Aggregate Sales and Operations Planning Chapter 14 Aggregate Sales and Operations Planning

Copyright 2011 John Wiley & Sons, Inc. Lecture Outline The Sales and Operations Planning Process Strategies for Adjusting Capacity Strategies for Managing Demand Quantitative Techniques for Aggregate Planning Hierarchical Nature of Planning Aggregate Planning for Services Copyright 2011 John Wiley & Sons, Inc.

Sales and Operations Planning Determines resource capacity to meet demand over an intermediate time horizon Aggregate refers to sales and operations planning for product lines or families Sales and Operations planning (S&OP) matches supply and demand Objectives Establish a company wide plan for allocating resources Develop an economic strategy for meeting demand Copyright 2011 John Wiley & Sons, Inc.

Sales and Operations Planning Process Copyright 2011 John Wiley & Sons, Inc.

Monthly S&OP Planning Process Copyright 2011 John Wiley & Sons, Inc.

Meeting Demand Strategies Adjusting capacity Resources 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 Copyright 2011 John Wiley & Sons, Inc.

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 Copyright 2011 John Wiley & Sons, Inc.

Strategies for Adjusting Capacity Overtime and under-time Increase or decrease working hours Subcontracting Let outside companies complete the work Part-time workers Hire part-time workers to complete the work Backordering Provide the service or product at a later time period Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Level Production Demand Units Time Production Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Chase Demand Demand Units Time Production Copyright 2011 John Wiley & Sons, Inc.

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 Copyright 2011 John Wiley & Sons, Inc.

Quantitative Techniques For AP Pure Strategies Mixed Strategies Linear Programming Transportation Method Other Quantitative Techniques Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Pure Strategies Hiring cost = $100 per worker Firing cost = $500 per worker Inventory carrying cost = $0.50 pound per quarter Regular production cost per pound = $2.00 Production per employee = 1,000 pounds per quarter Beginning work force = 100 workers QUARTER SALES FORECAST (LB) Spring 80,000 Summer 50,000 Fall 120,000 Winter 150,000 Copyright 2011 John Wiley & Sons, Inc.

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 Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Chase Demand Strategy 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 SALES PRODUCTION WORKERS WORKERS WORKERS QUARTER FORECAST PLAN NEEDED HIRED FIRED Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000 Copyright 2011 John Wiley & Sons, Inc.

Level Production with Excel Inventory at end of summer Input by user =400,000/4 Cost of level production = inventory costs + production costs Copyright 2011 John Wiley & Sons, Inc.

Chase Demand with Excel Workforce requirements calculated by system No. of workers hired in fall Production input by user; production =demand Cost of chase demand = hiring + firing + production Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Mixed Strategy Combination of Level Production and Chase Demand strategies Example policies no more than x% of workforce can be laid off in one quarter inventory levels cannot exceed x dollars Some industries may shut down manufacturing during the low demand season and schedule employee vacations during that time Copyright 2011 John Wiley & Sons, Inc.

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 Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. LP MODEL Minimize Z = $100 (H1 + H2 + H3 + H4) + $500 (F1 + F2 + F3 + F4) + $0.50 (I1 + I2 + I3 + I4) + $2 (P1 + P2 + P3 + P4) 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) Copyright 2011 John Wiley & Sons, Inc.

Setting up the Spreadsheet Target cell; cost of solution goes here Solver will put the solution here When model is complete, Solve Click here next Demand Constraint Workforce Constraint Production Constraint Cells where solution appears Copyright 2011 John Wiley & Sons, Inc.

Setting up the Spreadsheet Click these boxes Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. The LP Solution Optimal production plan Cost of optimal solution Solution is a mix of inventory, hiring and firing Extra report options Copyright 2011 John Wiley & Sons, Inc.

Level Production for Quantum Input by user Excel calculates these Cost of level production Copyright 2011 John Wiley & Sons, Inc.

Chase Demand for Quantum Input by user Excel calculates these Cost of chase demand No. workers hired in Feb. Copyright 2011 John Wiley & Sons, Inc.

LP Solution for Quantum Solver found this solution Constraint equations in these cells Optimal solution Copyright 2011 John Wiley & Sons, Inc.

Transportation Method EXPECTED REGULAR OVERTIME SUBCONTRACT QUARTER DEMAND CAPACITY CAPACITY CAPACITY 1 900 1000 100 500 2 1500 1200 150 500 3 1600 1300 200 500 4 3000 1300 200 500 Regular production cost $20/unit Overtime production cost $25/unit Subcontracting cost $28/unit Inventory holding cost $3/unit-period Beginning inventory 300 units Copyright 2011 John Wiley & Sons, Inc.

Transportation Tableau Copyright 2011 John Wiley & Sons, Inc.

Transportation Tableau Copyright 2011 John Wiley & Sons, Inc.

Burruss’ Production Plan 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 Copyright 2011 John Wiley & Sons, Inc.

Excel and Transportation Method Period 2’s ending inventory Regular production for period 1 Cost of solution Copyright 2011 John Wiley & Sons, Inc.

Other Quantitative Techniques Linear decision rule (LDR) Search decision rule (SDR) Management coefficients model Copyright 2011 John Wiley & Sons, Inc.

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 Sales and Operations Plan Master production schedule Material requirements plan Shop floor schedule All work centers Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Disaggregation Breaking an aggregate plan into more detailed plans Create Master Production Schedule for Material Requirements Planning Copyright 2011 John Wiley & Sons, Inc.

Collaborative Planning Sharing information and synchronizing production across supply chain Part of CPFR (collaborative planning, forecasting, and replenishment) involves selecting products to be jointly managed, creating a single forecast of customer demand, and synchronizing production across supply chain Copyright 2011 John Wiley & Sons, Inc.

Available-to-Promise (ATP) Quantity of items that can be promised to 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) – Capable-to-promise quantity of items that can be produced and mad available at a later date Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. ATP Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. ATP Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. ATP 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 Copyright 2011 John Wiley & Sons, Inc.

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 Copyright 2011 John Wiley & Sons, Inc.

Aggregate Planning for Services Most services cannot 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 Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Yield Management Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Yield Management Copyright 2011 John Wiley & Sons, Inc.

Yield Management Hotel should be overbooked by two rooms NO-SHOWS PROBABILITY P(N < X) 0 .15 .00 1 .25 .15 2 .30 .40 3 .30 .70 Optimal probability of no-shows P(n < x)  = = .517 Cu Cu + Co 75 75 + 70 .517 Hotel should be overbooked by two rooms Copyright 2011 John Wiley & Sons, Inc.

Linear Programming Decision Analysis Tools and Techniques Chapter 14 Supplement Linear Programming Decision Analysis Tools and Techniques

Copyright 2011 John Wiley & Sons, Inc. Lecture Outline Model Formulation Linear Programming Model Solution Solving Linear Programming Problems with Excel Sensitivity Analysis Copyright 2011 John Wiley & Sons, Inc.

Linear Programming (LP) A model consisting of linear relationships representing a firm’s objective and resource constraints A mathematical modeling technique which determines a level of operational activity in order to achieve an objective, subject to restrictions called constraints Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Types of LP Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Types of LP Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Types of LP Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. LP Model Formulation Decision variables symbols representing levels of activity of an operation Objective function linear relationship for the objective of an operation most frequent business objective is to maximize profit most frequent objective of individual operational units (such as a production or packaging department) is to minimize cost Constraint linear relationship representing a restriction on decision making Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. LP Model Formulation Max/min z = c1x1 + c2x2 + ... + cnxn subject to: a11x1 + a12x2 + ... + a1nxn (≤, =, ≥) b1 a21x1 + a22x2 + ... + a2nxn (≤, =, ≥) b2 : an1x1 + an2x2 + ... + annxn (≤, =, ≥) bn xj = decision variables bi = constraint levels cj = objective function coefficients aij = constraint coefficients Constraints Copyright 2011 John Wiley & Sons, Inc.

Highlands Craft Store Labor Clay Revenue Product (hr/unit) (lb/unit) ($/unit) Bowl 1 4 40 Mug 2 3 50 There are 40 hours of labor and 120 pounds of clay available each day Decision variables x1 = number of bowls to produce x2 = number of mugs to produce Resource Requirements Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Highlands Craft Store Maximize Z = $40 x1 + 50 x2 Subject to x1 + 2x2 40 hr (labor constraint) 4x1 + 3x2 120 lb (clay constraint) x1 , x2 0 Solution is x1 = 24 bowls x2 = 8 mugs Revenue = $1,360 Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. Simplex Method Mathematical procedure for solving LP problems Follow a set of steps to reach optimal solution Slack variables added to ≤ constraints to represent unused resources x1 + 2x2 + s1 = 40 hours of labor 4x1 + 3x2 + s2 = 120 lb of clay Surplus variables subtracted from ≥ constraints to represent excess above resource requirement. 2x1 + 4x2 ≥ 16 is transformed into 2x1 + 4x2 - s1 = 16 Slack/surplus variables have a 0 coefficient in the objective function Z = $40x1 + $50x2 + 0s1 + 0s2 Copyright 2011 John Wiley & Sons, Inc.

Solving LP Problems with Excel Objective function =C6*B10+D6*B11 =E6-F6 =E7-F7 =C7*B10+D7*B11 Decision variables bowls (X1) = B10 mugs (x2) = B11 Click on “Data” to invoke “Solver” Copyright 2011 John Wiley & Sons, Inc.

Solving LP Problems with Excel After all parameters and constraints have been input, click on “Solve” Objective function Decision variables C6*B10+D6*B11≤40 and C7*B10+D7*B11≤120 Click on “Add” to insert constraints Click on “Options” to add non-negativity and linear conditions Copyright 2011 John Wiley & Sons, Inc.

Copyright 2011 John Wiley & Sons, Inc. LP Solution Copyright 2011 John Wiley & Sons, Inc.

Sensitivity Analysis Sensitivity range for labor; 30 to 80 lbs. Sensitivity range for clay; 60 to 160lbs. Shadow prices – marginal values – for labor and clay. Copyright 2011 John Wiley & Sons, Inc.