Tag Archives: Recruiting

Social Engineering: The Human Element of Sourcing & Recruiting Candidates

Why is the “Boolean Black Belt” writing and presenting about social engineering?

Well, it’s actually quite simple. It all started over 20 years ago when I began working for a small, privately held IT staffing firm in Northern VA. In pursuit of becoming the top performing recruiter, I not only had to get very good at quickly finding the right people, I also had to get very good at getting those people to respond to my outreach efforts, to be open to speaking candidly with me, and ultimately to convert to candidates. As we all know, unless you are responsible for sourcing names only, finding people is only half the battle – although a critical half, as you can’t convert someone into a hire that you haven’t found in the first place. ;)

While the vast majority of the content I’ve written about since 2008 has been about finding people online and in databases, that’s only one of my three “superpowers” – things that I believe I developed exceptional strength in that enabled me to become a top performer in my firm. The other two include my time/performance management approach and what I have now learned to be social engineering.

Social engineering is, according to Chris Hadnagy, creator of the Social Engineering Framework, “The art, or better yet, science, or skillfully maneuvering human beings to take action in some aspect of their lives.”

I saw Chris speak at the 2011 SourceCon in NY, although he didn’t really dive deep into the concepts of the book he had published at the end of 2010 – Social Engineering, The Art of Human Hacking, and it wasn’t until Jeremy Roberts wrote about Chris’s book in early 2015 that I actually got around to purchasing and reading the book.

As I was reading the first half of the book, I had many epiphanous moments when I realized that many of the things I had been doing in my candidate messaging and when on the phone with potential candidates beginning nearly 20 years prior and continuing over the years training my teams to perform had names (elicitation, framing, preloading, etc.) and psychological reasons why they worked (e.g., empathy, scarcity, social proof, obligation & reciprocity, etc.). This inspired me to present on the topic at sourcing and recruiting conferences, as it makes it 10X easier to explain and transfer to people when you can attribute names to specific techniques and explain the “why” behind why you should do it and why it works.

This deck from SourceCon 2018 in Vegas, where the whole theme was social engineering and we had a keynote by Jessica Clark (who I sourced and Shannon Pritchett successfully recruited), and is the latest iteration of my social engineering content that I have also presented at LinkedIn Talent Connect, SOSUEU, Bullhorn Engage and the Northwest Recruiters Association (NWRA). It provides a high-level overview of many social engineering strategies and tactics that I have personally used in a “white hat” manner when seeking to influence potential candidates to respond to outreach efforts, be open to speaking candidly with me, provide high quality referrals, and convert to being a qualified, interested and available (QIA) candidates.

As you will see in the deck, social engineering is essentially the human element of sourcing and recruiting candidates. Enjoy!

Video: Discussing AI in Sourcing and Recruiting

I recently had the chance to participate in a Google Hangout with Jeremy Roberts of HiringSolved as an introduction to the speakers of their upcoming conference on Feb 7 in NYC (HIREconf).

You can watch the recording of our chat here or play the video below to learn a little about my background and my thoughts about the evolving role of technology and specifically artificial intelligence solutions when it comes to sourcing and recruitment, which will be the topic of my opening keynote at HIREconf. I’m planning on addressing how intelligent machines are changing talent acquisition and how sourcers and recruiters can prepare for today and tomorrow.

https://youtu.be/8yOHA2d66jU

The folks at HiringSolved have really put together a solid list of speakers for their 1 day event in NYC:

Here’s a peek at the agenda:

hireconf-agenda

If you can make it, I’d love to see you there!

The Best Boolean and Semantic Search Tool

While many people are hungry for specific Boolean search strings to copy and paste and for search tools that make searching for people “easier” and even “do the thinking for you,” there simply is nothing that can come remotely close to what you can do when you think properly and ask the right questions.

Yoda Think Before You Search

That’s right – the most powerful thing you can incorporate into your people search efforts isn’t Boolean logic, a search “hack,” Chrome extension, search aggregator, semantic search solution or anything you can buy – it’s your brain. Your level of understanding of and appreciation for the unique challenges posed by human capital data in any form (social media profiles, resumes, etc.) directly correlates to your ability to extract value from any data source. The same is true of the thought processes you apply before and during your search efforts.

A little over a year ago, I presented for the 3rd time at LinkedIn’s Talent Connect event in London, and I spoke about how to leverage LinkedIn’s massive stockpile of human capital data for sourcing and recruiting. LinkedIn recorded the session and uploaded the video to YouTube, and I recently noticed the video had over 65,000 views. Now, while that is puny in comparison to the nearly 1B views Adele’s Hello video has racked up, I was surprised to see so many views given the niche content.

Although the source of human capital data that I focus on in the video happens to be LinkedIn, practically everything I talk about is equally applicable to any source you can use to find people to recruit.

So, if you use any source of human capital data to find and recruit people (e.g., your ATS/CRM, resume databases, LinkedIn, Google, Facebook, Github, etc.) and you really want to understand how to best approach your talent sourcing efforts, I recommend watching this video when you have the time.

Enjoy, and feel free to let me know your thoughts!

 

How to Get People to Respond to Recruiting Emails & Messages

When it comes to sourcing and recruiting, it’s gotten easier to find people but it’s gotten more difficult to get people to respond to emails, InMails, social messages and voicemails.

The poor quality and lack of sophistication of most recruiter messaging, along with rampant spamming, certainly hasn’t helped. Unfortunately and yet somewhat thankfully, the bar of what people expect to receive from recruiters has been set fairly low, so the opportunity for improvement is massive. The good news is that becoming more effective at getting people to respond to recruiting outreach efforts is relatively easy because marketing & advertising has already blazed the trail – sourcers and recruiters would do well to leverage what effective sales & marketing teams has been doing for decades.

In 2014 and 2015, I spoke at Talent 42, SOSUEU, and LinkedIn Talent Connect conferences on the challenges of getting people – especially “passive,” highly recruited talent – to respond to recruiter outreach efforts. The decks I used for the presentations were mostly images, so I decided to add text to the slides so that the core concepts could be understood by anyone whether they attended those conference sessions or not simply by viewing the presentation (I wish more presenters would do this!).

Sourcing & Recruiting Candidate Funnel & Output Calculators

Candidate Sourcing FunnelHave you ever wondered:

  1. How many resumes, social profiles, names, etc., you have to identify to result in 1 hire?
  2. How efficient your sourcing/recruiting/hiring process is?
  3. How many candidates you need to submit to fill your position?
  4. How more effective messaging/engagement strategies and tactics can measurably improve your efficiency?
  5. How wonderful it would be if you could educate your hiring manager/team on exactly how much effort goes into producing 1 hire, and the effects of a poor assessment/hiring process?
  6. The # of hires per month a sourcer/recruiter can affect per month based on their daily activity?
  7. How many sourcers/recruiters you need to achieve a target # of hires per month?

If you answered “Yes!” to any of the above, you’re in luck, because I’ve whipped up a couple of candidate funnel and sourcing team calculators that can help you answer those questions and more.

Candidate Sourcing Funnel Calculators

You can grab a copy of the file here or simply click the image below:

Candidate Sourcing Funnel Calculator

By entering your target # of hires and setting your percentages/conversion ratios at each step of the funnel, you can see the estimated number of people you would have to identify in order to achieve your hiring goal, as well as the estimated number of people you will actually talk to and submit for consideration, and the number of interviews that would need to take place.

As you could imagine, this data can be used to manage expectations of hiring teams, because in some scenarios, the local talent pool might not be big enough (i.e., there may not be 67 local Mandarin speaking Ruby developers). :)

If you’re not doing so already, I highly recommend you start to measure the following per job, hiring manager, group/division, skillset, etc.:

  1. Response rates
  2. % of people who are QIA out of those who are successfully contacted
  3. % of candidates who pass prescreens (if any are used – e.g., technical, online assessments, etc.)
  4. % of candidates selected to interview
  5. % of candidates who receive an offer after interviewing
  6. % of people who accept their offer (and actually show up!)

If you’re measuring these data points, you can add them to your candidate funnel calculator to much more accurately predict how many people you will need to identify and submit in order to produce a hire.

More importantly, these data points can help you identify constraints/challenges in your candidate sourcing and recruitment process and you can work with your hiring teams to try to improve the conversion ratios at each step of the funnel. For example:

Response Rates

You could try to affect a higher response rate from potential candidates by working with the hiring team to create compelling descriptions of the work, team and environment, incorporate sound bites & testimonials from existing employees, and even leverage members of the hiring team to reach out to potential candidates. Higher response rates can drastically effect the candidate sourcing funnel, reducing the # of people that must be identified to achieve the target # of hires. Keeping everything else the same as the above sourcing funnel, simply changing the response rate from 25% to 40% can reduce the # of people needed to be identified from 67 to 42. If you could achieve a 75% response ratio, you’d only have to identify 22 people.

Submittal to Interview Ratio

If the % of candidates submitted that are selected to interview is lower than 100%, there could be a number of contributing factors to explore, such as:

  • The sourcers/recruiters don’t fully understand the position they are working on and the manager/group they are supporting and what entails the right match
  • The sourcers/recruiters are not doing a good enough job of packaging up their candidate submittals so that the hiring team can see them for the matches that they really are
  • The hiring team is being too picky and judging candidates on their resumes alone
  • The hiring team doesn’t really know what they are looking for (unfortunately, this happens too frequently!)

Prescreen

If the data shows that a relatively small % of people pass the prescreen, it might indicate that the prescreen is poorly designed, with either a poor user experience (I had a situation where the prescreen was so long and laborious people would simply abort and withdraw) and/or it is not an accurate way of determining candidacy.

Offer Acceptance

If the data shows a relatively low offer acceptance ratio, you should work with your hiring team to perform a root cause analysis, including following up with the people who have rejected offers to find out why and work with the hiring team to see if you can address any patterns (e.g., lower than market compensation, poor interview process, work seemed boring, etc.).

Local Talent Pool

Even with high conversion ratios all along the funnel, the number of estimated people that must be identified to produce the target # of hires might end up being an unrealistically high number depending on the requirements of the hiring team, and leveraging the data can foster a collaborative conversation on alternatives, such as opening up the search to non-local candidates, reducing some of the hiring requirements (e.g., the local talent pool for mobile application software engineers with ecommerce experience is small – the hiring team may decide that ecommerce experience isn’t actually necessary, opening up the local talent pool), etc.

Of course, you can build upon these calculators and to mirror your specific processes, as well as measure and model things such as % candidates submitted by sourcers that are “accepted” by the recruiters as viable, candidate:applicant conversion ratios, withdrawals, no shows (interviews and/or day 1 walk on), etc. Feel free to modify/build upon what’s already there to better suit your specific needs.

NOTE: You may notice some funny looking numbers showing up in the calculators at times (e.g., 75% of 2 isn’t 1), and this will be due to the fact that I formatted some cells to only display whole numbers (# candidates engaged, submitted, selected for interview, etc.). Feel free to reformat those cells to show 1 or 2 decimal places if you don’t mind seeing fractional numbers in those areas, although I do hope you realize fractional people don’t exist. :)

Sourcing/Recruiting Team Output Calculator & Team Estimator

On the second worksheet of the file above you will find a sourcing/recruiting team output calculator. Once you enter the number of people each sourcer/recruiter can consistently find/identify per day, the calculator will estimate the number of candidates engaged daily and the number of candidate submittals, interviews and hires affected daily, weekly and monthly per sourcer/recruiter.

You can also enter your target # of hires per month to estimate the # of sourcers/recruiters you will need to achieve your monthly hiring goal.

Daily Sourcing Recruiting Activity Output Calculator Per Sourcer or Recruiter

What Do You Think?

Let me know if you find these calculators helpful, and don’t hesitate to let me know if you find any glitches I need to fix or if you have suggestions for improving them.

Thanks!

How to Use Facebook for Social Recruiting Messaging

 

When it comes to sourcing and recruiting, you should not ignore the potential of Facebook given that it has 1.38B monthly active users and 890M daily active users.

Also, you should know that according to Jobvite’s 2014 Job Seeker Nation Report, 76% of social job seekers found their current position through Facebook.  Jobvite also found that while job seekers flock to Facebook, recruiters prefer LinkedIn when searching for potential candidates.

Jobvite 2014 Job Seeker Nation Report

That’s understandable, as LinkedIn is a professional social network and some profiles are as detailed as resumes. While Facebook users seem to be adding more professional information on a daily basis, that information is quite limited.

As I’ve written recently, even though Facebook’s Graph Search isn’t as powerful as it once was, finding people to recruit on Facebook is remarkably easy. If you want even more information on using Facebook to find people, check out Todd Davis’ Ultimate Guide to Sourcing and Recruiting on Facebook.

However, one thing that isn’t being written about much is using Facebook to reach out to potential candidates. Some people simply may not know all of the ways you can message people on Facebook (there is more than meets the eye, as you will see), and many sourcers and recruiters seem to get caught up on thinking that people will be “weirded out” by getting messages from them on Facebook – I’ll be addressing this as well. Continue reading

Video: My thoughts on Sourcing & the Future of Recruiting

 

At LinkedIn’s 2014 Talent Connect event in San Francisco, I had the opportunity to be interviewed on the topic of up-skilling recruiting teams.

Watch this short video to hear my thoughts on the ideal sourcing/recruiting team alignment, critical skills for any recruiting team, and the future of recruiting (hint –  it has something to do with data).

Insights from LinkedIn’s 2015 Global Recruiting Survey

 

LinkedIn Global Recruiting Trends

Job boards vs. social media: What’s the most significant source of hire for companies globally?

LinkedIn recently surveyed over 4,000 talent acquisition leaders in 31 countries, gaining insights into source of hire, quality of hire, quantity of hire, talent brand, the future of recruiting and more, so if you haven’t already downloaded and reviewed LinkedIn’s 2015 Global Recruiting Trends e-book, I highly recommend you do so by clicking here.

While I’m going to share a few of the insights from the Global Recruiting Trends e-book (including the job boards vs. social recruiting), I highly encourage you to compare them with LinkedIn’s country specific recruiting and staffing e-books (Southeast Asia, Australia, India, U.K., Italy, Belgium, etc.) which can be found here. There are some significant differences, specifically when it comes to source of hire.

Continue reading

Facebook’s Hiring Surprise is Good For Sourcing & Recruiting

 

Nearly a year ago I stumbled across an interesting post on LinkedIn that revealed that Facebook’s single biggest recruiting focus was NOT what most people would assume.

Can you guess what it might be?

Facebook Open Jobs and Recruiting Needs

Software engineering? Nope.

Infrastructure? Wrong.

People and recruiting? Not even close. Continue reading

Talent42 Keynote: Building Talent Pipelines

 

Glen Cathey - Talent42In theory, building a talent “pipeline” sounds like an ideal strategy, ensuring that you always have a steady supply of the talent you’re looking for.

In reality, there are many issues with building talent pipelines, and they all “leak” extensively.

I recently delivered the closing keynote at the always excellent Talent42 technical recruiting conference where I explored the core issues associated with building talent pipelines, proposed that talent acquisition is essentially responsible for managing a company’s human capital supply chain, and challenged the audience to see that the “war for talent” is really a supply chain management competition.

If you have a difficult time seeing the parallels between talent acquisition and supply chain management, take a look at the definition of supply chain management according to the CSCMP (Council of Supply Chain Management Professionals): “Supply chain management encompasses the planning and management of all activities involved in sourcing, procurement, conversion, and logistics management…It also includes the crucial components of coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers.”

Talent acquisition certainly involves the planning and management of all activities involved in sourcing, procuring/converting candidates and all associated logistics – as such, I believe HR/recruiting organizations need to leverage proven production and supply chain management principles (e.g., Lean, kanban, Just-In-Time, etc.) in their recruiting processes and strategies to gain competitive advantages.

Unfortunately, many companies seem to be very late to the game in this regard. As the ultimate owners of talent acquisition, HR/recruiting should be the experts in human capital supply chain management and processes, leading innovation in this space. However, I have found several examples of global I.T. professionals innovatively leveraging Lean principles to recruit people for their own teams and to manage recruiting processes that should serve as a serious wake-up call to HR/recruiting organizations.

If you’re curious about the core problems associated with proactively building talent pipelines and would like to learn about the many benefits of applying lean principles to the recruiting process, including reducing the “7 deadly wastes,” employing kanban and enabling Just-In-Time delivery, take some time to navigate through the Slideshare below.

My live presentation deck was comprised mostly of images, so I’ve published a modified version that can be consumed without the benefit of hearing me speak to the concepts.

Enjoy, and please do share your thoughts.

How to Find Active & Passive Software Engineers on Stack Overflow

 

Stack Overflow CareersDo you source and/or recruit software engineers?

Would you like to know how to find software engineers on Stack Overflow who are actually interested in hearing about new career opportunities?

For free?

If you answered YES!, YES! and YES! – you’re in in luck, because I am going to show you how to find active and passive job seekers on Stack Overflow for free. Continue reading

Sourcing vs. Recruiting – What’s the Difference?

 

While you may not  know that Balazs Paroczay recently posted a rebuttal of my proposed definition of sourcing, I strongly suggest you read his argument, as I appreciate his perspective as well as the fact that he disagrees with me on the definition of sourcing and I’d like to hear your opinion.

I believe disagreement is important and valuable, because it fuels critical thinking and forward progress.

Before I get to Balazs’s post, I’d like to get your take on a recent disagreement I had with Recruiting Animal. Continue reading

Twitter Sourcing Tool Tactics Cloud Shuts Down

 

Tactics Cloud NoticeI hope my blog post wasn’t somehow the kiss of death for Tactics Cloud, but in only a matter of weeks after writing about how awesome I thought their Twitter search solution was, they will no longer be offering Tactics Cloud as they have decided to focus our efforts on new opportunities.”

Although Derek Zeller discovered that you could still access and search Twitter with Tactics Cloud via this link, the Tactics Cloud crew said they will be shutting that down shortly. At the time of this post, that link was still working, although I am sure that won’t last long.

Enjoy it while you can, before your only real option for searching Twitter bios is Followerwonk and good ol’ fashioned X-Ray searching. Continue reading

Excellent New Twitter Talent Sourcing and Recruiting Tool

 

Tactics CloudDo you leverage Twitter in your sourcing and recruiting efforts?

If NO – I strongly recommend you read my 14 Tips on How to Use Twitter for Social Recruiting and see the two comments from Matt Chiasson.

If YES – would you be interested in a better way to search for and find people in your target talent pool on Twitter?

Look no further!

I received a notification from the Google+ Social Recruiting community last week that Hung Lee believes he found something that “pretty much destroys FollowerWonk as a Twitter sourcing tool.

“Destroy” is a strong word, but I would say Tactics Cloud gives FollowerWonk a thorough beating and I will be using Tactics Cloud as my primary tool when searching for people on Twitter. Continue reading

LinkedIn Represents Over 60% of U.S. Non Farm Employment

LinkedIn Statistics Feburary 2014 277M 93 Million USIn certain sourcing and recruiting circles, it’s in vogue to say that you shouldn’t rely heavily on LinkedIn for your talent acquisition needs.

In fact, some people will go so far as to say that LinkedIn is “overfished” for talent and that recruiters are lazy if they use LinkedIn as their primary source of potential candidates. Whenever I hear that kind of sentiment, I simply have to laugh. LinkedIn’s latest stats claim 93M+ U.S. profiles.

To believe that a talent pool the size of LinkedIn’s is “overfished” is like saying the Pacific Ocean is overfished, that you can’t find fish in the Pacific Ocean that others haven’t already caught, and that you would be lazy to fish in the Pacific Ocean. Yeah – there’s just too many fish in the Pacific Ocean…we should go find some other place to fish. Right.

You might be surprised to learn that most people find, review and take action on less than 20% of LinkedIn’s users, but that’s the topic of a separate post I will write in the near future. In the meantime, contemplate my claim.

LinkedIn Represents Over 60% of U.S. Non Farm Employment

Let me share with you an interesting statistic I recently calculated and shared at SourceCon in Atlanta. The U.S. Bureau of Labor and Statistics is showing preliminary figures for total non farm employment in January 2014 at 137,500,000 (I rounded up). Continue reading

What is Sourcing? I Propose a New Universal Definition.

 

Definition of Sourcing on TwitterWhat better time than at the beginning of a new year to take a critical look back at where we’ve come from, to reflect on our current state and to look forward to a next step in the evolution of sourcing?

It believe it would certainly be helpful and beneficial to have a universally agreed upon definition of exactly what sourcing is. If you’ve attended any sourcing and/or recruiting conferences, it doesn’t take long to notice people using “sourcing” to describe different types of activities. When anyone talks about the sourcing function at their company, it immediately begs the question of exactly what the sourcers are tasked with. Do they find people and pass them on to recruiters to contact, or do they also engage the people they find? The same goes for hiring sourcers – one of the first questions is always whether or not they will be responsible for engaging potential candidates. 

Am I the only person who thinks this is a bit absurd, if not just unhelpful and annoying?

The fact that there is no universally agreed upon definition of what sourcing is when it comes to talent acquisition has always bothered me. Don’t you think it’s well past time to move the ball forward and make the attempt to develop a single definition of “sourcing?”

Historically, sourcing was typically used to refer to talent identification only – name generation, org charting, finding resumes and social profiles, etc. However, I have noticed over the past few years that more people and companies are starting to use sourcing to describe both the identification and the engagement of talent, which aligns with what I’ve always believed sourcing to be.

Let’s take a look at other people’s opinions on what sourcing is and leverage what sourcing is considered to involve when it comes to procurement to see if we can achieve some parity before I share with you my proposed definition of sourcing. Continue reading

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.

Analytics, Big Data & Moneyball HR/Recruiting for Dummies

 

Analytics Big Data Moneyball Recruiting for DummiesThe interest in leveraging big data, analytics and Moneyball in HR and recruiting is gaining significant steam.

Ever since my first article on the subject back in 2011, I’ve set up Google Alerts and Hootsuite streams set up to catch any mention of big data, analytics and/or Moneyball in conjunction with HR, sourcing or recruiting,  and the volume of activity is bordering on surprisingly massive and overwhelming, and I’m not the only person to notice this.

Yes, it does seem like everyone is talking about big data in HR.

 

Twitter Big Data Post

 

In 2012, “big data” was mentioned in 2.2M tweets by 980,000+ authors, at a peak rate of 3,070 times per hour!

However, as is often the case with relatively new and nebulous concepts, there is quite a bit of confusion surrounding big data and Moneyball and how they can be applied to HR and recruiting, as evidenced by the obviously incorrect usage of the terms in many cases. It’s also nearly impossible to stay on top of all of the content being generated on the subject (although I am trying my best!).

This is precisely why I’m going to take the opportunity to clear up any confusion by concisely explaining the concepts of big data, analytics, and Moneyball as it relates to HR and recruiting, as well as illustrate some obviously incorrect references to these concepts in recent articles, including those from the Wall Street Journal, Forbes, The Economist, The New York Times, and more.

I’ll tackle analytics first, big data second, and then Moneyball in HR/recruiting, leveraging Slideshare presentations and YouTube videos from experts for support. Continue reading

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

 

There have been numerous articles written about fake LinkedIn profiles, and some are really easy to spot because their names aren’t even names.

 

 

Then there are LinkedIn profiles with names that appear real but the profiles are obviously fake.

 

 

This person profile actually has some endorsements. I’m pretty sure this is a picture is of Sophie Turner, who plays Sansa Stark in Game of Thrones (I’m really looking forward to season 3!)

 

 

Next we have LinkedIn profiles that look like real people, at least when it comes to the profile details, but the profiles are likely created by recruiters and perhaps even hiring managers (yes – this happens…stay tuned for a future post on this subject), and the photo is obviously not the photo of the person who created the profile.

And finally, there are LinkedIn profiles that are likely to be real people – where the details of the profile accurately reflect the person behind the profile – but the profile picture isn’t real.

I refer to these profiles as LinkedIn Catfish.

Catfish on LinkedIn

Have you seen the film Catfish or the MTV series based on the film?

The movie is a documentary about the evolution of Nev Schulman’s online relationship with a girl on Facebook who ultimately ends up not being who she was pretending to be online. The television show follows the same format, finding people who are in online relationships with people they’ve never met, performing research on the people, and arranging an in-person meeting to determine if the people are really who they are portraying themselves to be on Facebook.

One of the techniques that Nev Schulman consistently uses on the television show to determine whether or not the people are lying about who they are is Google Image Search in conjunction with Facebook photos.

I’ve posted a few “real or fake” challenges on Twitter from time to time, and while some LinkedIn profiles are obviously fake, others can be quite difficult to determine. I believe some LinkedIn profiles are really examples of “Catfish,” where the people are real but they are using other people’s photos.

How do I know?

From time to time I use Google Images to check LinkedIn profile photos of the people that are sending me invitations to connect as well as some of the profiles that LinkedIn claims are “people I may know.”

I thought I would share some of my findings with you, starting with some obviously fake LinkedIn profiles and progressing to some that I believe are in fact real people who just happen to be using someone else’s image for their LinkedIn profile image.

Let’s start with something I found the other day when I glanced down to the “People you may know” section on LinkedIn.

 

 

When I clicked on Lola’s profile, I found it devoid of any content, which of course immediately makes it suspect.

 

 

Where it gets interesting is when you perform a Google Image Search for that photo – multiple Facebook hits:

 

 

Now let’s take a look at a few LinkedIn profiles of “developers” that I think are really fake profiles created by recruiters.

First is “Alison Cork.”

 

 

If you try searching for Alison Cork using the first name and last name fields in LinkedIn, this profile doesn’t appear to exist anymore.

Taking a look at the “People also viewed” list on the right side of “Alison Cork’s” no-longer-existing profile, I spotted Elizabeth Rose, a “developer at Chevron,” and Danielle Baker, a “web developer at Pfizer.”

 

 

If you click the link to “Elizabeth’s” profile, you’ll see that at least the details all seem to align (date of graduation, data of first work experience, location of school and current location, etc.) – someone took at least a little effort to make this profile seem like a real developer. However, I believe this profile is really the creation of a recruiter looking to use the profile to connect with other developers.

Checking Google Images for the profile photo shows the possible origin:

 

 

“Danielle” below is a similar example.

 

 

If you click the link for this profile, it’s similar to “Elizabeth’s” in terms of being relatively well filled out/detailed.

Performing a Google Images search for “Danielle,” this is what you’ll find:

 

 

Now I’d like to move on to the category of people who *could” be the people with the experience listed on the profile, but they are using someone else’s picture for their LinkedIn profile photo.

For example – this person came up on LinkedIn as someone I might know.

 

 

I blurred the details because this *could* in fact be a real person, and on top of that – they seem to work in sourcing/recruiting. The profile mentions they have worked in recruiting leadership roles at some very prestigious companies, and they have given one (definitely real) person at one of those companies a recommendation (but haven’t received any).  If you’re extremely curious and a tad bit technically savvy, you can probably find this profile – it is public.

When I performed a Google Image search for the profile picture, here’s what is returned:

 

 

So what do you think – is this profile of a real person?

Why the term “Catfish?”

Apparently (at least according to Internet and other lore), the use of the term “catfish” comes from the story about the early days of shipping live cod, where the fish’s inactivity in their tanks during shipment resulted in fish with a mushy texture and bland taste. Someone had the idea to ship the cod with some catfish in the tank, because catfish often conflict with cod in the wild, so during shipment, the catfish would harass the cod and keep them active, resulting in cod with the proper texture and taste, as if they were caught fresh. In the movie, one of the characters theorizes that the person Nev thought he was having a relationship with was like a “catfish” – serving to keep him active, always on his toes, and always thinking.

When you’re on the Internet – even on professional networking sites such as LinkedIn, you always have to be on your toes. Some of the people you’re finding and connecting with may not be who they appear to be, and they might not be real people.

Even so, you may want to connect with some of these folks anyway (as I do in some cases).

Why?

If you fully appreciate and understand the X-degrees of separation concept, there is value in connecting with the “wrong” people because they can actually be conduits to the “right” people. In fact, it could be argued that in many cases, the *only* way to add some of the “right” people you’d like to have in your network  is to connect with the people who are connected with them – even the ones that don’t seem to make sense on the surface.

If you connect directly with a “catfish” profile has been created by a recruiter or hiring manager specifically to connect with software engineers, and they have been successful in connecting to many of them at the 1st degree, then those software engineers would be in your 2nd degree network on LinkedIn. With a free account, you’d be able to see their full names in any people search.

Also, as a 1st degree connection, you have the option to search their connections if they haven’t shut that down (the 2 “developers” above haven’t), and you also have access to their contact details – so if you’re really curious, you could ask them directly about the reality of their profile.

:)

 

Why Facebook Graph Search is No Threat to LinkedIn…For Now

 

Facebook's Graph Search options of special interest to sourcers and recruiters: Employer, Position, Employer Location, Time Period, School, Class Year, ConcentrationAs with all new and bright shiny objects, people are quick and eager to make blind and wild predictions, and Facebook’s Graph Search is an excellent example.

Facebook announced Graph Search on January 15th, and there are already 100’s of articles published on the possibilities, including how Graph Search will challenge Google in advertising, Match.com & eHarmony in online dating, Yelp and others in services, travel and entertainment, and yes, even LinkedIn and Monster in recruiting.

When Mark Zuckerberg himself says “One of my favorite [Graph Search] queries is recruiting. Let’s say we’re trying to find engineers at Google who are friends of engineers at Facebook,” it’s hard to not get excited about the possibilities of tapping into the data Facebook has on over 1,000,000,000 users globally, and over 167,000,000 users in the U.S. alone.

Don’t worry – this isn’t another Facebook-Graph-Search-is-an-awesome-disruptor article.

Rather than throwing fuel on the Graph Search fire, I am happy to throw a wet blanket instead.

Don’t get me wrong – I’m excited to use Graph Search, and I know sourcers and recruiters will be able to make use of it. However, there are some major limitations to Facebook and Graph Search specifically that I want to recognize and bring to light that will clearly explain why it isn’t a threat to LinkedIn. Continue reading