Top Responsibilities:
Position summary
Reporting directly to the head of operations, the process excellence analyst is responsible for enhancing operational efficiency and customer experience by analyzing data-driven processes, designing capacity plans, developing actionable operation scorecards and implementing process excellence program. Ensuring alignment with organizational objectives while fostering a culture of continuous improvement and operational efficiency. This role combines critical thinking, analytical expertise, and process optimization skills to improve workflows and drive organizational success
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Process Excellence & Optimization:
Map and document processes, identifying inefficiencies and areas for improvement.
Lead process improvement initiatives using Lean, Six Sigma, and Agile methodologies.
Collaborate with operations and IT teams to automate manual processes.
Monitor and analyze performance data to track KPIs and ensure continuous improvement.
Facilitate workshops and training to promote best practices and a culture of continuous improvement.
Align process changes with strategic objectives and compliance requirements.
Data Analysis & Process Improvement:
Conduct comprehensive process analysis and root cause investigations.
Develop data-driven models to simulate process improvements and measure ROI.
Build dashboards and visualizations using tools like Power BI and Tableau to present insights.
Operational Scorecards & Performance Tracking:
Implement and maintain scorecards to monitor KPIs and align performance with business goals.
Regularly review data, identify trends, and recommend corrective actions.
Present operational insights and ensure alignment in decision-making processes.
Business Analysis:
Gather business requirements, conduct gap analyses, and recommend system or process enhancements.
Design and implement tools to support operational improvements.
Staffing Models & Capacity Planning:
Analyze workforce data to develop staffing models and capacity plans.
Use predictive analytics to forecast future resource needs.
Design scalable models that align with business demands and flexibility for varying workloads.
Train managers on using models effectively and adjust based on feedback and performance data.