Subject Overview

Aggregate Production Planning examines medium-term decisions that balance demand, production capacity, workforce, inventory, backorders and sourcing across products or product families. The subject integrates classical planning models with sales and operations planning, optimization, risk analytics, digital technologies, sustainability and managerial governance.

Learning Goal

Students will be able to design, optimize, evaluate and govern aggregate production plans; integrate them with organizational planning systems; and make strategic, data-driven decisions under capacity, cost, service, sustainability and uncertainty constraints.

Syllabus

1. Foundations of Aggregate Production Planning

Learning Objective: Explain the purpose, scope, planning horizon, decision variables, performance measures and terminology of aggregate planning within operations strategy and hierarchical production planning.

Category: foundation

2. Demand, Capacity and Planning Data

Learning Objective: Translate forecasts and orders into aggregate demand; assess capacity, productivity, utilization and resource constraints; and prepare consistent planning data by product family, period and facility.

Category: foundation

3. Aggregate Planning Costs and Trade-offs

Learning Objective: Model regular-time production, overtime, hiring, layoffs, inventory, shortages, backorders, subcontracting, idle capacity and changeover costs while evaluating cost, service and workforce trade-offs.

Category: core

4. Classical Aggregate Planning Strategies

Learning Objective: Compare level, chase and mixed strategies and determine their operational, financial, customer-service and human-resource implications using graphical and tabular methods.

Category: core

5. Mathematical Optimization Models

Learning Objective: Formulate and solve aggregate plans using linear programming, transportation models, mixed-integer programming and goal programming, including objectives, constraints, feasibility and sensitivity analysis.

Category: core

6. Workforce and Capacity Planning

Learning Objective: Develop workforce and capacity policies covering staffing, shifts, overtime, flexible labor, learning effects, equipment availability, subcontracting and capacity expansion or reduction.

Category: application

7. Inventory, Backlog and Service-Level Decisions

Learning Objective: Integrate inventory buffers, safety stock, backorders, lost sales and service targets into aggregate plans and evaluate their effects on working capital and customer experience.

Category: core

8. Planning Under Uncertainty and Risk

Learning Objective: Use scenario analysis, rolling horizons, simulation, stochastic and robust optimization, sensitivity analysis and contingency planning to manage uncertain demand, supply, lead times and costs.

Category: advanced

9. Sales and Operations Planning and Integrated Business Planning

Learning Objective: Design the S&OP/IBP cycle, including demand review, supply review, reconciliation, executive decision-making, financial integration, accountability and cross-functional conflict resolution.

Category: strategic

10. Hierarchical Planning and Execution Integration

Learning Objective: Disaggregate aggregate plans into master production schedules and connect them with MRP, capacity requirements planning, scheduling, procurement, distribution and shop-floor execution.

Category: application

11. Aggregate Planning in Services and Diverse Operating Environments

Learning Objective: Adapt planning models to services, process and discrete manufacturing, seasonal operations, project-based settings and perishable or high-variety products using suitable capacity and demand levers.

Category: application

12. Multi-Site, Supply Chain and Sustainable Planning

Learning Objective: Coordinate production, sourcing, logistics and capacity across facilities and partners while incorporating resilience, carbon emissions, energy use, circularity and social sustainability constraints.

Category: strategic

13. Digital Planning, Advanced Analytics and AI

Learning Objective: Evaluate ERP, advanced planning systems, cloud platforms, digital twins, predictive analytics and AI-assisted optimization; address data quality, explainability, cybersecurity, human oversight and model risk.

Category: contemporary

14. Implementation, Governance and Emerging Directions

Learning Objective: Lead aggregate-planning implementation through KPIs, dashboards, decision rights, audit controls, ethics, workforce fairness and change management; assess autonomous planning, real-time sensing and future resilient planning systems.

Category: contemporary