1. OPIM 204 – Aggregate Planning 1 Aggregate Planning OPIM 3104 Instructor: Jose Cruz

2. OPIM 204 – Aggregate Planning 2 Lecture Outline Aggregate Planning Process Strategies for Adjusting Capacity Strategies for Managing Demand Quantitative Techniques for Aggregate Production Planning Aggregate Planning for Services

3. OPIM 204 – Aggregate Planning 3 Aggregate Planning Determine the resource capacity needed to meet demand over an intermediate time horizon –Aggregate refers to product lines or families –Aggregate planning matches supply and demand Objectives –Establish a company wide game plan for allocating resources –Develop an economic strategy for meeting demand

4. OPIM 204 – Aggregate Planning 4 Aggregate Planning Process

5. OPIM 204 – Aggregate Planning 5 Meeting Demand Strategies Adjusting capacity –Resources necessary to meet demand are acquired and maintained over the time horizon of the plan –Minor variations in demand are handled with overtime or under-time Managing demand –Proactive demand management

6. OPIM 204 – Aggregate Planning 6 Strategies for Adjusting Capacity Level production –Producing at a constant rate and using inventory to absorb fluctuations in demand Chase demand –Hiring and firing workers to match demand Peak demand –Maintaining resources for high-demand levels Overtime and under-time –Increasing or decreasing working hours Subcontracting –Let outside companies complete the work Part-time workers –Hiring part time workers to complete the work Backordering –Providing the service or product at a later time period

7. OPIM 204 – Aggregate Planning 7 Level Production Demand Units Time Production

8. OPIM 204 – Aggregate Planning 8 Chase Demand Demand Units Time Production

9. OPIM 204 – Aggregate Planning 9 Strategies for Managing Demand Shifting demand into other time periods –Incentives –Sales promotions –Advertising campaigns Offering products or services with counter- cyclical demand patterns Partnering with suppliers to reduce information distortion along the supply chain

10. OPIM 204 – Aggregate Planning 10 Quantitative Techniques For APP Pure Strategies Mixed Strategies Linear Programming Transportation Method Other Quantitative Techniques

11. OPIM 204 – Aggregate Planning 11 Pure Strategies Hiring cost= $100 per worker Firing cost= $500 per worker Regular production cost per pound = $2.00 Regular production cost per pound = $2.00 Inventory carrying cost= $0.50 pound per quarter Inventory carrying cost= $0.50 pound per quarter Production per employee= 1,000 pounds per quarter Production per employee= 1,000 pounds per quarter Beginning work force= 100 workers Beginning work force= 100 workers QUARTERSALES FORECAST (LB) Spring80,000 Summer50,000 Fall120,000 Winter150,000 Example:

12. OPIM 204 – Aggregate Planning 12 Level Production Strategy Level production = 100,000 pounds (50,000 + 120,000 + 150,000 + 80,000) 4 Spring80,000100,00020,000 Summer50,000100,00070,000 Fall120,000100,00050,000 Winter150,000100,0000 400,000140,000 Cost of Level Production Strategy (400,000 X $2.00) + (140,00 X $.50) = $870,000 SALESPRODUCTION QUARTERFORECASTPLANINVENTORY

13. OPIM 204 – Aggregate Planning 13 Chase Demand Strategy Spring80,00080,00080020 Summer50,00050,00050030 Fall120,000120,000120700 Winter150,000150,000150300 10050 SALESPRODUCTIONWORKERSWORKERSWORKERS SALESPRODUCTIONWORKERSWORKERSWORKERS QUARTERFORECASTPLANNEEDEDHIREDFIRED Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

14. OPIM 204 – Aggregate Planning 14 Mixed Strategy Combination of Level Production and Chase Demand strategies Examples of management policies –no more than x% of the workforce can be laid off in one quarter –inventory levels cannot exceed x dollars Many industries may simply shut down manufacturing during the low demand season and schedule employee vacations during that time

15. OPIM 204 – Aggregate Planning 15 Aggregate Planning for Services 1.Most services can’t be inventoried 2.Demand for services is difficult to predict 3.Capacity is also difficult to predict 4.Service capacity must be provided at the appropriate place and time 5.Labor is usually the most constraining resource for services

16. OPIM 204 – Aggregate Planning 16 Yield Management

17. OPIM 204 – Aggregate Planning 17 Yield Management P( n < x )  C u C u + C o where n = number of no-shows x = number of rooms or seats overbooked C u = cost of underbooking; i.e., lost sale C o = cost of overbooking; i.e., replacement cost P= probability

18. OPIM 204 – Aggregate Planning 18 Yield Management (cont.)

19. OPIM 204 – Aggregate Planning 19 Yield Management: Example NO-SHOWSPROBABILITYP(N < X) 0.15.00 1.25.15 2.30.40 3.30.70 Optimal probability of no-shows P(n < x)  = =.517 C u C u + C o 75 75 + 70.517 Hotel should be overbooked by two rooms