Tomorrow's Recruitment: Big-Data Robots Bring Better Hires

Posted June 27 2013

big-dataIn Tomorrow's Recruitment: Big-Data Robots Bring Better Hires, author Emma Byrne argues that "big data predicts successful hires far better than your HR department."  Furthermore, through use of big data, companies can "find talent that your competitors miss, stop you over-paying for great talent, and keep that talent."

According to Gartner, big data is defined as "high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization."  The size and complexity of these data sets is often difficult for traditional data management and processing tools to handle.  

CTK's IT SME has assisted numerous companies both large and small with definition and execution of information strategies including big data.  CTK agrees that big data concepts can aid in recruiting of candidates, and that we'll see continued growth in use of publicly available 3rd party data (e.g., LinkedIn, Facebook), advanced analytics and automation within recruiting.  That said, this does not imply that recruiting organizations need big data - much like the .com boom during the late '90s, organizations should not jump on the big data bandwagon before carefully considering enterprise big data needs (including HR) and associated benefits.  For instance, while collection and analysis of 3rd party unstructured data may be more advanced than other business functions, the volume and velocity of data needs for an HR department typically pales in comparison to meterology, financial services, physics simulations, internet search and other similar businesses/functions with exabytes of data and high velocity needs.  Furthermore, big data concepts like collection and analysis of unstructured data, advanced analytics, etc. can occur without big data toolsets.  

At a minimum, CTK recommends that organizations clearly outline how big data will be used before making an investment.  How will collection of 3rd party salary information impact our compensation strategy?  What social data should we collect (e.g., Facebook, Twitter, LinkedIn)?  What analytical models can be created to influence hiring decisions?  At what frequency do we need to collect and analyze this information?  Ultimately, the behaviors measured through big data collection and advanced analytics should align with the behaviors within your competencies and competency-based talent management processes.

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