HR Metrics and Analytics 2016: 2-Day In-person Seminar
Course Description:To be ahead of the game, HR professionals need to look out the windshield, not the rear view mirror. Keeping track of employee turnover and absenteeism are examples of HR metrics, not HR analytics. Metrics are data based on historical performance. They are useful in measuring progress, but they do nothing to help you make decisions that will change the future.
This workshop will teach participants how to identify the key human drivers that explain why some workers are high performing, what truly motivates people to work harder, what training courses deliver the most value to the Company and much more.
HR professionals have powerful intuitions and strong hunches, but to "sell" their ideas, they need data to back them up. This Seminar will help HR professionals test hypotheses and make a "business case" for their ideas.
Today, HR leaders can easily use technology to develop analytics and make key predictive decisions.
Difference between analytics and metrics
How analytics can be used to significantly help the business
Case studies to demonstrate real life projects
How to develop an analytics model
Data needed and how to use Excel to develop analytic formulas Using analytics in selection process, the biggest opportunity in the HR area
Availability and use of HR data
Pre-identifying the desired outcome
What to do with Predictive Analytics findings
Selecting the right interventions
Mixing art and science
Day One (8:30 AM – 5:00 PM)
8:30- 8:45: Meet & Greet
8:45- 9:00: If you could see the future, how would you use this gift in your job?
9:00- 10:00: Introduction to HR Analytics.
What is HR Analytics
How is it different from marketing, risk and other analytics
How is Analytics different from metrics
10:00- 11:00: Case Studies on HR Analytics
11:00- 12:00 Designing the Analytics Models
Assessing the availability and veracity of data
What is your outcome variable (“Y” Variable)
How to select the “Y” Variable
How to determine the “X” variables
Examples of “X” and “Y” variables
12:00- 1:00: Lunch
1:00- 1:30: Collecting the data
Output data versus subjective data
Developing a powerful and validated survey
Open-ended (narrative) questions
Engagement Survey, bi-product of the process
The need for calibration
1:30- 2:00: Processing the data
How to select the data processing tool
2:00- 4:00: Let’s talk (Small Groups)
What is your desired “Y” Variable?
Why did you select it?
What is the business case to for this project?
How “solid” is your “Y” variable data
What is your hypothesis on what drives the “Y” variable?
Do you have the “X” variable data?
4:00- 4:30: Group Debrief
4:30- 5:00: Summary, Reflections and Agenda for Tomorrow
Day Two (8:30 AM – 5:00 PM)
8:30- 8:45: Meet and Greet
8:45- 9:30: Basic statistics and analytical tools
9:30- 11:30 Small Group exercise – developing powerful analytic model for your project
Describe your proposed project with partner(s)
Elicit feedback from partners on the project. (How solid is the data? How available is it? What is your desired outcome variable (“Y” variable). How will you generate the “X” variables? How will you test them?
Select 3 or 4 projects among all of them and assign a team for each project.
Begin the analyses using excel and/or other statistical software.
Identify preliminary findings
11:30- 12:00: Present to other participants
12:00- 1:00: Lunch
1:00- 2:00 Completing the Diagnostic Phase: What is next?
Discuss presentations. What was done well? Was the data there? Good Y variable? Did they miss any possible X variables? How was their analysis and use of analytic software?
2:00- 2:30: New trends in HR Analytics
2:30- 3:30: Other uses for HR Analytics
3:30- 5:00: Selecting the right intervention after completing HR Analytics