Perceptyx Continues Culture of Innovation With Hot Spot Reporting and Sentiment Analysis to Uncover Insights With Ease
Leveraging machine learning and artificial neural networks to find people and business insights in an instant.
SAN DIEGO, April 12, 2018 (Newswire.com) - Perceptyx, the employee survey and people analytics platform that helps companies truly listen to their employees and immediately discover the insights they need to make business decisions with greater speed and confidence, announced today two new innovations to expedite the process of gaining insight and taking action – across all levels of the business. Leveraging machine learning and artificial neural networks, Perceptyx’ innovations focus on sentiment analysis within survey comments and discovering demographic hot spots deep within an organization’s complex hierarchy.
Identifying and mitigating challenges has always been an important function for leaders and HR practitioners. However, in large and complex organizations, uncovering these challenges – or even knowing where to look – can be extremely difficult. In many cases, small pockets deep within the organization may significantly impact employee experience and organizational performance; but without having visibility to these areas, they can often go unnoticed. Leaders within large organizations need specialized tools to help them quickly identify and implement corrective actions to remain at peak performance.
Perceptyx has always had a rich culture of innovation, but for us innovation takes shape not only in the technology itself, but in how we can apply it to the business context. These new tools allow us to surface issues for leaders faster than ever before.
John Borland, Co-Founder & CEO
Perceptyx’ new Hot Spot report utilizes state-of-the-art procedures to quickly mine large, complex datasets to identify risks at any level within the organization – across many topic areas such as attrition, unionization, organizational change, and diversity & inclusion. “Minimizing the time it takes to find important survey and people insights is a continued and significant body of work at Perceptyx,” says Dan Harrison, Ph.D., director of Innovation and Org Development. “The new Hot Spot Report will save leaders time by bringing critical areas to the surface in a single mouse-click.”
Likewise, advances in comment analysis procedures mean that important observations are backed up with deeper qualitative insights from employees. Perceptyx’ new comment sentiment analysis tool leverages convolutional neural networks (CNN) and natural language processing (NLP) to deliver instant insights across hundreds of thousands of survey comments in over 150 languages. This rich sentiment data can now be used to quickly focus survey results around those employees who share a similar viewpoint, allowing leaders to easily move from qualitative data back into more specific quantitative data.
John Borland, Co-Founder & CEO, adds, “Perceptyx has always had a rich culture of innovation, but for us innovation takes shape not only in the technology itself, but in how we can apply it to the business context. These new tools allow us to surface issues for leaders faster than ever before.” New Hot Spot reporting and enhanced comment sentiment analysis improves the speed with which leaders at all levels of the organization can find important observations and take appropriate action, improving overall organizational performance.
About Perceptyx
Perceptyx is the employee survey and people analytics platform that helps hundreds of the world’s largest and most complex organizations to truly listen to their employees and immediately discover insights they need to make business decisions with greater speed and confidence. A trusted partner to companies like Nike, Hitachi, American Airlines, and P&G, Perceptyx has been enabling people and organizations to thrive for over 15 years. To learn more, please visit www.perceptyx.com.
Press Contacts:
Daniel Norwood
Perceptyx
+1 (951) 676 4414 x201
[email protected]
Source: Perceptyx, Inc.
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Tags: Employee survey, engagement, human resources, machine learning, neural networks, people analytics