Analytics Recruiting : Big data and Algorithms

July, 05, 2016 by Brooke McLaughlin author workhoppers

People Analytics or analytics recruiting is gaining importance in the way in which organizations seek talent. More specifically, we are talking about massive data analysis known as Big data. By leveraging more concise data and Big Data platforms in the Cloud, that work as intelligent human capital machines, it will lead us to the creation of new standards in the recruitment of talent. This phenomenon is strengthening with the use of algorithms that complement the capacity of analysis and the categorization of multiple types of data.  Statisticians, mathematicians and engineers have entered the realm of HR and this is changing the landscape.

This phenomenon of using analytics recruiting is also changing the role of the recruiter. Even more relevant, is that the depth of information available opens up new pathways for organizations, enabling them to make decisions in talent acquisition that are well supported, predicting performance, and developing the planning of the work force providing real value to companies.

data

External sources of Data

Some external sources of Data can help improve our analytics recruiting and help identify the best candidate.

  • Online information that points to candidate details associated with them such as;  Databases of Resumes, profiles on social networks (LinkedIn, Facebook, Twitter), records of employment and many other options.
  • External data accumulated internally: CV, job applications, scanned business cards and third party databases.

In addition, Human Resources can apply tests to analyze candidates and measure patterns and specific skills.

Internal sources of Data

People are nowadays leaving more traces of what they do at work. These traces of data can be harvested and used with multiple goals (e.g. to improve the performance of the individual and the organization, and as a benchmark with other employees).  Data can be collected from understanding the activities of people at work such as:

  • How they use computers and phones at work.
  • What they say on social networks.
  • Their movements within the office and/or with customers/suppliers.
  • Turnover due to commuting or non-competitive remuneration.

Benchmarks

Analysis on this available information allows you to do benchmarking:

  • Big Data facilitates the identification of the key characteristics of the best performing individuals in the organization and may be used in the pre-selection of candidates based on their match with these necessary qualities.
  • Real-time data enables you to identify what works and what is failing in the recruiting process.
  • Historical data on recruited employees is available allowing you to know: those who remain in the organization, those who received promotions, those that performed well, and those that did not make it and why.

Benchmarking Analytics recruiting

Algorithms

In order to complement the information we develop algorithms that in addition “learn” as they are used.

These algorithms use the information of the practical aspects of work in addition to the relationships and interests that the employees mention in their social networks.

They help to identify and measure personality and behavior of candidates to make comparisons with successful members of the working team.

Analytics recruiting with Big Data and algorithms are discovering talent that conventional networks of recruitment are not detecting.

Evidence tell us that if recruitment does its job properly, employees tend to remain with the organization, enjoy their work and eventually the company recovers the cost of hiring and training more quickly and with greater certainty.

 

Translated from Original article written by Laszlo Beke: Big data y Algoritmos presentes en la busqueda de talento

 

Workhoppers

 

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