Course Description:
This seminar is designed for participants who wish to learn and apply what is taught on day 1 to their own data. On day 2 of the seminar, participants can create metrics that are business-focused and easy to create. Consequently, participants are encouraged to collect internal data and bring their laptops to the seminar. We will be using excel to create and analyze the data, and to create metrics. In addition, the instructor will demonstrate how to use statistical software to identify "drivers", selected variables drive or predict impact on various metrics.
Learning Objectives:
- Difference between analytics and metrics
- How to pick high-powered metrics
- What comes after establishing 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
Areas Covered:
- Availability and use of HR data
- HR Metrics
- Hypothesis generation
- Pre-identifying the desired outcome
- What to do with Predictive Analytics findings
- Selecting the right interventions
- Mixing art and science
Who Will Benefit:
This session will be of interest to all Global HR professionals with strategic responsibilities. But, specific HR functions will benefit from HR Analytics as follows:
- Organization Development professionals will learn how to identify attributes of high performing employees
- Recruiters will have tangible factors on which to decide whether candidates go forward or not
- Hiring Managers can expect less training time and faster ramp-up time of new hires.
- Co-workers will observe and appreciate new employees who fit the job and culture.
- Compensation professionals will design very effective incentive plans based on statistically proven skills and behaviors.
- Trainers will be able to identify or design training programs that have the most leverage on improving business performance.
- HR Professionals
- HR Manager
- Planning and Audit Managers
- Business Analysts
- HR Heads
- CEO
- CFO
- Department Managers
- Risk Managers
- Team Lead/Managers
Topic Background:
To be ahead of the game, HR professionals need to look out the rear view mirror and the windshield. Keeping track of employee turnover and absenteeism are examples of HR metrics, not HR analytics. Metrics are data based on historical performance and are useful in measuring progress, but they do little to help you make decisions that will change the future.
This workshop will teach participants how to identify the key human metrics and drivers to measure and improve HR and business performance.
Based on the tenant that “one cannot improve what one does not measure”, metrics are very useful in establishing a baseline and measuring improvement. But, selecting the right metrics is key. Do you really want to increase the speed of hiring new people? It is a worthy goal but, if it results in the selection of poor quality new-hires, you will have won the battle and lost the war. This seminar will help you select powerful metrics that are tailored to your organization and geared toward improving business and HR performance.
Beyond metrics, this seminar will focus on micro variables that predict high performance. HR Analytics is the use of data to 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.
- 08.30 AM - 08.45 AM: Meet & Greet
- 8:45 AM - 9:00 AM: : 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 - 10:30: Case Studies on HR Analytics
- Capital One
- Micron
- RE/MAX
- Starbucks
- 10:30- 11:30 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
- 11:30 - 12:30: Lunch
- 12:30 - 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
- Excel
- SPSS
- New Software
- 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
- 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: Selecting the right intervention after completing HR Analytics
Thomas Palladino
Senior Human Resources Consultant
Tom Palladino has held numerous HR leadership positions in companies that included Conoco Phillips, Starbucks Coffee, Wells Fargo, Capital One, First Data and Green Plains Renewable Energy.
His interest in HR Analytics started in 1998 while he was consulting for Starbucks. At that time Starbucks was growing rapidly around the world. Tom was tasked with designing a methodology that would identify employee attributes that correlate with business performance. His HR analytics model was initially applied to new subsidiaries in Asia and Europe enabling the company to inculcate select Starbucks values to create a “performance-driven brew”. Later, Tom’s protocol was successfully applied throughout the United States.
In his HR leadership positions, Tom consistently applied analytics to identify high-leverage HR practices that delivered the highest possible business results.
In 2012, Tom started Refined Analytics (refinedanalytics.com) and has delivered powerful diagnostics and solutions to companies that include RE/MAX, Micron, PepperJax Grill and other organizations around the world.
Today, Tom is focusing on clients in India, China and Indonesia. He is also on the faculty of a university based in Iowa where he teaches Human Resources, Change Management and Lean Six Sigma.
Tom has his bachelor’s degree in Labor Relations from Cornell University and a graduate degree in Dispute Resolution from Creighton University. He resides in Omaha, Nebraska.
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