Moveworks Launches Employee Experience Insights to Help CIOs Identify and Prioritize High-Impact Initiatives

EXI uses new techniques in Natural Language Understanding to help businesses identify the biggest issues slowing employees down

Moveworks launched Employee Experience Insights (EXI) — an analytics and insights solution that uses breakthrough techniques in Natural Language Understanding (NLU) and machine learning to uncover the issues slowing employees down the most. It gives CIOs an actionable to-do list based on which initiatives will maximize productivity and ROI.

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“Every help desk is sitting on a treasure trove of information that could prevent future issues, before they happen”

Today, business leaders face an impossible task: Increase operational efficiency, improve the employee experience, and do it all without first understanding what’s slowing employees down. A recent report found that 82% of leaders acknowledge that employees will consider leaving if their current employer does not provide access to the tools, technology, or information they need to do their jobs well. Nearly three in five employees who do experience this frustration said it makes them less productive. And yet, none of these leaders have had visibility into what’s slowing productivity and what’s not, so their ability to actually fix these problems is limited — until now.

Employee Experience Insights uses advanced techniques in NLU and machine learning to analyze and categorize data coming in from customers’ ITSM systems. It offers CIOs granular insights into the biggest issues plaguing each employee persona — allowing leaders across every department to remove inefficiencies and resolve employees’ frustrations in real time. And, while current ITSM insights tools focus primarily on tickets and SLAs, EXI focuses entirely on people, which means businesses now have answers to critical questions, like:

• Which apps do employees need access to on day one?
• What are the biggest issues remote employees are running into?
• What are the most common issues employees spend time troubleshooting?
• How long is Sales waiting for support for critical issues, vs. Engineering, vs. Marketing?
• How does our performance compare to industry standards and internal benchmarks?

“At Databricks, we know the right data and AI can transform how an organization does business,” said Naveen Zutshi, CIO of Databricks. “My job is to empower our digital workforce with the tools and technologies they need to perform at their best. With Moveworks’ sophisticated NLU and Employee Experience Insights, we have meaningful and actionable data to turn thousands of requests into an efficient plan of action and a best-in-class employee experience.”

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Employee Experience Insights relies on Moveworks’ proprietary NLU models to understand and categorize each employee issue. While most out-of-the-box NLU models are only able to categorize 20 – 30% of a company’s tickets when attempting this same analysis, Moveworks’ NLU models are able to categorize 100% of them. That’s because our models are trained on three different sources:

• Best-in-class language models: Language is complex, nuanced, and often challenging for machines to accurately decipher. That’s why the Moveworks platform is built on a foundation of best-in-class language models — like BERT and GPT — that enable it to interpret the infinite nuance of human language.
• Employee support requests: Employees use different language at work than they do in their personal lives. Moveworks is trained on over 400M employee support requests, which allow it to discern how employees communicate in their day-to-day work environments.
• Customer data: Each company has its own unique language — whether it’s the name of their Wi-Fi network, or the names and titles of each employee. Moveworks is trained on each customer’s unique entities to ensure it can detect what the employee needs in their own environment.

“Every help desk is sitting on a treasure trove of information that could prevent future issues, before they happen,” said Bhavin Shah, CEO of Moveworks. “But business leaders have not yet been able to extract value from this data because the majority of AI models fail to understand the vast ambiguity of human language. Recent advancements in NLU have changed that — and it’s a milestone that will fundamentally change the way business leaders make decisions moving forward.”

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