Rejuvenation Of HR Practices by Analytics

Published by MBA Skool Team, Published on December 15, 2015

Analytics can be defined as the scientific process of transforming data into insights for making better decisions. In simple terms, one can say that analytics is the science of logical analysis while analysis is nothing but the qualitative and statistical data which is gathered from a sample. Analytics generally relies on the simultaneous application of statistics, computer programming and operation research to quantify performance. The whole dynamics of analytics was changed by the sports industry when they started using real-time stats and video analysis and predictive analysis to inform their management, for player development, introducing training methods, scheduling practice sessions etc.

But what we need to understand is that in this competitive environment, the data we collect be it from secondary sources or primary sources is like a natural resource to us i.e. we must know what exactly do we need to extract from that data. To use this data to its advantage an organization uses HR Analytics or Talent Analytics which helps to manage the employee’s talent with the technology. HR Analytics is an application of sophisticated data mining and business analytics techniques to HR data.

Image: pixabay


HR analytics mainly includes advanced analysis (stats are analysed), workforce analysis (includes maintenance of manning ratio & attrition rate), performance assessment analysis (via appraisals) and predictive analysis (future scenarios are planned and decisions are made accordingly). The concept of workforce reporting and analytics helps make better and more informed decisions about employees. For instance, the chart below shows how tactical reporting can lead into predictive analytics. If we break it down to three categories then we can understand the concept of predictive analysis which is a part of HR analytics:

• WHAT is happening? : Hindsight [Capture HR data by reporting or collecting the data from secondary(archives) or primary (surveys, appraisal forms) sources]

• WHY is it happening? : Insight (Making sense of the data collected by analysing and monitoring it)

• WHAT should happen? : Foresight (Develop predictive models)

These three categories ultimately help to optimize return on investment (ROI) on human capital.

Source: Deloitte

After analysing the data, an organization must know how to utilize it and where will this data help in the organization’s growth. That’s where HR Analytics comes into play as it is responsible for aligning workforce (HR Strategy) with the corporate strategy for which,

• An organization is supposed to leverage their employee data so as to improve operational performance.

• Focus towards making HR department more data driven.

• Develop capability to perform “Predictive Analytics”, about their workforce.


The key aspects of HR Analytics is to correlate business data and manpower (HR) data to conclusively show the impact the HR department is having on the organisation as a whole and establishing a cause-and-effect relationship between what an HR does and the business outcomes. Then creating strategies based on the information extracted. Some more applications of HR analytics are:

• To cut costs & increase financial accountability in slowing economy.

• Understanding the drivers of performance and retention.

• Using statistics to decide who to hire.

• Predicting job satisfaction.

• Analysing how pay correlates to performance etc this all can be done by:

o Identifying the opportunities for HR impact.

o By prioritising HR investments and actions.

o Demonstrating the bottom-line impact of HR practices and programmes.

To perform these above stated tasks, an organization needs an equally competent and capable HR analytics team. This team should have skills like program management capacity, business understanding, consulting skills, the capability to visualise data, ability to manage data, executive presence and should have the ability to solve business problems. It is observed that these kinds of HR teams are four times more likely to be highly regarded by their business counterparts due to their data-driven based decision-making, giving them a true potential to help change the business. For example- Google has created a people analytics function with its own director and a staff of 30 employees (i.e. researchers, analysts and consultants) who study employee related issues and make decisions accordingly.


Some of the challenges faced by the HR analytics team are:

• To identify what data should be captured and how to use this data to model and predict capabilities so that the organisation gets an optimal return on investments (ROI) on its Human Capital.

• A lot of structured and unstructured data is received by the organization and to clean that data takes a long time. Also, a lot of incomplete data is also received which makes it difficult to obtain effective outcomes.

• Maximum managers have years of “experience” and “belief systems” that holds them back from using the data science. They take it on their ego when it comes to trusting the facts and figures.

• The biggest challenge to big data analytics is getting people to change their behaviour once they have the data. They have to convince their managers to adopt analytical decision making.

• HR Analytics is ethically challenging because the power of handling big data increases the power of institutional awareness. This power has to be used with a lot of responsibility.

• Confidentiality/Privacy must be ensured and organizations should do everything possible to protect sensitive data sets and be open & clear on what is done with that data.

With the increase in the use of analytics, it is the future HR managers who have to decide whether they want to “Follow the gut or follow the data”.

This article has been authored by Shikhi Mehrotra from FORE School of Management


[i] Competing on Talent Analytics by Thomas H. Davenport, Jeanne Harris and Jeremy Shapiro.

[ii] The potential and challenges of HR Analytics by Cindy Waxer.

[iii] Change your company with better HR Analytics by Mick Collins.

[iv] Big Data in Human Resources: A World of Haves And Have-Nots by Josh Bersin(2009).

[v] accessed on 18th September 2015.

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