With each passing day, an increasing amount of data is being generated and transmitted by and about more people than ever before.

At Google’s 2010 Atmosphere convention, Google CEO Eric Schmidt stated that “There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.”

In case you were wondering, an Exabyte is 1,000,000,000 gigabytes, or 10,000,000 terabytes. That’s a lot of information.

Interestingly, Google’s CEO may have actually underestimated the amount of data being generated at the time. From their research, RJMetrics believes that a more accurate figure would be approximately 6.6 exabytes every 2 days. One thing is for sure – the number is even bigger today.

What does any of this have to do with recruting? Why should HR, recruiting and sourcing professionals, as well as corporate executives care about big data?

Well, because a chunk of big data is human capital data, and as I have been ranting about for the better part of 3 years, human capital data can be leveraged to identify and hire more great people more quickly.

If you’re a dinosaur recruiter or sourcer, I don’t recommend you read the rest of this post, because:

1. I will challenge they way you think and work, and that might make you uncomfortable
2. You’ll probably think it’s a load of garbage
3. It might make you aware of your pending extinction (the precise timing of which is debatable)

I have to warn you that this is not a short, quick-hit post – this may be the longest single post I have ever written, which explains why you didn’t see a post from me last week. I wrote this piece to introduce a human capital paradigm shift, to challenge the long-standing conventional wisdom in HR and recruiting, and to (hopefully!) provoke progressive thought from my peers. If that’s not your thing, turn back now.

If you want a glimpse into the future of talent identification and acquisition, you’re always interested in figuring out how your company can gain a competitive advantage, and you’re wondering what the heck my “Moneyball recruiting” reference could possibly be about, then read on. 

What is Big Data?

Wikipedia claims that “Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.”

Other sources attempting to define big data include “the tools, processes and procedures allowing an organization to create, manipulate, and manage very large data sets…”

Regardless of definition, the big data concept centers around huge amounts of data that are not only increasing in volume, but also in velocity and variety.

The data velocity aspect is the speed at which new data is generated. One example of the increasing velocity of human capital data would be social media posts/updates. For example, Twitter crossed the 200M tweets/day mark in June - that’s 1 billion tweets every five days. How’s that for velocity?

The variety of data sources and types should be obvious, especially when it comes to human capital data – LinkedIn profiles (which can now be converted into resumes/CVs) and updates, Facebook, Google+ and Twitter profiles and updates, recommendations/awards/endorsements, blogs, blog comments, mobile updates, press releases, and much, much more.

The Big Deal about Dig Data

According to MGI and McKinsey’s Business Technology Office, “The amount of data in our world has been exploding and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus…Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.”

MGI’s research into big data offered several key insights, including:

1. “Data have swept into every industry and business function and are now an important factor of production, alongside labor and capital.”
2. Big data “can unlock significant value by making information transparent and usable at much higher frequency.”
3. “As organizations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days, and therefore expose variability and boost performance. Leading companies are using data collection and analysis to conduct controlled experiments to make better management decisions; others are using data for basic low-frequency forecasting to high-frequency nowcasting to adjust their business levers just in time.”
4. ” The use of big data will become a key basis of competition and growth for individual firms. From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, and capture value from deep and up to real time information. Indeed, we found early examples of such use of data in every sector we examined.”
5. “There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

The dig deal about big data is that data can be used to make better decisions.

While McKinsey found that some companies are using data collection and analysis to make better management decisions, I think there is a huge opportunity to collect and analyze human capital data, specifically to make better hiring decisions - to gain a holistic advantage over competitors by finding, identifying, and enabling the recruitment of top talent. 

Data Science and Talent Science

If you were really paying attention when you read point #5 above, you would not be surprised to learn that the hottest job you never heard of is based on data science. Yes, the highly skilled, nerdy-cool job that companies are scrambling to fill is that of the data scientist.

While there are many different ways of explaining what data science is, data scientists collect, extract and analyze information from large datasets and deliver actionable intelligence to non-data experts.

In a recent Fortune Magazine article, Michal Lev-Ram explains that “A data scientist helps companies make sense of the massive streams of digital information they collect every day, everything from internally generated sales reports to customer tweets. The gig which requires the specialist to capture, sort, and figure out what data are relevant is one part statistician, one part forensic scientist, and one part hacker.”

The article goes on to explain that while data scientists have been been playing key roles at companies like Google and Amazon for quite some time now, a variety of other companies such as Wal-Mart, Foursquare and Bitly are hiring data scientists to analyze their data and provide intelligence that can lead to better business decisions or new products. Furthermore, Deep Nishar, Senior Vice President of Products & User Experience at LinkedIn, was quoted as saying “Data engineers are already harder to find than search engineers, and that’s a sign of the times.”

According to this article, data scientists are already an integral part of competitive intelligence, a field encompassing a number of activities, such as data mining and analysis, that can help businesses gain a competitive edge. Ken Garrison, CEO of the industry group Strategic and Competitive Intelligence Professionals (SCIP), explains, “The field involves collecting data, analyzing it and delivering the data as intelligence that is actionable.”

“The question facing every company today, every startup, every non-profit, every project site that wants to attract a community, is how to use data effectively,” writes Mike Loukides, Vice President of Content Strategy for O’Reilly Media, on the O’Reilly radar website. He adds, “not just their own data, but all the data that’s available and relevant.”

There is already a significant shortage of people with the talent necessary for companies to take advantage of big data of any form, let alone human capital data.

When it comes to taking advantage of the vast and ever-increasing quantities of human capital data available, the sourcers of tomorrow will not be the average sourcers of today – a small subset of them will evolve into data scientists/engineers specializing in human capital data. Perhaps they will be known as Talent Engineers or Talent Scientists?

Regardless of title, data scientists in support of talent identification and acquisition efforts will collect, extract and analyze human capital information from large datasets and deliver actionable intelligence to hiring managers and teams.

In other words, these data scientists will find and identify top talent and enable better data/fact-based sourcing and hiring decisions, empowering their employer with the competitive advantage of consistently hiring the best people.

Moneyball Recruiting

If you’re unfamiliar with Moneyball, the term comes from Moneyball: The Art of Winning an Unfair Game, a book by Michael Lewis about the Oakland Athletics baseball team and its general manager Billy Beane. Its focus is the team’s modernized, analytical, sabermetric approach to assembling a competitive baseball team, despite Oakland’s disadvantaged revenue situation. Simply put, the Oakland A’s didn’t have the money to buy top players, so they had to find another way to be competitive.

The central premise of Moneyball is that the collected wisdom of baseball insiders (including players, managers, coaches, scouts, and the front office) over the past century with regard to player selection is subjective and often flawed.

Through the use of rigorous statistical analysis of baseball player performance and game records and Sabermetrics, the Oakland Athletics picked players based on qualities that flew in the face of conventional baseball wisdom and the beliefs of many baseball scouts and executives. In 2002, with approximately $41 million in salary, the Oakland A’s were competitive with larger market teams such as the New York Yankees, who spent over $125 million in payroll that same season.

When Sabermetrics was introduced into baseball, it was immediately rejected by many simply because it was new, different, leveraged statistics over intuition and experience, and frequently questioned conventional wisdom with regard to traditional measures of baseball skill evaluation. For instance, Sabermetricians doubt that batting average is as useful as conventional wisdom says it is because team batting average provides a relatively poor fit for team runs scored.

While baseball traditionalists scoff at the sabermetric revolution and have disparaged Moneyball for emphasizing concepts of sabermetrics over more traditional methods of player evaluation, the impact of Moneyball upon major league front offices is undeniable.

For example, teams such as the New York Mets, New York Yankees, San Diego Padres, St. Louis Cardinals, Boston Red Sox, Washington Nationals, Arizona Diamondbacks, Cleveland Indians, and the Toronto Blue Jays have hired full-time Sabermetric analysts.

Interesting, yes?

Oh, and the 2004 Boston Red Sox built their 2004 team with Moneyball in mind (the General Manager at the time was one of Billy Beane’s disciples). They also happened to win the World Series in 2004, ending the “Curse of the Bambino.”

Coincidence?

If you’ve seen the Moneyball trailer (or movie), you will hear one of the quotes that struck a chord with me, which was ”You don’t put a team together with a computer.”

When I first heard that quote when I saw the Moneyball trailer, I immediately thought of all of the people who respond to my articles with “recruiting is about people and not about technology” (e.g., sourcing, information retrieval, databases, analytics, etc.). I also thought about all of the great people I’ve hired and the powerful teams I have put together with a computer.

When I recently wrote about using predictive analytics in recruiting, I received a response on Twitter from a well-known recruiting personality who was highly dubious of the ability to use text and data to predict who might be a good hire for any particular hiring need.

I expected that kind of response, primarily because leveraging predictive analytics in identifying and hiring people contradicts conventional recruiting wisdom (e.g., “recruiting is about people and not about technology”).

Much of what is accepted as sourcing, recruiting and hiring best practices today is largely based upon conventional wisdom - ideas or explanations that are generally accepted as true.

However, the problem with any conventional wisdom is though the ideas or explanations are widely held, they are also largely unexamined and untested, and thus not necessarily true.

Conventional wisdom can be a significant obstacle to the acceptance of new information or the introduction of new ideas, theories and explanations, in many cases due to the fact that conventional wisdom is often made of ideas that are convenient, appealing and deeply assumed. At some point, however, these assumptions and beliefs can be be violently shaken when they no longer match reality at all.

Some people would call this violent shaking of conventional wisdom disruptive innovation, and I believe it is coming to talent acquisition in the form of Moneyball recruiting.

What Could Moneyball Recruiting Look Like?

Is there an equivalent to Moneyball in recruiting – in challenging conventional HR and recruiting wisdom and identifying and hiring top talent through the use of data, statistics, empirical evidence and objective facts?

I believe there definitely could be. Yes – it just hasn’t been developed yet.

Here are just a few ways we could apply the Moneyball concept/analogy to talent acquisition:

1. Moving away from using largely subjective means of assessing talent and making hiring decisions to more objective, fact and empirical data-based means
2. Identifying and acquiring top talent looking for traits, experience, accomplishments and information overlooked by traditional recruiting and assessment methods
3. Challenging conventional wisdom as to what top talent looks like and where it comes from (e.g., Ivy league schools, high G.P.A., certifications, M.B.A’s, experience at certain companies, etc.)
4. Developing objective performance measurements that are relevant across any role, responsibility, company, and industry and that stick with each person as they move through their career, similar to a credit score
5. Individual companies developing “secret sauces” for sourcing, analyzing and evaluating potential hires based on their own data and factual statistical analysis of the makeup of their ideal hire and employee
6. Breaking away from the idea that the only way to hire great people is to “buy” and poach them from competitors or specific companies (look at how incestuous Facebook, Google, LinkedIn, Microsoft, Apple and Yahoo are with regard to their talent pool)

I think it would be fascinating to objectively examine the conventional wisdom that referrals are the best hires. I know that might sound like blasphemy to some, as many simply assume referrals are the best hires, but surveys based on people’s subjective opinions of who the best employees are aren’t objective, and they certainly aren’t based on empirical evidence. Besides, referrals may score highly on quality-of-hire metrics based more on a self-fulfilling prophecy than anything else.

It’s one thing to say, think and feel that referrals produce the highest quality of hire, and it’s entirely another to prove it with objective, factual data.

In reality, referrals may in fact simply be the least-worst source of hire. Contemplate that little gem for a bit – I’ll be writing a post on it in the near future.

What about our assumptions on where great people come from?

For example, we know there is a talent war going on, specifically between tech titans such as Facebook, Google, LinkedIn, Microsoft, Apple and the usual suspects. We can easily guess as to why any one of those companies would like to hire someone from one of the others, but is the reasoning behind it and the practice of it based on conventional wisdom and assumption or based on proof that these people make great hires?

Unless someone performs a real study into the matter, I say it’s all based on assumption. If you think I am wrong, show me the unequivocal proof.

Here’s where some real Moneyball recruiting can be implemented – instead of paying top dollar for an already highly paid industry retread, develop and use a structured and proven data and fact-based methodology for identifying the next superstar from a non-obvious company out or straight out of school. Wouldn’t it be interesting to see where the real game-changer employees come from, and not just assume they come from the obvious short list of companies? Who’s really to say that the best Facebook engineer isn’t one that came from IBM, GE, or some obscure company?

If we believe what is written and said about Google – Google prefers people who have high G.P.A.’s and targets people who have graduated from specific schools – two of which (so my sources tell me and LinkedIn verifies) are Stanford and Berkeley. Is this based on the perceived value of achieving a high grade point average and graduating from certain schools or it is based on factual, data-based proof?

Wouldn’t it be interesting if Google went back through all of their hires – every single one of them – and found ways of objectively measuring their actual impact/value, and then crunched the data to find out what schools their fact-based top performers came from and what their G.P.A.’s were? Would the facts support the conventional wisdom and subjective preference for high grade point averages and certain schools? It certainly can’t be overlooked that some very smart, driven, and talented people never get the chance to go to a prestigious school based on a number of uncontrollable factors, not the least of which is socioeconomic status.

Regardless, it would be extremely valuable for Google (and any company!) to find out for a fact any patterns in the backgrounds and makeup of their top talent and then leverage them in their sourcing and recruiting efforts.

While we’re challenging assumptions, is a college degree really necessary to be a top performer?

Many companies make a college degree a prerequisite for hiring for specific roles or even at all, and many well-respected companies have hiring managers that are degree and university snobs – rejecting resumes based on schools attended and degrees earned.

If you work for such a company, I have a few names for you: Steve Jobs, Bill Gates, Mark Zuckerberg, Michael Dell, and Sean Parker. Do any of them ring a bell?

Outliers you say? Perhaps, but they are certainly proof you don’t need a college degree to be successful, and they just happen to be the most well-known successful college drop-outs – there are no doubt countless other successful people who never went to college or dropped out – they just aren’t in the public eye.

What if you could leverage data to identify the potential in people before they were 18, regardless if they were on a path to college or not? And no, we’re not talking about intrinsically flawed data like G.P.A. and SAT scores. How many brilliant, high-potential people could be given the right opportunity to fully realize their potential, regardless of whether or not they were born into the right family, in the right place, at the right time, and the stars aligned for them to be able to attend a prestigious university, let alone any college?

And if you think point #3 above is far fetched and an impossibility, Identified.com (funded in part by Google CEO Eric Schmidt, by the way) has already tried to come up with a numerical score for individuals based on work history, education history, and social network. It has some serious flaws (the subject of another post), but it shows that there is already a movement to try and represent and rank people based on a single numerical score, and Identified.com won’t be the only foray into that space. I believe that there is a significant opportunity for companies to develop their own data-based and statistically driven talent identification and acquisition models.

Final Thoughts

Is there already a way to leverage data and technology to increase the probability of finding and identifying people who are capable of being the next “A” player and significant contributor to your team?

Yes, I know there is. It already exists, albeit in a very crude form using tools and technologies in ways they were not intended nor designed for.

If only companies would start to focus their business intelligence and predictive analytics horsepower that many already currently use (and spend  millions on) for marketing, product development, sentiment analysis, healthcare, etc., and focus it on human capital data to enable better hiring decisions (which always starts with talent identification, aka sourcing, by the way), we would begin to see Moneyball-like disruption develop in the HR and recruiting function.

There is no denying that we are well into the Information Age, which is characterized by the ability of individuals to find and transfer information freely, and to have instant access to knowledge that would have been difficult or impossible to find previously. The digital revolution has already begun and we are seeing a shift from traditional industry that the industrial revolution brought through industrialization, to an economy based on the manipulation of data and information, i.e., an information society.

As such, I agree wholeheartedly with Mike Loukides that “The future belongs to the companies who figure out how to collect and use data successfully.”

However, I’d add that the future belongs more accurately to the companies who figure out how to collect and use human capital data successfully.

That’s because the companies that can consistently hire great people, through identifying people and basing hiring decisions on data and not intuition and conventional wisdom, are more likely to develop the best teams.

And the best teams win.

Even if you aren’t a baseball fan (I’m not!), I highly recommend you read Moneyball or at least watch the movie – I am not alone in seeing that value and underlying message of Moneyball can be applied to HR and recruiting, and certainly almost anything that has to do with building teams and businesses.

The old guard in baseball thought that using statistics and unconventional measures of performance through the use of Sabermetrics defied everything they knew about baseball. They were right.

If you think the idea of leveraging data and statistics to find and hire top talent defies everything we know about human resources and recruiting, I say you’re right.

I also say it’s a good thing, and that we’re just getting started.

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?

Corporate Leadership – Is Your Money Where Your Mouth Is?

Most people agree that any given company’s only sustainable competitive advantage is to identify, attract, recruit and retain great people.

If the executive leadership of any company really believed that their people are their greatest asset, and that hiring great people is critical to their long term success as a business, why would they limit their sourcers and recruiters to using common Internet search engines to search free and unstructured data?

Do they really believe that they are enabling their talent acquisition team with the highest probability of success in consistently being able to find, attract and recruit top talent?

Think about it – if you’re using Internet search engines to source potential candidates, you’re using Google, Bing and other sites in a manner for which they were certainly not specifically designed, and you’re searching unstructured data that everyone has free access to.

Does that sound like you’re being enabled with a competitive advantage in any way?

There’s no denying that valuable information can be mined from the Internet, and there is no doubt that the more knowledgeable you are with regard to leveraging Internet search engines, the more quickly and easily you can retrieve information others cannot and do not find.

However, I believe that technology-enabled talent sourcing is many years (at least a decade) behind what it should and could be at this point, and a huge contributing factor has been the last 10+ years spent focusing primarily on Internet search.

Sourcers and recruiters responsible for sourcing should not be asked by their employers to become sourcing MacGuyvers – having to inventively use common and unspecialized tools that everyone has access to to solve their company’s talent acquisition challenges.

You could technically play a game of baseball with a broomstick, a tennis ball and just your hands for catching, but you’d lose to a similarly skilled team that used the same bats, balls and gloves that Major League Baseball pros use.

Sourcing: Beyond the Internet

Boolean search does not = Internet search, although you would be hard-pressed to believe that based on the majority of information published on the topic, at least within sourcing and recruiting circles.

A good bit of the “Boolean” search advice you can find online isn’t really focused on Boolean logic at all – you’ll find that a large chunk of the sourcing advice and information actually consists of Internet search engine tips and tricks and specific website “hacks.”

Being able to effectively leverage Internet search engines is important and helpful for any sourcer or recruiter, but searching unstructured and public data certainly has its limitations, and there are much more powerful search engines available that were designed from inception for powerful text retrieval.

There is no denying that the Internet is a big pile of unstructured data, a good deal of which is old and outdated – and that there is plenty of “stuff” out there that can’t even be retrieved, simply because it’s never been indexed.

Let’s also recognize that just because you can search the Internet doesn’t make it highly searchable. I define highly searchable as the ability to quickly and easily retrieve highly specific information with a very low rate of false positives. A good bit of the work any sourcer or recruiter has to perform when sourcing with Internet search engines is attempting to remove false positives.

Of course, there is no denying that searching the Internet with standard or Custom Search Engines (e.g. Google CSE’s) can uncover valuable information.

However, when it comes to deeper/information rich human capital data such as resumes, there aren’t actually as many CV’s/resumes on the Internet as some people would have you believe. Moreover, it could easily be argued (and perhaps proven with a little more effort) that the majority of the resumes that ARE retrievable with Google or Bing are those of Information Technology professionals. There are many professions for which there are remarkably few CV’s/resumes, if any, retrievable via Internet search.

When it comes to shallow/information poor human capital data, such as press releases, lists, directories, etc., I’d argue that there isn’t even as much of that as most people assume (some people make BIG assumptions), and it’s certainly not evenly distributed across all job types and industries.

Beyond Boolean: Sourcing Methodologies

Sourcing is so much more than Boolean strings. I’ve written about this extensively before, so I won’t go into too much of my supporting argument in this post.

What I will stress here is that Boolean logic is simply the simplest way to construct a query, which is a formal statement of an information need, which in turn is the basic building block of an information retrieval process.

The AND, OR and NOT Boolean search operators are just the “glue” that combine all of the actual search criteria together into a single query.

It doesn’t get any simpler than “I want all of these things” (i.e. AND), “I want at least one of these things” (i.e. OR), and “I don’t want these things” (i.e. NOT). If it wasn’t simple, my daughter would not have learned Boolean logic in the first grade in public school - Venn diagrams and all.

When it comes to sourcing, what I feel is significantly lacking is a focus on the information retrieval process, which involves the analysis and interpretation of the data retrieved, and is infinitely more important than any specific search string or Boolean search operator.

The most critical component of any query are the search terms and phrases that are included or strategically excluded (and I am not talking about negating false positives), which should be arrived upon through a consistently applied iterative and incremental process.

In spite of this, much of what can be found online in terms of sourcing advice is focused on how to use Boolean operators, Internet search commands and site specific hacks.

There is a reason why companies that create software utilize and follow software development process methodologies - and they have been doing so since the 1960′s! Why? It’s simple – because they are seeking to find repeatable, predictable processes that improve productivity and quality.

Inconsistent processes lead to inconsistent results. So will a complete lack of a process.

I strongly believe that if the global sourcing community moved more in this direction, focusing more on the sourcing process and data analysis and interpretation rather than the searches themselves, and more specifically Boolean operators and Internet search commands, sourcing would gain more respect, attention and investment, especially from leaders and executives who currently equate sourcing to searching Google for people.

The Future of Sourcing: From Internet Hack to Data Scientist

Have you heard the term “Big Data?” How about “data scientist?”

I would not be surprised if most sourcers, recruiters and HR professionals had no idea what “Big Data” meant, or what it could possibly mean for the future of talent acquisition.

I also would not be surprised if most people immediately rejected the idea that data scientists already have a place in recruiting teams and HR departments.

That’s unfortunate, because I think it’s time more people in our industry started to think outside the box of that has been limiting progressive thought and preventing advancements in the utilization of technology to create a competitive advantage in talent acquisition.

As such – I highly recommend you read this report from McKinsey Global Institute – Big data: The next frontier for innovation, competition, and productivity. While you’re reading it, the whole time think about how the concepts and practices could be applied to human capital data and hiring decisions.

Imagine a future where human capital data that can be readily found online in the public domain is automatically retrieved and captured (or live-linked to, find.ly style) and combined with private sources of human capital data into structured data sets that enable predictive analytics and that can be manipulated via highly precise and specific information retrieval capabilities that make Google look like a child’s toy.  Literally!

I can’t say when this future will become a reality, but it can’t come soon enough for me!

I firmly believe the future of sourcing will involve an evolution from Internet Hacking to Data Science.

What is largely done manually now via Internet search will be automated and information from disparate sources will be aggregated into proprietary data sets that will become a company’s competitive advantage when it comes to identifying, engaging, recruiting and making hiring decisions to acquire top talent.

Companies are already sitting on mountains of human capital data that they have captured over the years in their ATS/CRM systems, yet few if any companies are really tapping into the latent power of that pool of data.

It doesn’t take a huge mental leap to see that today’s (top) sourcers will be tomorrow’s data scientists enabling the companies that they work for to identify top talent and make better hiring decisions – read this article on the Rise of the Data Scientist, which is from 2009 no less!

Data scientists are already an integral part of competitive intelligence efforts for many companies, mining and analyzing data to help their companies to gain a competitive advantage. Unfortunately, it seems that pretty much all data scientist jobs today appear to be focused on everything BUT enabling talent identification and acquisition.

You may also find this interesting – LinkedIn has a Principal Data Scientist, and he came from Google. Of course, he’s focusing his talents on creating a better LinkedIn solution. I believe it is only a matter of time before companies begin to harness the power of data science to enable faster and better hiring decisions.

Final Thoughts

I believe that technology-enabled talent sourcing and recruiting is perhaps a decade behind what it should and could be at this point, and a huge contributing factor has been the fact that for the last 10+ years, many people still equate sourcing with Internet search.

Searching through unstructured Internet data that everyone has equal access to with dummied-down and non-specialized search engines doesn’t afford a company with a strategic competitive advantage.

You don’t see companies doing this with their product development, marketing, financial analysis, or business intelligence efforts – their data and BI analysts and data scientists are not limited to using Google for information retrieval and analysis, nor are they limited to searching information solely in the public domain.

There’s a reason for that. Using specialized information retrieval, analysis, and visualization solutions to gain intelligence from a proprietary mashup of data affords companies with information and insights that their competitors won’t be able to match.

Going back to the MacGuyver comparison – he was able to make use of mundane materials to create unorthodox solutions to any problem he faced. Imagine if he actually had the right or the best tools available?

If you’re one of those few MacGuyver-level sourcers or recruiters who can make magic from mundane resources everyone else has access to – good for you.

However, imagine what you could accomplish if you had highly specialized tools specifically designed for mining vast and proprietary human capital data sets dynamically compiled from multiple sources that enabled predictive analytics, empowering you to leverage data to more quickly identify, engage and recruit people who are more likely be ideal additions to your company.

Can anyone help me make this dream a reality?

While there is much written on the subject of how to search the various talent sources available to recruiters and sourcers today, such as the Internet, LinkedIn, Facebook, Twitter, Google+, ATS/CRM systems, etc., there does not seem to be much written about their ROI as sources of talent/human capital information.

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

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

Why is Data Depth and Searchability Important?

Quite simply, the deeper the data offered by and the more searchable the the source is, the higher the ROI for your sourcing efforts.

All electronic sources of talent are NOT created equal, and some offer sourcers and recruiters instrinsic advantages with regard to the ability to more quickly and precisely find more of the right people, yielding higher productivity.

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

Shallow Data Depth

The whole point of using information systems to search for candidates is to find people who have specific skills and experience, and typically people who live in a specific location.

It’s not terribly difficult to find PEOPLE, but it can be very challenging to find the RIGHT people.

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

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

Many shallow sources of candidate information simply do not provide ANY information regarding some of these details. This is because the majority of people who use sites like Twitter and Facebook often don’t include professional/employment information on their profile.

With little or no information to go on, it is extremely difficult to search for and identify candidates who have a high probability of at least meeting the minimum requirements for your opening, let alone exceeding them.

Low Searchability

While you can certainly search Facebook to find people – Facebook has significant limitations with regard to its “searchability.” Facebook simply was not designed to be highly searchable, at least not to find people you don’t know, and certainly not based on professional info beyond title and employer.

You may think I am crazy for saying that the Internet isn’t very “searchable,” but most search engines, including Google, don’t even support full Boolean logic.

Also – the Internet itself is unstructured, which makes it intrinsically difficult to find exactly what you’re looking for without drowning in a sea of false positive results. Sniffing out and following candidate leads based on shallow information and using sources that aren’t by design highly searchable comes with the territory of being a sourcer or recruiter, and the thrill of the hunt can be quite satisfying.

However, the angle of this article is ROI, or even more specifically ROTI (Return on Time Invested) – which is a good measure of productivity (Productivity + Work / Time).

Trying to search shallow data sources with limited search capability can be an incredibly slow and time consuming process, as well as result in a significantly low return on time invested. I refer to this as “low yield” sourcing, and its cause is the shallow depth of information available and poor searchability of the sources – which cripples your ability to control or even identify critical candidate variables.

Deep Data But Low Searchability

In this quadrant we have many ATS/CRM solutions, as well as Internet resumes.

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

While this deep level of talent data is wonderful – it’s of little use if your ability to search for and retrieve the data is limited. Unfortunately, many ATS/CRM solutions aren’t very searchable.

In fact, some are laughably unsearchable, considering a major reason for storing human capital data is (you would think) to be able to retreive it to take action on it.

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

When it comes to the Internet - while you can search the Internet and find resumes, only Bing supports queries employing full Boolean logic. The irony there is that Bing limits you to 10 search terms or 150 characters (the documentation vs. realized results is sketchy).

It’s nice that Google gives you 32 search terms, but in some cases, this limits your ability to configure queries that are precise enough and/or remove all false positives.

And while finding some local resumes can be done using Internet search engines, it is difficult to be sure if you are actually finding ALL of, or even the best available, resumes.

Because the Internet is unstructured, when you search for area codes, state abbreviations, and zip ranges (as you can with Google), you often get a number of false positive results. And if a person puts their resume online but does not list an address or a phone number – good luck trying to find them as a local candidate.

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

Highly Searchable but Shallow Data

Here we have Twitter and LinkedIn.

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

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

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

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

Deep Data and Highly Searchable

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

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

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

Sourcers and recruiters can run Boolean strings and structured queries when searching job board resume databases to precisely target specific experience, years of experience, education, certifications, environmental/project, and industry experience.

Those who are particularly adept can even achieve semantic search by crafting Boolean strings that go well beyond buzzword matching and target specific responsibilities, or in other words, what the candidates have actually done as well as what they have done it with.

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

Talent Warehouse

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

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

The core of a Talent Warehouse is a relational resume database. We’ve already established that resumes are deep sources of human capital data – but you may have noticed that on the chart above, “Talent Warehouse” is actually higher on the scale of data depth than other sources of resumes. “What’s a deeper source of human capital data than a resume you ask?” A Talent Warehouse adds more depth to resumes through the use of comments/notes and tags – sourcers and recruiters can add additional information to candidate records and resumes based on phone screens, in-person interviews, references, tests and evaluations, etc.

Imagine being able to search for candidates based on information contained in their resumes AS WELL AS information gleaned from the candidates through interviews. Imagine that!

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

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

This kind of search interface and engine can enable sourcers and recruiters to quickly and precisely find quantities of well qualified candidates. In the hands of an adept Talent Miner, a Talent Warehouse can yield a high volume of results with a high percentage of candidates who have specific skills and experience, specific responsibilities, specific years of experience, specific environmental/project experience, and who live in a specific area.

What this essentially affords a recruiter is the ability to leverage technology to find, contact, and establish and build relationships with more of the right people more quickly – increasing effectiveness and productivity!

Final Thoughts

You can find and hire people by searching any electronic source of talent data – resume or otherwise.

However, searching shallow and less searchable sources such as Twitter, Facebook, Google+, blogs, the Internet and other similarly shallow sources of candidate data takes a higher amount of effort for a smaller return – a low ROI. This results in low yield sourcing and recruiting and ultimately lower productivity.

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

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

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

And if your private candidate database/ATS/CRM isn’t as searchable as it could be - consider doing something about it- because it should be. Make the conscious decision to focus the majority of your e-sourcing efforts on the highest ROI sources – those with deep data and those that are highly searchable.

Posting a job online is perhaps the first action most companies take to attract talent when they have an opening.

However, posting jobs in an attempt to attract qualified talent has many intrinsic flaws, and here are the top 4 in my opinion:

1. Posting jobs a passive strategy
2. Posting jobs offers no control over candidate qualifications
3. Job advertisements only attract candidates who are actively looking
4. Posting jobs isn’t social!

In comparison, sourcing from Internet, LinkedIn, online resume databases, ATS/CRM systems and similar resources to discover and identify qualified candidates is an active strategy which offers significant control over candidate qualifications, can be used to specifically target passive and even non-job seekers, and is 100 times more social!

Read on for a more in-depth analysis of posting jobs vs. sourcing candidates, as well as to have your eyes opened to a new way of looking at the value/ROI of posting jobs.

Job Posting is a Passive (lazy?) Strategy

Posting jobs online is a passive, sit-back-and-wait talent attraction strategy wherein there is no action taken other than that of publishing the job to various sites.

If identifying, attracting and hiring top talent is critical to any company’s ability to create and maintain a competitive advantage, does it make sense to rely heavily on a method of talent attraction that involves little-to-no effort?

Posting jobs online anywhere – whether it be on a corporate site, LinkedIn, Facebook, or a niche job board – is essentially the lowest level of effort anyone can take towards the goal of hiring your next game-changing employee.

Job Posting Offers No Control Over Candidate Qualifications

To me, posting a job is just like setting a trap. In setting a trap, the strategy is to set it in a place where you think your quarry might come across it and be ensnared.

Wherever you place the trap, you are essentially hoping that the specific type of animal you’re looking to capture will wander into it.  This is very much a passive, hope-based strategy, and hope is actually not a strategy.

For example, if you are trying to snare a rabbit, you could just as easily end up snaring a raccoon, a skunk, an opossum – or basically any small animal that wanders by, simply because you have no control over what, if anything, gets snared.

This is the same with job posting.

If you post a job for a windows system engineer with a minimum of 5 years of experience, an MCSE certification and web hosting industry experience - literally ANYONE can respond, whether they have the appropriate experience, certification, or industry experience or not.

As a passive, zero-percent control  strategy, you simply cannot control who responds – unqualified, under qualified, over qualified, out of area, etc.

This isn’t just my experience and opinion.

A recent Atlanta Business Chronicle article cited a study of 501 hiring managers by Robert Half and CareerBuilder which found that 44 percent of resumes presented to hiring managers are submitted by unqualified applicants. Additionally, the 2009 EDGE Report also found that 47 percent of hiring managers cited under-qualified applicants as their most common hiring challenge.

No one should be surprised by such a high percentage of un- and under qualified applicants, because you can’t control what wanders into the traps!

As critical as attracting and hiring the right people is for any company to perform well, does it make sense to rely heavily on a strategy that puts 100% of the selection control in the hands of the job seeker and 0% in yours?

Job Posting Attracts the Smallest Percentage of Job Seekers

Not only can you not control who responds to your job posting, but the only people who are going to get “snared” by the trap you’ve set are people who are actively looking for a job, and active job seekers represent the smallest percentage of the available talent pool.

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

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

Now, unlike many people, I don’t think there is anything intrinsically wrong with active job seekers – they are not all desperate, unemployable people (can you believe people in the recruiting industry actually believe that?).

However, the real issue at hand is that with job posting, you are essentially missing the other 86% of the workforce.

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

That’s an issue!

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

Your Ads and Postings are Invisible to Most People

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

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

Even for those people who do “see” or “tune in” your ad/job posting – the reality is that most will not take action.

Changing a job is a big, stressful deal. Most casual, passive, and practically all inactive job seekers will not likely be inspired to take any action and explore leaving their current position just because they saw an online job ad, let alone one on their Facebook page.

SEO Is Not Enough

I agree 100% with Marvin Smith that SEO is not enough.

How could it be anyway?

For SEO to work, you have to have someone searching for jobs and/or information about your company, and as we’ve already seen, that is going to be the active job seekers and perhaps some of the casual job seekers – which is only a small sample of the available talent, the clear minority.

Posting Jobs isn’t Social

Social Recruiting continues to the quite the rage in the talent acquisition community.

However, most people HR and recruiting professionals agree that posting jobs online isn’t social, even if they are on LinkedIn, Twitter, or Facebook.

That’s simply because in order for something to be social, it has to involve engagement and interaction between people.

Sourcing is an Active Strategy

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

Instead of setting a trap and taking no effort other than to wait for the right person to stumble across it (aka, “post and pray”), when you create and execute searches to source for potential candidates, you are actively “hunting” for talent – targeting people with specific qualifications and experience, who live in specific areas – regardless of their job search status.

Instead of waiting (and hoping) for the right people to respond to a job posting, sourcers take decisive action to go out and identify and proactively engage and attract talent.

Sourcing Affords Significant Control Over Candidate Qualifications

When it comes to searching for candidates, I’m focusing specifically on resume and LinkedIn profile search, because searching for deep human capital data offers significant intrinsic advantages over shallow data. Resumes and some LinkedIn profiles offer more depth of identifying information, which enables sourcers and recruiters with a high degree of control over critical candidate variables.

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

Remember that windows system engineer with a minimum of 5 years of experience, an MCSE certification and web hosting industry experience I used as an example earlier in this post?

While it is impossible to post a job that can guarantee you that only people who perfectly match the requirements will apply, it is entirely possible (and quite easy!) to write a query to find people who do have the right type and years of experience, the required certification, as well as the right industry experience.  That’s because 100% of the control over who you find and identify is in your hands, not someone else’s.

Sourcing Can Target Passive and Non Job Seekers

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

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

Are you ready for a paradigm shift?

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

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

But you still have their resume in your ATS.

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

Statistically, the majority of resumes in online resume databases are of people who are likely to be not looking or passively looking.

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

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

Sourcing is Social

Yes, you read that right – I said sourcing is social.

Unless your idea of sourcing involves name generation only with no candidate engagement, sourcing is most definitely social.

A sourcer or a recruiter sourcing their own candidates can and should engage prospective candidates socially via InMails, Facebook messages, tweets and DMs, LinkedIn and/or Facebook group discussions, or just plain old email dialogues for that matter.

However, sourcing can go even more social – actually picking up the phone (gasp!) and calling a potential candidate and having a live conversation with them is a 100 times more social than any online/social media exchange. Imagine that – real, live conversations in today’s social media-crazed world.

An Alternative View of Job Posting

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

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

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

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

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

ATS Search Capability is Critical

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

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

Final Thoughts

Will there ever be a time when jobs aren’t posted online?

I’m not sure if we will ever get to that point, because it could be argued that posting jobs online is a logical thing to do and is certainly a part of a balanced “diet” of recruiting methods, and it can produce results.

However, if you or your organization relies heavily on posting jobs to find the right candidates at the right time, let alone the best candidates available, I believe you are at a serious competitive disadvantage.

Job posting is essentially like trapping: set the snare and do nothing but wait (and hope!) for the right person to stumble by – an inherently passive, hope-based strategy that affords you absolutely no control over what wanders in. To make matters worse, the only people who will search for or even “see” ads for jobs are those who are actively or casually looking, which is the smallest slice of the talent pie.

That’s right – you simply can’t snag those highly sought after “passive” candidates via posting jobs online.

On the other hand, as a truly active strategy, sourcing candidates affords everything that job posting fails to: control over candidate qualifications and the ability to specifically target and engage passive and even non-job seekers socially. Instead of waiting for the right people to come to you, you simply go out and find them, without a care for whether they woke up that morning thinking about finding a new job or if it was the furthest thing from their mind.

I am aware of many companies that spend quite a bit of time, effort and money on their job posting efforts, including “interactive recruiting solutions.” It makes me wonder if as much time, energy, and money is being spent on enabling their proactive sourcing capability, which would afford them with significantly more control over candidate qualifications and quality, as well as more truly social engagement with the highly coveted “passive” talent pool.

When assessing job posting solutions and efforts, I believe the less obvious but true value of job posting lies primarily in the collection of active candidates and the ability to cultivate them over time through regular engagement (electronic and over the phone) into more experienced/qualified candidates who will inevitably become passive/inactive job seekers.

If you listen to certain people in the recruiting industry, you’d think that being able to leverage information systems for talent discovery and identification will be an obsolete skill for recruiters and that sourcers will have to find another profession in the near future.

According to these folks, people with sourcing skills won’t be necessary because the future of sourcing will lie in total automation – they believe that applications that employ semantic search, AI and NLP (Natural Language Processing) will be able to perform the entire candidate matching process for you.

However, neither Watson, Artificial Intelligence, Natural Language Processing nor semantic search will be putting any sourcer or recruiter out of a job anytime soon unless all they’re doing is basic keyword and title searching.

Be Wary of Total Automation

As I have said countless times before, you should not seek to automate that which you do not fully understand (e.g., human capital information retrieval) and that you cannot accomplish manually.

If an organization hasn’t already mastered manual human capital information retrieval via Boolean queries and LinkedIn’s faceted search, then they should most certainly not try to implement a solution that automates candidate matching.

Admittedly, some roles and hiring profiles are incredibly easy to match based on most recent title (e.g., accountant, customer service, account manager/executive, etc.) coupled with a few supporting keywords. I’ve used a number of solutions that employ semantic clustering for concept matching and I have to say they do remarkably well for these kinds of roles.

Unfortunately for the people who make these solutions and fortunately for some (who make a living off of being able to do what matching apps cannot), semantic and AI matching applications don’t do very well with anything approaching even moderately complex hiring profiles where the best indicator of relevance isn’t easily determined by basic title and keyword conceptual matching.

Thankfully, I’ve never had the luxury of being able to find a volume of well qualified and matched candidates by typing in a title or two and a few keywords from job descriptions.

I say thankfully because I would not have developed the skill I have now had I started my career in recruiting focusing on roles where basic keyword and title searches allowed me to find a suitable number of relevant results, I would never have developed an interest in human capital information retrieval, and this blog would not exist!

My entire career has been focused on higher-level information technology and finance and accounting positions, including those requiring up to and over Top Secret clearances. For these kinds of roles, basic title and keyword searching yields essentially what anyone else can easily find and match with little thought (offering me no competitive advantage), as well as a flood of false positives to wade through. I’m often called in to figure out how to find candidates when all other attempts and solutions – both human and AI – have failed.

If an organization’s talent needs can be met solely by basic keyword and title searching, you certainly don’t need people to manually perform the searches, and we don’t need to wait for Watson-level performance because even todays semantic search solutions can take care of this level of retrieval.

However, always realize that not all results are created equal, and every search – automated via AI or otherwise – returns some relevant results and excludes some relevant results. Do not be “wowed” by semantic matching applications that can return what appear to be good results – you can be guaranteed that you’re also missing some fantastic candidates, and there is no automated solution for exploring dark matter.

I am positive that over time, semantic search/clustering, machine learning, and NLP solutions specifically designed for talent discovery and identification using human capital data will make advancements and their effectiveness will improve.

What I am not so sure of is how many jobs will actually be displaced by these solutions. In fact, some new jobs are certain to be created as a result of these applications.

Specialized Technology Requires People with Specialized Skills

Take a look at the emergence of ERP and Business Intelligence solutions as an example.

Have applications like SAP or Oracle’s HRMS, Financial and Supply Chain solutions eliminated jobs?

Perhaps some lower-level positions, but it is quite clear that they have created a great many jobs, and some ridiculously high level/paying! Some people with highly specialized experience with specific SAP modules can earn over $200/hour – and that’s not just for technical people – it’s for functional experts as well!

You would think that multi-million dollar software applications would do all of the HR and accounting work for you. The reality is that these applications don’t do any real “work” themselves.

Here’s a one-word search for SAP on Indeed:

Notice how many “Analyst” jobs come up even though I didn’t search for the term. That’s because SAP applications don’t perform any real work on their own – they store and move data (via reports and such), but people are required to make sense of it.

Business Intelligence solutions such as SSAS, Cognos, Essbase, or Business Objects don’t “work” on their own – they require people to configure, use, and analyze the information provided by them.

Highly specialized applications require people with the specialized skills and experience to use them, to make sense of, interpret and to make decisions based on the data and information provided by them.

Artificial Intelligence Requires Real Intelligence

The operative word in the phrase “Artificial Intelligence” is “artificial.”

Just as with ERP and Business Intelligence applications, when it comes to sourcing and recruiting solutions that use semantic clustering, AI, and NLP – people will be needed to implement, maintain, upgrade, customize and of course actually use the semantic search and matching solutions in production to find top talent.

Thinking that a semantic search solution for recruiting will run automatically without some guidance from a power user is like believing that companies can rely solely on the “canned” reports that come with HRMS and Financial ERP systems and Business Intelligence solutions. They don’t – practically no one does!

A non-customized semantic search solution that isn’t tailored specifically for the organization and multiple business units using it is essentially equivalent to a “canned” report that comes with PeopleSoft, SAP or Microsoft out of the box. I do quite a bit of work in the Information technology space, and I’ve seen a steady need for well over a decade for people with expertise in creating custom cubes, views and reports using ERP and BI applications.

If you think about it, a report is really just a query for the retrieval of information to analyze. Not much different than searching for, retrieving and analyzing human capital data for potential candidacy!

Additionally, non-customized semantic search solutions can nullify competitive advantage. If 5 companies who are constantly battling it out for top talent all use the same semantic search application, all 5 companies will find all of the same people. That means no competitive advantage. Perhaps even more importantly, they’ll also be totally unaware of the people their semantic search solution could not find – a common hidden talent pool of Dark Matter profiles that cannot be tapped by any of the companies.

Ultimately, Jeffrey Liker nailed it when he said “Computers move information, people do the work.” Computers and applications will always be able to move and sort data faster than a person – but in the end, people are needed to analyze the resulting information and make decisions.

The Future of Sourcing

The future of sourcing will see an increased usage of ever-improving semantic search and artificial intelligence candidate matching solutions.

Lower-level sourcing roles, such as name generation and searching with basic titles and keywords, will be all but eliminated. Software will be able to do this level of sourcing thousands of times faster than people can, and even more cost effectively than human outsourcing solutions that can currently cost $8 – $15/hour. This is because this level of sourcing is little more than moving data from once place to another (e.g., from the web, Monster, or LinkedIn to an ATS) – there is little to no analysis involved.

However, on the other end of the sourcing spectrum, it’s a totally different story.

Just as there are currently hundreds of thousands of people who are responsible for having functional and analytical expertise with today’s widely used Financial, HRMS, SCM ERP and BI applications to query and analyze data and information, people within HR, Recruiting and Talent organizations will eventually be required to have highly specialized skills and abilities with regard to leveraging  human capital data through the use of semantic search solutions for talent discovery, identification and matching.

In the future, the process of creating and automating effective queries of human capital data for talent discovery and identification will be incredibly similar to what a BI analyst currently does when they design data cubes and produce reports from them. Instead of Applicant Tracking Systems, companies will build Talent Warehouses which will become their source of significant competitive advantage with regard to identifying and acquiring top talent.

The talent discovery and identification solutions of the future will require people with specialized skills and experience to use them effectively, to customize them for specific business units and ever-evolving hiring needs, and to “teach” and steer matching applications to continually improve them and make them better.

Will you be one of those people?

I will be!

Hopefully it won’t take too long for companies to value and invest as heavily in sourcing and recruiting just as they currently do with their multi-million dollar Data Warehousing, Business Intelligence and Decision Support Systems.

Investing millions in ERP and BI solutions is great – but what about investing millions into enabling your organization to find, hire and retain the talented, game-changing people who will be using the ERP and BI solutions to analyze your financial, product and sales data and make decisions that can save or make your company millions?

What’s more critical and strategic to the sustained and long term success of a company than talent acquisition and retention?

As sourcing and matching technology advances, they will require people with the specialized skills and experience to use them, to make sense of the results returned (and not returned!) by them, and to interpret and make decisions based on the data and information provided by them.

As will likely always be the case, the value that humans bring to any endeavor is in the ability to do what machines and applications cannot.

While no company has a flawless recruiting system, process or solution, there is a glaring problem shared by many corporate recruiting functions from which the Fortune 500 and the Big 4 are not immune.

As some of the most respected companies in the world invest quite a bit of time, energy and money into social recruiting efforts, interactive recruiting solutions, LinkedIn, Facebook, Twitter, and career site optimization, one critical piece of the recruiting puzzle seems to be all but completely overlooked.

Before you read any further – do you believe you have an idea of what I might be talking about?

From the conversations I’ve had over the years with many corporate recruiters and recruiting leaders from small companies all the way to the Fortune 500 and the Big 4, as well as the contract recruiters who are hired to help these companies source and recruit talent, I believe that the #1 mistake in corporate recruiting is the failure to fully realize and take appropriate action on the value of the human capital data they already possess.

The #1 Mistake in Corporate Recruiting

In my opinion, the single biggest corporate recruiting flunk is the failure to accurately value and appropriately leverage the human capital data they have in their applicant tracking and/or CRM systems.

Let me show you the depth and complexity of some of the contributing factors of this issue.

The Shiny New Candidate Syndrome

A bachelor’s degree in psychology certainly doesn’t make me a psychologist – but it doesn’t take an advanced degree to recognize that it seems to be human nature to want what they don’t already have.

Certainly I cannot be the only person to be confused by companies investing a large amount of time, focus, energy and money into social recruiting, fancy and high-tech job posting systems and optimized career sites in order to identify and attract new candidates when they might already have the best candidate sitting in their ATS.

Getting a shiny new candidate via your Facebook advertising campaign or your LinkedIn Recruiter account is perceived by some to be “cutting edge,” sexy and seems to afford bragging rights at recruiting conferences. Heck, anything recruiting related that can be tagged as “social” is certainly cooler than ATS mining (for those few companies that can and actually do mine their ATS!).

However, who is to say you don’t actually have faster and lower cost access to better qualified candidates already in your database?

To be sure, the most recently identified candidate is not necessarily the best candidate, and I can speak from experience when I say that some of the best candidates I have ever placed came from “old” resumes – some as old as 4 years since the last update. Someone I recently trained was happy to report he had made a placement by calling a candidate whose resume had not been updated in over 6 years!

Instead of focusing so heavily on trying to find “new” candidates from external sources, companies should spend more time leveraging the candidates they already have at their fingertips.

Resumes acquired in the past that were never reviewed by someone are essentially new candidates – they might be “old” in your ATS, but they’re new to you when you finally dig them up and review them for the first time! There are plenty of “new,” unidentified candidates in corporate ATS/CRM resume databases – you just have to look for them!

The Big Fat Ugly Assumption

Why are so many companies and recruiters focused on looking outside their own database in places like LinkedIn, Monster, Twitter, Facebook, etc. for talent?

I’ll tell you why.

Although largely unspoken and unrecognized, the big fat ugly assumption in recruiting is that every candidate captured in an ATS/CRM has been reviewed, and that if a candidate fits for any position, someone would know.

Nothing could be further from the truth!

I’d estimate that a good portion of every ATS consists of candidates whose resumes have been acquired, but not reviewed, and thus not identified. If that sounds a bit backward, that’s because it is.

When relying on job posting for the majority of the acquisition of candidate resumes, you can actually acquire a resume that is not reviewed. And if you haven’t reviewed a candidate’s resume, you can’t identify them as a potential match for any position, let alone the one they responded to.

If your organization isn’t putting enough emphasis on searching your resume database, you can be assured you have plenty of candidates that have technically been “acquired” because you’ve captured their resume, but have not been identified because no one reviewed them, and thus they cannot be matched to any position.

Even if a company does review 100% of all applicants for the positions they apply to, many great candidates are still overlooked, are not properly identified and are never matched to positions they are qualified for. See “Right Candidate, Wrong Job,” and “The Time Value of Resumes” below.

Do not make the mistake of assuming that someone has searched for and reviewed every possible candidate match in your corporate ATS/CRM. As I said above, there are plenty of “new,” unidentified candidates in corporate ATS/CRM resume databases – you just have to search for them.

A Heavy Reliance On Posting Jobs

Many companies rely heavily on posting jobs for talent attraction and acquisition. I’m aware that some companies get such a high volume of responses from their online job postings and career sites that their recruiters are so buried with reactively processing applicants that they practically have no time to proactively source candidates from their own ATS.

While it may sound like a good thing to have a steady stream of people interested in joining your company and applying to your job postings, no matter what technology or solution you use, there are some serious limitations and universal truths to using job postings to identify talent:

• Posting jobs is a passive candidate identification and acquisition strategy – you are 100% reliant on the right people finding or stumbling across your opening.
• Posting jobs offers no control over the qualifications of the candidates who apply – the phrase “post and pray” is quite accurate, because it comes from the fact that you are essentially hoping that the people you want and need actually find and apply to your opening.
• While 100% of the people who apply to online job postings are interested in the positions they are applying to, a good portion aren’t actually qualified for them (which is both a bad and a good thing – more on this later).
• Posting jobs – via web 1.0, 2.0, or x.0 – primarily attracts the attention of active job seekers only, which is the minority of all people. The Bureau of Labor and Statistics estimates that approximately 14% of all people are “actively” seeking a new job. Even if you add in the estimated 20% of people who are “casually” looking for a new job, you are still missing nearly 66% of the workforce if you rely heavily on posting jobs to find your next great hire.
• Passive and non-job seekers simply do not “see” job postings, even if you place them on their Facebook or LinkedIn pages. Sorry.

It is a HUGE mistake to place a large amount of the control over your talent acquisition strategy in the hands of others – the talent you’re hunting.

Without a strong focus on proactive ATS/resume database mining, you’re primarily in reactive mode, waiting for the people you want and need to come to you, and you can simply cannot target and tap into the elusive and highly valued “passive candidates.”

Right Candidate, Wrong Job

Assuming that every resume submitted into an ATS is reviewed (remember what I said earlier about this assumption), what happens to all of the people who apply online to job postings who are great people, but just aren’t qualified for the specific position they apply to?

If a person doesn’t meet the basic qualifications of the position they directly applied to, does that mean they don’t meet the basic qualifications of other open positions?

Of course not.

The unfortunate reality is that every company in existence is sitting on a pile of people who are a great match for a position other than what they directly applied to. Unless a recruiting organization focuses specifically on mining their resume database, a great many of these people will never be matched to the positions they actually are qualified for.

The Time Value of Resumes

What happens to all of the people who apply to positions that they are not yet fully qualified for, but will be in 1-3 years?

Unfortunately, in most cases the answer to the above question is absolutely nothing, which is both unacceptable and a significant opportunity for all companies.

If I had $1 for every time I have heard a recruiter say that it’s a waste of time to search “old” resumes because they’re old and “out of date,” I’d be a millionaire. Resumes don’t spoil, and they don’t have a “best used by” date – I cannot stress enough how shortsighted it is, as well as just plain wrong, to believe that a resume over 1 year old is worthless.

Just as a point of reference – not too long ago I spoke with someone in a recruiting leadership function from a Big 4 firm that mentioned their organization “purged” millions of resumes during a migration to a new ATS. Ouch!

Failing to search your resume database for people who applied to positions 1-3 or even more years ago is an epic #fail.

While I could write a small book on the many reasons as to why, for the sake of this post, let me just say that it’s quite easy to calculate a person’s career trajectory, and calling people with “old” resumes is a very effective way of recruiting passive candidates – including non-job seekers that you simply cannot identify and acquire through any other means.

Resumes do not lose their value as they age – they actually do gain value over time.

If your organization is burdened by a large collection of worthless old resumes – I will gladly give them a good home.

Black Hole ATS

Practically every company has an internal database filled with 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 possession and be viewed and leveraged as a significant resource and competitive advantage.

However, this post on Weddles gives us a glimpse of just how wrong we would be to think such a thing. 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.

Many Applicant Tracking Systems have horrible search interfaces and extremely limited search capability. Prospective candidates go in, but they don’t come back out. If you can’t easily search your internal database, how can you find the top talent hidden within, let alone determine the total candidate population?

This problem is not isolated to small companies with home-grown Applicant Tracking Systems. I recently spoke with a corporate recruiter from a well-known and highly visible Fortune 500 brand who told me that it’s easier for her to find candidates on Monster and then cross reference the names in her ATS than it is to actually source candidates from her ATS.

Epic #fail!

If you’re sitting on a stockpile of resumes and applicants, you should be able to quickly, easily, and precisely retrieve exactly what you need. If your ATS/CRM doesn’t have advanced information retrieval capability – it’s time you took action to remedy that so you can begin to fully leverage all of the human capital information you’ve harvested, likely at significant cost.

You Don’t Need LinkedIn to Leverage 3 Degrees of Separation

One of the great features of LinkedIn is that it is easy to see beyond your direct connections and to leverage 3 degrees of separation.

However, you don’t need LinkedIn to leverage degrees of separation. To think the value of an ATS resume database is limited solely to the direct access to the people contained within is a serious mistake.

Every person in an ATS database knows other people, who also know other people.

The resumes you have direct access to essentially represent 1st degree connections, through which you can reach 2nd and 3rd degree connections and beyond.

You’d be surprised what happens when you call people from your ATS simply to network with them and ask for help. Why more companies don’t realize that the value of their ATS goes FAR beyond just the people contained within is a mystery to me.

Lessons to be Learned

While it is a huge mistake for companies and recruiters to fail to fully realize and take appropriate action on the value of the human capital data they already possess, mistakes are simply opportunities to learn.

It won’t take much effort for recruiters and the companies they work for to begin to fully leverage the human capital data buried in their ATS databases.

Lessen the obsession with finding the next “new” candidate via external sources and bright shiny social channels and focus more time extracting the value from candidates that are already in your possession but have yet to be truly identified or acted upon. Not fully leveraging an internal resume/candidate database, which has likely been built through significant time, effort and money is a serious flaw in any talent acquisition plan. In some way, shape or form, every candidate record in an ATS has been paid for, and there is simply no sense in paying for something that you don’t use.

Recognize that while posting jobs online can open the candidate floodgates, posting jobs to attract talent some serious limitations, not the least of which is the fact that it is a completely passive talent acquisition strategy offering no control over candidate qualification variables. Also, don’t forget that job postings can only attract active and casual job seekers, limiting you to only 1/3rd of the talent pool available at best.

Mining your ATS is a proactive sourcing and recruitment strategy which affords you significant control over critical candidate qualification variables, and you can specifically and strategically target and tap into the other 66% of the talent pool by searching for resumes that have not been updated or acquired in over 6 months. If you get “too many” applicants to your job postings, make sure there is at least 1 person (ideally more!) who doesn’t have anything to do with processing applicants – you need to have resources that spend 100% of their time proactively mining your ATS as well as external sources.

Ensure your ATS/CRM is highly searchable – if your ATS/CRM is as easy to search as it is to put candidates in, you will be able to fill more of your company’s openings from talent you’ve already sourced. Any opening you can fill with candidates already in your internal system saves you the time, effort, and cost of advertising and searching for “new” candidates. Filling openings with candidates already in your ATS can afford you significant and measurable cost-per-hire, time-to-identify, and time-to-fill benefits.

Having a highly searchable ATS/CRM can help you reduce your reliance on paid resources if you currently use them (LinkedIn, Monster, etc.). Strive to ensure that your ATS/CRM is more searchable than LinkedIn, Monster and even the Internet itself. It should not be easier to search and identify potential candidates via external sources than it is to mine your own private candidate database!

In addition to high searchability, your ATS/CRM should have robust and easy to use contact management functionality to enable recruiters to stay in touch with the people who enter the ATS. Maintaining regular communications with candidates, regardless of their job search status, allows an organization to be ready to take appropriate action when the candidate’s status changes, or when a new position opens for which the person is an excellent fit. Plus, staying in touch with candidates ensures that resumes never get too out of date (if you’re bothered by that sort of thing)  - it’s easy to request an updated resume each year using solid contact management functionality.

And last but certainly not least – be sure to recognize that the value of your ATS database goes well beyond the people contained within. Every person in your internal database knows people, who in turn know other people. Leverage those degrees of separation for professional networking and ask for help in the form of referrals.

I thoroughly enjoyed reading Amybeth Hale’s recent “Sourcing: The Next Sexy Thing” post on the SourceCon website. In her article, she quoted Chris Brogan, who opined that unstructured data gathering, “analytics tools and the people who know how to drive them will be the next sexy thing.“

I could not agree more!

In fact, I published an article over 2 years ago in which I  proclaimed that leveraging human capital data for talent discovery, identification and acquisition was the sexiest function in recruiting.

Unfortunately that was back in 2009, when pretty much no one read my blog, so I am updating and reposting it here for the global sourcing and recruiting community to absorb and respond.

What’s The Sexiest Function in Recruiting?

In February of 2009, I read this excellent post on the Google blog written by Jonathan Rosenberg, SVP, Product Management at Google, and I was especially excited when I got to this part:

“Hal Varian likes to say that the sexy job in the next ten years will be statisticians. After all, who would have guessed that computer engineers would be the cool job of the 90s? When every business has free and ubiquitous data, the ability to understand it and extract value from it becomes the complimentary scarce factor. It leads to intelligence, and the intelligent business is the successful business, regardless of its size. Data is the sword of the 21st century, those who wield it well, the Samurai.” (emphasis mine)

Hal Varian, Chief Economist at Google gets it.

Reid Hoffman of LinkedIn gets it.

Unfortunately, too few people in the HR and recruiting function get it, and even fewer executives who proclaim that their people are their competitive advantage do.

“Get what?” you ask?

I’m talking about the fact that the ability to understand and extract value from data is a scarce factor and a significant source of competitive advantage.

When it comes to recruiting top talent, the ability to understand and extract value from the ever-increasing amount of human capital data available to everyone is the scarce factor in talent identification and acquisition, and it leads to intelligence and success in business through the ability to hire more of the best people more quickly!

As such, the sexist function in talent acquisition is sourcing!

The Big Deal about Human Capital Data

Every day, more information about more people is made available electronically in the form of data, and I would argue that not only is the sheer volume of human capital data increasing, but it’s accelerating as well.

This comes from a variety of activities that people perform: responding to job postings with resumes and entering them into corporate databases, creating social media profiles online, posting resumes on the Internet and in online job boards (e.g. Monster, Dice, CareerBuilder, etc.), being mentioned in press releases, blogging, Tweets, foursquare check-ins, LinkedIn network updates, etc.

With the amount of human capital data available increasing at an accelerating rate, it is becoming more important for organizations to be able to leverage these sources of human capital data for talent identification and acquisition.

There is no denying that building relationships with potential candidates is at the core of effective recruiting, and I don’t think that will ever change. However, what has changed is that if you can take advantage of and tap into the power of the unprecedented amount of human capital data available to sourcers and recruiters today (which increases and accelerates every day!), you can quickly find, engage and develop relationships with and recruit more of the right people.

I’ll say it again because I don’t want anyone to scan past this critical point –  effectively leveraging human capital data enables recruiters and companies to develop relationships with and recruit more of the right people! Especially the coveted “passive” candidates.

If your definition of success (or acceptable paycheck) is based on achieving more than 1 to 2 hires per month, you are at a significant competitive disadvantage if you cannot leverage human capital data.

If you CAN effectively leverage human capital data for talent identification and acquisition, it is a productivity MULTIPLIER.

And for those who believe that the best people can’t be found online or in a database, I would argue that with each passing day, there are fewer and fewer people that cannot be digitally discovered either directly or indirectly through networking or referral recruiting with people who can be found online or in your ATS.

Sourcer = Data Analyst?

I think the term “sourcing” does not do the role/function of leveraging human capital data for talent identification proper justice. I think that what most people refer to as a sourcing function is really more accurately labeled as human capital data analysis.

Data analysis is defined as a process of gathering, analyzing, and transforming data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making.

If you take a look at a typical data analyst job description, you’ll see responsibilities such as:

• Collaborate with business process owners to identify opportunities; define business requirements, and design and implement solutions designed to maximize efficiency and productivity
• Perform complex data mining and aggregation; critically examine the results
• Accumulate, analyze, and interpret data in understandable terms for the customer from multiple systems
• Analyze complex data including: structured, unstructured, and plain text
• Develop analytic approach in collaboration with project staff
• Respond to ad-hoc and standing customer requirements
• Utilize in-house database applications
• Perform data capture, cleansing and migration
• Research new data sources and analytical tools
• Support analysis results at customer meetings
• Utilize query languages  (SQL)
• Conduct competitor and benchmarking analyses

Here is the same job description, adapted to sourcing/recruiting:

• Collaborate with managers and business unit owners to identify opportunities, define position requirements, and design and implement talent identification solutions and processes designed to maximize efficiency, productivity, and results
• Perform complex talent mining and aggregation; critically examine the results for relevance, qualifications, and probability of match to hiring requirements
• Accumulate, analyze, and interpret human capital data in understandable terms for the customer from multiple systems, including, but not limited to the Internet, resume databases, and social media
• Analyze complex human capital data including: Resumes, social media profiles, blog posts, press releases, and unstructured plain text
• Develop analytic approach in collaboration with project staff
• Respond to ad-hoc and standing customer requirements
• Utilize in-house Applicant Tracking Systems and database applications
• Perform data migration, permanently capturing human capital data from multiple sources and entering them into corporate ATS/Talent Warehouse
• Research new human capital data sources and analytical/search tools
• Support analysis of search results at customer meetings
• Utilize query languages (Boolean)
• Conduct competitor and benchmarking analyses

If you are a sourcer or are responsible for sourcing potential candidates, what do you think of the above job description?

Sourcing is Much More than Boolean Search

As demonstrated by the above exercise, a sourcer or a recruiter performing sourcing is essentially functioning as a data analyst that is analyzing human capital data for talent identification and acquisition.

This process involves analyzing and interpreting hiring needs and requirements, often with poor or incomplete information, leaving them to piece the puzzle together. Once the needs have been understood, they intelligently assess and strategically select available information resources to leverage, translating hiring qualifications into precise information retrieval strategies to search targeted sources of talent-related data and quickly retrieve relevant results – human capital data representing people who have a high probability of meeting or ideally exceeding the basic qualifications of the hiring needs.

A talented human capital data analyst is capable of leveraging information sources and systems with such speed and precision to enable organizations to achieve Just-in-Time sourcing and recruiting – identifying and acquiring the right talent, in the right amount, at the right time, without the need for having to recruit people ahead of need and building talent pipelines that may not be recruitable when the actual need arises.

Human capital data analysts are capable of searching databases and systems containing data representing millions of people to quickly and precisely uncover, identify, and tap into the talent pools that exist in every source of human capital data to target people with specific educational requirements, years of experience, current and prior roles and responsibilities in specific environments and in some cases in specific companies. That’s no small feat!

Whereas data analysts responsible for working with financial, product, customer or other types of data are responsible for producing reports and analyzing information for meaning and identifying relationships to assist with strategic decision making, human capital data analysts are responsible for identifying and assisting in the acquisition of a company’s most precious assets – its talent, and potentially (and ideally!) the next “game changing” employees who can take the company to the next level.

What’s Your Competitive Advantage?

Most well run companies know that the true scarce resource is talent – and that identifying, acquiring, and retaining top talent is a company’s only true and sustainable competitive.

The more ubiquitous human capital data becomes, the more critical it becomes that companies employ people with strong information retrieval and human capital data analysis skills who are capable of leveraging information systems more quickly, precisely, and accurately than the competition to identify top talent and target them for acquisition.

As Jonathan Rosenberg of Google stated, there is significant intelligence and value in data, but it does not come from simply having access to the data – it comes from the ability to understand and extract value from the data.

I would argue that the most critical asset of any company is its human capital – and the most critical step in the human capital supply chain is the process is identifying human capital.

Don’t agree?

Consider this – you simply cannot engage, develop relationships with, acquire, or retain people you haven’t identified in the first place.

Final Thoughts

There is a reason why companies pay financial analysts, data analysts and business intelligence analysts very good money – because they are knowledgeable specialists and they perform highly critical functions that cannot be fully automated. Typically, the more critical the corporate function, the more specialized and capable the resources are, the more they are compensated, and quite often, the more advanced the technology solutions they employ.

I think that the majority of HR/recruiting organizations as well as many corporate executives haven’t yet figured out that analyzing human capital data for talent identification and acquisition is a highly specialized, valuable, and critical function.

While there are opportunities to automate some aspects of human capital information retrieval, it would be foolish to rely on a software solution alone for your talent identification and acquisition needs. No company relies solely on software to make critical business decisions – computers and applications are used to move and present information (reports, etc.) and then people perform the real work in the form of analyzing the information and making decisions.

It’s also a mistake to rely on entry level, junior, and/or low cost resources for talent discovery and identification. In case you haven’t noticed, there’s a continual war for talent being waged. Do you really think it’s a wise corporate strategy to try to cut costs and corners and battle it out with your competitors with less experienced and non-specialized resources?

As I’ve previously asserted, the most critical step in the human capital supply chain is the process is identifying human capital, because you simply cannot engage, develop relationships with, acquire, or retain people you haven’t identified in the first place. As such, don’t you think it would be wise to employ highly specialized, experienced, and capable resources in talent discovery and identification roles?

Not only is human capital data sexy, it is the sword of the 21st century – those who wield it well will win the battles they fight in war for talent.

Do these quotes sound familiar?

• “People are our greatest asset.”
• “The only real sustainable competitive advantage of any company is the recruitment and retention of great people.”
• “Talent is our #1 priority as a company.”
• “Your technologies, products and structures can be copied by competitors, but your people can’t be.”
• “No matter what kind of business you are in, having the right people determines your company’s success or failure.”
• “The ability to find and hire the right people can make or break your business. It is as plain as that. No matter where you are in the life cycle of your business, bringing in great talent should always be a top priority.” – Michael Dell

How many times have you read or heard something similar?

The ubiquitous “people are our greatest asset” sentiment sounds good, and no doubt feels good to say, but whenever I hear or read it, the first question that comes to my mind is “What are you doing to ensure that you are identifying and acquiring the right people?”

If you believe that finding and acquiring top talent is your #1 priority, then I have a few questions for you.

Critical Questions for Sourcers and Recruiters

• What do you do on a consistent basis to ensure that you are finding and recruiting top talent – the best people that can be found?
• Do you have a strategy to find the best candidates?
• Once you have identified a candidate who is a match for the need you are sourcing and/or recruiting for, how do you know they are a good candidate beyond the skills and experience match?
• Are the people you find the best people you can find, or the first people you could find, or the easiest people for you to find?
• Do you think that the people who apply to your jobs posted online are the best candidates available? How would you know?
• What is your strategy to find great people that your competitors can’t and don’t find?

Critical Questions for Companies

• If talent is your #1 priority, where does your investment in talent identification and acquisition rank compared to all other corporate expenditures? (Payroll doesn’t count)
• How much does your company spend on business intelligence applications and data warehousing? (Ballpark estimate will do)
• Do you think that acquiring and analyzing customer, product, sales, etc., data in order to make better business decisions is more important to your company’s long term success than acquiring and analyzing human capital data to make better hiring decisions?
• How much does your company spend on applications and technologies that enable your company to discover and identify great people? (Most ATS’s and CRM’s don’t count)
• Do you have a budget for sourcing and recruiting technology and process R&D?
• What is your talent identification and acquisition strategy? (Posting jobs and soliciting referrals doesn’t count – more on this in a bit)

Talent Attraction & Referrals vs. Talent Discovery and Identification

Jim Collins, the author of Good to Great, has said that many companies think that a cunning strategy or great performance will attract the right applicants, but that’s backward – people must come first.

I could not agree more.

Talent attraction, whether it be in the form of employer branding efforts, posting jobs online or social recruiting via social media, is not a method of discovering and identifying talent that involves any assurance of or control over candidate quality.

Soliciting referrals from current employees is generally accepted as a sound talent discovery strategy, and many companies publish data that suggests that referrals do tend to be “higher quality” and have a higher retention rate. I think this is mostly due to the fact that people typically avoid referring others that would reflect poorly upon themselves, so the selection process does have a bit of built-in candidate quality control.

However, while we all know that referrals are a great source of hires, are referrals really the best people you or your organization are capable of finding?

Soliciting employees for referrals is one of the easiest and lowest cost methods of talent discovery, so it’s no wonder it’s so popular as a method of talent discovery. However, referral recruiting isn’t guaranteed to net you the best people available to be found if you really tried.

Referral recruiting can only yield you people that someone in your organization knows, and the right or best people are not always already known to someone in your company.

Talent attraction efforts and soliciting referrals have their place – I’m not challenging that. However, companies that claim that talent is their #1 priority need to incorporate a strategy of talent discovery and identification that involves actively researching and hunting for top talent – specifically those great people who:

1. Are not already known to someone in your company and cannot be referred to you
2. Are doing an excellent job for their current employer and won’t ever “see” employer branding or a job posting even if it was placed directly in front of them

Investing in Talent Discovery and Identification

Jim Collins has said, “People are not your most important asset. The right people are.”

Practically all technologies, products and services can be copied and rarely remain a company’s competitive advantage for long. Being able to consistently find and hire the right people is truly the only means by which a company can attain a sustainable competitive advantage, regardless of industry.

Spending time and money on posting jobs, social recruiting efforts, and executing a sound referral recruiting strategy will always yield candidates, but they are not enough to ensure that you are discovering the best people that can be found and identified.

While many companies think it’s logical and necessary to invest large sums of money and effort into business intelligence applications to analyze product, customer, sales and all other kinds of data, too few companies invest anything beyond trivial amounts of money and effort into technologies, applications and research that can help them actively acquire and analyze human capital data to make better hiring decisions and create a sustainable competitive advantage.

So what are you doing to ensure that you are identifying and acquiring the best people for your company?

I recently listened to an interview with DeeDee Doke of Recruiter.co.uk in which she related to Amybeth Hale that the perception in the U.K. is that sourcing is an entry level career in the recruiting industry.

Apparently, using information systems for talent discovery and identification is perceived by many as a junior role and skill across the pond.

I’m saddened by this, and what makes it worse is that this sentiment isn’t limited to the U.K. – there are plenty of people in the U.S. as well as the rest of the world who feel the same way.

This perception most likely comes primarily from the fact that many people don’t really yet understand, appreciate or know how to fully leverage the latent power of human capital data.

Yes, there is deep latent power hiding in data of all forms – all you need to do is take a look at business intelligence solutions and how much money companies spend on them (millions) to get a basic appreciation of the power of data.

Unfortunately, it doesn’t seem that many companies value human capital data in the same manner that they value their sales, product and customer data. 

What is Human Capital Data?

I define human capital data as any information, typically text-based, that can be used as a basis for gaining insight into what kind of contribution a person could be capable of making to an organization.

Of course, the most familiar source of human capital data is the resume.

With resumes having been around for quite some time, there are those who feel resumes are dead (they’re not, nor will they ever die – they will just evolve). Regardless of how they change or what you may eventually call them in the future, there will always be a need for a searchable summary of a person’s experience and accomplishments.

Personally, I love resumes. They are deep sources of human capital data – information that can be analyzed to enable me to gain predictive insight into a person’s capabilities based on what they have been paid by others to do in the past.

In addition to resumes, social networking sites such as LinkedIn, Twitter and Facebook can be excellent sources of human capital data, in addition to the Internet itself, with blogs, press releases and various treasures just waiting to be found.

Today, sourcers, recruiters and companies have more access to more human capital data than ever.

Could this very fact perpetuate the perception that sourcing is a junior role, simply because resumes, social networking profiles and Internet content is so easily accessible? I definitely think so, but it’s based on faulty logic.

Accessing human capital data is the easy part. Every search “works.” Anyone can type in a title and a couple of keywords into LinkedIn, Monster, their ATS or the Internet and get results.

Easy right?

In fact, it’s so easy you can outsource it for $5/hour. Heck – even a an intern with no experience can do it!

Finding Some vs. Finding the Best

Getting some results from searches has never been the challenge – it’s always been easy.

What most people fail to grasp is that finding some results is not the same as finding the best results. Sure, your query pulled up some people who have the right title and seem to have the right experience, but have you ever wondered if the ones you found are the best people available to be found in the source you’re searching?

That is what we’re trying to do, right – find and hire the best people that can be found?

Feeling good about searching for a title and some keywords and getting some results is like feeling good about hitting a golf ball. If you don’t care about precisely where the ball goes, simply making contact with the ball and making it go somewhere feels like an accomplishment.

However, some people are capable of not only hitting the ball, but making it go farther than most and exactly where they want to go. Holes-in-one are actually possible. Professional golfers know this and are constantly working on being able to get the ball in the cup with the least number of strokes possible – they are not happy just to hit the ball around. They also get paid quite a bit of money – because they get the best results.

What Does Your Target Look Like?

One of the challenges associated with understanding the latent potential of human capital data is that there is no known target to aim for. Golfers have the advantage of knowing where their target is – it already exists on the green.

The problem with sourcing is that the best candidates are not already identified, and each one can look completely different – there is no predefined target resume that is automatically indicative of top talent. Some of the best candidates have unimpressive resumes that leave you with little clue as to their true potential, let alone what they have already accomplished for other employers.

Except for the most complete and detailed LinkedIn profiles, social network data gives you a much less predictive sense of the true capabilities of the person the data represents.

On top of all of this, a good percentage of all of the available search results of each and every source of human capital data are never actually found, and most people are completely unaware of this.

What are You Trying to Accomplish?

If you’re looking for people who have the lowest golf scores – you should look for the highly paid professionals. They’re getting paid the most because they get the best results. However, if you’re not keeping score, you might be satisfied with any weekend duffer.

If you’re looking to identify and acquire top talent, you should look for professional knowledge workers who understand, appreciate and can fully leverage the latent power of human capital data – they get the best results. However, if you’re happy with just filling positions, you might be satisfied with the results produced by entry and junior level sourcers and recruiters.

Now that one year has passed since I wrote the original post, I have decided to significantly update and repost it – you can find it here.