Dear Seniors,
Greetings of the day.
Can any one please explain what is HR Analytics and its benefit ??
How it can be implemented in a pharma company specifically for recruitment process??
Regards,
Vandana Gond
8108450999
From India
1Greetings of the day.
Can any one please explain what is HR Analytics and its benefit ??
How it can be implemented in a pharma company specifically for recruitment process??
Regards,
Vandana Gond
8108450999
From India
Hi Vandana,
Human resource analytics (HR analytics) is an area in the field of analytics that refers to applying analytic processes to the human resource department of an organization in the hope of improving employee performance and therefore getting a better return on investment. HR analytics does not just deal with gathering data on employee efficiency. Instead, it aims to provide insight into each process by gathering data and then using it to make relevant decisions about how to improve these processes. pls check below link
What is HR Analytics? - Definition from Techopedia
The Recruiting dashboards and pre-configured analytical workflows provide a complete set of recruiting metrics that measure the efficiency and effectiveness of the entire recruitment life cycle, from pre-hire to post-hire employment. It enables optimization of candidate sourcing; analysis of the recruitment pipeline and ―hire to-retire‖ process efficiency; analysis of time to fill to support optimization; monitoring of vacancies; and measurement of quality of hires and their retention by source. Providing this comprehensive ability to monitor quality of hire differentiates a company’s HR Analytics for the recruiting process; it does not stop at hire, but continues through employment and beyond to provide an ongoing quality of hire analysis. With the Recruitment subject area, recruiting specialists can see job applicants, hire ratios, and retention rates by recruiting source. They can drill into performance of new hires to assess the quality of these hires. By analyzing these effectiveness metrics, an organization can fine tune its recruiting strategy, balancing costs, retention, and performance. Through the Retention subject area and its dashboards, managers can view the voluntary turnover for top performers and can drill down to see the reasons they are leaving. Then, guided through a set of workflow analyses, they can determine corrective actions to address any retention issue. Users can monitor performance at first service milestone of new hires, along with separations and separation rate, assisting them to gain a total picture of new hire quality
From United Arab Emirates, Abu Dhabi
Human resource analytics (HR analytics) is an area in the field of analytics that refers to applying analytic processes to the human resource department of an organization in the hope of improving employee performance and therefore getting a better return on investment. HR analytics does not just deal with gathering data on employee efficiency. Instead, it aims to provide insight into each process by gathering data and then using it to make relevant decisions about how to improve these processes. pls check below link
What is HR Analytics? - Definition from Techopedia
The Recruiting dashboards and pre-configured analytical workflows provide a complete set of recruiting metrics that measure the efficiency and effectiveness of the entire recruitment life cycle, from pre-hire to post-hire employment. It enables optimization of candidate sourcing; analysis of the recruitment pipeline and ―hire to-retire‖ process efficiency; analysis of time to fill to support optimization; monitoring of vacancies; and measurement of quality of hires and their retention by source. Providing this comprehensive ability to monitor quality of hire differentiates a company’s HR Analytics for the recruiting process; it does not stop at hire, but continues through employment and beyond to provide an ongoing quality of hire analysis. With the Recruitment subject area, recruiting specialists can see job applicants, hire ratios, and retention rates by recruiting source. They can drill into performance of new hires to assess the quality of these hires. By analyzing these effectiveness metrics, an organization can fine tune its recruiting strategy, balancing costs, retention, and performance. Through the Retention subject area and its dashboards, managers can view the voluntary turnover for top performers and can drill down to see the reasons they are leaving. Then, guided through a set of workflow analyses, they can determine corrective actions to address any retention issue. Users can monitor performance at first service milestone of new hires, along with separations and separation rate, assisting them to gain a total picture of new hire quality
From United Arab Emirates, Abu Dhabi
Dear Vandana
The post from RNair2000 is an excellent one and gives you a good overview.
Here are a few pointers on the topic from my end:
1. Analytics is not for everyone! Analytics is a process of correlating and evaluating data... And therefore, if you are in a company that doesn't have a reasonable quality of data, then it might give you a mucked-up scenario. For instance, if you have partial data... and decide to refine it later, your analytics tool will have a nightmare!!! We were evaluating training needs of drivers and the accidents said that the buses had 'hit' another vehicle... Now, there was no record of whether it hit the front or back or side! These details affect the training requirements and technological upgrades considerably.
2. If your decisions aren't data driven, you are definitely not for analytics. I recall in one of my pharma clients... The client wanted to bring in a 'standard process', but failed to actually follow that... In fact, he went ad hoc, despite spending a fortune on his performance management system. For such people, analytics doesn't really help...
3. If you don't know where to use the data (i.e., what indicators are meaningful), you are certainly not a candidate for analytics. Most times, the managers are not aware of where and how to use a report. They spend hours in 'defining' the reports and understanding the kinds of indicators. However, to put that in a smooth-flowing process requires a deeper understanding of the analytics process. Most times this is given a lower priority in the organization. The result is that the legacy process prevails as it is within the 'comfort' levels of the company.
4. If you don't have a proper roadmap of how to 'graduate' from one level to another, you are definitely going overboard with the whole concept. Effective analytics requires a stringent control over all the elements viz. data, updation frequency, updation quality, representativeness checks, etc. And each metric needs a 'minimum' amount of data / substrate information to give meaningful results. If you don't have a proper roadmap of when to use what data, how, and why... you are probably going to spend a lot of money in customizing your analytics tool.
Hope these help...
In case of questions, please let me know. Will be glad to answer.
From United States, Daphne
The post from RNair2000 is an excellent one and gives you a good overview.
Here are a few pointers on the topic from my end:
1. Analytics is not for everyone! Analytics is a process of correlating and evaluating data... And therefore, if you are in a company that doesn't have a reasonable quality of data, then it might give you a mucked-up scenario. For instance, if you have partial data... and decide to refine it later, your analytics tool will have a nightmare!!! We were evaluating training needs of drivers and the accidents said that the buses had 'hit' another vehicle... Now, there was no record of whether it hit the front or back or side! These details affect the training requirements and technological upgrades considerably.
2. If your decisions aren't data driven, you are definitely not for analytics. I recall in one of my pharma clients... The client wanted to bring in a 'standard process', but failed to actually follow that... In fact, he went ad hoc, despite spending a fortune on his performance management system. For such people, analytics doesn't really help...
3. If you don't know where to use the data (i.e., what indicators are meaningful), you are certainly not a candidate for analytics. Most times, the managers are not aware of where and how to use a report. They spend hours in 'defining' the reports and understanding the kinds of indicators. However, to put that in a smooth-flowing process requires a deeper understanding of the analytics process. Most times this is given a lower priority in the organization. The result is that the legacy process prevails as it is within the 'comfort' levels of the company.
4. If you don't have a proper roadmap of how to 'graduate' from one level to another, you are definitely going overboard with the whole concept. Effective analytics requires a stringent control over all the elements viz. data, updation frequency, updation quality, representativeness checks, etc. And each metric needs a 'minimum' amount of data / substrate information to give meaningful results. If you don't have a proper roadmap of when to use what data, how, and why... you are probably going to spend a lot of money in customizing your analytics tool.
Hope these help...
In case of questions, please let me know. Will be glad to answer.
From United States, Daphne
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HR Analytics in practise.pdf