HR - Talent forecasting
Chris_Axe
New Altair Community Member
Hello Community!
Straight to subject if you don't mind
My company need to know witch persons from HR database is qualifying for Talent pool. I have tried to find some basic rules to write a PL/SQL procedure, but it seems the process is much heuristic that i thought! I will transpose that in next simple fact: weight of attributes changes dynamically for each person and i should adapt code permanently and that it's not a viable solution i guess. After comparing my results with an HR expert pool list, recognition of talents with my script is bellow 50%...
After some diggings on the web i get to next conclusion: Certainly RapidMiner could help me to get much better results! My expectations is around 75% of correct identifications.
And now some data:
-number of employees around 8000
-number of employee attributes 9
What do you think? It can be done? The dataset is too small to get expected results?
kind regards.
chris
Straight to subject if you don't mind
My company need to know witch persons from HR database is qualifying for Talent pool. I have tried to find some basic rules to write a PL/SQL procedure, but it seems the process is much heuristic that i thought! I will transpose that in next simple fact: weight of attributes changes dynamically for each person and i should adapt code permanently and that it's not a viable solution i guess
. After comparing my results with an HR expert pool list, recognition of talents with my script is bellow 50%...After some diggings on the web i get to next conclusion: Certainly RapidMiner could help me to get much better results! My expectations is around 75% of correct identifications.
And now some data:
-number of employees around 8000
-number of employee attributes 9
What do you think? It can be done? The dataset is too small to get expected results?
kind regards.
chris
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Answers
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Hi,
Straight to the answer if you don't mind: Cannot say it
What do you think? It can be done? The dataset is too small to get expected results?
The size of the data set is not important (although 8000 samples for 9 attributes usually sounds good to me). The problem is that I don't have any idea what is encoded by those 9 attributes. If it is merely stuff like Name, Address, Zip Code etc. you will probably end up with bad results. If they are really describing some skills etc. this might work out well for a well-designed and optimized process. If you reach 51%, the desired 75% or 99,99% will be evaluated during model creation and optimization and usually is not something which can be guaranteed before - at least not by somebody not familiar with the details and hardly any experience on this specific topic...
Just model the data and evaluate it - then you will know!
Cheers,
Ingo0
