Chapter 14 Sales and Capacity Planning Russell and Taylor Operations and Supply Chain Management,...

Chapter 14

Sales and Capacity Planning

Russell and Taylor

Operations and Supply Chain Management, 8th Edition

© 2014 John Wiley & Sons, Inc. - Russell and Taylor 8e

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

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Learning Objectives

• Appreciate the interface of marketing, finance, and operations in S&OP planning

• Describe the monthly S&OP process and the importance of reconciling differences

• Utilize various tools and techniques to adjust capacity and manage demand

• Evaluate a demand scenario and select an appropriate S&OP strategy

• Describe hierarchical planning and the process of determining available-to-promise

• Determine overbooking, single orders, and fare class strategies for revenue management in services

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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

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Sales and Operations Planning Process

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Monthly S&OP Planning Process

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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

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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

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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

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Level Production

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Chase Demand

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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

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Quantitative Techniques For AP

• Pure Strategies• Mixed Strategies• Linear Programming• Transportation Method• Other Quantitative Techniques

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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 80,000Summer 50,000Fall 120,000Winter 150,000

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Level Production Strategy

Level production


Cost of Level Production Strategy

SALES PRODUCTIONQUARTER FORECAST PLAN INVENTORY

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Level Production Strategy

Level production

= 100,000 pounds(50,000 + 120,000 + 150,000 + 80,000)

4

Spring 80,000 100,000 20,000Summer 50,000 100,000 70,000Fall 120,000 100,000 50,000Winter 150,000 100,000 0

400,000 140,000Cost of Level Production Strategy

(400,000 X $2.00) + (140,00 X $.50) = $870,000

SALES PRODUCTIONQUARTER FORECAST PLAN INVENTORY

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Chase Demand Strategy


SALES PRODUCTION WORKERS WORKERS WORKERSQUARTER FORECAST PLAN NEEDED HIRED FIRED

Cost of Chase Demand Strategy

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Chase Demand Strategy

Spring 80,000 80,000 80 0 20Summer 50,000 50,000 50 0 30Fall 120,000 120,000 120 70 0Winter 150,000 150,000 150 30 0

100 50

SALES PRODUCTION WORKERS WORKERS WORKERSQUARTER FORECAST PLAN NEEDED HIRED FIRED

Cost of Chase Demand Strategy

(400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

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Level Production with Excel

Inventory atend of summer

Input by user=400,000/4

Cost of level production= inventory costs + production costs

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Chase Demand with Excel

Workforce requirementscalculated by system

No. of workershired in fall

Production input by user;production =demand

Cost of chasedemand = hiring +firing + production

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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

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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

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LP MODELMinimize 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) 14-23


Setting up the Spreadsheet

Target cell;cost of solutiongoes here

Solver will put thesolution here

When model is complete, Solve

Click here nextDemand Constraint

Workforce Constraint

Production Constraint

Cells where solution appears

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Setting up the Spreadsheet

Click these boxes

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The LP Solution

Optimal production plan

Cost of optimal solution

Solution is a mixof inventory, hiringand firing

Extra report options

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Level Production for Quantum

Level = 12,000/12 = 1,000

Input by user

Excel calculates

these

Cost of level production

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Chase Demand for Quantum

Input by user

Excel calculates

these

Cost of chase demandNo. workershired in Feb.

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LP Solution for Quantum

Solver foundthis solution

Constraintequationsin these

cells

Optimal solution

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Transportation Method

1 900 1000 100 5002 1500 1200 150 5003 1600 1300 200 5004 3000 1300 200 500

Regular production cost $20/unitOvertime production cost $25/unitSubcontracting cost $28/unitInventory holding cost $3/unit-periodBeginning inventory 300 units

EXPECTED REGULAR OVERTIME SUBCONTRACTQUARTER DEMAND CAPACITY CAPACITY CAPACITY

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Transportation Tableau

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Transportation Tableau

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Burruss’ Production Plan

1 900 1000 100 0 5002 1500 1200 150 250 6003 1600 1300 200 500 10004 3000 1300 200 500 0

Total 7000 4800 650 1250 2100

REGULAR SUB- ENDINGPERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY

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Period 2’s endinginventory

Regular productionfor period 1

Cost of solution

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Excel and Transportation Method


Other Quantitative Techniques

• Linear decision rule (LDR)• Search decision rule (SDR)• Management coefficients model

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Hierarchical Nature of Planning

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Disaggregation

• Breaking an aggregate plan into more detailed plans

• Create Master Production Schedule for Material Requirements Planning

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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

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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) –

(CO until the next period of planned production) • Capable-to-promise

• quantity of items that can be produced and made available at a later date

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ATP

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ATP

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ATP

ATP in April =

ATP in May =

ATP in June =

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ATP

ATP in April = (10+100) – 70 = 40

ATP in May = 100 – 110 = -10

ATP in June = 100 – 50 = 50

= 30

= 0

Take excess units from April

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© 2014 John Wiley & Sons, Inc. - Russell and Taylor 8e 14-44

Rule Based ATP


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

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Yield Management

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Yield Management

NO-SHOWS PROBABILITY P(N < X)

0 .15 .001 .25 .152 .30 .403 .30 .70

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P(n < x) =

Cu

Cu + Co

Revenue = $100/night

Maintenance = $25/night

Overflow = $70/night

Co = $70

Cu = $100 - $25 = $75

Optimal probability of no-shows


Yield Management

NO-SHOWS PROBABILITY P(N < X)

0 .15 .001 .25 .152 .30 .403 .30 .70

Optimal probability of no-shows

P(n < x) = = .517Cu

Cu + Co

7575 + 70

.517

Hotel should be overbooked by two rooms

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Copyright 2014 John Wiley & Sons, Inc.All rights reserved. Reproduction or translation of this work beyond that permitted in section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permission Department, John Wiley & Sons, Inc. The purchaser may make back-up copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages caused by the use of these programs or from the use of the information herein.

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