Qualitative Analysis Powered by AI: Transforming Learner Feedback into Actionable Insights

Written by Explorance.

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In today’s corporate landscape, organizations are swamped with a ton of employee data. The abundance of qualitative feedback can be particularly overwhelming, from discussions on feedback channels and engagement surveys to comments about the onboarding processes and career development programs. The challenge lies not in gathering data but in analyzing it to create actionable insights that drive positive change within the organization. So, how do we navigate this sea of qualitative data to extract the valuable nuggets that can revolutionize the employee experience?

As learning and HR professionals increasingly recognize the importance of qualitative analysis, AI is becoming a game-changer in deciphering and leveraging employee comment feedback. According to a survey by Brandon Hall Group™, 84% of organizations prioritize the acceleration of AI and data analytics in learning and human capital management.

To delve deeper into AI’s transformative power, Explorance recently participated in a panel discussion moderated by Claude Werder, Senior Vice President and Principal Analyst at Brandon Hall Group™. The panel featured industry experts Duane Draper from Microsoft, Steve Lange, and Michael Cohen from Explorance.

Here are four takeaways from their conversation to help organizations understand how AI helps make sense of what learners tell us:

1. Education and Awareness

While AI holds tremendous potential, many organizations are still in the early stages of understanding its capabilities. Educating stakeholders and fostering a learning culture is essential to maximizing the benefits of AI-driven analytics. By championing AI initiatives and providing training in analytical skills, organizations can bridge the knowledge gap and unlock AI’s full potential in interpreting learner qualitative feedback.

This approach aligns with the objectives of Explorance World 2024, where leaders from various industries, including Higher Education, Human Resources, and L&D, will convene to share insights, strategies, and innovations that harness feedback data and AI for actionable outcomes.

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2. Topics Requiring Immediate Attention

Due to the difficulties of analyzing qualitative data, organizations risk missing crucial information about the employee experience. “Are there needles in the feedback haystack that we would have missed that could cause irreparable harm to the organizations?” asked Claude Werder during the panel. “That’s where AI can show its value.”

Using AI-powered tools like Explorance MLY, organizations can quickly gain deeper insights into learner feedback, enabling them to get ahead of sensitive issues requiring immediate attention.

3. From Data to Action

Harnessing the full potential of learning analytics hinges on the ability to extract actionable insights from vast datasets. Explorance emphasizes the importance of asking the right questions of the data—engaging in a dialogue that unveils nuanced insights and informs strategic initiatives.

“One of the questions we get often from clients is around ‘speed to insight’—how do I do things faster? That’s where AI can take some of the time out of our day,” commented Steve Lange. “By sifting through our learning analytics data, especially qualitative data, and summarizing it into what it means. Are there any actions here, any comments of concerns—that’s the value that AI can bring.”

Through MLY, Explorance enables organizations to efficiently sift through mountains of qualitative feedback, identifying critical insights that might otherwise go unnoticed. By embracing AI-driven analytics, organizations can unlock hidden opportunities and continuously improve learning outcomes.

“There is just no way we have time to read through hundreds of comments and correlate them into insights,” Duane Draper added. As soon as [Explorance] MLY was brought to us last fiscal year, we jumped on it and have gotten some really good results so far.”

4. Infrastructure Management and Governance

Effective governance frameworks are crucial for the successful implementation of AI-driven analytics. Organizations must prioritize data integrity, privacy, and risk management to build trust and ensure compliance with regulatory requirements. Clear data usage and privacy policies, along with robust infrastructure management practices, are essential to supporting AI implementation effectively.

AI is not just a tool but a catalyst for transformation in learning and development. By harnessing the power of AI-driven analytics, organizations can unlock valuable insights from learner feedback, drive continuous improvement, and ultimately enhance the overall employee experience. As we navigate the evolving landscape of AI and analytics, one thing remains clear: Ais like Explorance MLY can revolutionize how we understand and leverage learner feedback, paving the way for a brighter future in learning and development.

Watch the exclusive webinar on-demand now and learn how AI helps make sense of what Learners tell us.

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