an introduction to hr analytics
DESCRIPTION
human resource analytics is a new and fast growing industry. This presentation tries to introduce the reader to a few terms.TRANSCRIPT
HR Analytics
and Everything you wanted to know about
Organizational Analytics
Marketing Analytics
Financial Analytics
Operations Analytics
HR Analytics ?
HR Analytics
drawback of spreadsheetshttp://blog.revolutionanalytics.com/2012/11/using-r-in-the-human-resources-department.html
There is a lot of data out there and it’s stored in different formats. Spreadsheets have their uses
but they’re limited in what they can do. The spreadsheet is bad when getting over 5000 or 10000 rows
– it slows down. It’s just not designed for that. It was designed for much higher levels of interaction.
drawback of traditional modes
BUT ----HR Team is rarely trained in analytics
HR Analytics
sourcing
performance& compensation
attrition
HR Analytics
sourcing he use of assessment tools to “pre-assess” a candidate’s potential to be successful within a specific role within the organization. These tools are already providing a “predictive” look at the candidate skills and abilities by modeling their responses against the best scenario for success
http://www.sas.com/knowledge-exchange/business-analytics/innovation/analytics-creates-a-healthier-workforce-%E2%80%A6-and-bottom-line
HR Analytics
performance and compensationhttp://www.hrexecutivecircle.com/pdf/SAS_HCM_White_Paper.pdf
and
http://www.payscale.com/compensation-today/2009/11/the-value-of-compensation-analytics
and
http://www-03.ibm.com/software/products/en/cognos-incentive-compensation-management
HR Analyticsattrition also known as Predictive Retention Modelinghttp://www.hrintelligenceblog.com/en/?p=658
Track and analyze critical skills, and predict which skills will be lost and when by predicting turnover.
HR Analytics Providershttp://hexaware.com/hr-analytics-services.htmhttp://www.accenture.com/us-en/Pages/service-human-capital-workforce.aspxhttps://support.sas.com/software/products/hcm/index.htmlTraining on HR Analytics ?http://jigsawacademy.com/lp/2014/HR/
HR AnalyticsHR Analytics:
Driving Return on Human Capital
Investment
http://www.oracle.com/us/solutions/ent-performance-bi/045039.pdf
Studies show that
companies that use
HR analytics have:● 8% higher sales growth● 24% higher net operating income growth● 58% higher sales per employee
Case Studies
Trendwise Analytics -Banglore Indiahttp://www.slideshare.net/TrendwiseAnalytics/trendwise-hr-analytics
Case Studies
Google - Project Oxygenhttp://www.nytimes.com/2011/03/13/business/13hire.html?_r=0
1. Be a good coach.
2. Empower; don't micromanage.
3. Be interested in direct reports, success and well-being.
4. Don't be a sissy: Be productive and results-oriented.
5. Be a good communicator and listen to your team.
6. Help your employees with career development.
7. Have a clear vision and strategy for the team.
8. Have key technical skills so you can advise the team.
Case Studies
Google - HRan HBR Case Study
http://hbr.org/product/google-s-project-oxygen-do-managers-matter/an/313110-PDF-ENG
and
http://www.forbes.com/sites/meghancasserly/2013/07/17/google-management-is-evil-harvard-study-startups/
People Analytics @ Google
http://www.amcham.ie/download/Helen%20Tynan%20AmCham%20talk%2031102013%20(1)%20(1).pdf
http://googleresearch.blogspot.in/2012/06/hello-sciencemeet-hr.html
Google People and Innovation Lab (Google Pi Lab)
Additional Linkshttps://www.nordlab.co/pages/people_lab
Case Studies
Using R in the HRhttp://blog.revolutionanalytics.com/2012/11/using-r-in-the-human-resources-department.html
R gets over the limitations of spreadsheets:
In the business world we really don’t need to know every row of data, we need to summarise it, we need to visualise it and put it into a powerpoint to show to colleagues or clients.
http://blog.hrtecheurope.com/2012/08/more-r-in-hr/
The great thing about R is that it cuts down the software budget to zero, and with GUIs cut down training to weeks. You can quickly move from spreadsheet world to being able to build models and predicting outcomes.
Analytics Techniques Used (mostly)
Decision Trees - for segmentationhttp://www.statmethods.net/advstats/cart.html
Regression -attritionhttp://www.statmethods.net/stats/regression.html
Data Visualization -
including spatial and interactive
Trend , Outlier and Patterns (TOP)
From a Google HR ppt Googled
Thanks
Thanks
compiled by Decisionstats
contact https://www.linkedin.com/in/ajayohri