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SHRM 2017 Annual Conference & Exposition
This session will show you how you can have the right compensation data to help you win the talent war.
PowerPoints/Handouts Available

Repeated Tuesday at 4:00 p.m.

The compensation data landscape has changed. HR and compensation professionals have more choice than ever in data sources. At the same time, employees are more informed of their market value. For some, this is a shift towards more positive conversations, but it can be scary without the right data to back you up. This session will review trends impacting compensation, overview the growing data market and considerations for selecting sources, and illustrate how organizations use compensation data to forward your business strategies. This session will help you:

  • Get a better understanding of the factors that are contributing to this tight talent market. 
  • Understand the spectrum of sources of compensation data, as well as how to evaluate their usefulness for attendee organizations. 
  • Understand how compensation drives your business strategy as well.

 

 
Date(s) & Time(s): 
Monday, June 19, 2017 - 2:00pm to 3:15pm
Presenter: 
Katie Bardaro
VP, Data Analytics
Payscale
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Katie Bardaro, Vice President of Data Analytics, joined PayScale in 2008. In addition to leading the Data Analytics team and building and maintaining PayScale's proprietary compensation model, Katie serves as PayScale's Lead Economist. She has provided analysis on compensation data and trends for print/online and broadcast media including The Wall Street Journal, The New York Times, Bloomberg Businessweek, The Economist, CNBC, CNN Money, USA Today, Forbes, and Business Insider, among others. Katie holds a bachelor's in economics from the College of the Holy Cross and a master's in economics from University of Washington, with a focus in labor economics and econometrics.

SESSIONS:
Location: 
255-257
Amount of Credit: 
1.25
Credit Type: 
•SHRM PDCs
Session Type: 
Concurrent Session
Competency: 
HR Expertise
Critical Evaluation
Intended Audience: 
Mid-Level
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