickly find great candidates. You either know how to wield Boolean operators to quickly find the best talent available in these resources or you don’t. Your ability (or lack thereof) isn’t due to the Boolean operators themselves – it’s knowing how to use them and the search strategies you apply.

If you are in a sourcing and/or recruiting role and you are not fluent in Boolean, you are no different than someone who owns a set of golf clubs, but who cannot play very well. It’s not the clubs – it’s on you.

More information about more people is being stored somewhere electronically every day and it will only continue to accelerate and increase. Whether you realize it or not, if you are not adept at interfacing with databases, applications, the Internet and social networks (in other words, creating Boolean search strings) to find and retrieve human capital data you are already at a significant competitive disadvantage, and it will only get worse over time.  Technology can be a productivity multiplier, but only if you know how to use it to its full potential. 

I continue to be fascinated by recruiting and staffing professionals who show no desire to learn how to apply Boolean logic to query sources of candidates for talent.  Hearing a sourcer or recruiter complain about having to learn how to harness the power of Boolean search strings is like running into someone on a golf course complaining that golf is a difficult game.  Why are they on the golf course? Why are they even trying to play if all they are doing is complaining about how hard it is? They’ve chosen to play the game – why don’t they stop complaining, take some more golf lessons, practice a lot, and get better? Golf is golf – the game doesn’t really change – it doesn’t get more difficult with each passing day. People who set a goal of becoming good at golf make a conscious decision to get better and take lessons and practice a lot to improve their skill and ability.

Similarly, if you’ve chosen a career in recruiting and staffing (by design or by accident), instead of making excuses and complaining about how hard it is to learn Boolean logic and to create effective Boolean search strings, why not stop complaining, make a conscious effort to improve your skill and ability – get some training on how to create and leverage effective Boolean search strings, and practice a lot to get better? In this case, it’s not a hobby – it’s your career! What could be more important than learning how to be more effective at your chosen career?!?!?

Technology isn’t going away.  There won’t be any less information about people stored electronincally in the future – quite the opposite. Learning how to apply Boolean logic to create effective search strings to leverage information systems to increase your effectiveness and your productivity as a sourcer or recruiter isn’t that difficult – all it takes is a conscious decision to commit to improving your game, getting some training, and lots of practice.

Do you speak the local language?

If you traveled to a foreign country where you don’t speak the local language, you would find yourself in a situation where there are questions you would want to ask people and things you’ll need to know, and nearly everyone you run into would be able to help you - but because you can’t articulate in a manner that the locals understand, they can’t assist you and provide you with what you need. 

Most people would be rightfully frustrated in this kind of scenario – knowing that nearly everyone you run into can help you with the answers or the information you need, but you just can’t express yourself in a way anyone can understand.  Some people respond to this by speaking more slowly or more loudly (or both!) – but of course this does not help one bit.  In fact, it may simply annoy the locals and make them less likely to want to try and help you. Others might try and get a phrase or translation book to try and communicate.  Have you ever had to try and communicate with someone who does this?  It’s painful, but it’s a step better than gesticulating wildly and speaking in a different language slowly and loudly.

If you were fluent in the local langauage – none of this would be an issue. You’d be able to communicate quickly and effectively with nearly anyone you come into contact with and get the answers you seek or the information you need.

Working with computerized systems is no different. Just about every day, most people interface with information systems of some kind – computers (laptops, PDA’s, smart phones, etc.), the Internet (web sites, web applications, social media), and databases. Yet most people don’t speak the “native language” of computerized systems. If you don’t speak the local language, why would you assume that the locals automatically “know” what you’re looking for and that you should be able to get you precisely the information you need? 

So – what’s the “local language” of computerized systems? Boolean.

Pretty much any information system from which you need to retrieve information from speaks Boolean, whether you realize it or not. Let’s take Internet search engines for example. Most people don’t realize that they are indirectly using Boolean logic when they type words into Google’s search bar. Google simply ”dummied-down” the search interface so that every space between words or phrases are implied ANDs.

Google’s “advanced search” is less dummied-down, but it’s still in a format where most people don’t realize they are simply translating their queries into Boolean ANDs, ORs, and NOTs. However, most people who are fluent in Boolean skip the “advanced search” interface and directly write their own queries as opposed to using a translator.  Ever hear of the concept of “lost in translation?” If you can speak the native language – you don’t need a translator and you don’t risk losing anything in translation.

If you’re looking to get information from any computerized system (cloud-based or otherwise) – it’s no different than going to another country where you don’t speak the language.  To get what you want, and especially exactly what you want quickly, you will have to learn the language of the locals. The more fluent you are in the local language, the more precisely you are able to articulate and quickly get exactly what you’re looking for. In the case of any electronically stored information – you have to learn how to speak with computerized systems. The more fluently you can communicate in Boolean, the quicker you can get exactly what you’re looking for. 

Boolean is actually a very simple “language” – and much easier to learn than any “natural language” such as Italian, German, Japanese, or English, for that matter. However, I don’t see many people enthusiastically attempting to master Boolean even though they seek information from computerized systems on a daily basis.

Am I the only person that sees how backward and just plain wrong this is? That’s literally like going to a foreign country where you do not speak the local language, and not even TRYING to learn the native language, yet being frustrated when you can’t get what you want.

When a person tries to search a site, system, or database and does not find what they’re looking for, in many cases it does not mean that the information doesn’t exist.  It’s more likely that the person can’t properly and effectively “ask” for the information – it’s no different than trying to ask for directions from someone who speaks a different language.  

When it comes to recruiting and staffing – every day, more information about more people is available somewhere electronically – whether it in an internal database or ATS, or in the “cloud” on the Internet, on a job board, a social network, a (micro)blog, a press release, a group discussion…the list goes on. And the number of places you can find electronically stored information on people will only continue to increase.

So we have all this great information about all of these people, and the amount of information and the number of people we can find information on continues to grow - so how do we get it? Well, if it’s stored somewhere electronically, it’s on some sort of computerized system, we have to be able to speak fluently with these systems. 

It’s not necessarily all about the Booleans – it’s about leveraging information systems to identify and acquire talent/human capital.  And you can’t do that effectively without learning to be fluent in the local language.

Top 15 Common Secondary Sourcing Mistakes

I’ve had the opportunity to assess, train and coach hundreds of recruiters from  corporate and agency environments responsible for performing sourcing functions, and I’ve been exposed to many myths, misconceptions and mistakes when it comes to leveraging information systems for sourcing and recruiting. I’d like to take a moment to share my observations on what I think some of the major mistakes that are commonly made in secondary sourcing efforts. Originally, I wanted to make this a “Top 10″ post – but if you read this post within the next 2 minutes, you get 50% more free! 

In no particular order:

#1 Overanalyzing resumes

Resumes are by nature imperfect and are poor representations of a person’s experience and capabilities, so apply what I call the “10 second rule:” Don’t read resumes – scan them. If you can’t absolutely disqualify/rule out a candidate based on reviewing their resume in 10 seconds, pick up the phone and call them. You’ll be pleasantly surprised.

#2 Running overly generic/basic searches

You’ll get correspondingly generic and basic results, typically what I’ve overheard people refer to as “too many.” People making this mistake unknowingly increase the size of the Hidden Talent Pool of candidates they don’t find.

#3 Making assumptions about candidates from their resumes

See mistake #1. Ever hear the phrase “don’t judge a book by its cover?”

#4 Not spending at least 10 minutes thinking about and researching your search strategy before you start running searches and making calls
You should always take time to analyze your search criteria to assess the possibility that your search terms may not find all qualified candidates, and in fact might actually be eliminating viable candidates. I have found that the more time I spend on the front-end of a search, the more relevant my results become, which in turn increases my productivity by enabling me to find more and better candidates more quickly. Imagine that!

#5 Seeing each resume only as a potential match for the position you’re working on
Any resume database you have access to can be leveraged in much the same way as LinkedIn can – every person is actually a conduit to a larger network of people. So even if a particular resume you’re reviewing doesn’t appear to be an ideal match – they actually might be (see mistakes #1 and #3), and they may know someone who is.

#6 Assuming 1 search finds all qualified candidates

It’s actually impossible. Trust me.

#7 Searching only resumes posted within 30 days when searching major job boards

Did you know that 75% – 80% of all resumes on the major job boards are dated over 30 days old? You should never limit yourself to only searching resumes posted in the last 30 days – some of the best passive and active candidates have resumes 31 to 365 + days old online. And most people don’t call them.

#8 Not calling candidates that appear to be under- or over-qualified

First, see mistakes #1 and #3. Second, see mistake #5. Third, people who are in fact too junior or too senior for your current needs might fit future needs. Fourth, people who are either too junior or too senior for a particular position might work with or know someone who is an exact match.

#9 Submitting the first 2 -3 candidates you find that fit your job/hiring profile and moving on to the next open position

Sound crazy? I can hear someone asking, “Why shouldn’t I submit the first candidates I find that fit the requirements?” Well, ask yourself this – what’s the statistical probability that the first 2 people you speak magically happen to are the best candidates you can possibly find? The most closeable and controllable? The most “affordable?” Recruiting and staffing should not be conducted on a FIFO basis, but on a BIFO basis.  You saw it here first. Think about it.

#10 Thinking that after searching a particular source of candidates (your ATS, a job board, the Internet, LinkedIn, etc.) that you’ve found all of the available candidates and cannot find any more.

You’re wrong – invariably you’ve left behind Hidden Talent Pools of people who do match your positions, but you could not find them because your Boolean search strings made it impossible to do so. Being aware of this is a major step on the path towards secondary sourcing enlightenment. See mistake #4.

#11 Thinking that the major online job boards have poor quality candidates

Read this post on not believing the hype that the job boards have low quality candidates.

#12 Relying solely or heavily on title-based searches

Not all companies use the same titles for the same roles and responsibilities – so making this mistake contributes to you populating Hidden Talent Pools with every candidate that matches your hiring profile or job order but has a title that you didn’t think of and include in your search. See mistake #4.

#13 Not using the NOT operator

It’s the least utilized, and in my opinion, actually the most powerful standard/basic Boolean operator – it’s not just for getting rid of stuff you don’t want. I will dedicate an entire post to the NOT operator in the near future. Puns intended.

#14 Only using skill/tech terms (e.g., Java, Oracle, Accounts Payable, SOX, etc.) when creating Boolean search strings

The best searches don’t rely solely on skill/technology based terms, but also include responsibility terms (administer, configure, create, manage, reconcile, coordinate, design, etc.) and environmental terms (enterprise, host*, etc.) where applicable. This is the first step in moving beyond simple buzz-word matching.

#15 Spending 80% of your time using low-yield resources that can only provide 20% (or less!) of the potentially available results

For example – spending hours searching the Internet for candidates and not heavily/effectively leveraging your internal resume database/ATS. While you can certainly find great people on the Internet, the Internet is not indexed specifically to enable sourcing and requires many tricks and tweaks to yield relevant results. If you have access to an ATS or internal resume database – it’s specifically designed to store and retrieve resumes, and probably has more local and more qualified candidates than the Internet, and might actually have a better seach interface enabling more precise searching – see this post as a dramatic example of this point. Also – if you have access to any of the major job boards – they actually have a larger percentage of passive job seekers than active and they have some fantastic candidates – see mistakes #7 and #11.

This is by no means an exhaustive list, but it certainly covers some of the most common major mistakes sourcers and recruiters make while performing secondary sourcing.

Have a mistake to add to the list? Post a comment and let me know.

Thanks!

I recently received a request from a reader to come up with some example Boolean Strings for finding software engineers on Facebook who are from Top 10 schools (Stanford, Berkeley, MIT, CMU, etc) and live in the Silicon Valley.

***Quick disclaimer***
I am definitely not a Facebook sourcing guru – I don’t see it as a high yield source for proactive and highly precise sourcing as it is a relatively “shallow” source of information, it’s search interfaces are quite limited, and when x-raying into Facebook you can’t see much information. I’d invite anyone reading this that has suggestions and best practices to please add them.

Okay, now that I got that out of the way, searching inside Facebook for people that you don’t “know” (they aren’t your “friends” yet) has become more and more restricted over time. There are a few ways to search for people within Facebook – I will cover 3.

Inside Facebook

#1 Facebook’s basic search interface
http://www.facebook.com/srch.php?ref=ffffc

As you can see from the screenshot, on this page you can search by school OR employer. Not a real help for what you’re trying to accomplish – finding web developers from specific schools. Although you can search by school here, it doesn’t allow us to drill down into interests, combine a school with an employer, or even pick a location.

#2 Another Facebook search interface

On the previous screenshot’s interface, I actually ran a search only choosing Berkeley and did not pick an employer. Here are the results:

Once you get the results – you can see it’s over 500 and they are from all years/graduating classes and locations. However, if you scroll down to the bottom, you can now add a specific company. I chose Sun Microsystems – that narrows the results down to 227

And you can sift through the results to check location and see that many of the results are in fact in the Silicon Valley, and also view each person’s friends to try and find more people. You could do this systematically covering all of the top schools you’d like to target and all of the top employers in the Silicon Valley you’d like to see people from. This can be a good start to reaching out to some of these people and becoming their “friend,” or taking the information you find here and performing some more research, cross-referencing LinkedIn, blogs, and other sites to find out more about them. However – with this search inside Facebook, we still don’t have any control over what these people actually do.

#3 Facebook’s “advanced” search
http://www.facebook.com/advanced.php

Here you can find Facebook’s “advanced” search interface – where you can search within your network and Friends or your location. So if you live in the Silicon Valley, you should be able to search profiles in your desired area.

Although this is supposedly an “advanced” search interface – you can see it is actually quite limited. On this page you cannot search by school. However, you can search by academic concentration (you could shoot for Computer Science and such), activities and interests (web development and design…), as well as company and position (target company and software engineer, etc.). However, because you cannot search by specific school – this interface does not enable you to achieve your goal of targeting people by skill/experience as well as college/university. But for other searches – this interface can yield results for you.

Outside of Facebook
We can use the site: command on most major search engines to look specifically within Facebook and try to find people.

• Sometimes people don’t enter all of their information – like school, experience, titles, skills, specific location, etc. If it’s not there – you can’t find it.
• When using a search engine to search into a site like Facebook, you’re not searching structured data. So searching for Stanford might yield a result where the word “Stanford” is mentioned on the profile somewhere, but it isn’t where the person when to school. That’s what I call a false positive.
• To my knowledge, you can only find public profiles using the site:command

I was not provided any specific programming languages or frameworks to target in my searches, so I just chose a few as an example – they can be switched up as you see fit. I also started with 2 of the schools that were mentioned – feel free to build out the list.

Using a search engine like Google:
site:facebook.com (java | php | python | C#) inurl:people “silicon valley” (stanford | berkeley)

You’ll notice that when you run that search and check the results – you won’t find a large number. I found 2. The issue goes back to the point I made about if a person doesn’t explicitly mention a specific search term you’re looking for – you simply can’t find them by using that search term. Facebook isn’t a resume database – most people don’t fully flesh out their profiles with tons of technical detail with regard to their skills and experience.

When it comes to reviewing the results – you won’t see the programming languages or even the college names (sometimes) because you aren’t connected to, or in Facebook-speak aren’t “friends” with the people – so you can’t see their profile page where the search terms are. However, they are in there somewhere.

Let’s look at one of the results I got:

You can try to add people like this as a friend and then contact them, or simply try sending them a message, or view his friends – and from checking them, several went to Stanford. But without digging more into each of them, we can’t tell from the surface what they do (web developers or lawyers…), or where they live. If you click on Kai you can see he is a Stanford ’05 alum.

You could run the same search but go a little North to the bay area just to check it out:
site:facebook.com (java | php | python | C#) CA inurl:people “san francisco” (stanford | Berkeley)

You could also search for groups that might contain web developers:
site:facebook.com inurl:group (software | web | internet | online | java | php | python) (~develop | ~design | ~architect) “silicon valley”

Here are a few I stumbled across:

Silicon Valley CodeCamp
http://www.facebook.com/group.php?gid=6125701762

Stanford Entrepreneur Network
http://www.facebook.com/group.php?gid=5950997467

Bay Area Girl Geek Dinners
http://www.facebook.com/group.php?gid=20463663760

LinkedIn

Since searching Facebook was a low-yield exercise, I’d feel guilty ending this post without getting you better results. So let’s focus the same kind of searches on LinkedIn and see what we get:

site:linkedin.com (Berkeley | Stanford) (java | php | python | .Net) (web | internet | software) (develop | design) “san francisco bay area” -intitle:directory -intitle:updated

569 results – and I only tried 2 schools. I used a San Jose, CA zip code in LinkedIn – it considers the San Jose area part of the “San Francisco Bay Area” – a 50 mile radius. Searching into LinkedIn using the site: command is fraught with the same issues as we encountered when searching Facebook – it’s unstructured data. So do expect some false positives – it won’t be 100% perfect. I checked through the results and many are local developers who have gone to Stanford or Berkeley.

Of course, you could also search inside of LinkedIn – but that’s another post.

The Internet

And if you wanted to try and take a shot at finding resumes on the Internet itself:

(inurl:resume | intitle:resume) (java | asp | C# | perl | python | php) (design | develop) 94002..95156 CA (berkeley | Stanford | MIT) (web | internet) -job -jobs

That’s a 25 mile radius search from 95125 and yields 586 results. Sweet.

So can anyone see why I’m not crazy about using Boolean strings to search Facebook? Can you find great people in Facebook? Sure! Can you run precise queries to quickly find large volumes of highly matched people with specific skills and experience? No.

Would an oil company avoid drilling the largest oil fields they have access to and instead spend tons of time and money looking for and drilling the smallest oil deposits they could find? It only makes logical sense for sourcers and recruiters to leverage high yield sources first and low yield sources last.

I hope you found this helpful!

-Boolean Black Belt