This document is about the HR analytics. This is published by Big IT Jobs.

1. HR Analytics
And everythingyouwantedto knowabout

2. Organizational Analytics
• Marketing Analytics
• Financial Analytics
• Operations Analytics
• HR Analytics ?

3. HR Analytics
• There is a lot of data out there and it’s stored in different
formats. Spread sheets have their uses but they’re limited in
what they can do. The spread sheet 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

4. HR Analytics
Sourcing
Performance
& Compensation
Attrition

5. HR Analytics
• Sourcing
• The 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 modelling their responses against
the best scenario for success.

6. Performance And Compensation

7. HR Analytics
• Attrition also known as Predictive Retention Modelling
• Track and analyse critical skills, and predict which skills will be
lost and when by predicting turnover.

8. HR Analytics
• Driving Return on Human Capital Investment
• HR analytics have:
• 8% higher sales growth
• 24% higher net operating income growth
• 58% higher sales per employee

9. Case Studies
• Google - Project Oxygen
• Be a good coach.
• Empower; don't micromanage.
• Be interested in direct reports, success and well-being.
• Don't be a sissy: Be productive and results-oriented.
• Be a good communicator and listen to your team.
• Help your employees with career development.
• Have a clear vision and strategy for the team.
• Have key technical skills so you can advise the team.

10. Additional Links

11. Using R in the HR
• R gets over the limitations of spread sheets:
• 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.
• 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 spread sheet world to being able to
build models and predicting outcomes.

12. Analytics Techniques Used
• Decision Trees - for segmentation
• Regression –attrition
• Data Visualization - including spatial and interactive
• Trend , Outlier and Patterns (TOP)

13. Thank You