AI-Powered Employee Engagement
A recent report depicts that 85% of employees are actively disengaged in their workplaces, this amounts to a whopping $7 trillion in lost productivity globally.
At a Glance
Engagement approaches such as basic employee surveys & limited data analysis does more harm than to deliver actionable insights.
Azilen being a proficient HR Tech. innovator has delivered an AI-powered solution, that engages employees like never before into an enthusiastic, self-motivated, and growth-oriented culture.
Key Highlights
Employee Behavior Mapping
Data-Backed Insights
Smart Surveys & Feedback
Sentiment Analysis
Advanced Machine Learning
Predictive Analytics
Challenges
- High Volume Data Analysis
- Discover Emerging Org. Trend
- Dynamic & Self-Learning ML Engine
- Monitor Real-time Feedbacks
- Gauge Employee Sentiments
About Client
The customer based in the U.S. is a technology reformist serving over a thousand businesses to treasure their most valuable resource i.e. Employees. With a firm ambition to deliver collective intelligence across the organizations, the customer aims to provide an advanced solution that elevates the entire employee engagement experience.
HRTECH
Industry
ENGAGEMENT
Domain
USA
Location
How we helped?
Azilen commenced a strategic engagement with the customer to achieve an AI embraced solution to analyze the textual data and generate detailed insights to identity & categorize emerging organizational themes. This ultimately proved to drive better business decisions, open communication & higher engagement.
5M+
Data Records Utilized
70%
Accurate Predictions
Self Learning
Machine Learning Models
The Solution
Unfeigned Employee engagement is a mystery for most of workplaces. Traditional engagement tools dependent on manual operations are inadequate for generating insights into how and what employees really feel.
Azilen brought forth the idea to utilize Artificial Intelligence (AI) & Machine Learning (ML) to overcome longstanding crises of smart Employee engagement & deliver real-life benefits for the end-users. It all started with extensive research & analysis of customer’s existing platform with over millions of data records.
This led to an improvised product strategy & a roadmap that enabled us to streamline processes, interpret data better, provide more accurate predictions, and cut down costs.
With more than 8 years of experience in Employee Engagement, the customer had acquired enormous data records from various Survey responses, Employee Comments, Email trails, Ongoing conversations, and much more.
Multiple ML techniques, approaches & areas were identified to build an AI responsive solution. Below are glimpses of some of the targeted areas:
1. Corporate Listening
- A Large amount of data was analysed to derive the trending topics in organization, sentiment analysis to have better insights about employee’s workplace mood & other aspects that aim to flag even the smallest issue faced by employees.
- Implementation of ML model with Unsupervised Learning using clustering techniques & BERT language model for feature extraction.
- Millions of records were extracted & a text corpus was formed. The ML model identified different clusters, hidden patterns, and a provided grouped dataset in form of Word cloud.
- This word cloud revealed quick insights based on frequent phases or themes used in the employee comments on overall.
- HR Domain-specific model with ready available API for external integration.
Artificial Intelligence is taking a major leap into Employee Engagement through its effective incorporation in multiple areas, right from record handling and data management to effective engagement and retention of valuable talent. In fact, this has opened new avenues to streamline multiple processes associated with on-site and remote employees for better business operations. A valuable AI Tool:
Boosts Org. Productivity & Ultimately Bottom Line | Provides Transparent Processes & Communications | Reduces Human Bias
Its Outcome
Corporates can listen to the employees’ feedback and analyze the pain areas, gauge the overall sentiments, and generate insights for Employee centric actions. This in turn leads to a reduction in attrition rate and boosts employee productivity.
2. Corporate Culture Co-relation
- A dataset of pre-defined trends was collected & a custom ML model was trained to identify the trend relations from employee responses.
- This model uses the classification technique developed using XLNet state-of-the-art language model (neural network).
- Generation of Training Data Set: An extensive exercise to manually label 50k records to train the Machine Learning model using the Supervised Learning approach.
- Advanced Text embedding & classification techniques were implemented to derive resulting trends. Also, multiple iterations with sets of labeled data were executed to achieve the desired accuracy.
Its Outcome
Corporates can flourish an interactive culture by actively looking upon trending culture drivers & acting upon employee’s feedback. This helps to establish a connection between the two and ensures a healthy & productive workplace environment.
Many other areas related to employee engagement such as smart feedback, retention, workplace culture, wellness were targeted to derive accurate AI-based predictions.
Salient Characteristics
- Multi-Label Classification
- Easy Integration: API Based Models
- Deep Learning Methods
- Data-Driven Decisions
- Scalable ML Models
- Cloud Architecture
