Aggregate Planning & Scheduling: Strategies, Models & Real-World Applications

Core Concepts

What is Aggregate Planning?

Aggregate planning determines total production levels (or service capacity) over a planning horizon to meet forecasted demand while minimizing costs. Unlike short-term scheduling, it focuses on workforce levels, inventory, overtime, subcontracting, and backorders—not individual products.

graph TD
    A["Aggregate Planning Inputs"] --> B["Demand Forecast"]
    A --> C["Production Capacity"]
    A --> D["Costs: Labor, Inventory, Overtime, etc."]
    A --> E["Constraints: Union rules, lead times"]
    A --> F["Strategic Goals: Profit, market share"]
    F --> G["Output: Production Plan"]
    G --> H["Workforce Levels"]
    G --> I["Inventory Policy"]
    G --> J["Subcontracting Needs"]

Key Idea: Aggregate planning answers:

• How many units to produce each month?
• How many workers to hire/fire?
• When to use overtime or subcontractors?

In the Real World

1. eSewa (Nepal) uses aggregate planning to balance call-center staffing with seasonal demand spikes (e.g., Dashain/Tihar). Their workforce levels rise 30% during festivals, with temporary hires trained in advance.
2. Nabil Bank applies aggregate planning to loan approval scheduling: During monsoon (low demand), they hire temporary loan officers; in winter (peak season), they use overtime for existing staff.
3. Daraz (Alibaba Group) leverages inventory aggregation to stock best-selling items (e.g., mobile phones) in central warehouses, then uses local hubs for last-mile delivery—reducing stockouts by 40%.

Aggregate Planning Strategies

Worked Example: Nabil Bank’s Loan Processing

Scenario: Nabil Bank expects loan applications to rise by 25% in winter (Nov–Feb) due to agricultural season needs. Current staff: 50 loan officers (8-hour shifts). Processing rate: 10 loans/officer/month. Winter demand: 6,500 loans.

Step 1: Calculate Current Capacity

• Baseline capacity: 50 officers × 10 loans = 5,000 loans/month.
• Winter demand: 6,500 loans → Shortfall of 1,500 loans.

Step 2: Strategy Options

Optimal Choice: Hybrid of part-time hires (10 officers) + overtime (for 5 officers).

• Cost: $1,200 (part-time) + $3,000 (overtime) = $4,200.
• Alternative: Subcontracting would cost $450,000—100x more expensive.

Aggregate Planning Techniques

1. Graphical Method

• Plot demand vs. capacity over time.
• Adjust workforce/inventory to minimize cost.
• Best for: Small businesses (e.g., a Kathmandu-based bakery planning Diwali orders).

graph LR
    A["Time (Months)"] --> B["Jan"] --> C["Feb"] --> D["Mar"]
    B -->|"Demand"| E["500 units"]
    C -->|"Demand"| F["800 units"]
    D -->|"Demand"| G["600 units"]
    B -->|"Capacity"| H["400 units"]
    C -->|"Capacity"| I["700 units"]
    D -->|"Capacity"| J["500 units"]
    H -->|"Gap"| K["Hire 10 workers"]

2. Mathematical Models

• Linear Programming: Minimize costs subject to constraints (e.g., max overtime hours).
• Simulation: Model scenarios (e.g., "What if 20% of workers call in sick?").
• Used by: NTC for network maintenance scheduling during monsoon.

3. Heuristic Methods

• Rule-based approaches (e.g., "Always hire if demand > capacity by 15%").
• Example: Daraz’s "peak-season hiring rule" for Diwali sales.

Scheduling: From Aggregate to Detailed Plans

After aggregate planning, scheduling assigns tasks to specific time slots, machines, or workers.

Key Scheduling Techniques

Case Study: Toyota’s Lean Aggregate Planning

Challenge: Toyota faces seasonal demand swings (e.g., 30% higher sales in summer due to road trips). Solution:

1. Level Production: Maintain constant output; use inventory buffers (e.g., stockpile tires in spring).
2. Just-in-Time (JIT) Scheduling: Deliver parts only when needed (reduces waste).
3. Flexible Workforce: Cross-trained workers switch between models (e.g., Corolla → Hilux). Result:

• Inventory costs ↓ by 40%.
• Customer wait times ↓ by 50% during peak seasons.

mindmap
  root((Toyota’s Aggregate Planning))
    Level Production
      Constant Output
      Inventory Buffers
    JIT Scheduling
      Supplier Coordination
      Kanban System
    Flexible Workforce
      Cross-Training
      Overtime Management
    Outcome
      Cost Savings
      Customer Satisfaction

Exam Tip

1. Define Clearly: Start answers with:
   • "Aggregate planning is a medium-term decision-making process that balances supply and demand by adjusting workforce levels, inventory, and subcontracting to minimize costs while meeting customer requirements."
2. Use Formulas: Memorize the aggregate planning cost model: $$\text{Total Cost}=C_w\times W+C_i\times I+C_o\times O+C_s\times S$$ Where:
   • $C_w$ = Workforce cost, $W$ = Number of workers
   • $C_i$ = Inventory holding cost, $I$ = Inventory level
   • $C_o$ = Overtime cost, $O$ = Overtime hours
   • $C_s$ = Subcontracting cost, $S$ = Subcontracted units
3. Compare Strategies: Exams often ask to contrast chase vs. level strategies—use the table above.
4. Real-World Links: Always tie answers to Nepalese examples (e.g., NTC, banks, Daraz) for full marks.
5. Diagrams: Draw Gantt charts or simple graphs to illustrate scheduling trade-offs.