How does the use of big data influence the future of candidate hiring?

 

Data-Based Hiring

Acquiring the best hire for meeting an organization’s identified talent gaps, is an avowed objective of recruiters. In an effort to accomplish this goal, talent search agencies and companies doing direct recruitment through their HR verticals are now moving away from the traditional methods of selection to technology-based ones. Big data analytics is fast becoming an almost indispensable compatriot in the recruitment process.

We are all prolific data-generating machines. And this data is being gathered through multiple digital touchpoints with which we interact almost every moment. Every action of ours on any digital device, be it a screen-tap, click, search, stream, download, and upload, forward, share, scan, swipe, etc., generates data. Figures suggest that we create around 2.5 quintillion bytes of data every day. With more than 2.8 billion monthly active users, Facebook alone is said to store 300 petabytes or more of pictures and videos. The exponentially growing social media users are likely to cross over 4.4 billion individuals by 2025.  The volume and velocity of data generation are phenomenal. This humongous data is a readily available source of deep information, especially enabling social profiling. The methodology of people analytics is premised on this, and consequently, it becomes a useful tool for recruitment.

 

Applications of Big Data in Recruitment

Companies across the spectrum of businesses are using this source, the big data, for need-based solutions. The recruitment industry is no exception. In the 2018 Global Recruiting Trends Report, top uses of data in talent acquisition are proportioned as under:

  • 56% Increase Retention
  • 50% Evaluate Skill Gaps
  • 50% Build Better Offers
  • 46% Understand Candidate Wants
  • 41% Do Workforce Planning
  • 39% Predict Candidate Success
  • 38% Assess Talent Supply & Demand
  • 31% Compare Talent Metrics to Competitors
  • 29% Forecast Hiring Demands

Leveraging big data for decisions on ideal hires calls for the application of analytical tools. Slicing and dicing the big data, structured or unstructured, throws up information about the candidates’ profiles, their footprints in the digital space, their tastes, preferences, likes, and dislikes. The entire gamut of a person’s online life, updated till the time of data processing, is visible. It can be used for the purpose of corroborating facts submitted by the job aspirant in their resumes/applications and for determining whether the applicant meets the criteria of selection standards set by the recruiter. It is a fast way of shortlisting and sifting out the below-par applicants and/or persons that, even though acceptable otherwise, may have personalities that may not align with the culture of the organization.

Big data analytics also provide insights that help in predicting trends of success of potential candidates in a given assignment, possibilities of attrition, degree of engagement, etc., which are helpful in making decisions for the long run. These are important considerations for recruiters as they impact costs.

Big data analytics-based recruitment is now taking root because it offers many advantages. Broadly,  some of the benefits that may accrue by following data analytics hiring strategy are:

  • Speedier processing and informed decision making gives a competitive edge for the given pool of talent
  • Provides a qualitatively higher set of hires
  • Overcomes human errors and biases
  • Helps in monitoring and meeting regulatory compliance issues
  • Enables workforce planning
  • Provides cost efficiencies

 

Well Thought-out Strategy

To make optimal use of big data analytics, companies need to put in place a cohesive Data-Driven Recruitment Strategy. This is essential as it will set in place the metrics of recruitment required to be matched to the analysis. Data analytics will only help if it is interpreted correctly. Which data to use, which source is more relevant, what are the desired parameters of selection, which data set may be ignored, what personal traits are red flags, etc., are some of the questions a recruiter should address. Parameterising the requirement is a tacit pre-condition. It is a given that an unfocused approach will not yield the right results. Once the employer delineates the specifics, the analysis will provide a more meaningful and almost 360° perspective of the candidate’s personal and professional profile.

While adopting big data analytics, one challenge that needs to be kept uppermost is that of data governance and ethics. Misuse and leakage of sensitive data can invite strictures with grave consequences. Safekeeping of data, accessibility, and integrity is of paramount importance and watertight safeguards should be an integral part of any data usage strategy.

 

The Human Factor

Leveraging big data is today helping organizations to meet their myriad human resources challenges. Long-term planning and strategies for recruitment, retention, and engagement of employees are feasible through the insights provided by data interpretation. Smart data-driven decisions improve efficiencies and meeting of organizational goals. Being data-backed, the acceptability of such decisions by the employees stands considerably improved as biases are eliminated.

 

Conclusion

Using big data analysis and algorithms are cost-effective ways of capturing a more comprehensive view of not only job seekers but also existing employees. But judgment based on analytics alone will not suffice. It is unlikely that artificial intelligence and machine learning will reach a stage of development that will do away with the application of human intervention. In recruitment too, while the donkey’s work may be better done through machines, the final call will have to be taken by the recruiter, especially in light of the fact that data on social media may be manipulated and exaggerated. Just how much weightage to be given to the analysis and how much to the recruiter’s perception and gut feeling in face-to-face interaction with an applicant, is not an easy decision. There is no denying that Big data recruiting can provide insights and patterns about the potential of a candidate in a more cost-efficient manner than through traditionally followed recruitment methods. But we should not lose sight of the fact that in the end,  recruitment is still a people profession.