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Integrating AI Sentiment Analysis with Traditional HR Metrics

September 3, 2024
Blog
4 min read

Although classic HR metrics such as turnover rates and employee engagement scores serve as a valuable yardstick, they often fail to capture the full spectrum of employee sentiment. Using AI in HR can complement existing HR metrics by providing a deeper understanding of the emotions behind employee sentiment.

This all points to a new ‘next frontier’ for AI in human resources and employee sentiment analysis, one that marries technological savvy with intimate awareness of what motivates people at work, enhancing AI in human resources management.

The Limitations of Traditional Metrics

Understanding the limitations of traditional HR metrics can help illuminate the true value of AI sentiment analysis. Traditional HR metrics are primarily quantitative, focusing on measurable data points such as:

  • How many employees does the company have?
  • How many managers?
  • How many staff per manager?
  • How much do they earn?

While these numbers certainly can represent workforce trends, they are insufficient to understand subjective employee experiences. Research from Deloitte reveals that 80% of employee data is unstructured, meaning that most data sits in the form of emails, survey comments, and social media posts that HR does not tap. This is where AI can truly make a difference.

Sentiment Analysis: A Window into Employee Emotions

AI sentiment analysis uses machine learning to extract emotional insights from text. It draws on the language employees use when discussing topics, events, or policies in order to gauge sentiment within their organization.

According to a report by McKinsey, many companies that used sentiment analysis to track or gauge employee feedback reported a 10% improvement in workforce engagement. In other words, if organizations want to boost workforce morale, sentiment analysis may be the key. Employing AI in human resources management promises even more actionable insights into nuanced areas like pay equity analysis.

grid of employee headshots highlighting some of the individuals

Enhancing HR Metrics with Sentiment Analysis

Using AI in HR can give us a more complete picture of the workforce. Here are a few applications of AI sentiment analysis.

  • Employee Engagement: Positive or negative sentiment derived from within organizations from employee sentiment surveys and HR surveys helps identify drivers of engagement and disengagement to address specific issues.
  • Turnover Prediction: Sentiment analysis of employee communications can accurately detect warning signs of dissatisfaction before employees quit, which can enable managers to take corrective action. A study by IBM found that sentiment analysis improved their ability to predict employee attrition by 20%.
  • Performance Reviews: Using NLP on employee performance reviews can pinpoint existing biases or deeper systemic issues that may creep into employee evaluations and workforce metrics. Organizations can use this data to create more equitable — and fair — performance management practices.
  • Training Effectiveness: AI Sentiment analysis of feedback on different training programs can help you pinpoint what your staff thought the training missed, so you can make adjustments and ensure better ROI down the line.
  • Spotting Implicit Bias in Recruitment: Sentiment analysis can find subtle cues of implicit bias in recruitment materials such as job descriptions and candidate resumes. This can help alleviate subtle biases that might discourage diverse candidates.
  • Monitoring for Inequity: AI in human resources management can be a powerful force for equality. Internal employee communications such as email, Slack channels, or other internal communication tools can help organizations monitor their own culture in real-time so they can identify any negative cultural wave relating to diversity, pay equity, and inclusion before it forecloses necessary action.

In addition, AI sentiment analysis offers real-time feedback and input into sentiment around key company milestones and events such as product launches and town hall meetings.

Real-World Applications

Many organizations already use sentiment analysis to inform their HR strategy:

Microsoft: Used employee sentiment analysis to gauge reactions to a new performance review system. This helped them identify areas of concern and make improvements to increase employee satisfaction.

IBM: Utilized sentiment analysis to analyze posts on their internal social network. This allowed them to understand employee sentiment on various topics, including a proposed overhaul of their performance review system.

T-Mobile: Implemented sentiment analysis to analyze customer service interactions. This helped them identify common customer pain points and improve their overall customer experience.

office desk with virtual employee sentiment markers hovering over seats

Integrating AI Sentiment Analysis: Best Practices For Using AI in HR

  1. Clearly Define Objectives: Figuring out which HR issues you want to tackle with sentiment analysis and where you are manually spending significant amounts of time reading through large amounts of text. To properly use AI in human resources management, you need to plan ahead.
  2. Pick the Right Tools: Assess available tools and sentiment analysis platforms to see which best suits your company and budget. Sometimes, custom tools like a personalized HR dashboard can help you realize your objectives quickly and efficiently.
  3. Ensure Data Privacy: Prioritize the security and confidentiality of employee data.
  4. Add to Human Insights: AI is a tool, not a replacement for HR. You’ll get better results when you use employee sentiment analysis to extend, rather than replace, human insights and decision-making.

The Road Ahead

Integrating AI sentiment analysis with traditional HR metrics is not just a trend, but a transformative shift in how organizations understand and manage their workforce through sentiment analysis. By harnessing the power of data to listen to employees accurately and at scale, HR can make more informed decisions and, in turn, empower the organization to achieve success.

From improving performance to realizing equity, the benefits of using AI in HR have made it a necessity for growing businesses. Harness the transformative power of AI for human resources management with Jara Analytics today. Get in touch to find out how you can drive performance with AI sentiment analysis, including integration with real-time listening platforms, performance reviews, and so much more.