Analytics is always an important topic and trend in every part of business and HR is also not far behind. Today many organizations are looking for metrics or analytics in HR which are not just related to people but also on processes such as recruitment, retention, compensation, succession planning, benefits, training & development, performance and appraisal and many others. In short Talent analytics is becoming more popular these days as companies are doing lot of efforts to cultivate and align HCM with core business objectives in order to achieve a competitive fringe.
HR analytics does not only gathering data on employee; instead it aims to provide insights into each process by using data to make relevant decisions, improve the processes and operational performance. HR collects enough data on employee’s personal information, compensation, benefits, retirements, attrition, performance, succession time to time so it is important to use it properly to interpret the outcome and spots the trends.
Some typical benefits and use cases of analytics are as follows:
- Improve organizational performance through high quality talent related decisions
- Forecast workforce requirements and utilization for improved business performance.
- Optimization of talents through development and planning.
- Identify the primary reasons for attrition and identify high-value employees for leaving.
- Provide the source of competitive platform for the organizations
- Manages applicants in better way on basis of qualification for a specific position.
- Recognize the factors which turn the employee satisfaction and productivity.
- To determine the individuals KPIs on the business.
- Enabling HR to demonstrate its benefaction to achieving corporate goals.
Analytics also used in HR to prepare cost and investment on their talent pool like cost per hire, cost per participation on training, revenue and expense per employee. It provides opportunity for defining strategy for retention and hire plan. It can also give complete picture of an organizational head counts based on demographics – age, gender, geographical, departmental, qualifications etc.
The facts are also not different on HR analytics. A survey by MIT and IBM reported that companies with a high level of HR analytics had:
- 8% higher sales growth
- 24% higher net operating income
- 58% higher sales per employee
As mentioned before as well though there are currently many analytics options in HR but few of they are really becoming popular these days.
One such is Talent analytics; which is more qualitative and is basically for processes from talent management like personal development, recruitment, succession planning, retention etc. It can help organizations to better analyze turnover, identifying top performers, identifying the gaps and develop the proper training for them. It can also find out reasons for attrition and provide options to take strategic decision for retention as well.
Workforce analytics is another common one which is more quantitative; it helps leaders to develop recruiting methods and specific hiring decisions, optimizing organization structure, identify quantify factors for job satisfaction; determine the need of new departments and positions. It also helps the organization to identify, motivate and prepare its future leaders. Align and motivate workforce and continuously improve the way of work.
Workforce analytics are more inherent, based on knowledge transfer, not on data based. But every organization wants to back up their decision from data and facts. Predictive Analytics, based on statistics, data and becoming more attractive. It helps leaders to take more strategic decisions based on the facts. Data are generally presented in graphic, statistical reports, dashboards which are easy for leaders to understand. It offer leaders to provide solutions to some complex decision making processes and helps them in determining critical situations like tacking pay gaps, set of workers who are always at risk of resigning, understanding the psychographics (personality, interest, work styles etc.) of employees, behavioral qualities of applicants and many more.
So now organizations are involving themselves more into data management, analysis and further interpretation of data. To get this complex analysis working they need off course mastery in data science and statistics. Organizations those who taken this step already understand the benefit that data brings to their decisions and the value that these decisions bring to the organization.
We should also keep in mind that analytics is not measured based on size but by the impact that the results have on decisions. Also it is basically increase organizational effectiveness so just creating only reports with no such value on decision making and optimization will increase cost for the companies.
In other words analytics is a journey not a goal…