Employee Morale Survey | Employee Satisfaction Survey - TraceData Research
Client Overview
Our client is a leading automotive parts manufacturer based in India. They operate four large scale production units, employing 5000+ workers. The business is globally recognised for delivering precision engineered components top-tier automobile OEMs across Asia and Europe. Despite strong process automation, the business was facing inconsistent productivity across shifts, particularly during night operations and rotational duties.
Challenges They Faced
The client faced several persistent people-related challenges that affected shift productivity and overall plant efficiency. The key challenges they faced are-
An increase in unplanned leaves and late arrivals, especially during weekends and rotational schedules, disrupted workflow planning and output targets.
20–25% drop in productivity was regularly observed during night and rotational shifts compared to day shifts.
Supervisors and HR lacked real-time insight into employee mindset, burnout indicators, or team sentiment shifts.
Many team leaders lacked training in people management, resulting in communication gaps and ineffective resolution of minor workplace conflicts.
Learn How Other Sector’s Unveiling Workplace Insights with Tracedata’s Employee Engagement Survey
Our Approach
To address the productivity challenges, TraceData implemented 90-days people analytics program across four manufacturing facilities. Our program was a blended shift-specific employee engagement surveys, behavioural analytics, and supervisor mapping.
Here’s how we executed the program-
Shift-Specific Engagement Surveys: We created customised survey for day, night, and rotational shifts focusing on job satisfaction, workplace fatigue, superior interaction quality, and more. This helped us in identifying shift-based sentiment disparities.
AI-Based Sentiment and Stress Analysis: Using analytics engine, we scanned over thousand qualitative responses to highlight burnout markers, emotional tone shifts, micro-conflict indicators, and key phrases signalling disengagement. This helped us in identifying hidden emotional stressors, especially in night shifts and certain departments.
Survey Findings: The key survey findings include-
37% increase in shift productivity where engagement initiatives were piloted.
28% reduction in unplanned absenteeism in rotational shifts.
35% lower burnout scores in departments with supportive supervisors.
Low-engagement teams had 2x the error rate compared to high-engagement teams.
Productivity Correlation Modelling: We overlaid sentiment scores with operational KPIs like output per hour, error frequency, downtime and absenteeism. This model clearly showed that high morale teams were 29% more productive and had 35% lower rework rates.
Dashboard Deployment and Benchmarking: We deployed live dashboards to enable shift-wise morale tracking, daily absenteeism alerts, supervisor-level team insights, and benchmarking between units. This dashboard served as a real-time command centre for HR and plant heads to take data-backed decisions.
Outcomes
Our 90 days employee analytics initiative delivered transforming results across all manufacturing units. TraceData’s shift-specific engagement diagnostics and real-time dashboards helped client in taking data-backed actions. The key outcomes were-
Shift productivity increased by 37% within two quarters, driven by improved morale, team dynamics, and optimized supervisor engagement.
Unplanned absenteeism dropped by 28%, particularly in rotational shifts where employee feedback was most critical.
Error rates fell by 22% due to higher emotional investment from workers and clearer communication structures.
Employee satisfaction score rose by 41%, based on follow-up pulse surveys conducted post-intervention.
Client Testimonials
“Before partnering with TraceData, we relied heavily on gut feeling to assess workforce issues. The level of data-backed insight they brought in was eye-opening. Their approach did not just identify problems—it gave us a roadmap to solve them.”
— Head of Operations, East Zone Plant
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TraceData Research
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