Dear Seniors,
Greetings of the day.
Can anyone please explain what HR Analytics is and its benefits? How can it be implemented in a pharmaceutical company, specifically for the recruitment process?
Regards,
Vandana Gond
Email: vandana8181@gmail.com
Phone: 8108450999
From India
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1Greetings of the day.
Can anyone please explain what HR Analytics is and its benefits? How can it be implemented in a pharmaceutical company, specifically for the recruitment process?
Regards,
Vandana Gond
Email: vandana8181@gmail.com
Phone: 8108450999
From India
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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
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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
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Dear Vandana,
The post from RNair2000 is excellent 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. Therefore, if you are in a company that doesn't have a reasonable quality of data, 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 the training needs of drivers, and the accidents indicated that the buses had 'hit' another vehicle. However, there was no record of whether it hit the front, back, or side. These details significantly affect the training requirements and technological upgrades.
2. If your decisions aren't data-driven, you are definitely not for analytics. I recall one of my pharma clients who wanted to implement a 'standard process' but failed to follow it and instead went ad hoc, despite spending a fortune on the performance management system. For such individuals, 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. Often, managers are unaware of where and how to use a report. They spend hours defining the reports and understanding the types of indicators. However, translating that into a smooth-flowing process requires a deeper understanding of the analytics process. Unfortunately, this aspect is often given a lower priority in the organization, leading to the persistence of legacy processes due to the company's comfort levels.
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 necessitates stringent control over all elements, such as data, updating frequency, updating quality, representativeness checks, etc. Each metric requires a minimum amount of data/substrate information to yield meaningful results. Without a proper roadmap detailing when to use what data, how, and why, you may end up spending a significant amount of money customizing your analytics tool.
Hope these insights help. If you have any questions, please let me know. I'll be glad to answer.
From United States, Daphne
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The post from RNair2000 is excellent 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. Therefore, if you are in a company that doesn't have a reasonable quality of data, 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 the training needs of drivers, and the accidents indicated that the buses had 'hit' another vehicle. However, there was no record of whether it hit the front, back, or side. These details significantly affect the training requirements and technological upgrades.
2. If your decisions aren't data-driven, you are definitely not for analytics. I recall one of my pharma clients who wanted to implement a 'standard process' but failed to follow it and instead went ad hoc, despite spending a fortune on the performance management system. For such individuals, 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. Often, managers are unaware of where and how to use a report. They spend hours defining the reports and understanding the types of indicators. However, translating that into a smooth-flowing process requires a deeper understanding of the analytics process. Unfortunately, this aspect is often given a lower priority in the organization, leading to the persistence of legacy processes due to the company's comfort levels.
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 necessitates stringent control over all elements, such as data, updating frequency, updating quality, representativeness checks, etc. Each metric requires a minimum amount of data/substrate information to yield meaningful results. Without a proper roadmap detailing when to use what data, how, and why, you may end up spending a significant amount of money customizing your analytics tool.
Hope these insights help. If you have any questions, please let me know. I'll be glad to answer.
From United States, Daphne
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HR Analytics in practise.pdf