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Operations Management Chapter 13 – Aggregate Planning PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 6e Operations Management, 8e © 2006 Prentice Hall, Inc Hall, Inc © 2006 Prentice 13 – Outline Global Company Profile: Anheuser-Busch The Planning Process The Nature Of Aggregate Planning Aggregate Planning Strategies Capacity Options Demand Options Mixing Options to Develop a Plan © 2006 Prentice Hall, Inc 13 – Outline – Continued Methods For Aggregate Planning Graphical and Charting Methods Mathematical Approaches to Planning Comparison of Aggregate Planning Methods © 2006 Prentice Hall, Inc 13 – Outline – Continued Aggregate Planning In Services Restaurants Hospital National Chains of Small Service Firms Miscellaneous Services Airline Industry Yield Management © 2006 Prentice Hall, Inc 13 – Learning Objectives When you complete this chapter, you should be able to: Identify or Define: Aggregate planning Tactical scheduling Graphic technique for aggregate planning Mathematical techniques for aggregate planning © 2006 Prentice Hall, Inc 13 – Learning Objectives When you complete this chapter, you should be able to: Describe or Explain: How to aggregate planning How service firms develop aggregate plans © 2006 Prentice Hall, Inc 13 – Anheuser-Busch Anheuser-Busch produces nearly 40% of the beer consumed in the U.S Matches fluctuating demand by brand to plant, labor, and inventory capacity to achieve high facility utilization High facility utilization requires Meticulous cleaning between batches Effective maintenance Efficient employees Efficient facility scheduling © 2006 Prentice Hall, Inc 13 – Aggregate Planning Determine the quantity and timing of production for the immediate future Objective is to minimize cost over the planning period by adjusting Production rates Labor levels Inventory levels Overtime work Subcontracting Other controllable variables © 2006 Prentice Hall, Inc 13 – Aggregate Planning Required for aggregate planning A logical overall unit for measuring sales and output A forecast of demand for intermediate planning period in these aggregate units A method for determining costs A model that combines forecasts and costs so that scheduling decisions can be made for the planning period © 2006 Prentice Hall, Inc 13 – The Planning Process Long-range plans (over one year) Research & Development New product plans Capital investment Facility location/expansion Top executives Operations managers Intermediate-range plans (3 to 18 months) Sales planning Production planning and budgeting Setting employment, inventory, subcontracting levels Analyzing cooperating plans Short-range plans (up to months) Operations managers, supervisors, foremen Responsibility © 2006 Prentice Hall, Inc Job assignments Ordering Job scheduling Dispatching Overtime Part-time help Planning tasks and horizon Figure 13.1 13 – 10 Transportation Example Important points Quantities in each column designate the levels of inventory needed to meet demand requirements In general, production should be allocated to the lowest cost cell available without exceeding unused capacity in the row or demand in the column © 2006 Prentice Hall, Inc 13 – 51 Transportation Example Table 13.7 © 2006 Prentice Hall, Inc 13 – 52 Management Coefficients Model Builds a model based on manager’s experience and performance A regression model is constructed to define the relationships between decision variables Objective is to remove inconsistencies in decision making © 2006 Prentice Hall, Inc 13 – 53 Other Models Linear Decision Rule Minimizes costs using quadratic cost curves Operates over a particular time period Simulation Uses a search procedure to try different combinations of variables Develops feasible but not necessarily optimal solutions © 2006 Prentice Hall, Inc 13 – 54 Summary of Aggregate Planning Methods Techniques Solution Approaches Important Aspects Graphical/charting methods Trial and error Simple to understand and easy to use Many solutions; one chosen may not be optimal Transportation method of linear programming Optimization LP software available; permits sensitivity analysis and new constraints; linear functions may not be realistic Management Heuristic coefficients model Simple, easy to implement; tries to mimic manager’s decision process; uses regression Table 13.8 © 2006 Prentice Hall, Inc 13 – 55 Aggregate Planning in Services Controlling the cost of labor is critical Close scheduling of labor-hours to assure quick response to customer demand Some form of on-call labor resource Flexibility of individual worker skills Individual worker flexibility in rate of output or hours © 2006 Prentice Hall, Inc 13 – 56 Five Service Scenarios Restaurants Smoothing the production process Determining the workforce size Hospitals Responding to patient demand © 2006 Prentice Hall, Inc 13 – 57 Five Service Scenarios National chains of small service firms Planning done at national level and at local level Miscellaneous services Plan human resource requirements Manage demand © 2006 Prentice Hall, Inc 13 – 58 Law Firm Example (1) Category of Legal Business (2) Best Case (hours) (3) Likely Case (hours) Trial work Legal research Corporate law Real estate law Criminal law 1,800 4,500 8,000 1,700 3,500 1,500 4,000 7,000 1,500 3,000 1,200 3,500 6,500 1,300 2,500 19,500 39 17,000 34 15,000 30 Total hours Lawyers needed (4) Worst Case (hours) (5) Maximum Demand in People (6) Number of Qualified Personnel 3.6 9.0 16.0 3.4 7.0 32 15 12 Table 13.9 © 2006 Prentice Hall, Inc 13 – 59 Five Service Scenarios Airline industry Extremely complex planning problem Involves number of flights, number of passengers, air and ground personnel Resources spread through the entire system © 2006 Prentice Hall, Inc 13 – 60 Yield Management Allocating resources to customers at prices that will maximize yield or revenue Service or product can be sold in advance of consumption Demand fluctuates Capacity is relatively fixed Demand can be segmented Variable costs are low and fixed costs are high © 2006 Prentice Hall, Inc 13 – 61 Yield Management Example Room sales Demand Curve Potential customers exist who are willing to pay more than the $15 variable cost of the room 100 Passed-up contribution 50 $ margin = (Price) x (50 rooms) = ($150 $15) x (50) = $6,750 $15 Variable cost of room © 2006 Prentice Hall, Inc Some customers who paid $150 were actually willing to pay more for the room Money left on the table $150 Price charged for room Price Figure 13.5 13 – 62 Yield Management Example Demand Curve Room sales 100 Total $ margin = (1st price) x 30 rooms + (2nd price) x 30 rooms = ($100 - $15) x 30 + ($200 - $15) x 30 = $2,550 + $5,550 = $8,100 60 30 © 2006 Prentice Hall, Inc $15 Variable cost of room $100 Price for room $200 Price for room Price Figure 13.6 13 – 63 Yield Management Matrix Predictable Unpredictable Duration of use Price Tend to be fixed Tend to be variable Quadrant 1: Quadrant 2: Movies Stadiums/arenas Convention centers Hotel meeting space Hotels Airlines Rental cars Cruise lines Quadrant 3: Quadrant 4: Restaurants Golf courses Internet service providers Continuing care hospitals Figure 13.7 © 2006 Prentice Hall, Inc 13 – 64 Making Yield Management Work Multiple pricing structures must be feasible and appear logical to the customer Forecasts of the use and duration of use Changes in demand © 2006 Prentice Hall, Inc 13 – 65 ... Hospital National Chains of Small Service Firms Miscellaneous Services Airline Industry Yield Management © 2006 Prentice Hall, Inc 13 – Learning Objectives When you complete this chapter, you... Research & Development New product plans Capital investment Facility location/expansion Top executives Operations managers Intermediate-range plans (3 to 18 months) Sales planning Production planning... employment, inventory, subcontracting levels Analyzing cooperating plans Short-range plans (up to months) Operations managers, supervisors, foremen Responsibility © 2006 Prentice Hall, Inc Job assignments
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