A recruitment researcher, also called talent miner, works closely with teams and help build top-tier talent pipelines and mapping reports.

The value of a talent Miner

There are people 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.

While those people are actually right (to an extent), but it’s not that simple.

While anyone can manually write or automate basic searches and find some people, those searches only return a small percentage of the available talent that can be found and they also exclude qualified people. Moreover, there are actually many different levels of searching human capital data in the form of resumes, social media profiles, etc., most of which cannot be replicated or automated by software solutions available today.

Talent mining is a new concept in recruitment. Hiring is one the most important functions of Human Resources Management. In today’s fast-growing world, it plays even more than a critical role for the organizations because of the rapid pace of the technology and digitization. In the field of recruitment, selection and hiring, there are many different but similar concepts such as talent finding, talent acquisition, head-hunting which address this function. Despite that, however, these concepts are not enough to explain this crucial process entirely, especially when it comes to Information Technologies (IT) sector. Therefore, as sHR., we introduce a new concept called “Talent Mining”.

Talent mining seeks to solve the talent shortage in the world. Recently, employers experience difficulty to fill job vacancies due to the lack of available talent. In the market, there is a labor supply-demand imbalance; especially, in the IT sector. Therefore, traditional methods and strategies are neither enough nor valid anymore to solve the global workforce crisis. For that, some organizations have already started adopting new strategies to overcome the talent shortage like utilizing non-traditional –or previously untried- recruiting practices.

Talent Mining – what is it anyway?

Talent Mining uses Data Mining, which according to Wikipedia is the process of sorting through large amounts of data and picking out relevant information, or “the nontrivial extraction of implicit, previously unknown, and potentially useful information from data” and “the science of extracting useful information from large data sets or databases.”

Talent Mining therefore is the science of sorting through large amounts of human capital/talent-related data, typically found in articles, web pages, resume databases, on the Internet, in social networking profiles, blog posts, etc., and extracting out relevant and useful information from the data that can be used for talent identification and acquisition.

Talent Mining is commonly performed manually and automatically, through the creation and execution (or saving for routine execution, as in the case of search agents or alerts) of Boolean search strings to retreive human capital/talent data from which a recruiter can use for knowledge discovery and talent identification and acquisition.

True Talent Mining goes well beyond “buzzword matching,” and in the hands of an expert Talent Miner, Boolean search strings can be used to perform Semantic Search – using semantics, or the science of meaning in language to produce highly relevant search results – even from unstructured data. How’s THAT for sexy?

Data analysis

If you want to identify who will be successful in the future, you should look at who is successful now. If you want to find candidates with the same strengths as your organisation’s most successful staff, you can analyse new and old video interviews on YouTube, etc to look for patterns of success among your own staff. After that, it’s a simple matter of finding candidates who exhibit the same patterns.

Big Data has given rise to a number of recruiting techniques designed to make recruiting efforts more precise and accurate. While these techniques predate the rise of Big Data, the explosion of available information has led to the development of algorithm-driven recruiting software solutions (as well as firms that specialize in algorithm-driven recruiting); and helped refine the tools and techniques used specifically for recruiting. These tools and techniques include data mining, keyword filtering, and testing.

By analyzing from where successful candidates have been hired can simplify the recruiting process as well. For example, a firm whose internal analyses have revealed that 49% of their top performers had their initial contact with a recruiter from Viadeo, may lead the firm to reduce advertising on LinkedIn, and instead ramp up recruitment efforts on the French social networking site.

Recruiters and human resources professional can also combine data mining with predictive analytics – the use of statistical methods and techniques to forecast the probability of a likelihood occurrence using historical data, to generate predictions about a candidate’s likely tenure with the firm should they be hired. These insights can also be used to provide parameters for the recruiting of external candidates.

Data mining, or as some recruiters call it “talent mining” can be done manually or automatically online. Individual recruiters and/or software can search online resume databases (internal or external), professional social network profiles, or other websites of interest for personnel who might be a match for an opening.

Social networks, in particular, capture significant information about an individual. Recruiters can determine not only whether a candidate might be a good fit for the culture of the firm, but also whether they might be successful there, by assessing this information against internal profiles of high performing candidates. For example, a firm’s highest performers may spend a small amount of time on a single social network. A candidate who spends considerable time on multiple social networks might raise some flags. Alternatively, a social network might indicate that the candidate is engaged in activities that might impair their productivity, such as excessive drinking or high-risk hobbies, such as extreme sports. These insights can be helpful to the diligent recruiter.

Keyword filtering

Using desired skills and other characteristics as keywords, recruiters can run searches in popular search engines, on professional and non-professional search engines, in public or private online communities, and on other online properties. This can yield promising leads, who recruiters can contact for an informational or formal interview.

Keyword filtering is also helpful when screening out applicants who have applied for a position through a web-based talent management application (either proprietary or from a third-party recruiter). Recruiting software automatically scans submitted resumes and cover letters for specific keywords, rejecting those without them, and returning to recruiters only the candidates who fit the job description on paper.

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