Description:
This program is designed to equip production and operations professionals with the skills to analyze, interpret, and optimize production data to improve efficiency, reduce costs, and support strategic decision-making. Participants learn to apply data analytics, visualization tools, and predictive modeling to monitor production processes, manage resources, and enhance overall operational performance.

Learning Objectives:

By the end of the program, participants will be able to:

• Understand the role of data analytics in production and operations management
• Collect, clean, and process production and operations data
• Apply statistical and analytical methods to identify trends, bottlenecks, and inefficiencies
• Develop dashboards and reports to communicate insights effectively
• Use predictive analytics to forecast production requirements and optimize workflows
• Identify opportunities for cost reduction, process improvement, and resource optimization
• Ensure accurate data-driven decision-making in production planning and execution
• Integrate analytics into Lean Manufacturing, Six Sigma, and quality improvement initiatives

Target Audience:

• Production Managers
• Operations Managers
• Production Planners and Coordinators
• Manufacturing Analysts
• Process Improvement Specialists
• Supply Chain Analysts
• Quality Assurance Professionals

Training Contents:

Module 1: Introduction to Production Management Analytics

• Overview of production management functions
• Importance of data-driven decision-making in manufacturing
• Key performance indicators (KPIs) for production efficiency

Module 2: Data Collection and Management

• Identifying relevant production and operations data sources (ERP, MES, SCADA)
• Data cleaning, validation, and preprocessing
• Integration of production data from multiple systems

Module 3: Descriptive and Diagnostic Analytics

• Production trend analysis and variance tracking
• Root cause analysis of bottlenecks and downtime
• Analysis of cycle times, machine utilization, and yield

Module 4: Predictive Analytics in Production Management

• Forecasting production demand
• Predictive maintenance and downtime prevention
• Material requirement and capacity planning using predictive models

Module 5: Prescriptive Analytics and Optimization

• Production scheduling and workflow optimization
• Resource allocation and workforce planning
• Inventory optimization and cost containment strategies

Module 6: Visualization and Reporting

• Creating dashboards and visual reports for production KPIs
• Using BI tools (Power BI, Tableau, Qlik) for operational insights
• Communicating data-driven recommendations to management

Module 7: Advanced Analytics Applications

• Lean Manufacturing and Six Sigma analytics
• Process improvement through data-driven insights
• Energy, waste, and sustainability analytics in production

Module 8: Case Studies and Hands-On Projects

• Analyzing production datasets to identify inefficiencies
• Simulation of production planning and scheduling scenarios
• Capstone project: optimizing production metrics using data analytics

Training Delivery Methods:

• Instructor-led lectures
• Hands-on exercises with real production datasets
• Group discussions and problem-solving workshops
• Case studies and scenario-based exercises
• Assessments, quizzes, and final project

Duration:

• 3–5 days (24–40 hours) depending on depth and practical exercises

Certification:

• Certified Production Management Data Analyst (CPMDA)
• Optional alignment with APICS CPIM, Six Sigma, or Lean Manufacturing credentials