Role of Big Data in Human Resource Management

By: Vikash Kumar on December 20th, 2018

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Role of Big Data in Human Resource Management

Big Data

Those who have been practicing Human resource management for years knows the importance of relying on data analytics for creating an enhanced work culture or else they might lag behind that of other departments.

Many of you tend to hold the purse strings that HR deals with people, they do not require dealing with large-scale data efforts and have gone to the back of the queue as a result. With the ever-growing technology advancement, Human Resource professionals have started embracing the future: data analysis.

Using big data for HR purposes means:

Using a statistical model means all the presumptions are being replaced with validation, hunches with data. In also involves intuition with success ratios, rather than abandoning responsibility to an algorithm. In today’s fast-paced world, structuring large quantities of different information isn’t easy, but it’s doable. And here is went big data comes into play. As a result,

    • Decrease cost of bad hires- With the help of HR analytics, you can observe a significant decrease in the cost of bad hires. A wrongfully chosen employee can cost the company way beyond than their salary and benefits. In addition to this, recruitment costs, training expenditures, productivity loss and negative reviews from clients are just a few examples of what the wrong person in the wrong place can do.
    • Increase retention rates- If you hire someone you spend quite a significant amount of time, energy and money on him or her and what happens when he or she resigns? You start looking for a new candidate and the entire cycle repeats. With the help of big data technology, algorithms created by big data consultants tend to nominate individuals by studying the employee’s online activity, profile updates, employment history, job performance, and payroll data. If you find systems raising red-flags to a valued employee, it means it’s time for a raise or requires more challenging role or some more training to keep them from leaving. It may quite interest you to know that several companies like Xerox, Wal-Mart and Credit Suisse already do and are seen achieving impressive results, most noteworthy, increasing retention up to 20%.
    • Predict performance- How do you know that the given profile is the right fit for your work culture? After considering tons of job’s requirements and existing top performers, you may find things difficult to handle. So what can be done is? Think of using HR analytics models which use existing records of successful candidates to create profiles of high performers. The end goal is to design a targeted head-hunting tool able to send personalized messages to the right talent.

      Although some freelancing platforms have already started using this approach, in particular, I personally feel that predictions is significant to evaluate future job openings, promotions, and even layoffs in a company. Big data could help save time and money on recruitment.

    • Improve benefits packages- Have you identified what perks employees want as a part of their salary package? Following the insurance companies’ footsteps, employers gather health-related data of their staff and candidates. As a result, more attractive and useful packages can be created with help of results achieved. Also, the company should be transparent to avoid legal issues related to discrimination practices. This can be done by revealing about collecting such data stating the final goals,
    • Legal and ethical issues- Privacy is one of the major concern when big data is the subject. I have seen many of you afraid that the numbers could work against them and end up reporting such practices in the name of discrimination. However, it becomes just a risk management technique.

Analytics & HRM Glossary

  • Analytics- As the name implies, analytics are solutions that allow people to come up with meaningful patterns in regards to data. Typically used to quantify the performance of the organization, a product, an operation, a team, or even individuals in order to support business decisions. Data compilation to manipulation and statistical analysis are the main elements of analytics.
  • Business Intelligence- They are basically software products which allow business users to choose data from a system or multiple systems, manipulate data and produce reports including data in a variety of forms.
  • Workforce Analytics- This methodology makes use of software to apply statistical models to employee related data to optimize human resource management (HRM). It may quite interest you to know that it can well assist leaders in developing recruiting methods, making general and specific hiring decisions, and retaining the best talent.
  • Predictive Analytics- Uses the analysis of current and historical facts to predict unknown events using statistics, modeling, machine learning, and data mining.
  • Big Data- One of the most crucial terminology to take into account where software tools take a look at immense amounts of data across numerous systems within a tolerable elapsed time. In regards to human resource management, people-related data is used to better understand the organization's human capital, workforce capacity, risk, and business performance.
  • Workforce Planning- A perpetual process for determining and assessing the needs of an organization and its workforce. By instituting that process, a foundation is provided for human resource decisions, and profits can be maximized through strategic budgeting and planning.

About the Author: Working as a manager at, Vikash Kumar also has a passion of blogging, he likes to cover topics on Big Data in different technological aspects and also published his byline on different major platforms like Entrepreneur, YourStory, SAP and many other publications.

Want more on Big Data? Check out this podcast with author and Big Data expert Mark Follenweider:

About Vikash Kumar

Working as a manager at, Vikash Kumar also has a passion of blogging, he likes to cover topics on Big Data in different technological aspects and also published his byline on different major platforms like Entrepreneur, YourStory, SAP and many other publications.