HR Analytics

HR Analytics Solution

Know before 30 days, employees with high probability to resign


Most organizations deploy various tests and tools at the time of recruitment to determine the fitment of the potential candidate, but still the first 6 months attrition numbers in the IT/ITeS companies stands at anywhere between 20% to 50% (Source – Economic Times). Although, a certain churn is always accepted and healthy, the worrying trend is when a wrong fit comes in the organization and a performing employee leaves!! The worst is when we as Managers have no clue as to when will a good employee leave!

Thankfully, in this era of automation, we can deal with these issues with the help of HR Analytics.

Using Big Data and Predictive Analytics, we have developed automated modules which can be integrated into the current HRMS systems to help recruiters determine if a person is a right fit while recruiting. The Analytics modules have also been developed to predict an employee’s attrition with an accuracy of 80% and thereby help organizations to take preventive steps to retain performing employees.

Big Data Analytics helps HR to analyze large data sets from a variety of sources like Enterprise HRMS, T&A Systems, Social Media, Mobile Applications etc. that enables HR to make data driven decisions about employee recruitment, retention, training, compensation, organization effectiveness and career planning.

HR Analytics Process

It uses statistical tools on data captured in existing HRMS system to predict employee turnover, training needs and also analyze parameters affecting performance to enhance organization effectiveness.

Beyond traditional Management Reporting

HR Analytics

HR Analytics

arrow Opportune HR Analytics Report will help you determine:

  • Current attrition trend (monthly) across departments/supervisor & gender
  • Highlighting departments / supervisors having the maximum issue of attrition
  • Mentioning high risk attritions for the next 30, 60 & 90 days
  • Possible training & recruitment $s loss due to the attrition (with a p-value)
  • Highlighting top areas of improvements which can prevent attritions mentioned earlier
  • Employee churn rate over the period of next 30, 60 & 90 days

arrow Case study of a company operating in the domestic BPM segment:

This company has been in existence and successfully running operations for over eight years in the domestic BPM segment. With an employee base of over 5000 and an annual attrition rate of about 200%, the cost of hiring and training itself is phenomenal!! Here are some statistics:

Average Cost of Hiring : Avoidable Attrition :
Average Cost of Recruitment** (INR) rupee2,000.00 No. of Employees 5000
Average Cost of Training* (INR) rupee8,000.00 Six Month Attrition (Bad Hire) 150%
Average Cost of Hiring (INR) rupee10,000.00 Avoidable Attrition 7250
Total Overhead Cost of Bad Hiring (INR) rupee72,500,000.00
* First Month Salary
**Assumed recruitment done in house

Predicted versus Actual Attrition (Based on previous 12 Month Attrition Data):

Month Attrition

Make wiser hiring choices based on your company’s historical data

With the use of effective analytical tools at the recruitment stage to select the right fit and use of analytics on data from existing HRMS to get Early Warning Signals, first six months attrition rate was reduced by 10 percentage points in the first three months of the deployment of the tools. By extrapolating the results, the expected savings for the first year would be in the region of INR 20 million.

Considering that this is a domestic BPM company with extremely tight margins, the above gain is a significant improvement to the bottom line.

HR Analytics Functions

HR Analytics Chain

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