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April 18, 2019 Newswires
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Willis Towers Watson Adds Powerful Analytics Capabilities to Its Employee Engagement Software

Targeted News Service (Press Releases)

ARLINGTON, Texas, April 17 -- Willis Towers Watson, a risk management, insurance brokerage and advisory company, issued the following news release:

* * *

- New Advanced Analytics module boosts HR's ability to gain the deepest insights into employee opinions and attitudes

* * *

Willis Towers Watson (NASDAQ: WLTW), a leading global advisory, broking and solutions company, today announced a new release of its Willis Towers Watson Employee Engagement Software. The enhanced software now includes an Advanced Analytics module for its employee survey platform. This new capability is an add-on to existing Willis Towers Watson Employee Engagement Software and is now available for implementation.

The module enhances the software's analytical capabilities by integrating and analyzing multiple sources of survey data alongside an organization's own human resource information systems (HRIS) data. This will help organizations understand how employee opinions vary across multiple surveys and any information stored in HRIS, such as performance rating, reward, leadership or gender. The module's simple interface and data visualizations will enable HR and people analytics professionals to quickly find answers to critical talent, HR and business questions.

"This new module makes Willis Towers Watson Employee Engagement Software the most powerful in the industry," said Stephen Young, global practice leader, Employee Insights, Willis Towers Watson. "Analytics teams within HR functions need simple ways to house multiple data sets in one place and mine them for critical insights.

Until now, this has not been easy. Our new module takes clients' historical survey data and combines it with their own HRIS data to create the deepest insights into employee engagement. This will allow clients to spend time providing leadership with insights rather than scripting research tools or playing with multiple data files."

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