Understanding HR Analytics
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
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From India
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1Can 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 Removed For Privacy Reasons]
[Phone Number Removed For Privacy Reasons]
From India
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Dear Vandana, the post from RNair2000 is excellent and gives you a good overview.
Pointers on Analytics
Here are a few pointers on the topic from my end:
• 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 muddled 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.
• 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.
• 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.
• 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.
Regards
From United States, Daphne
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Pointers on Analytics
Here are a few pointers on the topic from my end:
• 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 muddled 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.
• 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.
• 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.
• 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.
Regards
From United States, Daphne
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HR Recruitment Process 112304.doc