Aggregate Planning

Planning Horizon Aggregate planning: Intermediate-range capacity planning, usually covering 6 to 18 months. Short range Intermediate range Long range Now6 months18 months

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

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

Balancing Aggregate Demand and Aggregate Production Capacity JanFebMarAprMayJun JanFebMarAprMayJun 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 What we want to do is balance out the production rate, workforce levels, and inventory to make these figures match up

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

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

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

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)

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

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

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

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

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

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

Capacity Options - Advantages and Disadvantages (1 of 4)

Advantages/Disadvantages (2 of 4)

Advantages/Disadvantages (3 of 4) OptionAdvantageDisadvantageSome Comments Using part-time workers 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.

Advantages/Disadvantages (4 of 4)

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

Basic Aggregate Planning Strategies for Meeting Demand  Level 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)  Chase 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.)  Maintaining resources for high demand levels Ensures high levels of customer service

Level Production Production Demand Units Time

Chase Demand Production Demand Units Time

Level Strategy: Forecast and Average Forecast Demand

Level Strategy: Cumulative Demand Graph Jan Feb Mar Apr May Jun Cumulative forecast requirements Cumulative level production using average monthly forecast requirements Reduction of inventory Excess inventory Cumulative Demand (Units) 7,000 6,000 5,000 4,000 3,000 2,000 1,000

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

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

Summary of Planning Techniques

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. Steps of Trial & Error Method

Aggregate Planning Using Pure Strategies (Example 1) Hiring cost= $100 per worker Firing cost= $500 per worker Inventory carrying cost= $0.50 pound per quarter Production per employee= 1,000 pounds per quarter Beginning work force= 100 workers QUARTERSALES FORECAST (LB) Spring80,000 Summer50,000 Fall120,000 Winter150,000

Level Production Strategy (1 of 2) QUARTERSALES FORECAST (LB) Spring80,000 Summer50,000 Fall120,000 Winter150,000 Level production = 100,000 pounds (50, , , ,000) 4

Level Production Strategy (2 of 2) Spring80,000100,00020,000 Summer50,000100,00070,000 Fall120,000100,00050,000 Winter150,000100,0000 Total400,000140,000 Cost = 140,000 pounds x 0.50 per pound = $70,000 SALESPRODUCTION QUARTERFORECASTPLANINVENTORY

Spring80,00080, Summer50,00050, Fall120,000120, Winter150,000150, SALESPRODUCTIONWORKERSWORKERSWORKERS QUARTERFORECASTPLANNEEDEDHIREDFIRED Cost= (100 workers hired x $100) + (50 workers fired x $500) = $10, ,000 = $35,000 Chase Demand Strategy

APP Using Mixed Strategies 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 January1000July500 February400August500 March400September1000 April400October1500 May400November2500 June400December3000 MONTHDEMAND (CASES)MONTHDEMAND (CASES)

Aggregate Planning (Example 2) Materials$5/unit Holding costs$1/unit per mo. Marginal cost of stockout$1.25/unit per mo. Hiring and training cost$200/worker Layoff costs$250/worker Labor hours required0.15 hrs/unit Straight time labor cost$8/hour Beginning inventory250 units Productive hours/worker/day7.25 Paid straight hrs/day8 Suppose we have the following unit demand and cost information: Demand/moJanFebMarAprMayJun

Demand/moJanFebMarAprMay Jun Given the demand and cost information below, what are the aggregate hours/worker/month, units/worker, and dollars/worker? Given the demand and cost information below, what are the aggregate hours/worker/month, units/worker, and dollars/worker? 7.25x /0.15=48.33 & 48.33x22= x8hrsx$8=$1408 Cut-and-Try Example: Determining Straight Labor Costs and Output

Chase Strategy (Hiring & Firing to meet demand) Lets assume our current workforce is 7 workers. First, calculate net requirements for production, or =4250 units Then, calculate number of workers needed to produce the net requirements, or 4250/ =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

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

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 $ Labor Material Storage Stockout

APP by Linear Programming where H t =# hired for period t F t =# fired for period t I t =inventory at end of period t P t =units produced in period t W t =workforce size for period t 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 P 1 - I 1 = 80,000(1) DemandI 1 + P 2 - I 2 = 50,000(2) constraintsI 2 + P 3 - I 3 = 120,000(3) I 3 + P 4 - I 4 = 150,000(4) Production1000 W 1 = P 1 (5) constraints1000 W 2 = P 2 (6) 1000 W 3 = P 3 (7) 1000 W 4 = P 4 (8) H 1 - F 1 = W 1 (9) Work forceW 1 + H 2 - F 2 = W 2 (10) constraintsW 2 + H 3 - F 3 = W 3 (11) W 3 + H 4 - F 4 = W 4 (12)

APP by the Transportation Method 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 inventory300 units EXPECTEDREGULAROVERTIMESUBCONTRACT QUARTERDEMANDCAPACITYCAPACITYCAPACITY

The Transportation Tableau Unused PERIOD OF PRODUCTION1234CapacityCapacity Beginning0369 Inventory300———300 Regular —1000 Overtime Subcontract500 Regular1200——1200 Overtime Subcontract Regular1300—1300 Overtime200—200 Subcontract Regular Overtime Subcontract Demand PERIOD OF USE

© The McGraw-Hill Companies, Inc., Burruss’ Production Plan Total REGULARSUB-ENDING PERIODDEMANDPRODUCTIONOVERTIMECONTRACTINVENTORY

© The McGraw-Hill Companies, Inc., Other Quantitative Techniques Linear decision rule (LDR) Linear decision rule (LDR) Search decision rule (SDR) Search decision rule (SDR) Management coefficients model Management coefficients model

Hierarchical Planning Process 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

Aggregate Plan to Master Schedule Aggregate Planning Disaggregation Master Schedule

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. Disaggregating the Aggregate Plan

© The McGraw-Hill Companies, Inc., Master Scheduling Process Master Scheduling Beginning inventory Forecast Customer orders Inputs Outputs Projected inventory Master production schedule Uncommitted inventory Figure 13.6

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

© The McGraw-Hill Companies, Inc., Projected On-hand Inventory Beginning Inventory Customer orders are larger than forecast in week 1 Forecast is larger than Customer orders in week 2 Forecast is larger than Customer orders in week 3 Figure 13.8

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

© The McGraw-Hill Companies, Inc., Time Fences in MPS Period “frozen” (firm or fixed) “slushy” somewhat firm “liquid” (open) Figure

Available-to-Promise PERIOD ON-HAND = Forecast Customer orders Master production schedule Available to promise PERIOD ON-HAND = Forecast Customer orders Master production schedule Available to promise ATP in period 1 = ( ) - ( ) = 40 ATP in period 3 = ( ) = 0 ATP in period 5 = ( ) = 170

Available-to-Promise Product Request 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? Available- to-promise Allocate inventory Revise master schedule Trigger production Lose sale Yes No Yes No Yes No Yes No Yes No

1.Most services can’t be inventoried 2.Demand for services is difficult to predict 3.Capacity availability 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 6.Labor flexibility can be an advantage in services Aggregate Planning for Services

Characteristics That Make Yield Management Work  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

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

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

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

Yield Management NO-SHOWSPROBABILITY

Yield Management NO-SHOWSPROBABILITYP(N < X) Expected number of no shows 0(.15) + 1(.25) + 2(.30) + 3(.30) = 1.75 Optimal probability of no-shows P(n < x)  = =.517 C u C u + C o

Yield Management NO-SHOWSPROBABILITYP(N < X) Expected number of no shows 0(.15) + 1(.25) + 2(.30) + 3(.30) = 1.75 Optimal probability of no-shows P(n < x)  = =.517 C u C u + C o Cost of overbooking [2(.15) + 1(.25)]$70=$38.50Cost of bumping customers (.30)$75=$22.50Lost revenue from no-shows $61.00Total cost of overbooking by 2 rooms Expected savings = ($ $61) = $70.25 a night