Introduction
In pharma production, seconds really do count, because in every tablet, vial, or capsule lies a strict quality assurance (QA) process intended to safeguard patients and meet regulatory requirements. But what if the same dedication to accuracy and control could be applied to the operational end of QA? That challenge and opportunity, drove a top pharmaceutical solutions company to Production Modeling India (PMI).
This case study examines how a targeted industrial engineering intervention assisted the client in revealing latent inefficiencies in their QA department and set the stage for more intelligent resource planning, leaner operations, and greater productivity without sacrificing compliance.
Client Profile and Project Background
• Increase productivity in QA operations
• Remove wasteful and non-value-added (NVA) activities
• Optimize use of human resources
• Establish a repeatable model for
Improvement that would be scalable throughout the larger QA organization. This wasn't merely about reducing cost, it was about building a more agile, efficient, and scalable QA platform aligned to the client's broader innovation ecosystem.
Maximizing Efficiency in Pharma Industry through Industrial Engineering Study
Challenges in Mind
• Repetitive and fragmented tasks.
• Limited visibility into where time was being lost.
• Inconsistent skill deployment and task overlaps.
• Underutilization of capable personnel during non-peak periods.
Given the department’s criticality to pharmaceutical safety and timelines, any inefficiency had a direct impact on both compliance and cost. A detailed study was needed to understand the inner workings of QA beyond what standard performance metrics could reveal.
PMI’s Structured Approach
PMI structured the interaction in a clean three-phase model that aimed to capture the nuances of knowledge-intensive, highly regulated work contexts:
Data Collection
Through virtual interactions and structured templates, PMI performed extensive interviews and task deconstruction:
• Interviewed 25% of QA associates.
• Conducted time-motion studies with 14% of QA associates.
Collected video-based and observational data across several QA functions, with an emphasis on Chemical Development and Formulations as proof of concept.
Data Analysis and Estimation
By applying a mix of time study methodology, Lean principles, and independent vs. combined input analysis, PMI was able to:
• Recognize 36% loss of productivity in terms of time.
• Categorize this loss into seven categories of Lean waste, ranging from over-processing to unnecessary motion.
• Develop a skill matrix to facilitate associate multi-skilling.
• Recommend a redesigned organogram to link manpower more effectively with workload.
Results and Conclusion
The results were both tangible and profound:
• 36% of time can be saved through lean activities.
• 9% headcount reduction possible through improved task alignment.
• Multiskilling initiative introduced with flexible deployment of workforce during peak or critical times.
• Updated organogram and workforce allocation plan communicated to the leadership.
• 40 actionable Kaizen ideas generated for short-term implementation.
Strategic Impact and Next Steps
The study gave not only numbers, but a blueprint. PMI was able to guide the client to understand how operational effectiveness could be infused into the DNA of a department that is historically risk mitigation and documentation oriented. With a refocused design and smarter utilization of seasoned QA professionals, the client is now able to:
- Scale the gains to other QA activities in disparate organizational units (OUs)
- Keep on driving lean change in a controlled and sustainable fashion
- Improve agility without jeopardizing regulatory compliance and product quality
The subsequent stage will be stabilizing change and propelling delivery by the noted 40 Kaizen actions, with ongoing tracking of manpower indicators to updated benchmarks.
Conclusion
This case study reaffirms a compelling concept: in fields where accuracy is not an option, operational excellence has to be as good as technical excellence. Through the application of industrial engineering techniques in a heavily regulated QA setting, PMI enabled the client to realize new degrees of productivity, flexibility, and control—reshaping quality assurance as a cost driver into a performance catalyst for the pharma future.
Particularly, Station 5C-010's material handling robot was found to be a chronic bottleneck, having the highest utilization and lowest availability in Zone 1. The other bottlenecks were 5C-030 and 5C-200, suggesting an upstream clustering of performance limitations. Line efficiency was computed at 93.4%, while machine availability throughout zones varied between 97% and almost 100%. The analysis also validated that the proposed buffers between downtime areas were adequate under existing operational conditions, avoiding cascading delays and preserving continuity of flow.