Strongbond Philippines Inc.

Transforming Hiring and Reducing Churn with Voice Analytics

HR use case
0 churn
within the first 3 months
100%
retention
Cost reduction
Significant decrease in hiring expenses
Module used: Voice analysis
Location: Philippines
Industry: Construction
Challenge
Strongbond Philippines Inc., a leading construction and retrofitting company based in the Philippines, faced significant workforce management challenges due to the seasonal nature of their projects. Each new project required the company to hire a large number of workers for construction sites, leading to several critical issues:

1. High Employee Churn

An alarming churn rate of 25-30% weekly caused constant operational disruptions.


2. Escalating Costs

Continuous hiring and training led to soaring costs, straining the company’s finances.


3. Workflow Disruptions

Frequent employee turnover disrupted workflows, reduced productivity, and impacted project timelines and quality.


4. Seasonal Fluctuations

Workforce requirements varied significantly with each project, making it difficult to maintain stability

Recognising these urgent issues, Strongbond Philippines approached InsightGenie to explore innovative solutions, particularly voice analytics technology, to identify candidates less likely to churn and improve workforce stability and operational efficiency.
Solution
InsightGenie proposed a novel approach using voice analytics technology to uncover behavioural tendencies indicative of a candidate's likelihood to remain with the company. The solution comprised several key components:

1. Voice Analysis

Collected and analysed voice samples from Strongbond's top-performing employees with the lowest churn rates to identify speech patterns associated with valued behavioural tendencies.


2. Tailored Assessment Dashboard
Created a customised dashboard assessing key indicators including temperament, integrity, systematic approach, communication skills, cooperation, job role fit, conscientiousness, and emotional stability.


3. Self-Serve Interview Platform
Developed a website where potential candidates could sign up for interviews, respond to questions, and have their voices recorded for analysis.


4. Automated Candidate Assessment
Utilised InsightGenie's voice analytics technology to analyse the recordings and provide insights into each candidate's behavioural tendencies and potential fit.
Result
The implementation of InsightGenie's voice analytics solution yielded significant results for Strongbond Philippines:

1) Improved Hiring Accuracy

Out of 44 candidates assessed, 94 were hired based on the voice analytics insights. Notably, none of these new hires churned within the first three months of employment.


2) Reduced Churn Rate

The company experienced a dramatic reduction in employee churn, leading to greater workforce stability.


3) Cost Savings

Lower churn rates resulted in reduced hiring and training costs.


4) Enhanced Project Efficiency

With a more stable workforce, Strongbond saw improvements in project timelines and overall efficiency.


5) Data-Driven Decision Making

The solution provided Strongbond with data-driven insights to support their hiring decisions.

This case study demonstrates the potential of voice analytics technology as a transformative solution for organisations seeking to enhance their hiring processes and reduce employee turnover, particularly in industries with high seasonal workforce fluctuations.
ABOUT THE CLIENT
Strongbond Philippines Inc. provides the nation with top-of-the-line structural retrofitting contractor services. Heavily focused on enhancing the safety and longevity of buildings and general infrastructure, they offer a range of solutions, including carbon fiber reinforcement, epoxy injection, and waterproofing. Based in Mandaluyong, the company aims to address structural deficiencies, improve the integrity of infrastructure, and “build a first-world Philippines for the Filipino people.”
0 churn
within the first 3 months
100%
Retention
Cost Reduction
Significant decrease in hiring expenses
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