Tag Archives: Boolean Search

Boolean Strings, Semantic and Natural Language Search – Oh My!

An entertaining blog post by Matt Charney was recently brought to my attention in which he tells the world to shut up and stop talking about Boolean strings – he argues that Boolean search is a dying art and that “investing time or energy into becoming a master at Boolean is a lot like learning the fine art of calligraphy or opening a Delorean dealership.”

You can read the snippet regarding Boolean Strings below – click the image to be taken to the entire post, in which Matt addresses mobile recruiting and employer branding.

Matt Charney Boolean Strings

I enjoyed Matt’s post and his approach, but I did not find his arguments to be thoroughly sound – although I suspect he wasn’t trying to make them so (after all, his blog is titled “Snark Attack”).

I’m going to take the opportunity to address the points Matt raised – not because I am trying to stay “relevant,” as some might suggest (my blog is a not-for-profit personal passion and I don’t consult/train for a fee), and also not because I have a vested interest in “keeping Boolean search alive” (because I really don’t) – rather, because I am still amazed that a fundamental lack of understanding of search and information retrieval – both “manual” Boolean search and “automated” taxonomy driven and/or AI-powered semantic search – and I am constantly trying to help people not only understand both, but also appreciate their intrinsic limitations, as well as separate reality from hype.

So, without further ado: Continue reading

LinkedIn Certification, Talent Connect and Boolean NOT Update

LinkedIn Recruiter Certification

In case you missed it, LinkedIn has launched a recruiter certification program!

LinkedIn Certification-Badge

If you think you’re ready to get certified, between now and December 31, 2013, LinkedIn will waive the exam fee for the first 500 customers that register for the LinkedIn Certified Professional—Recruiter certification exam. Click/see the coupon code below:

LinkedIn recruiter certification free

Before you attempt to take the certification assessment, you will definitely want to see what I only recently discovered about LinkedIn’s support of Boolean search exclusion operator (NOT vs. Minus sign) – skip to the bottom of the post to learn more.

LinkedIn Talent Connect

Talent Connect 2013 Logo

I’m honored to be presenting again at both Talent Connect events this month in Vegas as well as Talent Connect London, which happens to be the largest corporate recruiting event in Europe.

The event in Vegas is sold out, but you can view the live stream – click here to to register.

I will be presenting two sessions on LinkedIn talent sourcing on Wednesday the 16th in Vegas and one session on Thursday the 24th in London,  covering core principles and advanced strategies.

Now that LinkedIn has grown to over 238M profiles, finding people has become easier, but finding the right people has actually become more challenging. As such, knowing how to effectively source talent on LinkedIn is now more important than ever. In the foundation session, I’ll be reviewing information retrieval best practices, the importance of understanding the behavior of the people you’re looking for and that of your competitors, and how to develop the ability to ask better questions with Boolean logic. In the advanced session, I will cover Dark Matter concepts, Maximum Inclusion, Adaptive Search, Strategic Exclusion, and Moneyball Sourcing.

LinkedIn Boolean Search Exclusion: NOT vs. the Minus Sign

You may recall that I broke the story on LinkedIn’s undocumented Boolean search operator over two years ago.

In preparation for the LinkedIn Recruiter Certification, I inquired with the team at LinkedIn about any differences between the Boolean NOT operator and the minus sign (-).

They responded, and you should know that LinkedIn officially only supports the NOT operator for exclusion, as there are some “corner cases” in which the minus sign will not work for exclusion – this is true for searching LinkedIn for free as well as for LinkedIn Recruiter.

Now, if you’re a fan of words like I am, you may especially appreciate their specific use of the term “corner case,” which clearly came from their engineers. If you’re unfamiliar with the term, Wikipedia offers an excellent explanation:

corner case (or pathological case) is a problem or situation that occurs only outside of normal operating parameters—specifically one that manifests itself when multiple environmental variables or conditions are simultaneously at extreme levels, even though each parameter is within the specified range for that parameter.

For example, a loudspeaker might distort audio, but only when played at maximum volume, maximum bass, and in a high-humidity environment. Or a computer server may be unreliable, but only with the maximum complement of 64processors, 512 GB of memory, and 10,000 signed-on users.

Contrast a corner case with an edge case, an issue that occurs only at a (single) maximum or minimum parameter. For example, a speaker that distorts audio at maximum volume, even in the absence of other extreme settings or conditions.

Corner cases are part of an engineer‘s lexicon—especially an engineer involved in testing or debugging a complex system. Corner cases are often harder and more expensive to reproduce, test, and optimize because they require maximal configurations in multiple dimensions. They are frequently less-tested, given the belief that few product users will, in practice, exercise the product at multiple simultaneous maximum settings. Expert users of systems therefore routinely find corner case anomalies, and in many of these, errors.

Mind you, you can still use the minus sign in lieu of the Boolean NOT operator to exclude terms and OR statements, but be advised that there are some rare scenarios where the minus sign won’t work.

Now, I’ve personally never encountered a situation in which the minus sign did not work exactly as the NOT operator, so what are the corner cases in which the minus sign won’t work?

Ah, you know I have already asked the LinkedIn team…I am eagerly awaiting their response.

 

Is Boolean Search Boring and Less Effective than Semantic Search?

 

Boolean Search is Boring

Do you think Boolean search is boring, tiresome and ineffective, and that semantic search delivers faster results that count?

I was struck by the image Marc Drees used in his #SOSUEU: the day after post, which you can see above.

I would have loved to sit on that panel discussion and contribute my experience and thoughts on the subject – I was actually supposed to attend and speak but I left the sponsoring company just prior to the event.

Such is life. :)

Regardless, I am happy to weigh in here, and I believe that the majority of people simply aren’t looking at search properly in the first place.

I’ll address the statements from #SOSUEU in order.

Boolean Search is Boring

Let’s hit the reset button first and get a couple of things straight:

If Boolean search is boring, then searching the Internet, Amazon, etc.,  for anything is boring. Any time you use more than 1 term in your search on Google, Bing, Amazon, eBay, etc., you’re using Boolean search. The same is true with LinkedIn and many other sites you can search to find people. Am I alone in this simple understanding?

This may confuse some people, but “Boolean Search” isn’t about Boolean – it’s about search. Searching is about finding things you need and want, and there are many ways that you can search for and find those things. Do you find it more “exciting” to select from a list or check a box on a LinkedIn facet?

Github list and LinkedIn Facet

Whether you type in keywords, select from a list, check a box, apply a filter, etc., all you’re doing is configuring a query to get results to review.

I don’t think there is anything intrinsically “boring” about Boolean operators. I think the real issue is that some recruiters just don’t enjoy searching for people, and if you don’t enjoy something it’s common to find it boring. The same people who bash Boolean search don’t find typing terms into separate search fields, picking from lists and checking boxes exciting or particularly enjoyable.

Some people really like searching databases, social networks, the Internet, etc., for people to engage and recruit. Others would be happy to post jobs and wait for people to come to them and would rather not ever have to search for potential candidates to engage.

To say that Boolean search is boring is to say that carefully looking for and trying to find people (paraphrasing Merriam-Webster’s definition of search) is boring. Semantic search solutions alleviate the boredom of searching for those who find it tedious, because similar to posting a job and getting responses, semantic search solutions often allow you to enter minimal information and get results.

I’d be willing to bet that those same recruiters who don’t enjoy searching to find people to engage also don’t enjoy reviewing responses to job postings as many are unqualified – they would much rather be given a list of well matched people, which semantic search solutions claim to be able to do.

What do you think?

Boolean Search is Tiresome

If you think Boolean search is tiresome, I say you’re lazy.

Why?

Well, for basic Boolean search, we’re talking 2 operators and 2 of modifiers – in many search engines you don’t even need to type AND, as any old space will do.

Is typing in OR, -, ” ” and ( ) really tiresome?

Is filling out multiple search fields (e.g. Twitter below) any less tiresome than typing a couple of Boolean operators? By the way, the common elements of most “advanced search” interfaces are essentially AND’s (All of these words), OR’s (Any of these words), NOT’s (None of these words), and quotation marks (This exact phrase).  Oh wait – that’s basic Boolean, right? Snap!

Twitter Advanced Search Interface

While I love the concept of natural language queries, I actually find writing them tiresome and limiting (e.g. Facebook Graph Search).

Facebook Graph Search Tiresome

Is it less tiresome to use Facebook’s search fields? They’re all essentially linked by AND’s, btw.

Facebook Graph Search Interface

If there is anything that people really find tiresome about any non-semantic search, Boolean or otherwise, is that it requires you to think and expend mental energy.

I know – thinking is tough!

If you’re read a lot of my content over the years, you know I like to bring up the study of information retrieval techniques that bring human intelligence into the search process, otherwise known as Human–computer information retrieval (HCIR).

The term human–computer information retrieval was coined by Gary Marchionini who explained that “HCIR aims to empower people to explore large-scale information bases but demands that people also take responsibility for this control by expending cognitive and physical energy.”

I know the dream is to have computers read our minds so we don’t have to type a single search term – but until that day comes, you should be aware that experts in the field of HCIR do not believe that people should mentally “check out” of the information retrieval process and let semantic search/NLP algorithms/AI be solely responsible for the results.

Having said that, I can see why some people would see the process of building a massive OR string for all of the ways in which a person could possibly reference a certain skill or experience to ensure maximum inclusion as tiresome. It’s exhaustive work – especially if you don’t want to exclude great people who simply don’t reference their experience with the most commonly used search terms.

This is one of the main value propositions of semantic search solutions for people sourcing – through taxonomies and/or NLP-powered AI/algorithms, a user can enter in a single search term and effectively search for other related terms without requiring the user to know and search for all of the other related terms.

Sound great, right? Letting a taxonomies and/or algorithms doing the conceptual search work for you is certainly a lot less tiresome than having to perform research and pay attention to search results, looking for patterns of related and relevant terms to continually refine and improve Boolean searches.

To be sure, there are some solid semantic search offerings for talent sourcing on the market today that make sourcing talent faster and easier for people who find Boolean search boring, tiring, difficult and ineffective. However, to think that semantic search solutions don’t come with their own host of challenges and limitations would be ridiculous.

In case you haven’t see it before, you may want to quickly drive through my Slideshare on Artificial Intelligence and Black Box Semantic Search vs. Human Cognition and Sourcing derived from my 2010 SourceCon keynote to get a high-level overview of some of the challenges faced by semantic search solutions specific to talent sourcing.

If you don’t want to flip through the presentation, here’s a very brief summary:
  • Human capital data/text is often incomplete and widely varied – many people with the same job have different titles, explain their experience using different terms, and in many cases simply do not explicitly mention critical skills and experience
  • Semantic search solutions can only search for what is explicitly stated in resumes and social profiles
  • Taxonomies are difficult, if not impossible to make “complete” and thus they can exclude qualified talent
  • AI/NLP can be useful in determining related terms, but not necessarily relevant terms
  • Many semantic search solutions suffer from “once and done” query execution – there is no way to refine and improve searches or to exclude false positives/irrelevant results

Boolean Search is Ineffective

The effectiveness of Boolean search strings has more to do with the person writing the queries and the sources being searched and less to nothing to do with Boolean logic.

When used in a search, Boolean operators are essentially being used as a very basic query language, and according to Wikipedia, “an information retrieval query language attempts to find…information that is relevant to an area of inquiry.”

Any search a user conducts, whether they know it or not, is essentially a formal statement of an information need.

How effectively a user can translate their information need into a query/search string largely determines the relevance of the results – Boolean logic itself often has little to nothing to do with search relevance!

Assuming a sourcer/recruiter has a solid understanding of  what they’re looking for (a dangerous assumption, by the way – try giving 5 people the same job description and then ask them separately what they’re looking for), the effectiveness of any search they use, whether Boolean, faceted, semantic, etc., is more dependent upon the user’s ability to “explain” their needs to the system/site being searched via an effective query.

For example, let’s say you’re sourcing for a sales leader and you have a military veteran hiring initiative. Regardless of whether you decided to search your ATS (e.g. Taleo), LinkedIn, CareerBuilder, Indeed, etc., you’re essentially asking the same question, “Do you have anyone with experience leading sales teams who is also a veteran?” (among other things – just trying to keep it simple here).

How would you construct a Boolean search for a sales leader who is also a veteran?

How would (and/or could!) a semantic search engine search for a sales leader who is also a veteran?

Ultimately, it comes down to how many ways can someone who has sales leader experience could possibly express that experience on their resume or profile, and how many ways someone who is a veteran could possibly reference their veteran status.

Do you know them all?

Does any semantic search engine know them all? Some don’t know any because they simply aren’t included in their taxonomies. Others could use NLP to find some, but definitely not all. However, a person with decent sourcing skills could produce a veteran query like this one in about 5 minutes (not too tiresome) and continuously improve it:

(Army OR USAR OR “U.S.A.R.” OR “Army Reserve” OR “Army Reserves” OR Navy OR USN OR USNR OR “U.S.N.” OR “U.S.N.R.” OR “Naval Reserves” OR “Naval Reserve” OR “Air Force” OR USAF OR “U.S.A.F.” OR USFAR OR “U.S.A.F.R.” OR “Force Reserve” OR “Force Reserves” OR “Forces Reserve” OR “Forces Reserves” OR Marines OR “Marine Corp” OR “Marine Corps” OR USMC OR “U.S.M.C.” OR USMCR OR “U.S.M.C.R.” OR MARFORRES OR “Marine Expeditionary Force” OR MEF OR “Coast Guard” OR USCG OR “U.S.C.G.” OR USCGR OR “National Guard” OR Veteran OR “honorable discharge” OR “honorably discharged”)

The effectiveness of any search, Boolean or semantic, can be measured by the relevance of the results (e.g., a high percentage of the results are exactly what the searcher is looking for) and the inclusiveness of the results (how many relevant results are retrieved as a percentage of the relevant results available to be retrieved – those available but not retrieved are excluded into the abyss of Dark Matter).

Only the person conducting the search can judge the relevance of the results returned by any search, Boolean or semantic, as relevance is defined as the ability (as of an information retrieval system) to retrieve material that satisfies the needs of the user, and only the user truly knows what their needs are.

When it comes to inclusion, I am aware of some folks who are proponents of “good enough” searches and search solutions (e.g., finding some good people quickly is good enough and there is no need to find all of the best people).

Try telling your company’s executives that you really don’t care about finding the best people available to be found and that you believe that the quickest and easiest to find should be good enough for your company’s hiring needs.

Let me know how that works for you.

Okay, but what about Context and Weighting?

Some folks argue that Boolean search is ineffective due to the fact that Boolean searches are not contextual (e.g. you search for a term and it shows up not in the person’s recent experience, or in their experience at all) and that all terms in a query are given equal weight (e.g., if you search for 10 terms, some terms are likely to be more important than others, but basic Boolean logic doesn’t allow you to differentiate the value/relevance of specific terms).

Admittedly, some Boolean searches are.

However, if you have well parsed/structured data and a search interface that allows you to exploit that structured data, you can use simple Boolean logic to search contextually. For example, most recent/past employer and title, most recent/past experience, etc.

Some search engines do in fact allow you to assign different weights to terms within a single Boolean query (e.g. Lucene, dtSearch, etc.) – this functionality is sometimes referred to extended Boolean search. These same search engines allow you to search for terms in or exclude them from specific areas (e.g. top of the resume, bottom of the resume) via proximity search – functionality that also allows you to perform powerful user-specified semantic search at the verb/noun level to target people with specific responsibilities (have goosebumps yet?).

Okay, that was easy to address.

So, Is Boolean Search Boring and Less Effective than Semantic Search?

For some people, yes – Boolean search is boring, tiresome and less effective than semantic search.

For others, Boolean search is exciting, easy, and more effective than semantic search.

What do I know about any of this?

I’ve evaluated, implemented and used extended Boolean search solutions as well as semantic search solutions. In addition to using them myself on a regular basis, I help 100’s of recruiters use them effectively to find the right people for 1,000’s of real positions. From my practical hands-on experience, I can tell you that sometimes semantic search produces very good results – sometimes it doesn’t. Sounds similar to Boolean, yes?

To all of the “Boolean Bashers” out there – you’re missing the point.

The effectiveness of any Boolean search has more to do with more to do with the person writing the queries and the sources being searched and less to nothing to do with Boolean logic and search syntax

Let’s remember what the goal of sourcing is – to easily find and successfully engage people who are highly likely to be the right match for the roles being sourced/recruited for.

The ultimate sourcing solution would parse resumes and profiles into highly structured data that could be searched via semantic search (autopilot) and extended Boolean (manual control) to ensure that any user could quickly find the right people under any circumstance.

I’m honestly not sure why anyone believes sourcing solutions have to leverage semantic search and exclude Boolean/extended Boolean search capability.

Using Extended Boolean to Achieve Semantic Search in Sourcing

When it comes to sourcing and recruiting, semantic search is perhaps the most powerful way to quickly find people who have experience you’re looking for.

Now, I am not talking about black box semantic search (e.g., Google, Monster’s 6Sense, etc.).

I’m referring to user-defined semantic search, where you tell a search engine exactly what you want with your query, and the search engine doesn’t try to “understand” your search terms or “figure out” what you mean through taxonomiesRDFa, keyword to concept mapping, graph patterns, entity extraction, fuzzy logic, etc.

If you’re not very familiar with semantic search (for sourcing – not search engines), I strongly suggest you read my comprehensive article from January 2012 on the subject: The Guide to Semantic Search for Sourcing and Recruiting. Continue reading

How to Find Military Veterans for Sourcing & Recruiting

Military Veteran Hiring Career FairIn a similar vein to my recent diversity sourcing article, I wanted to create a resource for people looking to effectively search for and identify military veterans for recruiting.

While this posts focuses on the U.S. armed forces, I encourage folks from other countries to create and distribute similar searches to identify their own military veterans.

If you’re interested in all of the great things you can do for employer branding and talent attraction strategies for hiring veterans – you won’t find it here, because this post strictly focuses on the proactive online sourcing and identification of people who are either currently serving in or are veterans of the U.S. armed forces.

Read on to review:

  • An extensive military/veteran Boolean search I’ve constructed for use on LinkedIn, Monster, CareerBuilder, Dice, Indeed, your ATS, etc.
  • Veteran population information and resources Continue reading

Monster’s Undocumented Boolean Search Operators & Query Compression

 

Monster logo smallThe other week I came across a question regarding Monster’s search operators in the Boolean Strings group on LinkedIn and I realized that most people don’t know that Monster’s classic resume search has a few undocumented search operators as well as powerful semantic search capability.

In this article I will detail two of Monster’s undocumented search operators, how to compress your Boolean search strings by more than 30%, and remind you of Monster’s documented but seldom used NEAR search operator.

AND = & + OR = |

Although I can’t seem to find any documentation of it, Monster’s search functionality does support the & for the Boolean AND search operator as well as | for OR Boolean search operator – which can save on character space for longer queries.

While most people don’t run searches that will test Monster’s main search field limit of 500 total characters (including spaces), there are those sourcers and recruiters who extensively leverage conceptual search, employing comprehensive OR statements for each concept in their Boolean search string, which can easily exceed 500 characters, especially when searching for a number of target companies.

In cases such as these, it can be helpful to use the ampersand (&) for AND and the pipe symbol (|) for OR, effectively cutting the number of characters used for AND’s and OR’s by 60% (5 total characters down to 2).

For example, compare these two searches which return the exact same results:

  • iOS AND (ObjectiveC OR “Objective-C”) AND (cocoa OR xcode) AND (iPhone* OR iPad*) AND (“apple store” OR iTunes OR “app store”) AND (SQL* OR xib)
  • iOS & (ObjectiveC | “Objective-C”) & (cocoa | xcode) & (iPhone* | iPad*) & (“apple store” | iTunes | “app store”) & (SQL* | xib)

Even with a relatively short Boolean search string of 144 characters, you can save over 10% by using & and | (128 vs. 144 characters).

If you wanted to compress your queries further, you can actually eliminate all spaces in your Boolean search string with no negative effects.

For example – this Boolean search string returns the exact same results as the above two searches:

  • iOS&(ObjectiveC|”Objective-C”)&(cocoa|xcode)&(iPhone*|iPad*)&(“apple store”|iTunes|”app store”)&(SQL*|xib)

Sadly, Monster does not support the minus sign (-) for the NOT operator.

However, you do not have to type AND NOT, nor & NOT – a simple NOT will do.

In fact, you don’t even have to capitalize NOT or any other Boolean search operator, for that matter – lowercase not works exactly the same.

Thanks Monster!

Boolean Search: Who Needs AND Anyway?

Interestingly, most people also don’t know that you don’t have to type AND or & – similar to LinkedIn, Google, Bing, etc., any space can be an implied AND.

For example, this search runs exactly as the ones above:

  • iOS (ObjectiveC|”Objective-C”) (cocoa|xcode) (iPhone*|iPad*) (“apple store”|iTunes|”app store”) (SQL*|xib)

Furthermore, you don’t even have to use a space to leverage implied AND functionality – this search returns the exact same results:

  • iOS(ObjectiveC|”Objective-C”)(cocoa|xcode)(iPhone*|iPad*)(“apple store”|iTunes|”app store”)(SQL*|xib)

Now we’re down to 101 characters, which is nearly 30% more efficient than our original 144 character search.

How’s that for Boolean search efficiency?

If you’re wondering how I figured this stuff out, it’s actually quite simple – curiosity and experimentation.

I challenge you to be curious and to experiment – from time to time, simply ask, “I wonder what would happen if…..?” and give something a try.

Hopefully all of what I’ve shared with you today has made you curious about your other sources and how you might be able to experiment and tweak your searches for other sites to make discoveries and yield additional benefits.

If you you do – please let me know!

Monster’s NEAR Operator: Documented but Seldom Used

Although Monster’s extended Boolean NEAR search operator is documented, most people don’t use it. This is unfortunate, because proximity search is incredibly powerful and can help you zero-in on people based on what they’ve actually done vs. resumes containing search keywords.

Monster’s NEAR operator is an example of fixed proximity search, which can be used to return results with words, phrases or OR statements within 10 words of other words/phrases, or OR statements, which can enable semantic search at the sentence level.

Would you be interested in learning more about sentence level semantic search using the NEAR operator?

 

100+ Free Sourcing & Recruiting Tools, Guides, and Resources

 

It’s been a LONG time coming, but I finally got around to updating my free sourcing & recruiting tools, guides and resources page where I now keep a current list of the best of my work all in one place for easy bookmarking and reference.

You can find it here on my main page:

 

Here is where you can find all of the best of my Boolean Black belt content all in one place - free sourcing and recruiting how-to guides, tools, presentations, and videos - be sure to bookmark it, and if you're feeling  friendly, tweet it, share it on LinkedIn and/or +1 it on Google Plus.  Many thanks!

 

Additionally, I thought I might as well put all of my best work all in one blog post as well – over 110 of my articles in one place for easy referencing!

My blog is a pursuit of passion and not of profit – if you’ve ever found anything I’ve written helpful to you, all I ask is that you tweet this out, share it on LinkedIn, like it on Facebook, or give this a +1 on Google.

Many thanks for your readership and support – please pay it forward to someone who can benefit.

Big Data, Analytics and Moneyball Recruiting

Big Data, Data Science and Moneyball Recruiting

The Moneyball Recruiting Opportunity: Analytics and Big Data

Human Capital Data is Sexy – and Sourcing is the Sexiest job in HR/Recruiting! 

Is Sourcing Dead? No! Here’s the Future of Sourcing

The End of Sourcing 1.0 and the Evolution of Sourcing 2.0

How to Find Email Addresses

How to Use Gmail and Rapportive to Find Almost Anyone’s Email Address

Social Discovery

2 Very Cool and Free Social Discovery Tools: Falcon and TalentBin

Talent Communities

The Often Overlooked Problem with Talent Communities

Lean / Just-In-Time Recruiting / Talent Pipelines

What is Lean, Just-In-Time Recruiting?

Lean Recruiting & Just-In-Time Talent Acquisition Part 1

Lean Recruiting & Just-In-Time Talent Acquisition Part 2

Lean Recruiting & Just-In-Time Talent Acquisition Part 3

Lean Recruiting & Just-In-Time Talent Acquisition Part 4

The Passive Candidate Pipeline Problem

Semantic Search

What is Semantic Search and How Can it Be Used for Sourcing and Recruiting?

Sourcing and Search: Man vs. Machine/Artificial Intelligence – My SourceCon Keynote

Why Sourcers Won’t Be Replaced By Watson/Machine Learning Algorithms Any Time Soon

Diversity Sourcing

How to Perform Diversity Sourcing on LinkedIn – Including Specific Boolean Search Strings

How to Use Facebook’s Graph Search for Diversity Sourcing

Social Recruiting

How to Find People to Recruit on Twitter using Followerwonk & Google + Bing X-Ray Search

Google Plus Search Guide: How to Search and Find People on Google Plus

Facebook’s Graph Search Makes it Ridiculously Easy to Find Anyone

How to Effectively Source Talent on Social Networks – It Requires Non-Standard Search Terms!

How a Recruiter Made 3 Hires on Twitter in Six Weeks!

Twitter 101 for Sourcers and Recruiters

Anti-Social Recruiting

How Social Recruiting has NOT Changed Recruiting

Social Recruiting – Beyond the Hype

What Social Recruiting is NOT

Sourcing Social Media Requires Outside the Box Thinking

Social Networking Sites vs. Job Boards

LinkedIn Sourcing and Recruiting

Sourcing and Searching LinkedIn: Beyond the Basics – SourceCon Dallas 2012

LinkedIn’s Dark Matter – Profiles You Cannot Find

How to Get a Higher LinkedIn InMail Response Rate

The Most Effective Way to X-Ray Search LinkedIn

LinkedIn Catfish: Fake Profiles, Real People, or Just Fake Photos?

LinkedIn Search: Drive it Like you Stole It – 8 Minute Video of My LinkedIn Presentation in Toronto

How to Search LinkedIn and Control Years of Experience

How to Quickly and Effectively Grow Your LinkedIn Network

How to View the Full Profiles of our 3rd Degree Connections on LinkedIn for Free

How to Find and Identify Active Job Seekers on LinkedIn

LinkedIn Profile Search Engine Optimization

Free LinkedIn Profile Optimization and Job Seeker Advice

Do Recruiters Ruin LinkedIn?

The 50 Largest LinkedIn Groups

How to See Full Names of 3rd Degree LinkedIn Connections for Free

How I Search LinkedIn to Find People

LinkedIn’s Undocumented Search Operator

Does LinkedIn Offer Recruiters any Competitive Advantage?

Have You Analyzed the Value of Your LinkedIn Network?

Where Do YOU Rank In LinkedIn Search Results?

What is the Total Number of LinkedIn Members?

Beware When Searching LinkedIn By Company Name

LinkedIn Sourcing Challenge

How to Search for Top Students and GPA’s on LinkedIn

What’s the Best Way to Search LinkedIn for People in Specific Industries?

18 LinkedIn Apps, Tools and Resources

LinkedIn Search: What it Could be and Should be

How to Search Across Multiple Countries on LinkedIn

Private and Out of Network Search Results on LinkedIn

How to “Unlock” and view “Private” LinkedIn Profiles

Searching LinkedIn for Free – The Differences Between Internal and X-Ray Searching

Sourcing and Boolean Search

Basic Boolean Search Operators and Query Modifiers Explained

How to Find Resumes On the Internet with Google

Challenging Google Resume Search Assumptions

Don’t be a Sourcing Snob

The Top 15 Talent Sourcing Mistakes

Why Boolean Search is Such a Big Deal in Recruiting

How to Become a World Class Sourcer

Enough with the Exotic Sourcing Already – What’s Practical and What Works

Sourcing is So Much More than Tips, Tricks, Hacks, and Google

How to Find, Hire, Train, and Build a Sourcing Team – SourceCon 2013

How to Use Excel to Automatically Build Boolean Search Strings

The Current and Future State of Sourcing

Why So Many People Stink at Searching

Is your ATS a Black Hole or a Diamond Mine?

How to Find Bilingual Professionals with Boolean Search Strings

How to Best Use Resume Search Aggregators

How to Convert Quotation Marks in Microsoft Word for Boolean Search

Boolean Search, Referral Recruiting and Source of Hire

The Critical Factors Behind Sourcing ROI

What is a “Boolean Black Belt?”

Beyond Basic Boolean Search: Proximity and Weighting

Why Sourcing is Superior to Posting Jobs for Talent

The Future of Sourcing and Talent Identification

Sourcing is an Investigative and Iterative Process

Beyond Boolean Search: Human Capital Information Retrieval

Do you Speak Boolean?

Is Recruiting Top Talent Really Your Company’s Top Priority?

Sourcing is NOT an Entry Level Function

Boolean Search Beyond Google

The Internet Has Free Resumes. So What?

How to Search Spoke, Zoominfo and Jigsaw for Free

Job Boards vs. Social Networking Sites

What to Do if Google Thinks You’re Not Human: the Captcha

What if you only had One Source to Find Candidates?

Passive Recruiting is a Myth – It Doesn’t Exist

Sourcing: Separate Role or Integrated Function?

The #1 Mistake in Corporate Recruiting

How I Learned What I Know About Sourcing

Resumes Are Like Wine – They Get Better with Age!

Why Do So Many ATS Vendors Offer Such Poor Search Functionality?

Do Candidates Really Want a Relationship with their recruiter?

Recruiting: Art or Science?

What to Consider When Creating or Selecting Effective Sourcing Training – SourceCon NYC

The Sourcer’s Fallacy

Sourcing Challenge – Monster vs. Google – Round 1

Sourcing Challenge – Monster vs. Google – Round 2

Do You Have the Proper Perspective in Recruiting?

Are You a Clueless Recruiter?

Job Boards and Candidate Quality – Challenging Popular Assumptions

When it Comes to Sourcing – All Sources Are Not Created Equal

Boolean Search String Experiments

Boolean Search String Experiment #1

Boolean Search String Experiment #1 Follow Up

Boolean Search String Experiment #2

 

Google Plus Search Guide: How to Search & Find People on G+

 

Do you want to know how to search for people on Google+ by title/skill, company, AND location?

If so, you’ve come to the right place – I’m going to show you 3 different ways to find people on Google+, and only one of them allows you to reliably search for and find people based on where they live:

  1. Google+’s built-in search functionality
  2. FindPeopleonPlus
  3. Using Google to X-Ray search Google+ (the most effective way!)

Back in 2011 I wrote a post about how to search Google+ to find people in specific locations. At the time, Google+ wasn’t a ghost town, but it wasn’t exactly well populated.

Nearly 2 years later, that’s no longer the case – Google+ now has over 500M profiles, 235M+ of them actively using Google+ features, and 135M+ people are active in the Google+ stream, solidly positioning Google+ in the upper tier of the “Big 4” social recruiting sites (Facebook, LinkedIn, Google+, Twitter).

In fact, Google+ is now actually the #2 most actively used service online:

 

 

Google+ Native Search Functionality

While the massive change in users and activity has been great, one thing that unfortunately hasn’t changed is that Google+ still doesn’t have any built-in functionality to reliably search for people by specific location, which is critical to any sourcing and recruiting effort.

While Google+ has recently released a new “Find People” functionality, it doesn’t allow you to find people by where they are located.

What you can do, however, is search for people who work at specific companies using the “Find coworkers” search functionality and entering in any company.

Searching Google+ via Find Coworkers

 

Google+ Find Coworkers

 

For example, searching for “coworkers” at Rio Tinto (world leader in mining and processing):

 

 

Here are some of the results – all currently employed at the target company:

 

 

What you can’t do with this search functionality is search by people who work at specific companies in specific locations. which is critical to most sourcing and recruiting efforts.

However, if you’re new to Google+, you should be impressed by your ability to find anyone.

In this respect, Google+ is similar to Facebook’s Graph Search and unlike LinkedIn, as you don’t have to be connected to people or have them in Circles to find them and view their profiles, which is fantastic for sourcers and recruiters.

Searching Google+ via the Google+ Search Bar

Moving on to Google+’s search bar, you can try to find people in a specific location by simply typing in a city along with the rest of your query. For example, take a look at the results for a simple search such as “software engineer” “new york” “google”

 

 

Pretty decent results, right?

Don’t be fooled by appearances.

You can see from just that screenshot that not all of those people work at Google (although many do), and if you explore the results individually, you’ll find that they all mention “New York” somewhere (as they should, based on my search criteria) – but they don’t all live in New York.

For example, taking a closer look at one of the results:

 

 

You can see she attended school in New York, but her location isn’t revealed on her Google+ profile as it is for others.

Cross referencing her on LinkedIn shows she lives in California.

 

 

I’m not slamming Google+’s search bar – it does a decent job, but it doesn’t offer sourcers and recruiters the search precision they need.

Just to show you that Google+ isn’t only useful for sourcing and recruiting software engineers in the U.S., for my readers in Oz, here’s a simple search for people at Rio Tinto in Perth:

 

 

FindPeopleonPlus

Some of you may be aware of FindPeopleonPlus, which you can use to find people by employer, occupation, and location.

For example, here is a search for software engineers who work at Google and live in New York:

 

 

Looks great, right?

Unfortunately, according to their own website, FindPeopleonPlus has only indexed 45M users, which is now obviously a small portion of the total population of Google+ users.

The above search found 109 people, which isn’t too shabby. However, I’ll show you how to use Google to X-Ray search Google+ to find more people in a moment.

FindPeopleonPlus does have some great functionality – you can search for/sort people by gender (diversity sourcing!), education (specific university), employer, occupation, state, and city.

Interestingly, it appears they are busy building a “Career Platform” – I’m assuming this won’t be free because what they’ve already built can easily be used by recruiters to find candidates.

 

 

Hopefully they will speed up their performance – I noticed my searches lagged significantly. But maybe I’m just spoiled.

Oh, and I just had to share these two nuggets of gold I found when exploring FindPeopleonPlus for this post:

 

 

Matt’s got a sense of humor. Maybe Kelly can add the ability to search Google+ for people by employer, occupation and location like FindPeopleonPlus can.

Am I the only one that is confused and disappointed by the fact that the Google team hasn’t thought to offer a greater degree of search capability? Even Facebook’s Graph Search offers the ability to search by location, current and past employer, current title, etc.

I thought Google = search?

How to Find People on Google+ by Location: X-Ray Search

To this day, using Google to search Google+ remains the best way to reliably find people on Google+ by location.

Over time, Google+ has made multiple changes to Google+ profiles, so while my original (circa 2011!) Google+ X-Ray search still works, there are a few small adjustments I’ve made based on profile changes that allow even greater control over search results (thanks Google+ team!).

Back in 2011, when it came to listing locations on Google+ profiles, they were displayed in the “Places Lived” section.

“Places Lived” doesn’t exist anymore – it’s now just “Places,” and the word “lived” is no longer there to search for exactly as I did in the past.

However, location information from Google+ profiles is now often also displayed in the summary info at the top of a person’s profile, and it can be listed as “Lived in ________” or “Lives in _________” – you can search for either or both.

X-Ray Searching Google+ for “Lived in”

Here is an example of a Google X-Ray search of Google+ to find software engineers who work at Google in New York, using “lived in _______:”

site:plus.google.com “lived * new york” “software engineer” “works * google”

 

 

Here’s where it’s picking up the “Lived in,” which pulls from their list of locations on their profile.

 

 

Don’t be confused by or concerned with the past-tense “lived in.” For these folks, the first location listed is typically where they currently live…

 

…they just haven’t checked the “Current” box by the location when they edited their profile:

 

 

When checking some of the Google+ results to see if the the people did in fact live in the location I specified, I cross referenced them on LinkedIn.

Interestingly, when I cross referenced one of the results from my New York search on LinkedIn, their LinkedIn profile stated that they currently lived in Bulgaria instead of New York, which was initially disappointing, at least until I performed a Facebook Graph Search for her, where I was able to confirm she does in fact live in New York.

 

Google+ cross reference location on Facebook Graph Search

 

Hopefully I am not the only who finds this interesting, although not all that surprising when you think about it – Facebook can be more accurate than LinkedIn.

X-Ray Searching Google+ for “Lives in”

Here is the exact same search as above, which is a Google X-Ray search of Google+ to find software engineers who work at Google in New York – except in this case, I am using “lives in _______:”

site:plus.google.com “lives * new york” “software engineer” “works * google”

 

 

You’ll notice some dupes in the results for hits on the same person from multiple places on their profile, such as the “About” and “Videos” sections.

If you wanted to clean those up, you could run something like this:

site:plus.google.com “lives * new york” “software engineer” “works * google” -inurl:(about|photos|videos) – you’ll get 118 clean results from the original 135.

One thing you can do using Google to X-Ray search Google+ for profiles that you can’t do on FindPeopleonPlus is Boolean search with no limitations.

For the Boolean bashers (I know you’re out there!), basic Boolean logic allows the ability to search for multiple titles, skills, and or companies in a single search string. Although FindPeopleonPlus does support basic Boolean logic for keywords, they don’t allow the use of Boolean logic to simultaneously search for any of a number of employers or occupations/titles.

With a search interface similar to FindPeopleonPlus’s, you’re limited to one company, title, etc. at a time per search. Yes – it still “works,” but it feels like wearing mittens vs. fingerless gloves when you know how to get exactly what you want and you can’t get exactly what you want in a single search like you can with Google.

For example, we can search for any of 3 titles at once using Google to X-Ray search Google+:

site:plus.google.com “lives * new york” (programmer | developer | “software engineer”) “works * google” -inurl:(posts|about|photos|videos|plusones)

That Google search returns 137 results in New York.

With FindPeopleonPlus, you get 3 results in the entire world.

Going one step further with Google+ site: search, you can search for both “lived in” and “lives in” in the same string to get 152 results:

site:plus.google.com (“lives * new york” | “lived * new york”) (programmer | developer | “software engineer”) “works * google” -inurl:(posts|about|photos|videos|plusones)

Of course, you don’t have to target companies in your search strings.

In fact, you can also search for people that don’t even mention their employer in the “work” section (although they do mention it somewhere else):

site:plus.google.com (“lives * new york” | “lived * new york”) (programmer | developer | “software engineer”) -“works * “ -inurl:(posts|about|photos|videos|plusones)

Like this person:

 

Google+ search result profile with no current employer. Kind of. :)

 

There are many other interesting things you can do with Google+ X-Ray searches – I just wanted to provide you with a few “starter” searches to get you going.

Google+ Got Your Attention Now?

There’s no doubt that LinkedIn is “where it’s at” with regard to deep and highly searchable human capital data, and I don’t think LinkedIn is becoming “saturated” as many people seem to be suggesting recently – most sourcers/recruiters only find and review 20-30% of what’s available to be found on LinkedIn, leaving at least 50M (if not 100M+!) profiles unfound/unviewed. No, I am not exaggerating for effect.

Even with sourcers and recruiters only scratching the surface of LinkedIn, Google+ cannot be ignored.

Google+ now has more profiles than LinkedIn and is the most active social network in the world second only to Facebook. Yes, I know – Google+ haters/doubters like to argue about what “active” really means…who cares?!?! Most Google+ naysayers haven’t spent 5 minutes on Google+.

Get on Google+ and do some searches and I think you’ll be impressed with what you can quickly and easily find. Explore Google+ a little bit (actually USE it for a few weeks) and I think you’ll be surprised by the functionality and the many benefits and advantages if can afford sourcers and recruiters.

Check out the kind of information you’re missing if you’re not searching Google+:

 

 

Yes, that’s an email address I blurred out. It’s there for anyone to find – it’s not listed because I know them or have them in a Circle – because I don’t.

Unlike LinkedIn, I’ve found that software engineers and other non-recruiting professionals do include email addresses and sometimes even phone numbers on their profiles that anyone can see – like the phone number of this UX Engineer at Microsoft:

 

Google+ mobile phone number

 

Of course, there are many advantages of using Google+ in your sourcing and recruiting efforts that are beyond the scope of this post.

As for me – I don’t care if you never use Google+ for sourcing and recruiting. It just means I have less competition.

:)

 

Facebook Graph Search Sourcing and Recruiting Initial Test Drive

 

 

For those who don’t yet have access to Facebook’s Graph Search – I put together a video detailing 5 live searches for:

  • product managers who work at Microsoft and live in Seattle
  • software engineers who work at Google and live in New York
  • (developer OR programmer OR engineer)
  • underwriters in Charlotte
  • accountants who live near Alpharetta

I must say that playing around with Graph Search’s natural language query functionality and long list of search options is quite fun. You can easily search for diversity, current titles and employers, years of experience, and of course education.

However, as you can see in the video, my main concern about the limitations of Facebook’s usefulness in sourcing and recruiting is the lack of professional information and the the shallow depth of what is there to be found.

Being able to search for and match people by title and company is useful for some recruiting needs and completely useless for others who need to find professionals with specific experience that cannot be reliably predicted by title alone.

Of course, the allure of the potential of using Facebook for recruiting is largely based on the fact that Facebook has over a billion users globally.

However, Facebook’s challenge in any effort to become a major player in the recruiting solution space is that many people don’t view Facebook as a place to put their professional information so they don’t enter work information on their Facebook profile. Even if they did, they do have the opportunity to hide it from people they don’t know, which is great for them, but bad news for sourcers and recruiters.

What I found especially interesting from my initial test drive of Graph Search is that the number of results for each search was a small fraction of what I know has to actually be available, at least in theory, given the number of Facebook users.  For example, Graph Search returned less than 100 people for a search for people who are accountants in the Alpharetta, GA area, while LinkedIn has nearly 6,000. That’s a massive differential!

Do you think that the accountants on Facebook who live in the Alpharetta area just don’t put their work experience on their profile, or that they hide the info from being retrieved by people other than their friends? I’d argue the former at this point. Keep in mind that this issue not only affects search, it also affects advertising. You can’t use Facebook PPC ads to target people who don’t give you critical information to target.

I’ll be posting more videos soon – so stay tuned to see more practical Facebook Graph Search sourcing and recruiting examples.

Oh, and if you didn’t have time to watch the video, no – Facebook’s Graph Search doesn’t currently support Boolean logic.

 

No, Facebook's Graph Search doesn't currently support Boolean search. I am hoping the operative word is "currently," because the ability to run more specific and precise conceptual queries is critical to what sourcers and recruiters need to accomplish

 

 

My SourceCon Presentation – LinkedIn: Beyond the Basics

 

I was honored to be asked to present at the Dallas 2012 SourceCon event – which turned out to be the largest SourceCon event ever!

When I was talking with Amybeth Hale back at the end of 2011 about what I’d like to present on, I asked if anyone had ever run a session solely dedicated to LinkedIn.

Now, I’ve been to every SourceCon save 2 (the first one and 2011/Santa Clara), I’ve spoken at 5 of them, and I couldn’t recall anyone delivering a LinkedIn presentation, and neither could Amybeth (for the ones I missed or sessions I did not attend).

That struck me as beyond odd, given how valuable a resource LinkedIn is for sourcing and recruiting.

What you see below is the deck from my “LinkedIn: Beyond the Basics” session, complete with YouTube videos.

 

 

How Would You Search for these Positions on LinkedIn?

One of the things that has always struck me as extremely odd with regard to sourcing is the fact that there appears to be so little sharing of Boolean search strings.

While one can find basic search string examples in training materials and in various sourcing groups online, I know plenty of sourcers and recruiters that have never seen another person’s production search strings – those used to actually fill positions.

Why do you think that is? I have my ideas, and I’d like to know yours.

I believe there may be several contributing factors:

  1. Some people just don’t save their searches. If I were a betting man, from what I’ve seen over the past 15+ years, I’d wager that the majority of people don’t save their search strings. If they’re not saved anywhere – you severely limit any sharing opportunities to live, in-the-moment situations that may or may not ever present themselves.
  2. It simply never occurs to some people to share their searches with others – unless someone specifically asks, why would someone?
  3. Plain old insecurity. Some folks might not want to share their search strings with others because they are afraid theirs are somehow “wrong,” inferior or inadequate.
  4. The belief that their Boolean search strings are somehow their “secret sauce” and that in sharing their searches might somehow expose their competitive advantage.

What do you think?

How Would You Search for these Positions on LinkedIn?

Are you up to the challenge of sharing some of your searches with a global audience of talent acquisition professionals? Continue reading

Why Boolean Search is Such a Big Deal in Recruiting

In the past, 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
  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 sourcing, 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 engage, recruit, acquire, hire and develop 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 sourcers to perform feats of talent identification and acquisition most would think impossible.

Continue reading

Top 15 Common Talent Sourcing Mistakes

Practically everything I have learned about sourcing and recruiting didn’t come from a mentor or any formal training.

Instead, I learned how to become a top performing recruiter “the hard way.”

What that really means is that when it came to finding top talent, I tried a lot of things that didn’t work, and because I refuse to make excuses, give up, or accept anything less than the best results, I kept experimenting until I discovered things that enabled me to find people that others can’t and don’t.

With over fifteen years of experience in sourcing and recruiting, I’ve made my fair share of mistakes along the way. I’ve also had the opportunity to assess, train and coach corporate and agency sourcers and recruiters, which has exposed me to many myths, misconceptions and mistakes when it comes to leveraging information systems for sourcing and recruiting.

Here are what I believe to be some of the most common productivity-robbing and results-reducing mistakes sourcers and recruiters make when looking for the right match.

In no particular order… Continue reading

Is Your ATS a Black Hole or a Diamond Mine?

Most companies and staffing organizations, ranging from executive search sole proprietorships to staffing agencies to Fortune 500 companies, have internal databases filled with rich and actionable 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, this post on Weddles details that an 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 information retrieval capability.

As such, like a black hole, prospective candidates go in, but they don’t come back out.

If you can’t easily search your internal database, how can you determine the total candidate population, let alone find the top talent hidden within?

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.

The bottom line is that data has no value if you can’t retrieve it.

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/placements.

The Time Value of Resumes

Even after 15 years in recruiting, I am still shocked to hear HR pros, sourcers, recruiters, and talent acquisition leaders comment about how resumes get “stale” and lose their value after 6 months.

While the information on resumes certainly goes out of date over time, the resumes themselves do no lose their value.

In fact, I argue that resumes get more valuable over time.

This is because the active candidates you capture today become the passive and non job seekers in time – yes, those magical people that are supposedly so valuable and so difficult to find.

Right in your database.

With phone numbers and email addresses.

That person that responded to your job posting a year ago will not likely be actively looking today, will not have their resume posted online anywhere, and will not have updated their LinkedIn profile for quite some time – yet, you have their contact information, and it doesn’t take a rocket doctor to figure out what kind of opportunity they would be interested in.

Although you don’t know exactly what a person whose resume is a year or more old is doing now, most people follow a relatively predictable career trajectory.

I’ve personally dredged up resumes from an ATS that were over 4 years old and got them hired.

When I called one of these candidates, he asked me, “How did you know I was looking?” I replied, “I didn’t – your resume is 4 years old – I don’t even know if you’re doing the same kind of work.”

He was.

It also turned out he was beginning to think about making a change, but hadn’t even written his resume.

I had caught him at the perfect time, before anyone else could even imagine of finding him. The funny thing is that most people probably wouldn’t have even called him simply because his resume was “stale” and out of date.

This and many more similar examples I have prove the time value of resumes.

However, you can’t leverage the time value of resumes if you can’t quickly, easily, and precisely retrieve them!

Coal Into Diamonds

For each position sourced for and posted online, there are inevitably volumes of potential candidates that do not fit, as well as candidates that do not get interviewed and hired.

However, this does not mean that they are bad or unqualified people.

In fact, many of the people who respond to job postings are very good candidates – they’re just not very good at matching themselves.

Those under qualified candidates? While they may not meet the basic qualifications of the specific job the responded to, that doesn’t mean that they aren’t fully qualified for other jobs that are open now, or jobs that will open in the future.

In a year or two, they will have a year or two more experience and be a qualified candidate.  See the Time Value of Resumes above.

What about those over qualified candidates? While they may be “over qualified” for the position they applied to – they may in fact be qualified for other openings now and in the future.

What about those applicants that are a complete mismatch for the positions they applied to? They often match other currently open and future jobs.

How about the people who almost got the job? For every opening, there can only be one hire, so there is often a slew of strong runners-up that could be fantastic candidates for other opportunities.

Over the years, I’ve consistently found time and again that what appears to be coal can quickly turn into diamonds.

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 3 main ways a person can end up in a company’s ATS:

  1. They responded to a job posting
  2. Someone ran a search and found the candidate’s profile/resume on the Internet, on a resume database such as Monster, Dice, Careerbuilder, etc., or on LinkedIn and entered it into the database
  3. The person was a referral and entered into the system

In all three cases, someone – either a potential 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.

Looking to Build a Talent Community?

Everyone seems to want to build a “talent community” these days.

What I find funny is that many companies are already sitting on the makings of a talent community in their own ATS.

Anyone in your ATS got there either because they wanted to join your company (they responded to a job posting) or because you wanted them to join your company (you sourced them).

Can you think of a better population for a talent community?

If your ATS doesn’t have CRM functionality that enables you to stay in touch with the people who’ve expressed interest in your company and the people you’d like to potentially employ, it’s time for you to start thinking about what you can do about this, because you’re sitting on a diamond mine.

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!”

Demand an ROI on Your ATS!

Many companies spend tens of thousands to hundreds of thousands of dollars on their Applicant Tracking/CRM systems, and they should expect demand 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 You 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 or expressed interest in your company 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, Sovren, 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 simply because the sourcers and recruiters 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.

In my first year as an agency recruiter, I 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 Google, 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 and from people who have expressed an interest in joining your company.

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!

Boolean Search Strings, Referrals and Source of Hire

I read an article on ERE about the other day titled “Love Writing Boolean Instead of Recruiting? Then Don’t Read This Post.

While I happen to be pretty good at and thoroughly enjoy writing Boolean queries for talent mining, I actually love the entire recruiting life cycle. Sourcing is a means to an end, not a means in and of itself for me. Even so – with such a provocative post title (nice work John!), I had to read the article.

The article is a pretty strong pitch for Scavado, which “does the search work for you, saving hours of time otherwise spent developing Boolean search strings and applying them manually to each site searched.”

Things really got interesting when I got down to the comments on the article, as I stumbled into an interesting exchange between Amybeth Hale and Keith Halperin which covered direct sourcing, referral recruiting, and outsourcing sourcing at $6.25/hour.

Read on to learn my thoughts on all of the above. Continue reading

What is a Boolean Black Belt Anyway?

I’ve been blogging nearly 3 years 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 – but 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.

Interestingly, however, I’ve found that most sourcers and recruiters don’t even fully exploit the various powers of the OR and NOT operators – not even close.

So what is a “Boolean Black Belt” anyway? Continue reading

Talent Sourcing: Beyond Tips, Tricks, Hacks and the Internet

It’s bothered me for quite some time now that many people essentially equate sourcing with Internet search – using search engines such as Google and Bing to find resumes, lists, press releases, etc.

It bothers me because sourcing is so much more than that.

It also bothers me because I am aware that many companies (some quite large and well respected) limit their sourcers and recruiters primarily to the Internet as the only source of information.

I believe a major contributing factor as to why sourcing isn’t highly valued by some organizations and why sourcing doesn’t get as much widespread respect and recognition as it should is because too many people associate sourcing primarily with Internet search.

The future of talent sourcing will involve a shift from manual Internet search and ATS/CRM systems with only rudimentary search and analysis capability to highly specialized tools specifically designed for mining vast and proprietary human capital data sets dynamically compiled from multiple sources that enables predictive analytics.

It’s coming – will you be ready? Will you be ahead of the curve or behind it? Continue reading

Beyond Boolean Search: Proximity and Weighting

Beyond Basic Boolean

Most sourcing, recruiting, and staffing professionals are familiar with the basic Boolean operators of AND, OR, and NOT. However, I have found that few are familiar with what some refer to as “extended” Boolean functionality, such as proximity search and term weighting.

Proximity and term weighting, where supported, are not actually logical (Boolean) operators – they are more accurately referred to as text or content operators.

Whatever you call them – extended Boolean or text operators – they offer sourcers and recruiters significantly more control, power and precision when executing searches, and in the hands of an expert, they can enable semantic search. Continue reading

Beyond Boolean: Human Capital Information Retrieval

When I recently spoke at SourceCon in New York, I showed an example Boolean search string that could be used as a challenge or an evaluation of a person’s knowledge and ability.

The search string looked something like this:

(Director or “Project Manage*” or “Program Manage*” or PM*) w/250 xfirstword and (truck* or ship* or rail* or transport* or logistic* or “supply chain*”) w/10 (manag* or project)* and (Deloitte or Ernst or “E&Y” or KPMG or PwC or PricewaterhouseCoopers or “Price Waterhouse*”)

During the presentation, an audience member asked me why there wasn’t any use of site:, inurl:, intitle:, etc. I responded by acknowledging that for many, sourcing and Boolean search seems to be synonymous with Internet search – however, this is definitely not the case. Continue reading

Are You Fluent in the Language of Information Systems?

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 language – 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.

Every day, most people interface with information systems of some kind – computers (tablets, laptops, smart phones, etc.), the Internet (search engines, web sites/apps, 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.

Continue reading