Innovating Strategies to Predict Turnover and Boost Employee Engagement
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Employee engagement data provides a new lens that helps you see the biggest areas of risk for turnover in your organization. TINYpulse will walk through best practices and techniques for how to drill down into your organization, measure employee engagement by area or function, then translate that into a detailed view of your turnover risk and compare it to industry and regional benchmarks to see if your risk level is a red flag.
This webinar will also provide tools and techniques to help you prevent turnover and get your risk level in check, including improving employee engagement, taking the pulse of your team and creating a great workplace culture.
This webinar will help you and your organization:
- Identify best practices for assessing turnover risk in your organization
- Discover how to uncover the key reasons driving voluntary turnover
- Learn steps you can take to reduce turnover and increase workplace happiness
This webinar will address common challenges and give you:
- Tools and techniques for getting data to measure your turnover risk, including employee pulse surveys and sources for benchmark data for your industry and region.
- Tips on how to reduce unplanned turnover and improve employee satisfaction and engagement, with real-world examples of how companies have solved turnover problems with regular 1:1s, enabling peer recognition, increased transparency and open, anonymous feedback channels.
About TINYPulse: Thousands of companies use TINYpulse to assess employee engagement and retention risk. TINYpulse insights have been published in the Wall Street Journal, Harvard Business Review, USA Today, Forbes and Fortune. TINYpulse analyzes millions of data points from employee pulse surveys, LinkedIn, Glassdoor and the Bureau of Labor Statistics to help companies create a happier workplace. Join us for this exclusive webinar June 23rd 2 p.m. EST!
Participants will receive a complimentary two-week trial of the TINYpulse engagement platform to measure turnover risk.