Blog

How Do Employees Really Feel? The Power of Sentiment Analysis

Written by Explorance. December 10, 2023

An organization that gains an accurate understanding of its employees’ sentiments opens the door to improved performance and retention, a critical consideration amid varying opinions on public health measures and workplace restrictions. While many feedback processes prioritize expedited data gathering through concise, multiple-choice questions that channel opinions into predefined categories, this approach may inadvertently overlook nuance and deeper, firmly held opinions.

Presenting the opportunity for employees to describe those opinions in an open-text comment is a route to more honest feedback. The challenge, then, is in analyzing, understanding, and tabulating these text comments into insights that can then be used to drive meaningful action. This could involve tackling tens of thousands of sections of open-ended comments where a single word can drastically alter how an employee’s experience is portrayed.

The power and real-time insight of an AI-powered sentiment analysis solution like Explorance MLY can overcome this obstacle and help organizations get to the core of employees’ feelings. Below, we outline some of the key benefits of sentiment analysis solutions and how they can help organizations listen better to what their people have to say and, more importantly – act on that data.

What is Sentiment Analysis?

Sentiment analysis, also known as opinion mining, is a natural language processing (NLP) technique used to determine the sentiment or emotional tone expressed in employee open-text comments. The primary goal of sentiment analysis is to identify and extract subjective information from text, helping to understand the feelings, attitudes, and opinions of individuals or groups toward a particular topic, product, service, or event.

1. Beyond Word Associations

Sentiment analysis, a widely used method with applications across various sectors, can reveal various emotions in text comments from any source, such as employee engagement surveys, job review sites, and social media. Its effectiveness in handling open-ended feedback is noteworthy, thanks to the quick insights provided by automated solutions. The crux lies in considering the context of the feedback. Advanced AI-powered solutions, exemplified by Explorance MLY, go beyond simple word associations. They provide nuanced insights into specific comments, capturing the overall tone and emotion. By operating within informed contexts, Explorance MLY can accurately identify the true sentiment behind comments, even when expressed indirectly or through sarcasm.

2. Topic-Specific Sentiment Analysis

Learning about key topics through sentiment analysis is crucial for any leader in an organization. Solutions like Explorance’s MLY play a pivotal role by mapping employee responses and categorizing sentiments expressed in the text to critical areas such as leadership, professional growth opportunities, diversity, training quality, discrimination, job security, work-life balance, and current workloads. These topics significantly impact an employee’s motivation, productivity, and commitment to an organization in the long term.

Moreover, the ability to uncover hidden sentiments shared among many employees, sentiments that may not surface in multiple-choice evaluation forms, opens the door to adopting new policies or approaches that can comprehensively address underlying issues. Organizations can identify and resolve elusive, painful, yet undiagnosed problems by homing in on sentiments, resulting in a positive experience for employees who take the time to provide detailed feedback. This approach values the opinions expressed in confidential, open comments, showcasing how a detailed sentiment analysis solution improves workplace culture.

3. Deepening Insight

Enhancing the depth of sentiment analysis is achievable by integrating supplementary datasets. This involves combining and organizing text analysis outcomes with additional datasets, such as the employee’s tenure, department, current training status, position in the organizational hierarchy, and other relevant factors. The true strength of sentiment analysis emerges when it operates within the framework of a comprehensive Feedback Analytics strategy, which delivers added layers of context. This augmented information landscape contributes to sentiment analysis with a more robust background, bridging information gaps and presenting a clearer depiction of everyone’s employee experience.Top of Form

4. Context and Agility

While there are various approaches to sentiment analysis, ranging from manual human readers to machine learning techniques, two factors are critical: context and agility.

Context is the setting for a comment that shapes its meaning, the inter-related words and concepts that help us express meaning. Any system that can’t detect the context of unstructured comments will miss many sentiments and deliver shallow insights.

Agility is the ability to react quickly to changing conditions to understand and act on new information. Any system without agility will take a long time to update, miss new terms, and ignore fresh sentiments bubbling up from employees.

Explorance MLY combines long-term familiarity with Feedback Analytics and a direct focus on actual employee comments. This overcomes the limitations of earlier sentiment analysis systems and provides the deepest context available.

Furthermore, MLY’s machine learning algorithm, rigorously trained with actual employee comments, continues to improve over time, with no waiting for a new dictionary and no lag time to get a new module.

Key Takeaways

Integration Boosts Insight: Combining sentiment analysis with additional datasets, such as employee tenure, department, and organizational position, amplifies the depth of understanding, providing a more comprehensive view of employee sentiments.

Context is Key: Sentiment analysis is most effective when embedded within a broader Feedback Analytics strategy, enriching the analysis with contextual information. This integration helps bridge gaps and offers a clearer picture of employee experiences.

Data Synergy for Employee Insight: The synergy of sentiment analysis and integrated data enhances the power of understanding employee sentiments, contributing to a more nuanced and informed approach to shaping workplace dynamics.