• About
  • Key Challenges
  • Our Approach
  • Technology
  • Key Results

About Project

The IT industry has a high attrition rate, a grave concern for companies that foster talent and face losses in human resources and domain expertise. The annual attrition rate in the tech sector stands at a whopping 15%, and it isn’t lowering anytime soon. Brainvire created a predictive data science service that IT companies can leverage to retain employees, thereby reducing attrition rates in the industry.

  • IT Sector

    Business

  • South Asia

    Location

Business Goal 

We streamlined a robust machine-learning solution model in workforce planning to help businesses predict employee attrition. The predictive AI-driven model will employ cutting-edge machine learning algorithms to predict attrition with high accuracy based on data analysis.

Project Highlights

Portfolio

Key Challenges and Solution

Strategizing A Predictive Model

Our Brainers faced a dilemma while creating a model that predicted high attrition while assessing the risks simultaneously.

Streamlined a Comprehensive AI-Powered Model

Brainvire’s team implemented various strategies, including conducting exit interviews, environmental management, career development programs, recognition awards, monitoring progress, and more. Considering several factors, we enhanced the possibility of an employee attrition solution.

Security Risk

Ensuring the privacy and confidentiality of employee data collected during the exit interviews and surveys while still extracting meaningful insights.

Enabled Automation to Lower Security Risk

Brainvire implemented an automated process to clean and integrate data from exit interviews, surveys, and other sources. The process also identifies and corrects errors, fills in missing values, and more. Our efforts resulted in a lower risk ratio and enhanced the security of the predictive model.

Limited Data

We faced difficulty obtaining employee engagement data crucial for understanding attrition drivers.

Implemented Regular Pulse Surveys

The Brainvire team streamlined regular pulse surveys to gather continuous feedback on employee engagement and satisfaction levels, which provided valuable input on improving the AI-enabled employee attrition model.

Lack of Predictive Analytics

Brainers faced some difficulty in predicting attrition patterns and identifying high-risk employees.

Enabled a Predictive Analytics Model

Brainvire developed predictive analytics models using historical data to forecast attrition and identify employees at higher risk of leaving the organization.

Our Approach

Brainvire’s streamlined model will provide custom attrition solutions and actionable steps tailored to business needs by giving real-time insights.

Initiation

Initiation

Defining clear project goals, aligning the team for the project, and establishing a timeline for the model.
Stakeholder-Engagement

Stakeholder-Engagement

Engaged all the stakeholders, including HR, managers, and leadership, to understand organizational challenges.
Monitoring

Monitoring

Developing the model required continuous monitoring and evaluation.
Long-term Sustainability

Long-term Sustainability

Ensured sustainability of strategies for lasting reduction in attrition rates

Technology Stack

Front-end Tech

HTML

HTML

CSS 3

CSS 3

ReactJs

ReactJs

Back-end Tech

HTML

HTML

CSS 3

CSS 3

ReactJs

ReactJs

Server

HTML

HTML

CSS 3

CSS 3

ReactJs

ReactJs

Management Tools

HTML

HTML

CSS 3

CSS 3

ReactJs

ReactJs

Emerging Tech

HTML

HTML

CSS 3

CSS 3

ReactJs

ReactJs

Key Achievements

  • Improved Employee Satisfaction

    Implementing targeted retention strategies led to a noticeable decrease in employee turnover rates.

  • Increased Retention Rates

    Identifying at-risk employees through predictive models allowed for personalized interventions, resulting in higher retention rates.

  • Data-Driven Decision Making

    Adopting data-driven approaches enabled HR and management to make informed decisions regarding employee retention strategies.

  • Increased ROI

    The project demonstrated a measurable return on investment (ROI) by reducing turnover costs and improving employee satisfaction.

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Retain Your Finest Talent with Us

Retain Your Finest Talent with Us

By streamlining AI-powered predictive models, you can reduce your turnover costs, improve productivity, and retain talent. Contact us

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