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 Haery

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 Haery

Aggregate Planning Figure 13.2 Haery Product decisions Marketplace and demand Research and technology Product decisions Process planning and capacity decisions Aggregate plan for production Demand forecasts, orders Raw materials available External capacity (subcontractors) Workforce Inventory on hand Master production schedule and MRP systems Detailed work schedules Figure 13.2 Haery

Aggregate Planning Combines appropriate resources into general terms Part of a larger production planning system Disaggregation breaks the plan down into greater detail Disaggregation results in a master production schedule Haery

Aggregate Planning Strategies Use inventories to absorb changes in demand Accommodate changes by varying workforce size Use part-timers, overtime, or idle time to absorb changes Use subcontractors and maintain a stable workforce Change prices or other factors to influence demand Haery

Capacity Options Changing inventory levels Increase inventory in low demand periods to meet high demand in the future Increases costs associated with storage, insurance, handling, obsolescence, and capital investment Shortages can mean lost sales due to long lead times and poor customer service Haery

Capacity Options Varying workforce size by hiring or layoffs Match production rate to demand Training and separation costs for hiring and laying off workers New workers may have lower productivity Laying off workers may lower morale and productivity Haery

Capacity Options Varying production rate through overtime or idle time Allows constant workforce May be difficult to meet large increases in demand Overtime can be costly and may drive down productivity Absorbing idle time may be difficult Haery

Capacity Options Subcontracting Temporary measure during periods of peak demand May be costly Assuring quality and timely delivery may be difficult Exposes your customers to a possible competitor Haery

Capacity Options Using part-time workers Useful for filling unskilled or low skilled positions, especially in services Haery

Demand Options Influencing demand Use advertising or promotion to increase demand in low periods Attempt to shift demand to slow periods May not be sufficient to balance demand and capacity Haery

Demand Options Back ordering during high- demand periods Requires customers to wait for an order without loss of goodwill or the order Most effective when there are few if any substitutes for the product or service Often results in lost sales Haery

Demand Options Counterseasonal product and service mixing Develop a product mix of counterseasonal items May lead to products or services outside the company’s areas of expertise Haery

Aggregate Planning Options Advantages Disadvantages Some Comments Changing inventory levels Changes in human resources are gradual or none; no abrupt production changes Inventory holding cost may increase. Shortages may result in lost sales. Applies mainly to production, not service, operations Varying workforce size by hiring or layoffs Avoids the costs of other alternatives Hiring, layoff, and training costs may be significant Used where size of labor pool is large Haery

Aggregate Planning Options Advantages Disadvantages Some Comments Varying production rates through overtime or idle time Matches seasonal fluctuations without hiring/ training costs Overtime premiums; tired workers; may not meet demand Allows flexibility within the aggregate plan Sub-contracting Permits flexibility and smoothing of the firm’s output Loss of quality control; reduced profits; loss of future business Applies mainly in production settings Haery

Aggregate Planning Options Advantages Disadvantages Some Comments Using part-time workers Is less costly and more flexible than full-time workers High turnover/ training costs; quality suffers; scheduling difficult Good for unskilled jobs in areas with large temporary labor pools Influencing demand Tries to use excess capacity. Discounts draw new customers. Uncertainty in demand. Hard to match demand to supply exactly. Creates marketing ideas. Overbooking used in some businesses. Haery

Aggregate Planning Options Advantages Disadvantages Some Comments Back ordering during high-demand periods May avoid overtime. Keeps capacity constant. Customer must be willing to wait, but goodwill is lost. Allows flexibility within the aggregate plan Counter-seasonal product and service mixing Fully utilizes resources; allows stable workforce May require skills or equipment outside the firm’s areas of expertise Risky finding products or services with opposite demand patterns Haery

Quantitative Techniques For APP Pure Strategies Mixed Strategies Linear Programming Transportation Method Other Quantitative Techniques Haery

Pure Strategies Example: QUARTER SALES FORECAST (LB) Spring 80,000 Summer 50,000 Fall 120,000 Winter 150,000 Hiring cost = $100 per worker Firing cost = $500 per worker Regular production cost per pound = $2.00 Inventory carrying cost = $0.50 pound per quarter Production per employee = 1,000 pounds per quarter Beginning work force = 100 workers

Level Production Strategy = 100,000 pounds (50,000 + 120,000 + 150,000 + 80,000) 4 Spring 80,000 100,000 20,000 Summer 50,000 100,000 70,000 Fall 120,000 100,000 50,000 Winter 150,000 100,000 0 400,000 140,000 Cost of Level Production Strategy (400,000 X $2.00) + (140,00 X $.50) = $870,000 SALES PRODUCTION QUARTER FORECAST PLAN INVENTORY

Chase Demand Strategy Cost of Chase Demand Strategy SALES PRODUCTION WORKERS WORKERS WORKERS QUARTER FORECAST PLAN NEEDED HIRED FIRED Spring 80,000 80,000 80 0 20 Summer 50,000 50,000 50 0 30 Fall 120,000 120,000 120 70 0 Winter 150,000 150,000 150 30 0 100 50 Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

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

Mixing Options to Develop a Plan Chase strategy Match output rates to demand forecast for each period Vary workforce levels or vary production rate Favored by many service organizations Haery

Mixing Options to Develop a Plan Level strategy Daily production is uniform Use inventory or idle time as buffer Stable production leads to better quality and productivity Some combination of capacity options, a mixed strategy, might be the best solution Haery

Graphical and Charting Methods Popular techniques Easy to understand and use Trial-and-error approaches that do not guarantee an optimal solution Require only limited computations Haery

Graphical and Charting Methods Determine the demand for each period Determine the capacity for regular time, overtime, and subcontracting each period Find labor costs, hiring and layoff costs, and inventory holding costs Consider company policy on workers and stock levels Develop alternative plans and examine their total costs Haery

Number of production days Planning - Example 1 Month Expected Demand Production Days Demand Per Day (computed) Jan 900 22 41 Feb 700 18 39 Mar 800 21 38 Apr 1,200 57 May 1,500 68 June 1,100 20 55 6,200 124 Average requirement = Total expected demand Number of production days = = 50 units per day 6,200 124 Haery

Level production using average monthly forecast demand Planning - Example 1 Forecast demand 70 – 60 – 50 – 40 – 30 – 0 – Jan Feb Mar Apr May June = Month       22 18 21 21 22 20 = Number of working days Production rate per working day Level production using average monthly forecast demand Haery

Planning - Example 1 Cost Information Inventory carrying cost $ 5 per unit per month Subcontracting cost per unit $10 per unit Average pay rate $ 5 per hour ($40 per day) Overtime pay rate $ 7 per hour (above 8 hours per day) Labor-hours to produce a unit 1.6 hours per unit Cost of increasing daily production rate (hiring and training) $300 per unit Cost of decreasing daily production rate (layoffs) $600 per unit Haery

Planning - Example 1 Month Production at 50 Units per Day Demand Forecast Monthly Inventory Change Ending Inventory Jan 1,100 900 +200 200 Feb 700 400 Mar 1,050 800 +250 650 Apr 1,200 -150 500 May 1,500 -400 100 June 1,000 -100 1,850 Total units of inventory carried over from one month to the next = 1,850 units Workforce required to produce 50 units per day = 10 workers Table 13.3 Haery

Planning - Example 1 Costs Calculations Inventory carrying $9,250 (= 1,850 units carried x $5 per unit) Regular-time labor 49,600 (= 10 workers x $40 per day x 124 days) Other costs (overtime, hiring, layoffs, subcontracting) Total cost $58,850 Total units of inventory carried over from one month to the next = 1,850 units Workforce required to produce 50 units per day = 10 workers Table 13.3 Haery

Reduction of inventory Planning - Example 1 Cumulative demand units 7,000 – 6,000 – 5,000 – 4,000 – 3,000 – 2,000 – 1,000 – – Jan Feb Mar Apr May June Reduction of inventory Cumulative level production using average monthly forecast requirements Cumulative forecast requirements Excess inventory Haery

Demand Per Day (computed) Planning - Example 2 Month Expected Demand Production Days Demand Per Day (computed) Jan 900 22 41 Feb 700 18 39 Mar 800 21 38 Apr 1,200 57 May 1,500 68 June 1,100 20 55 6,200 124 Minimum requirement = 38 units per day Haery

Level production using lowest monthly forecast demand Planning - Example 2 Forecast demand 70 – 60 – 50 – 40 – 30 – 0 – Jan Feb Mar Apr May June = Month       22 18 21 21 22 20 = Number of working days Production rate per working day Level production using lowest monthly forecast demand Haery

Planning - Example 2 Cost Information Inventory carrying cost $ 5 per unit per month Subcontracting cost per unit $10 per unit Average pay rate $ 5 per hour ($40 per day) Overtime pay rate $ 7 per hour (above 8 hours per day) Labor-hours to produce a unit 1.6 hours per unit Cost of increasing daily production rate (hiring and training) $300 per unit Cost of decreasing daily production rate (layoffs) $600 per unit Haery

Planning - Example 2 In-house production = 38 units per day x 124 days Subcontract units = 6,200 - 4,712 = 1,488 units Haery

Planning - Example 2 In-house production = 38 units per day x 124 days Cost Information Inventory carry cost $ 5 per unit per month Subcontracting cost per unit $10 per unit Average pay rate $ 5 per hour ($40 per day) Overtime pay rate $ 7 per hour (above 8 hours per day) Labor-hours to produce a unit 1.6 hours per unit Cost of increasing daily production rate (hiring and training) $300 per unit Cost of decreasing daily production rate (layoffs) $600 per unit In-house production = 38 units per day x 124 days = 4,712 units Subcontract units = 6,200 - 4,712 = 1,488 units Costs Calculations Regular-time labor $37,696 (= 7.6 workers x $40 per day x 124 days) Subcontracting 14,880 (= 1,488 units x $10 per unit) Total cost $52,576 Table 13.3 Haery

Demand Per Day (computed) Planning - Example 3 Month Expected Demand Production Days Demand Per Day (computed) Jan 900 22 41 Feb 700 18 39 Mar 800 21 38 Apr 1,200 57 May 1,500 68 June 1,100 20 55 6,200 124 Production = Expected Demand Haery

Forecast demand and monthly production Planning - Example 3 70 – 60 – 50 – 40 – 30 – 0 – Jan Feb Mar Apr May June = Month       22 18 21 21 22 20 = Number of working days Production rate per working day Forecast demand and monthly production Haery

Planning - Example 3 Cost Information Inventory carrying cost $ 5 per unit per month Subcontracting cost per unit $10 per unit Average pay rate $ 5 per hour ($40 per day) Overtime pay rate $ 7 per hour (above 8 hours per day) Labor-hours to produce a unit 1.6 hours per unit Cost of increasing daily production rate (hiring and training) $300 per unit Cost of decreasing daily production rate (layoffs) $600 per unit Haery

Planning - Example 3 Cost Information Inventory carrying cost Month Forecast (units) Daily Prod Rate Basic Production Cost (demand x 1.6 hrs/unit x $5/hr) Extra Cost of Increasing Production (hiring cost) Extra Cost of Decreasing Production (layoff cost) Total Cost Jan 900 41 $ 7,200 — Feb 700 39 5,600 $1,200 (= 2 x $600) 6,800 Mar 800 38 6,400 $600 (= 1 x $600) 7,000 Apr 1,200 57 9,600 $5,700 (= 19 x $300) 15,300 May 1,500 68 12,000 $3,300 (= 11 x $300) June 1,100 55 8,800 $7,800 (= 13 x $600) 16,600 $49,600 $9,000 $9,600 $68,200 Cost Information Inventory carrying cost $ 5 per unit per month Subcontracting cost per unit $10 per unit Average pay rate $ 5 per hour ($40 per day) Overtime pay rate $ 7 per hour (above 8 hours per day) Labor-hours to produce a unit 1.6 hours per unit Cost of increasing daily production rate (hiring and training) $300 per unit Cost of decreasing daily production rate (layoffs) $600 per unit Table 13.3 Haery

Comparison of Three Plans Cost Plan 1 Plan 2 Plan 3 Inventory carrying $ 9,250 $ 0 Regular labor 49,600 37,696 Overtime labor Hiring 9,000 Layoffs 9,600 Subcontracting Total cost $58,850 $52,576 $68,200 Plan 2 is the lowest cost option Haery

Mathematical Approaches Useful for generating strategies Transportation Method of Linear Programming Produces an optimal plan Management Coefficients Model Model built around manager’s experience and performance Other Models Linear Decision Rule Simulation Haery

General Linear Programming (LP) Model LP gives an optimal solution, but demand and costs must be linear Let Wt = workforce size for period t Pt =units produced in period t It =units in inventory at the end of period t Ft =number of workers fired for period t Ht = number of workers hired for period t

LP MODEL Minimize Z = $100 (H1 + H2 + H3 + H4) + $500 (F1 + F2 + F3 + F4) + $0.50 (I1 + I2 + I3 + I4) Subject to P1 - I1 = 80,000 (1) Demand I1 + P2 - I2 = 50,000 (2) constraints I2 + P3 - I3 = 120,000 (3) I3 + P4 - I4 = 150,000 (4) Production 1000 W1 = P1 (5) constraints 1000 W2 = P2 (6) 1000 W3 = P3 (7) 1000 W4 = P4 (8) 100 + H1 - F1 = W1 (9) Work force W1 + H2 - F2 = W2 (10) constraints W2 + H3 - F3 = W3 (11) W3 + H4 - F4 = W4 (12)

Transportation Method- Example 1 1 900 1000 100 500 2 1500 1200 150 500 3 1600 1300 200 500 4 3000 1300 200 500 Regular production cost per unit $20 Overtime production cost per unit $25 Subcontracting cost per unit $28 Inventory holding cost per unit per period $3 Beginning inventory 300 units EXPECTED REGULAR OVERTIME SUBCONTRACT QUARTER DEMAND CAPACITY CAPACITY CAPACITY Haery

Transportation Tableau Unused PERIOD OF PRODUCTION 1 2 3 4 Capacity Capacity Beginning 0 3 6 9 Inventory 300 — — — 300 Regular 600 300 100 — 1000 Overtime 100 100 Subcontract 500 Regular 1200 — — 1200 Overtime 150 150 Subcontract 250 250 500 Regular 1300 — 1300 Overtime 200 — 200 Subcontract 500 500 Regular 1300 1300 Overtime 200 200 Demand 900 1500 1600 3000 250 1 2 3 4 PERIOD OF USE 20 23 26 29 25 28 31 34 28 31 34 37 20 23 26 25 28 31 28 31 34 20 23 25 28 28 31 20 25 28 Haery

Transportation Method- Example 1 1 900 1000 100 0 500 2 1500 1200 150 250 600 3 1600 1300 200 500 1000 4 3000 1300 200 500 0 Total 7000 4800 650 1250 2100 REGULAR SUB- ENDING PERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY Haery

Transportation Method- Example 2 Sales Period Mar Apr May Demand 800 1,000 750 Capacity: Regular 700 700 700 Overtime 50 50 50 Subcontracting 150 150 130 Beginning inventory 100 tires Costs Regular time $40 per tire Overtime $50 per tire Subcontracting $70 per tire Carrying $ 2 per tire Haery

Transportation Method- Example 2 Important points Carrying costs are $2/tire/month. If goods are made in one period and held over to the next, holding costs are incurred Supply must equal demand, so a dummy column called “unused capacity” is added Because back ordering is not viable in this example, cells that might be used to satisfy earlier demand are not available Haery

Transportation Method- Example 2 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 Haery

Haery

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 Haery

Other Quantitative Techniques Linear decision rule (LDR) Search decision rule (SDR) Management coefficients model

Hierarchical Nature of Planning Items Product lines or families Individual products Components Manufacturing operations Resource Level Plants Individual machines Critical work centers Production Planning Capacity Planning Resource requirements plan Rough-cut capacity plan Capacity requirements plan Input/ output control Aggregate production plan Master production schedule Material requirements plan Shop floor schedule All work centers

Available-to-Promise (ATP) Quantity of items that can be promised to the customer Difference between planned production and customer orders already received AT in period 1 = (On-hand quantity + MPS in period 1) – - (CO until the next period of planned production) ATP in period n = (MPS in period n) –

ATP: Example

ATP: Example (cont.)

ATP: Example (cont.) ATP in April = (10+100) – 70 = 40 = 30 Take excess units from April ATP in April = (10+100) – 70 = 40 ATP in May = 100 – 110 = -10 ATP in June = 100 – 50 = 50 = 30 = 0

Rule Based ATP Product Request Yes Is the product available at this location? Is an alternative product available at an alternate location? Is an alternative product available at this location? Is this product available at a different location? Available-to-promise Allocate inventory Capable-to-promise date Is the customer willing to wait for the product? Revise master schedule Trigger production Lose sale Yes No

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 coefficients model Heuristic Simple, easy to implement; tries to mimic manager’s decision process; uses regression Haery

Aggregate Planning for Services Most services can’t be inventoried Demand for services is difficult to predict Capacity is also difficult to predict Service capacity must be provided at the appropriate place and time Labor is usually the most constraining resource for services

Aggregate Planning for 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

Law Firm Example (3) (4) (5) (6) (3) (4) (5) (6) (1) (2) Likely Worst Maximum Number of Category of Best Case Case Case Demand in Qualified Legal Business (hours) (hours) (hours) People Personnel Trial work 1,800 1,500 1,200 3.6 4 Legal research 4,500 4,000 3,500 9.0 32 Corporate law 8,000 7,000 6,500 16.0 15 Real estate law 1,700 1,500 1,300 3.4 6 Criminal law 3,500 3,000 2,500 7.0 12 Total hours 19,500 17,000 15,000 Lawyers needed 39 34 30

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

Yield Management

Yield Management (cont.)

Yield Management: Example-1 NO-SHOWS PROBABILITY P(N < X) 0 .15 .00 1 .25 .15 2 .30 .40 3 .30 .70 .517 Optimal probability of no-shows P(n < x)  = = .517 Cu Cu + Co 75 75 + 70 Hotel should be overbooked by two rooms

Yield Management : Example-2 Price Room sales 100 50 $150 Price charged for room $15 Variable cost of room Demand Curve Potential customers exist who are willing to pay more than the $15 variable cost of the room Passed-up contribution Money left on the table Some customers who paid $150 were actually willing to pay more for the room $ margin = (Price) x (50 rooms) = ($150 - $15) x (50) = $6,750 Haery

Yield Management : Example-2 Price Room sales 100 60 30 $100 Price 1 for room $200 Price 2 $15 Variable cost of room Demand Curve 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 Haery

Yield Management Matrix Unpredictable Predictable Duration of use Price Tend to be fixed Tend to be variable Quadrant 1: Quadrant 2: Movies Hotels Stadiums/arenas Airlines Convention centers Rental cars Hotel meeting space Cruise lines Quadrant 3: Quadrant 4: Restaurants Continuing care Golf courses hospitals Internet service providers Haery

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 Haery

TIME - BREAK