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Garry Straker has more than 20 years of experience providing total rewards consulting services to a diverse list of clients from a variety of industries including technology, logistics, higher education, non-profit, healthcare, public sector, and more. Garry’s focuses on helping organizations achieve strategic goals by leveraging technology, data, and labor market insights to design sustainable, market-aligned total compensation plans. His expertise includes developing rewards programs that are appropriately aligned with workplace culture, and business priorities. Garry is an active member of WorldatWork and a board member of the Colonial Total Rewards Association. He is also a certified employee benefits specialist with fellowship status. He has been a presenter on human resources, compensation and benefits topics at national and regional conferences, including the WorldatWork Pay Equity Symposium, SHRM, CBIA, CUPA and SACUBO. In this episode, Garry Straker talks about sourcing and working with good sets of data. 

[0:00 -1:31] Introduction

•Welcome, Garry!

•Today’s Topic: Sourcing and working with good data. 

[1:32 -6:58] What are the biggest issues with getting good data for pay equity analyses

•Data is often incomplete

•Incomplete data should not prevent organizations from doing pay equity analyses

[6:59 -12:51] What are your thoughts on privacy laws concerning an organization’s people data? 

•Why this may be just the beginning

•What to do with an employee that may choose to opt out of HR processes

•Helping employees understand how their data is being used

[12:52 -13:29] Final Thoughts & Closing

•Thanks for listening!

Quotes:
“I think organizations are going to have to develop processes and systems to be able to compile a more complete data. It's not going to happen overnight . . . If they're going to continue to do pay equity analyses credibly, they're going to have to make a commitment to obtaining that data all the time.”

“I think US companies, and I think employers generally, are probably going to have to start helping employees understand how they're using their data.”

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