drawback of spreadsheets
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
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
performance and compensation
attrition also known as Predictive Retention Modeling
Track and analyze critical skills, and predict which skills will
be lost and when by predicting turnover.
HR Analytics Providers
Training on HR Analytics ?
Driving Return on Human Capital
Studies show that
companies that use
HR analytics have:
● 8% higher sales growth
● 24% higher net operating income growth
● 58% higher sales per employee
Trendwise Analytics -Banglore India
Google - Project Oxygen
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.
Google - HR
an HBR Case Study
People Analytics @ Google
Google People and Innovation Lab (Google Pi Lab)
Using R in the HR
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.
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 segmentation
Data Visualization -
including spatial and interactive
Trend , Outlier and Patterns (TOP)