Curious to learn more about my upcoming keynote at SourceCon 2010 in DC?
My session will essentially be a follow up to the keynote I presented at SourceCon earlier this year in San Diego. At the very end of my Resume Sourcing: Artificial Intelligence vs. Human Cognition presentation, I briefly covered some “bonus material” which included a quick overview of what I believe to be the 5 levels of Talent Mining.
At the SourceCon event at the International Spy Museum, I will dive more deeply into the concept of Talent Mining and the 5 levels that I have identified.
There are individuals in the HR/recruiting industry who believe that searching databases, the Internet, and social networking sites to source talent is relatively easy and that it can be automated through the use of technology.
On one hand, sourcing candidates is easy because we have more access to more human capital data than we ever have in the history of recruiting (the proverbial haystack is growing by the second!), and there are many solutions available that can automate candidate sourcing.
On the other hand, just because the haystack is growing doesn’t mean it is any easier to find the needles (it actually makes it harder!), and today’s automated solutions have serious limitations in their capabilities and are certainly unable to replicate the performance of a talented and creative sourcer or recruiter.
Sourcing is deceptively simple in that all searches “work” in that they return results, provided there are no syntax errors (and even then, some Boolean strings still return results!). However, not all search results are created equal. As such, sourcing candidates via databases, the Internet and social networking sites isn’t as simple as it may seem on the surface.
While literally anyone (or any application) can run a search and find some people, the real challenge lies in quickly identifying all of the best people available. Additionally, most sourcers and recruiters are not even aware that every search they run actually excludes qualified candidates from the results and/or buries them in the results so deep that they are never actually reviewed. But, they are there. And there’s a lot of them – I estimate up to 40% of available qualified candidates are never found or never actually reviewed in any given database or site. Some of the best potential candidates are simply never found despite the fact that they do exist to be found.
It is important to realize that not all search strategies and tactics are created equal. There are actually many different levels of Talent Mining, which I define as leveraging human capital data (in the form of resumes, social media profiles, etc.) for talent discovery and identification. Currently, only 2 of the 5 levels of Talent Mining I’ve identified can be replicated by software solutions – the other 3 require people with specific skills, knowledge and abilities.
In addition to exploring 5 levels of Talent Mining, I plan on delving into the concept of Talent Intelligence and discussing my visions for the future of sourcing – you won’t want to miss that!
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I look forward to seeing you at the SourceCon 2010 DC event!
About our guest author:
He began his recruiting career as a technical recruiter in January 1997 working for a small contingent staffing agency in Northern VA. With very little training and using an internal Lotus Notes-based CPAS resume database as his only source of candidates, through trial and error he taught himself the art and science of leveraging Boolean search strings to quickly extract large quantities of precisely matched and highly qualified candidates in direct response to client/manager needs.
Over the past 12 years, Glen has continued to develop a high level of expertise in leveraging information systems to achieve Just-In-Time talent identification and acquisition – sourcing, recruiting, and hiring/placing candidates from ATS-based resume databases, the internet, job board databases, social networking sites and any other source of human capital data he can get his hands on. His searching methodology has evolved into a fast, effective, and systematic process that involves successive and semantic searching tactics employing insightful and creative extended Boolean queries to quickly, thoroughly, and methodically uncover all potentially qualified candidates from the highest to lowest probability of match. He enjoys “cracking the code” of challenging hiring profiles and creating search strategies that quickly allow sourcers and recruiters to achieve successful hires, with the best candidate, typically in 24-48 hours, in 20 calls or less.
When not working a desk in a production capacity, Glen has recruited, trained and managed highly productive individual teams of up to 20+ recruiters responsible for 700 – 900 hires per year. In his current role – Glen trains and supports hundreds of Information Technology, Defense, Finance and Accounting, Clinical Research, and Health Information Management recruiters nationally that are responsible for over 10,000 hires annually.