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Data-driven Recruitment: A Guide to Next-Gen Hiring Processes

“Many are called, but few are chosen” Just another apt saying that perfectly fits the scriptwriting told by the movie ‘Moneyball’.

The movie is based on real events of how Oakland Athletics (A’s) general manager – Billy Beane – assembled a competitive team for 2002 baseball season with his incredible efforts. Players were recruited on a lean budget by employing data-generated analysis rather than the expensive traditional process of acquiring players.

The team of undervalued players ended up breaking all records of continuous wins against the teams with far deeper pockets. All thanks, to data-driven recruitment!

As the business environment grows more competitive, organizations need more efficient and robust talent acquisition practices. Data based recruitment seems a natural solution towards this goal.

Traditional Recruitment Methods Suffer Limitations

The amount of time and effort companies go through to find intelligent, reliable candidates is astronomical, especially when they want to recruit massively. Additionally, relying on job board postings, and making a hiring decision based on one or two interviews leads to inconsistent hiring because:

  • Human capacity is limited
  • Bias is real
  • All data is not readily verifiable

The hiring process mostly relies on guesswork as recruiters can never really be sure if the candidate would do a good job. The traditional process can result in wasting both the company resources and time.

Big Data Recruitment: How is it Better?

Big data analytics allows organizations to make smarter hiring decisions by:

  • Removing the subjectivity found in a traditional hiring approach
  • Overcome personal biases and hire based on identified capabilities
  • Replacing it with measurable data that supports a hiring decision

For big data analytics, data from various sources is used:

  • Social networks: Facebook, Twitter, blogs, comments, images, e-mail, videos, internet searches
  • Internet of Things: Sensors, satellite images, logs, weblogs, surveillance images, videos
  • Business Systems: E-commerce, commercial transactions, banking, credit cards, medical records

In data driven-recruitment, talent pool data is analyzed and interpreted to find the best candidates for the organization, that too, faster. Data from multiple sources and algorithms is consolidated and analyzed to recommend the most qualified candidate for an interview.

Data-driven recruitment, if applied well, can help enterprises discover candidates that can:

  • Fit into the organization’s corporate culture
  • Become strong team players ahead

As indicated by a report from LinkedIn, this approach enables recruiters to

  • Explore an expansive pool of candidate data
  • Analyze the results
  • Ask the correct questions about the roles they are recruiting for

For incorporating data into the hiring process, organizations must segment candidates based on the following data and criteria:

  • Work habits and cognitive abilities based on vetted assessments
  • Quality and ratings of employment referrals
  • Career values, interests and motivations
  • Generation of recruit

Setting Up Big Data Operations

A lot has been discussed about the enormous value that organizations can derive from data-driven recruitment. However, when it comes to weighing the advantages of leveraging big data, it is easy to overlook a key underlying issue:

“Majority of collected data is trapped in unstructured documents, machine logs, social media posts, etc.”

Further, the data may be at least a couple of months old, meaning there are no real-time insights. Moreover, mining insights from unstructured data is not just about extracting and integrating information. Instead, having data centers as a storage repository for holding and processing the vast amount of data.

A data center can be private or shared, simple or complex, housing the IT facilities of an organization, including:

  • Routers
  • Servers
  • Switches
  • Supporting components like backup equipment, air conditioning, and fire suppression facilities

Therefore, organizations who want to launch or expand a big data initiative like data-driven recruitment must keep the needs of power, uptime, and real estate on top. Along these lines, colocation data center facilities are preferred by many enterprises today as these facilities are highly:

  • Flexible
  • Scalable
  • Sustainable
  • Reliable

Such colocation facilities provide affordable space for hosting servers, along with the benefits of 24*7 monitoring and support.

Data Center Facilities in India With Global Standards

If your business has mission-critical needs, at that point you would want to focus on reducing latency. Similarly, you would also want to ensure that the geographic location of the data center facility works for you and is a combination of resiliency, disaster recovery, network connectivity as well as ease of access.

Fortunately, there are a wide range of options available. India now boasts of many providers having data centers in Hyderabad, Mumbai, Bangalore, Delhi, and other prime locations.

In terms of options, India offers plenty with about 150 colocation DCs across the country. Its data centers are spread out across India, which means that businesses should be able to minimize latency and lag issues across the country. The dedicated DC infrastructure offers highly efficient infrastructure for setting up needed computing and storage for big data operations.

Global colocation experts like STT GDC India offers multiple layers of redundancy across the network, physical security, power and cooling towards near 100% run-time SLAs. Additionally, the modern DCs are increasingly moving towards greener operations, especially the global players operating in India.

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