Data mining in HRM

sharee_2009sharee_2009 Member Posts: 3 Contributor I
Hi there...Is anyone able to help me...do give me some answers to the following questions :

1) How data mining can be used in the Human Resource Management / How data mining can be applied in the HR industry

2) Pros and cons of data mining in the HR industry

3) What examples to show that data mining is used in the HR industry

Thanks to all..GB


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    RyujakkRyujakk Member Posts: 17 Maven
    Hi there...

    I found a great site that probably has all the info you need: http://www.google.com/webhp?rls=ig#rls=ig&q=data+mining+human+resources

    Especially this article from Business Week called "Data Mining Moves to Human Resources" : http://www.businessweek.com/magazine/content/09_12/b4124046224092.htm

    - R
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    RalfKlinkenbergRalfKlinkenberg Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, RMResearcher, Member, Unconfirmed, University Professor Posts: 68 RM Founder
    Hi there,

    thanks for posting the web links on Data Mining for Human Resources. Here are some more answers and comments to your questions:

    1) Uses of Data Mining in Human Resources Management and the HR Industry:
    • Matching job positions to be filled and candidates: Data mining and text mining can help to better and faster match candidates and job profiles. This is particularly helpful in cases were large numbers of positions have to be filled or where large number of employees need to be assigned to new jobs or projects within a short period of time. Experts for this kind of matching can be found here at Rapid-I and also at at least one of the major big consulting companies. If you like, I can establish the contact to experts for this kind of application, for which RapidMiner can be deployed very successfully. Simply contact us: http://rapid-i.com/component/option,com_contact/catid,1/Itemid,30/
    • When comparing successful and less successful projects and/or teams, data mining and text mining can help to find distinguishing patterns and to thereby show reasons for success and deficiences that can for example be fixed by targeted trainings for the employees, e.g. if the lack of a certain skill often let to project failure while the presence of that skill more likely let to successful projects. We cover this kind of application in one of our RapidMiner training courses: Data Mining for Accounting, Controlling, and Fraud Detection with RapidMiner: http://rapid-i.com/component/page,shop.product_details/flypage,garden_flypage.tpl/product_id,49/category_id,14/option,com_virtuemart/Itemid,180/
    • Like stated in the Business Week article referenced in the previous reply, data mining can also support automated performance evaluation of employees. However, this is not free of risk. The key performance indicators used not always capture all relevant aspects of employee performance, but are sometimes overly simplistic.
    2) Pros and Cons of Data Mining in the HR Industry:
    • (+) more efficient and effective mapping of candidates to job,
    • (+) significant reduction of cost,
    • (+) significant reduction of time needed for the process and hence faster response times to candidates and faster filling of open positions,
    • (+) scalability: data mining can help to assign new jobs to thousands and even tens fo thousands of persons within a relatively short period of time; this is particularly helpful for job agencies and large corporations undergoing a restructuring as well as for service providers like consultancies with many projects and consultants to match on a regular basis.
    • (+) support in identifying reasons for success and failures in projects and teams in large corporations and organisations and thereby support in making companies more effective and efficient and hence more profitable, also scalable to large numbers of teams and projects.
    • (+) support in measuring employee performance and evaluating performance, possibly also for supporting hiring/firing/compensation decisions.
    • (-) if used by non-experts or with overly simplistic models, data mining results can lead to misinterpretations and wrong judgements (see last point in list 1 above).
    3) Examples of Data Mining Use in the HR Industry:
    • job agencies,
    • large consultancies with many consultants and projects and regular project (re)assignments,
    • large companies restructuring, for example after mergers or when down-sizing certain units, when trying to reassign as many employees to new position as fast, efficiently, and effectively as possible; for example a major German coal producer had to reduce its work force by many thousands employees and reassigned most of them to new jobs within a few months only with the help of data mining.
    I hope these examples help. Please contact us, if you would like to hear more details or if you would like to connect to an expert.

    Best regards,
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    sharee_2009sharee_2009 Member Posts: 3 Contributor I
    Thank you so much for the useful information and thanks for taking up some time to entertain my question..I do appreciate your effort..Certainly u guys have cleared some of my doubts on data mining...Hope that this topic would also benefit those who are interested in data mining...  ;)
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    landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
    it has passed quite some time since you asked the first time. I'm curious, which experiences did you make with using DataMining for Human Resource Management? It seems to me, you are still interested in, so the results can't be too bad.

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    FaridReFaridRe Member Posts: 1 Contributor I
    I've been working on the same topic for months but I'm new at Rapidminer, so I'm eager to know about researches had done with Rapidminer during these years on this topic. please share your experiments. 
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    yyhuangyyhuang Administrator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 364 RM Data Scientist
    Hi @FaridRe, one of the application is text mining. 
    a. Skillset matching
    HR received 1000+ applications for one software development position, they would not read everyone of these resumes. The would do keywords matching and entity detection on resume with text processing tools in RapidMiner
    b. Employee engagement reviews
    For the internal survey analysis, HR would like to know which areas needs to be improved for better engagement. What topics do the employees care most? What can the management do to reduce the turnover? You can extract the topics with LDA, for instances, to group the reviews into several clusters.
    Using the glassdoor reviews data, you can also extract sentiments, and area to be improved from pros/cons.
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