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HR Analytics in Retail Industry - Part 2

In this part we will elaborate on HR Analytics solutions.

What is HR analytics?

HR analytics is the application of data mining and statistical techniques to Human Resources data and can also be renamed as Workforce analytics, Predictive analytics or People analytics.

It helps in knowing the what, why, when and how of various HR functions like, Recruitment, Training, Succession planning, Performance management, retention and engagement. Workforce analytics can help organizations in taking strategic decisions and optimizing the approach to recruit, retain and motivate the workforce by analyzing the HR data.

Solutions offered by HR analytics:

To analyze an issue and make correct decisions, some key data like attrition, reason for leaving, performance, employee costs revenue etc. needs to be referred and this is already present in the database of the organization. Analytics correlate this internal data with external data like Salary Bench Mark and gives a detailed and statistically supported view for managers to take strategic decisions proactively.

Types of Solution:

Predictive Analytics solution:

·         Assist business leaders in predicting future needs and risks of the organization. Analytics tools apply the data mining and statistical modelling techniques to HR data and predict the future trends that aids in a more refined and timely planning.

Example- Seasonal demand, Retirement period

BI (Business intelligence) solution:

·         BI offers the flexibility to managers to generate ad-hoc reports using various reporting techniques, dashboards and scorecard for a quick view and decision making.

Organizational growth management solution:

·         Performance reporting tools can help in viewing the cost and performance pattern within the various units of organization. Managers can check for association with various other parameters for detailed analysis.

 

Applying analytics to HR Challenges:

(a)   Attrition analysis:

The various predictive models can help in identifying the attrition risk score of high performers across multiple units.  It can be done by using the various datasets like compensation, performance, market survey, demographic data, engagement scores of employees etc. Managers can find out the key reasons for attrition and can act to reduce the occurrence.

 

 

(b)  Forecasting recruitment needs:

Predicting resource requirement helps in effective resource utilization and in turn results in cost revenue balance.

Future requirement can be analyzed based on attrition rate, sales forecast, departmental growth prospects, project pipelines, current employees, seasonal need for a specific skillset, retirement data etc.

 

(c)   Employee profile selection and segmentation:

Use of Analytics leads to an effective talent management by segmentation & profiling. Employee data like location, department, and education can be combined with responsibilities to identify the specific set. This analysis can be used to identify the employees with specific skillset, training needs, program enrollment, diversity etc. Such Talent forecasting aids in the allocating the best fit resources as per the available opportunities

(d)  Appropriate profile selection and market benchmarking

One of the primary causes of attrition is the incorrect mapping of Employee and their role thereby making it essential that employee is mapped to a position based on the skillset and past performance. A more effective employee-role mapping can be accomplished by correlating the employee variables with profile variables like education, experience, skills and performance. The analysis output helps HR managers to identify the suitable profile leading to higher productivity and customer satisfaction.

 

The next and concluding part will discuss the key features of HR analytical tools and some major Players in the HR Analytics space.

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