Aggregate Planning Planning Horizon Aggregate planning Intermediate-range

Aggregate Planning

Planning Horizon Aggregate planning: Intermediate-range capacity planning, usually covering 6 to 18 months. Long range Short range Now Intermediate range 6 months 18 months

3 ©The Mc. Graw-Hill Companies, Inc. , 2004

Process planning Long range Strategic capacity planning Intermediate Forecasting & demand range management Manufacturing Sales and operations (aggregate) planning Sales plan Aggregate operations plan Services Master scheduling Material requirements planning Short range Order scheduling Weekly workforce and customer scheduling Daily workforce and customer scheduling

Operations Planning Activities • Long-range planning – – Greater than one year planning horizon Usually performed in annual increments • Medium-range planning – – Six to eighteen months Usually with monthly or quarterly increments • Short-range planning – – One day to less than six months Usually with weekly increments

Planning Tasks and Responsibilities

Aggregate Production Planning (APP) ü Matches market demand to company resources ü Plans production 6 months to 18 months in advance ü Expresses demand, resources, and capacity in general terms ü Develops a strategy for economically meeting demand ü Establishes a company-wide game plan for allocating resources

Balancing Aggregate Demand Aggregate Production Capacity Suppose the figure to the right represents forecast demand in units Now suppose this lower figure represents the aggregate capacity of the company to meet demand 10000 8000 6000 7000 6000 5500 4000 2000 0 Jan 9000 10000 Feb 9000 Jan Feb Mar 9900 Apr 8800 May Jun 9500 May Jun 8000 What we want to do is balance out the production rate, workforce levels, and inventory to make these figures match up 6000 4000 2000 0 Mar Apr

Aggregate Plan: Relationships Marketplace and Demand Forecasts, orders Product Decisions Process Planning & Capacity Decisions Aggregate Plan for Production Master Production Schedule, and MRP systems Detailed Work Schedules Research and Technology Work Force Raw Materials Available Inventory On Hand External Capacity Subcontractors

Inputs and Outputs to APP Capacity Constraints Demand Forecasts Size of Workforce Strategic Objectives Aggregate Production Planning Production per month (in units or $) Inventory Levels Company Policies Financial Constraints Units or dollars subcontracted, backordered, or lost

Aggregate Planning Inputs Ø Resources • Workforce • Facilities Ø Demand forecast Ø Policies • • Subcontracting Overtime Inventory levels Back orders Ø Common unit for measuring outputs Ø Costs • • • Inventory carrying Back orders Hiring/firing Overtime Inventory changes Subcontracting

Aggregate Planning Outputs • A plan that specifies the optimal combination of – production rate (units completed per unit of time) – workforce level (number of workers) – inventory on hand (inventory carried from previous period – Subcontracting levels (if any) – Backordering levels (if any)

Aggregate Planning Goals • • Meet demand Use capacity efficiently Meet inventory policy Minimize total cost

Aggregate Planning Strategies • Proactive – Alter demand to match capacity • Reactive – Alter capacity to match demand • Mixed – Some of each

Demand Management ü Shifting demand into other periods by incentives, promotions, advertising campaigns, pricing, etc. ü Offering product or services with counterseasonal demand patterns (counterseasonal product mixing) ü Backordering ü Creation of new demand ü Partnering with suppliers to reduce information distortion along the supply chain

Options of Adjusting Capacity to Meet Demand (1 of 2) Ø Producing at a constant rate and using inventories to absorb fluctuations in demand ie. changing inventory levels Ø Varying work force size (hiring and firing workers) so that production matches demand Ø Varying production capacity by increasing or decreasing working hours (overtime or idle time)

Options of Adjusting Capacity to Meet Demand (2 of 2) Ø Using part-time workers to change production rate Ø Subcontracting work to other firms Ø Providing the service or product at a later time period (backordering)

Strategy Details Ø Overtime & undertime - common when demand fluctuations are not extreme Ø Subcontracting - useful if supplier meets quality & time requirements Ø Part-time workers - feasible for unskilled jobs or if labor pool exists Ø Backordering - only works if customer is willing to wait for product/services

Capacity Options - Advantages and Disadvantages (1 of 4) Option Advantage Disadvantage Some Comments Changing inventory levels Changes in human resources are gradual, not abrupt production changes Inventory holding costs; Shortages may result in lost sales Applies mainly to production, not service, operations Varying workforce size by hiring or layoffs Avoids use of other alternatives Hiring, layoff, and training costs Used where size of labor pool is large

Advantages/Disadvantages (2 of 4) Option Advantage Disadvantage Some Comments Varying production rates through overtime or idle time Matches seasonal fluctuations without hiring/training costs Permits flexibility and smoothing of the firm's output Overtime premiums, tired workers, may not meet demand Allows flexibility within the aggregate plan Loss of quality control; reduced profits; loss of future business Applies mainly in production settings Subcontracting

Advantages/Disadvantages (3 of 4) Option Advantage Disadvantage Some Comments Using part-time workers Less costly and more flexible than full-time workers Good for unskilled jobs in areas with large temporary labor pools Influencing demand Tries to use excess capacity. Discounts draw new customers. High turnover/training costs; quality suffers; scheduling difficult Uncertainty in demand. Hard to match demand to supply exactly. Creates marketing ideas. Overbooking used in some businesses.

Advantages/Disadvantages (4 of 4) Option Advantage Disadvantage Some Comments Back ordering during highdemand periods May avoid Customer must overtime. Keeps be willing to capacity constant wait, but goodwill is lost. Many companies backorder. Counterseasonal Fully utilizes May require products and resources; allows skills or service mixing stable workforce. equipment outside a firm's areas of expertise. Risky finding products or services with opposite demand patterns.

The Extremes Level Strategy Chase Strateg y Production rate is constant Production equals demand

Basic Aggregate Planning Strategies for Meeting Demand ØLevel capacity strategy: • Keeping work force constant and maintaining a steady rate of regular-time output while meeting variations in demand by a combination of options (such as using inventories + subcontracting) ØChase demand strategy: • Changing workforce levels so that production matches demand (the planned output for a period is set at the expected demand for that period. ) ØMaintaining resources for high demand levels • Ensures high levels of customer service

Level Production Demand Units Production Time

Chase Demand Units Production Time

Level Strategy: Forecast and Average Forecast Demand 22 20 18 21 21 22

Level Strategy: Cumulative Demand Graph 7, 00 0 Cumulative Demand (Units) 6, 00 0 5, 00 0 4, 00 0 3, 00 0 Reduction Cumulative of inventory level production using average monthly forecast requirements Cumulative forecast requirements Excess inventory Jan Feb Mar Apr May 2, 00 Jun

Level Approach • Advantages – Stable output rates and workforce • Disadvantages – Greater inventory costs – Increased overtime and idle time – Resource utilizations vary over time

Chase Approach • Advantages – Investment in inventory is low – Labor utilization in high • Disadvantages – The cost of adjusting output rates and/or workforce levels

Aggregate Planning Methods Ø Graphical & charting techniques • Popular & easy-to-understand • Trial & error approach Ø Mathematical approaches • • • Linear programming Transportation method Linear decision rule (LDR) Search decision rule (SDR) Management coefficients model Simulation

Summary of Planning Techniques

Steps of Trial & Error Method 1. Forecast demand for each period 2. Determine capacities (for regular time, overtime, subcontracting) for each period 3. Identify policies that are pertinent 4. Determine costs (labor, hiring/firing, holding etc. ) 5. Develop alternative plans and costs 6. Select the best plan that satisfies objectives. Otherwise return to step 5.

Aggregate Planning Using Pure Strategies (Example 1) QUARTER Spring Summer Fall Winter Hiring cost Firing cost Inventory carrying cost Production per employee Beginning work force SALES FORECAST (LB) 80, 000 50, 000 120, 000 150, 000 = $100 per worker = $500 per worker = $0. 50 pound per quarter = 1, 000 pounds per quarter = 100 workers

Level Production Strategy (1 of 2) QUARTER SALES FORECAST (LB) Spring Summer Fall Winter 80, 000 50, 000 120, 000 150, 000 Level production (50, 000 + 120, 000 + 150, 000 + 80, 000) 4 = 100, 000 pounds

Level Production Strategy (2 of 2) QUARTER Spring Summer Fall Winter SALES FORECAST 80, 000 50, 000 120, 000 150, 000 Total PRODUCTION PLAN INVENTORY 100, 000 400, 000 20, 000 70, 000 50, 000 0 140, 000 Cost = 140, 000 pounds x 0. 50 per pound = $70, 000

Chase Demand Strategy QUARTER SALES PRODUCTION FORECAST PLAN Spring Summer Fall Winter 80, 000 50, 000 120, 000 150, 000 WORKERS NEEDED 80 50 120 150 WORKERS HIRED FIRED 0 0 70 30 20 30 0 0 100 50 Cost = (100 workers hired x $100) + (50 workers fired x $500) = $10, 000 + 25, 000 = $35, 000

APP Using Mixed Strategies MONTH January February March April May June DEMAND (CASES) 1000 400 400 400 MONTH July August September October November December DEMAND (CASES) 500 1000 1500 2500 3000 Production per employee = 100 cases per month Wage rate = $10 per case for regular production = $15 per case for overtime = $25 for subcontracting Hiring cost = $1000 per worker Firing cost = $500 per worker Inventory carrying cost = $1. 00 case per month Beginning work force = 10 workers

Aggregate Planning (Example 2) Suppose we have the following unit demand cost information: Demand/mo Jan Feb Mar Apr May Jun 4500 5500 7000 10000 8000 6000 Materials Holding costs Marginal cost of stockout Hiring and training cost Layoff costs Labor hours required Straight time labor cost Beginning inventory Productive hours/worker/day Paid straight hrs/day $5/unit $1/unit per mo. $1. 25/unit per mo. $200/worker $250/worker 0. 15 hrs/unit $8/hour 250 units 7. 25 8

Cut-and-Try Example: Determining Straight Labor Costs and Output Given the demand cost information below, what are the aggregate hours/worker/month, units/worker, and dollars/worker? Demand/mo Jun Jan Feb Mar Apr May 4500 5500 7000 10000 7. 25 x 22 8000 6000 7. 25/0. 15=48. 33 & 22 x 8 hrsx$8=$1408 48. 33 x 22=1063. 33

Chase Strategy (Hiring & Firing to meet demand) Lets assume our current workforce is 7 workers. First, calculate net requirements for production, or 4500 -250=4250 units Then, calculate number of workers needed to produce the net requirements, or 4250/1063. 33=3. 997 or 4 workers Finally, determine the number of workers to hire/fire. In this case we only need 4 workers, we have 7, so 3 can be fired.

Below are the complete calculations for the remaining months in the six month planning horizon

Below are the complete calculations for the remaining months in the six month planning horizon with the other costs included

Level Workforce Strategy (Surplus and Shortage Allowed) Lets take the same problem as before but this time use the Level Workforce strategy This time we will seek to use a workforce level of 6 workers

Below are the complete calculations for the remaining months in the six month planning horizon Note, if we recalculate this sheet with 7 workers we would have a surplus

Below are the complete calculations for the remaining months in the six month planning horizon with the other costs included Note, total costs under this strategy are less than Chase at $260. 408. 62 Labor Material Storage Stockout

APP by Linear Programming Minimize Z = $100 (H 1 + H 2 + H 3 + H 4) + $500 (F 1 + F 2 + F 3 + F 4) + $0. 50 (I 1 + I 2 + I 3 + I 4) Subject to Demand constraints where Ht = # hired for period t Ft = # fired for period t It = inventory at end of period t Pt = units produced in period t Wt = workforce size for period t Production constraints Work force constraints P 1 - I 1 + P 2 - I 2 + P 3 - I 3 + P 4 - I 4 1000 W 1 1000 W 2 1000 W 3 1000 W 4 100 + H 1 - F 1 W 1 + H 2 - F 2 W 2 + H 3 - F 3 W 3 + H 4 - F 4 = 80, 000 = 50, 000 = 120, 000 = 150, 000 = P 1 = P 2 = P 3 = P 4 = W 1 = W 2 = W 3 = W 4 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

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

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

50 Burruss’ Production Plan REGULAR SUBENDING PERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY 1 2 3 4 Total 900 1500 1600 3000 7000 1200 1300 4800 150 200 650 0 250 500 1250 500 600 1000 0 2100 ©The Mc. Graw-Hill Companies, Inc. , 2004

51 Other Quantitative Techniques ü Linear decision rule (LDR) ü Search decision rule (SDR) ü Management coefficients model ©The Mc. Graw-Hill Companies, Inc. , 2004

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

Aggregate Plan to Master Schedule Aggregate Planning Disaggregation Master Schedule

Disaggregating the Aggregate Plan • Master schedule: The result of disaggregating an aggregate plan; shows quantity and timing of specific end items needed to meet demand for a scheduled horizon. • Rough-cut capacity planning: Approximate balancing of capacity and demand to test the feasibility of a master schedule.

55 Master Scheduling Process Figure 13. 6 Inputs Outputs Beginning inventory Forecast Customer orders Projected inventory Master Scheduling Master production schedule Uncommitted inventory ©The Mc. Graw-Hill Companies, Inc. , 2004

56 Projected On-hand Inventory Projected on-hand = inventory Inventory from previous week - Current week’s requirements ©The Mc. Graw-Hill Companies, Inc. , 2004

57 Projected On-hand Inventory Figure 13. 8 Beginning Inventory Forecast is larger than Customer orders in week 3 Customer orders are larger than forecast in week 1 Forecast is larger than Customer orders in week 2 ©The Mc. Graw-Hill Companies, Inc. , 2004

58 Time Fences – points in time that separate phases of a master schedule planning horizon. ©The Mc. Graw-Hill Companies, Inc. , 2004

59 Time Fences in MPS Figure 13. 12 Period 1 2 “frozen” (firm or fixed) 3 4 5 “slushy” somewhat firm 6 7 8 9 “liquid” (open) ©The Mc. Graw-Hill Companies, Inc. , 2004

Available-to-Promise ON-HAND = 50 1 Forecast Customer orders Master production schedule Available to promise ON-HAND = 50 2 100 100 200 1 Forecast Customer orders Master production schedule Available to promise PERIOD 3 4 2 100 90 200 40 100 120 6 100 200 PERIOD 3 4 100 130 200 0 5 100 70 ATP in period 1 = (50 + 200) - (90 + 120) = 40 ATP in period 3 = 200 - (130 + 70) = 0 ATP in period 5 = 200 - (20 + 10) = 170 5 6 100 20 200 170 10

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

Aggregate Planning for Services 1. 2. 3. 4. Most services can’t be inventoried Demand for services is difficult to predict Capacity availability is also difficult to predict Service capacity must be provided at the appropriate place and time 5. Labor is usually the most constraining resource for services 6. Labor flexibility can be an advantage in services

Characteristics That Make Yield Management Work Ø Service or product can be sold in advance of consumption Ø Demand fluctuates Ø Capacity is relatively fixed Ø Demand can be segmented Ø Variable costs are low and fixed costs are high

Hotel: Single Price Level Sales Demand Curve $sales = Net price * 50 rooms =150*50 =$7500 Potential customers exist who are willing to pay more than the $15 Passed up variable cost Some customers profit who paid $150 for contributio the room were ns actually willing to pay more Money $15 variable cost of room left on the table $150 Price charged for room $ Sales = $ 6, 750 Price

Hotel: Two Price Levels Sale s Deman d Net prices are: Price #1 => $85 Price #2 => $175 Total sales = 1 st net price *30 + 2 nd net price *30 = $8100 $15 variable cost of room $100 Price #1 $Sales = $ 8, 100 $200 Price #2

Yield Management Cu P(n < x) Cu + Co where n = number of no-shows x = number of rooms or seats overbooked Cu = cost of underbooking; i. e. , lost sale Co = cost of overbooking; i. e. , replacement cost P = probability

Yield Management NO-SHOWS PROBABILITY 0. 25 2 3 . 15. 30 1

Yield Management NO-SHOWS PROBABILITY P(N < X) 0 1 2 3 . 15. 25. 30 . 00. 15. 40. 70 Expected number of no shows 0(. 15) + 1(. 25) + 2(. 30) + 3(. 30) = 1. 75 Optimal probability of no-shows Cu 75 P(n < x) = =. 517 Cu + Co 75 + 70 . 517

Yield Management NO-SHOWS PROBABILITY P (N < X ) Cost of overbooking 0. 15. 00 [2(. 15) + 1(. 25)]$70 = $38. 50 Cost of bumping customers 1. 25. 15 (. 30)$75 = $22. 50 Lost revenue from no-shows. 517 2. 30. 40 3. 30. 70 $61. 00 Total cost of overbooking by 2 rooms Expected number of no shows Expected savings = ($131. 225 - $61) = $70. 25 a night 0(. 15) + 1(. 25) + 2(. 30) + 3(. 30) = 1. 75 Optimal probability of no-shows Cu 75 P(n < x) = =. 517 Cu + Co 75 + 70