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.

I’ve read a few articles recently talking about IBM’s Watson and how the technology they developed may be the harbinger of unemployment for people in many professions.

Here’s one from Fortune magazine, asking if IBM’s Watson will put your job in jeopardy.

Here’s another suggesting that those who train others in Internet, social media, ATS, and resume database sourcing techniques and strategies will be eventually eliminated by semantic search solutions.

Watson Winning at Jeopardy isn’t Surprising

First, let’s first recognize that it’s an apples to oranges comparison between Jeopardy and sourcing/recruiting.

The ability to quickly research and answer trivia questions (or provide questions for the answers, in the case of Jeopardy) is a far cry from having to boil a hiring need (skills, capabilities, and specific responsibilities in specific industries and environments) down to a series of queries to mine flawed and incomplete human capital data (i.e., resumes and social media profiles) in order to return people who have a high probability of not only being qualified for the position, but also interested in the job (i.e. “recruitable”).

With trivia, all of the facts and information are readily accessible, completed and identifiable on the Internet, or in the case of Watson, saved on a multi-TB hard drive array.

It’s not really shocking that a highly specialized $900,000,000 to $1,800,000,000 (estimated 3 year cost of developing Watson) NLP (Natural Language Processing) computer can sort through 200 million pages of structured and unstructured content, including the full text of Wikipedia, to retrieve information faster than a human relying on memory alone.

Why is anyone surprised that Watson spanked people?

I wasn’t.

However, I can’t pass up the opportunity to point out that Watson did make mistakes – here’s one example in which Watson thought the answer was “Who is Picasso?” when the correct answer was “What is modern art?”

Who knew that the err is human, as well as inhuman?

The Unique Challenge of Human Capital Data

Unlike finding the answers to trivia questions, when it comes to finding and identifying qualified and talented people based on their resumes and social media profiles and updates, the information is often incomplete, and in many cases, critical bits of identifying data are simply not present.

For example, how do you find someone with Spring MVC experience when many people don’t mention it on their resume, nor on LinkedIn, Twitter, blogs, etc.?

I recently gave the world a tiny glimpse into the Dark Matter of LinkedIn – direct keyword, title, and even concept/relational search methods, used by humans or algorithms, can only retrieve results based on existing text.

Quite simply – if the text isn’t there to be retrieved or analyzed, a semantic search/NLP algorithm can’t do anything with it.

Good sourcers really do “read between the lines” of both the job description and requirements as well as the human capital data they are searching for and analyzing.

There is much more to high-level sourcing than keyword and title search/match.

There have been semantic solutions on the market for quite some time that can do keyword, title and concept matching reasonably well (as well as some that claim to, but don’t). The issue with those solutions that no one seems to (or wants to) realize is that they have limitations – they find some matches, exclude some, and bury others.

The real question is who, how, and why are some matches found and ranked highly, while others are excluded, and others ranked lowly but actually represent the best talent?

What Do I Know?

I have hands-on, practical experience (read: trying to find people to fill real jobs) with many of the “top shelf” semantic search applications out there, specifically designed for human capital data, so when I write or speak on the matter of semantic search, I’m not throwing around empty opinions.

I’ve seen what these solutions can do, and I’ve also directly experienced their limitations, including what they simply can’t do.

Unlike many people who write on the subject of semantic search, I have to personally find people and help others find and recruit talented, qualified candidates with highly specialized skills and experience within 24-48 hours of receiving a client request on a daily basis. If semantic search solutions (including the one I have access to) could speed up that process and help me find more and better candidates faster – trust me, I would use them!

I’ve witnessed a sourcer with 9 months of total experience find better qualified matches (and faster) than a big-name semantic search solution in front of one of the senior technical managers responsible for developing the product. It was eye-opening and even somewhat confusing for them, to say the least.

I’ve also spoken with sourcing/recruiting managers at Fortune 500 companies who have evaluated leading semantic search solutions and they passed on purchasing them because the solutions did not find more and better results faster than their sourcing/recruiting team.

Ultimately, it’s not about humans vs. technology – it’s about results.

The Solution is Part of the Problem

I’ve found the creators of semantic search products don’t seem to like it nor do they seem to really listen when you point out the flaws and limitations of their creations – and I’ve had exchanges with people who hold patents in this space.

I’ve also gotten the sense from talking with semantic search solutions providers that some of these folks believe that sourcers, recruiters and HR professionals don’t (and/or can’t!) really understand semantic search and more complex information retrieval strategies.

To their credit, if their perception (based on experience or otherwise) is that recruiters and HR professionals struggle with Boolean search – the most basic query “language” – why wouldn’t they assume that the average recruiter could not possibly understand and appreciate what’s going on “under the hood” of semantic search solutions?

However, it is folly to apply that stereotype to all sourcing, recruiting and HR professionals – there are plenty of us who actually know more about the specific challenges posed by human capital data and the practical needs and concerns of recruiting organizations than the people who are developing the solutions that we are supposed to intrinsically trust to automatically find the best people available.

I don’t hate – I appreciate semantic search. I simply want these solutions to live up to their hype. Semantic search vendors – listen to your current and potential customers – they just want your product to work better!

I’d like to extend an open invitation to any semantic search/NLP vendor – I will happily evaluate your product and make suggestions for improvements…for free! If you’re very confident in your solution, I’ll also write a review online. If you’d rather not have your product exposed publicly, I can also evaluate products privately. I really do want to accelerate the efficacy of semantic search applications for sourcing and recruiting!

I also want to educate others who may be buying these kinds of solutions so they are more knowledgeable and informed as to the pros and cons, capabilities and limitations of these solutions, and not sold simply on impressive sales pitches, techno-speak and “see how many results?” demonstrations. If you’re a potential customer of semantic search solutions, please be sure to include your best sourcers/recruiters in the evaluation process – if the only people who are evaluating a semantic search solution are HR, management, and procurement professionals who don’t actually search for top talent on a daily basis and won’t be using the proposed solution, you can easily be sold on a product that doesn’t actually work as well as you might think based on the sales presentation.

If you’re looking to buy a new flat screen TV or car, anyone can read reviews online, test drive them and compare them to competing products.  I find it interesting (and telling!) that you can’t do the same thing when it comes to recruiting and HR software.

When you buy a house – you get it inspected by a specialized professional before you buy it so you really know what you’re getting beneath the surface. Before you buy a semantic search solution, you should have it evaluated by a person who specializes in human capital information retrieval (who is also ideally a neutral third party!).

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?

Many people equate sourcing candidates with simply creating and running Boolean search strings.

In my opinion and experience, Boolean search neither adequately describes nor gives proper credit to what sourcers and recruiters are really doing when they leverage the Internet, resume databases, ATS/CRM applications and social networking sites such as LinkedIn to find candidates, and to what some very talented and highly skilled professionals are able to accomplish with human capital data.

I had the distinct honor of delivering the keynote presentation at SourceCon 2010 which was held at the International Spy Museum in Washington, DC. I spoke about a specialized form of information retrieval and text/data mining which I call talent mining, defined as querying and analyzing human capital data for talent discovery, identification, and ultimately acquisition.

At the strategic level, talent mining is the process of transforming human capital data into an informational and competitive advantage – much more than simply writing Boolean search strings.

Companies have been leveraging financial, product, customer, marketing and many other types of data for decades now, building data warehouses and using business intelligence solutions and analytics to make better, fact-based decisions.  I believe that we are just beginning to enter an age in which companies will start to understand and appreciate the power of leveraging human capital data to predictively identify more qualified candidates, make better hiring decisions, and make them faster and more efficiently than previously thought possible.

My vision and prediction of the next frontier in human capital and talent analytics involves companies building talent warehouses and specialized talent intelligence solutions that will enable them to quickly and predictively discover, identify and acquire top talent. While this may be many years off for most companies, it is quite possible to more effectively leverage the vast amount of human capital data available to just about everyone today. During my keynote, I detailed the 5 levels of talent mining, the specific advantages that talent mining affords over any other method of talent discovery and identification, and a glimpse into the future of sourcing and talent acquisition.

Below you can view the expanded version of the slide deck I used for the presentation, and you can view the video here. Enjoy!

This question has been burning in my mind for quite some time – why is it that so many ATS/recruiting CRM vendors offer poor or limited candidate search functionality? I’m not talking about ATS vendors you’ve never heard of – I’m talking about some of the biggest names in Applicant Tracking/Candidate Relationship Management applications.

I’m well aware that ATS’s serve many critical functions beyond searching for the candidates contained within them, but let’s pull no punches here – you can’t hire someone, or begin to automate candidate relationship management with someone you haven’t FOUND in the first place. And just because a candidate is buried somewhere in your database, it doesn’t mean you’ve actually found them (or can find them when you want or need to).

The bottom line is that data is of little to no value if you can’t retrieve the information you want, when you need it. What is the point of storing human capital data if you can’t precisely retrieve exactly what you want, when you want it? 

Deficiencies Defined

I won’t get into automated/system-side semantic search and match in this post – I’m going to focus on the ability to manually enter search strings to find candidates.

When I say “poor/limited” candidate search capability, I mean at least one or more of the following:

• Unnecessarily short search fields (e.g., 100 characters, including spaces!)
• Lack of full Boolean search (e.g., inability to use AND, OR, and NOT, nesting, etc.)
• Lack of stemming/root word search (e.g., admin* yeilds administrator, administration, etc.)
• Lack of field-based search (e.g., most recent experience, most recent title, education, etc.)
• Lack of searching by zip code radius

Critical Candidate Pool

A company’s internal candidate database is made up of people who have responded to that company’s job postings, people who went to the company’s website and entered their resume and information (not in response to a specific job), and people who were identified elsewhere (employee referral, LinkedIn, Twitter, Monster, niche job board, the Internet, etc.) and entered into the database by an employee. 

One could easily argue that this pool of candidates should be the first place sourcers, recruiters and hiring managers look when they need to find candidates. Unfortunately, this is not the case.

ATS = Candidate Source of Last Resort

A relatively common observation/complaint I hear from recruiting managers in corporate and agency staffing environments is that when it comes to running searches to find potential candidates, their sourcers and recruiters tend to search LinkedIn and the job board resume databases they have access to first, or at least before they search their internal ATS/CRM application. In many cases, recruiters with access to job board resume databases will only use their own ATS as a “source of last resort.”

A recent survey conducted by TalentDrive, which polled over 8,000 companies and staffing firms, confirms this to a shocking degree. They found that “98% of the companies surveyed did not find Talent from within the existing Company ATS.” In other words, candidates can check in, but they don’t check out.

Not quite as shocking, but equally disturbing is that an Online Sourcing Survey conducted by TalentDrive found that almost two-thirds (64%) of the employers represented by the survey’s participants did not know how many qualified candidates were in their own ATS databases.

I think I know one of the major contributing factors to both statistics - most ATS’s aren’t very searchable!

Strong Candidate Search Capability is Out There

I believe the reason why Applicant Tracking Systems are often used as the “source of last resort” is because most ATS’s have candidate search functionality that is far inferior to what sourcers and recruiters have available to them in LinkedIn, any of the major job board resume databases, and even Google. Can we blame recruiters for going first to sources they have access to that actually ENABLE them with the power and control to quickly find the people they need?

If you take a look at large repositories of deep human capital data, such as those offered by LinkedIn and the “big 4″ job board resume databases (Monster, Careerbuilder, Hotjobs, and Dice), you’ll find robust search capability. All accept full Boolean logic, accept relatively long/complex/precise search strings, feature zip code radius search, and offer field-specific searching. Monster takes Boolean search one step further by offering proximity search with the NEAR operator, and Careerbuilder offers advanced AI matching with their R2 functionality(which I think it powered by Sovren – can anyone confirm this?). 

Regardless of how many excellent candidates may be buried in a company’s ATS/CRM, if recruiters can’t run appropriately precise searches to quickly and easily retrieve highly relevant results, they are actually incentivized to use other sources to identify candidates. Sourcers and recruiters will naturally gravitate to what works for them, and unfortunately, in many cases, it isn’t their ATS.

The Customer is Always Right?

When I recently challenged a major ATS vendor regarding their extremely short candidate search field (100 characters, including spaces), their response included this interesting and unanticipated angle - they claimed that 99% of their clients are statisfied with their short search field. In other words, very few prospective or current customers of their ATS asked about, commented on, or asked for improvement of the short search field.

A representative of another well-known ATS chimed in on Twitter and said they also don’t come across many clients asking for more than 100 characters in the candidate search field.

I can only assume that their customers either aren’t very proficient at talent mining, don’t understand the value of human capital data, or worse – both. Regardless, we’ve already seen the statistics from TalentDrive’s surveys - most companies don’t even use their ATS to identify candidates. If they’re not using their ATS to find talent, why would they care about the length of the search field, or even if it supports basic Boolean logic? 

So what we have here is ATS vendors who are not developing and offering robust candidate search capability because their customers aren’t asking for it. Okay, I understand “the customer is always right,” but it’s a sad state of affairs when companies who create talent/human capital solutions are not incorporating strong/advanced candidate search capability into their products because their customers don’t understand the value and full potential of human capital data.

Whatever happened to educating and informing your customers, providing training, and offering a product that exceeds your customers’ expectations and provides them with a true competitive advantage?

100 Characters is Not Enough

I conducted a very informal poll on Twitter and Facebook, asking sourcers and recruiters what they thought of a 100 character candidate search field limit, and 100% of those who responded all felt that it would handicap their ability to find the right candidates. By comparison, Monster’s resume database has a keyword search field that accepts up to 500 characters, LinkedIn’s search field is bottomless (I just crammed 6003 characters in the keword field and LinkedIn laughed and asked, “Is that all you got?”), and even Google accepts up to 32 search terms (at an average term length of a little as 5 letters, that’s still 160 characters, NOT including spaces or operators). 

The TalentDrive survey discovered that the number one sourcing challenge facing companies currently is filtering through the mass of resumes and increased number of applicants. In other words, the candidate “haystack” is getting HUGE, and it’s becoming more challenging to sort through it to find the needles.

Ultimately, short and basic candidate searches are imprecise and yield a high volume of imprecise results, riddled w/false positives. Without more room to create search strings that are appropriately precise, relevance will suffer, and with more resumes to search through – the issue is exacerbated.

The Future of Staffing and Recruiting

I firmly believe that the one aspect of recruiting that has the most potential to improve the speed of talent identification (the time to find metric) and increase the quality and quantity of candidates identified is electronic talent discovery and identification. With each passing day, there is more data available on more people somewhere – on a social network, in a resume database, or in your ATS – and it will only increase and accelerate. The ability to slice and dice human capital data will afford companies a HUGE competitive advantage.

I will never get tired of quoting this passage from Google’s blog: “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.”

The ability to extract value out of human capital data is already, and will continue to be, THE complimentary scarce in recruiting and staffing – but most people just don’t know it yet. ATS/Recruiting CRM vendors need to step up, recognize this, and offer their clients solutions that enable them to truly capitalize on their human capital data and offer them a competitive advantage.

If anything, I feel that employers and staffing firms should provide their recruiters access to MORE powerful and capable candidate search functionality than publicly and widely available resume databases or social networks. If they don’t, their ATS will continue to be the candidate source of last resort.

I believe that ATS/CRM apps should essentially serve as talent intelligence solutions, not unlike business intelligence solutions and decision support systems. The power lies primarily in the the human capital data/information stored within, and the ability to retrieve and analyze that information for talent identification and to make hiring decisions. 

One Thing has Changed

I don’t believe that the majority of the recruiting life cycle has changed over the past 20 years, or will change all that much in the future. Building relationships with current and potential candidates will always be at the heart of the recruiting process.

However, the one step in the recruiting process that has changed dramatically is sourcing, or talent discovery/identification. Information systems and applications have evolved rapidly over the past 20 years, and will likely continue to do so. With more information available about more people growing with each passing day, information retrieval becomes absolutely critical.

The ability to instantly retrieve information about the right people at the right time can accelerate a company’s ability to build relationships with more of the right people more quickly, leading to faster and higher quality hires with less effort.

If you find that concept interesting, I suggest you read these two posts about Lean/Just-in-Time recruiting.

A Call to All ATS/Recruiting CRM Vendors

If you work for or use an ATS that has strong candidate search functionality – Congratulations, you are among the fortunate few! Vendors – make sure your customers fully understand and leverage that power. Users – take full advantage of the candidate search capability, and be sure to not use your ATS as a source of last resort. Those candidates in your ATS are there for a reason – either they expressed interest in joining your company, or someone in your company expressed interest in them! 

If you work for an ATS vendor with poor/limited candidate search functionality - Why do you offer sub-par candidate search capability? Recognize that the future of human capital information systems lies primarily in talent discovery and identification. Either build in your own robust candidate search capability, or simply integrate any one of a number of excellent 3rd party text search and/or resume parse/search/match applications that are available. Educate your current and potential customers and explain to them the value and potential of human capital data. CRM functionality is great, but is of little value without the ability to find the right people to begin to manage relationships with in the first place!

If you currently use an ATS with poor/limited candidate search capability - Send this article to your vendor. Let me know how they respond, and if/how they can answer the question of why they offer such poor/limited candidate search functionality. They’re essentially putting you at a competitive disadvantage!

Does your recruiting or staffing organziation have Talent Intelligence?

I believe that all staffing organizations should view and value their internal resume/candidate database/ATS as a proprietary business intelligence tool.  Business intelligence refers to applications and technologies that are used to gather, provide access to, and analyze data and information and help companies develop consistent and “data-based” business decisions — producing better results than basing decisions on “guesswork.”

I define “Talent Intelligence” as refering to applications and technologies that are used to gather, provide access to, and analyze Talent-related (Human Capital) data and information and help organizations develop consistent and “data-based” Talent-related decisions.

Business intelligence applications are usually 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 company’s ”Talent Warehouse” should serve 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.

Practically every Fortune 1000 company (and many smaller ones too) utilizes and leverages business intelligence solutions to make better decisions and run their companies more effectively and efficiently. However, very few – if ANY – companies actually have a true Talent Intelligence solution. 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 many vendor solutions currently on the market to be a true Talent Intelligence solution. Most are simply systems that track and organize applicants.

I find it ironic that companies in nearly every industry invest millions and millions of dollars on their data warehousing/business intelligence initiatives – just to be able to retrieve and analyze their data to enable them to make better business decisions, yet I’d argue that every company’s Human Capital is actually their most valuable and critical asset. So why is it that HR, recruiting, and staffing technology is so far behind in technologies used for gathering, retrieving, and analyzing financial, manufacturing, etc., data? 

Recruiting and staffing organizations should be looking to leverage technology to support the effectiveness and productivity of their sourcing and recruiting associates by building a deep and broad Talent Warehouse and empower their recruiters and sourcers with a search interface that affords them the ability to perform highly precise queries and semantic search strategies that execute quickly and produce highly relevant results.

While there are many important aspects of Talent Intelligence solutions that distinguish them from your garden-variety ATS and HRMS solutions, here are 2 critical aspects of building and utilizing a Talent Intelligence system:

Populating the Talent Warehouse

A Talent Warehouse should be both broad and deep. While Talent Warehouses vary in size, I would say on the low end, for smaller organizations in a single metro area, a Talent Warehouse should be no less than 20,000 resumes and/or candidate profiles. There is perhaps no upper limit to the size of a Talent Warehouse – larger corporate and agency staffing organizations often have several million resumes/candidate profiles in their repository.

Statistically – size does matter. Please take a look at this post I wrote about statistics and the size of resume databases a while back that goes into quite a bit of detail regarding normal distributions, the Central Limit Theorem, and the Law of Large Numbers. The short version is that more resumes/candidate profiles = a higher probability that you have a given quantity of candidates who match any given hiring need. This can enable Lean/JIT sourcing and recruiting.

In an ideal setup, a Talent Warehouse is fed new resumes/candidate profiles both manually (by sourcers, recruiters, and candidates themselves) and automatically (using search aggregators such as infoGIST, TalentHook, DataFrenzy’s RAM, etc.) from a wide variety of sources – to include the Internet, referrals/networking, Job Boards, RSS feeds/automated Internet search alerts, ad responses, career fairs (of all kinds), LinkedIn, Blogs, and various and sundry other social media.

Search Interface and Searchability

Having TONS of great talent/human capital data is wonderful, however – it’s of little value without the ability of a user to precisely extract out relevant and useful information from the system that can be used for quick and accurate talent identification and acquisition.

The value of a database (or Talent Warehouse) lies not only in the information contained within, but moreso in the ability of a user to extract out precisely and completely what the user needs. See this post to read more about this concept: The Value of a Database

When using information systems, sourcers and recruiters perform Talent Mining to extract useful and relevant human capital/talent data. Just as a data warehouse can be a significant enabler of commercial business applications, such as customer relationship management (CRM) applications, a Talent Warehouse can and should be a significant enabler of Human Capital Relationship Management (HCRM) applications.

The ideal search interface of a Talent Warehouse or Talent Support System should support 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.

Conclusion

A well designed and fully featured Talent Intelligence solution can significantly improve sourcer and recruiter effectiveness and productivity, reduce reliance on the major job boards, and reduce the amount of time sourcers and recruiters spend trying to source candidates via free but very low ROTI (return on time invested). It’s well past time for HR, recruiting and staffing technology to catch up to technologies such as data warehousing and business intelligence applications that have been utilized to support financial, manufacturing, and just about every other critical aspect of business for decades. After all, is there anything more important to an organization than Human Capital/Talent?