Sales and Capacity Planning

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

14-2

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

14-3

Sales and Operations Planning Process

14-4

Monthly S&OP Planning Process

14-5

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

14-6

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

14-7

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

14-8

Level Production

14-9

DemandU

nits

Time

Production

Chase Demand

14-10

DemandU

nits

Time

Production

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

14-12

Pure Strategies

14-13

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

Level Production Strategy

14-14

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

Chase Demand Strategy

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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

Level Production with Excel

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Inventory atend of summer

Input by user=400,000/4

Cost of level production= inventory costs + production costs

Chase Demand with Excel

14-17

Workforce requirementscalculated by system

No. of workershired in fall

Production input by user;production =demand

Cost of chasedemand = hiring +firing + production

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

14-18

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

14-19

LP MODEL

14-20

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)

Setting up the Spreadsheet

14-21

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

Setting up the Spreadsheet

14-22

Click these boxes

The LP Solution

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Optimal production plan

Cost of optimal solution

Solution is a mixof inventory, hiringand firing

Extra report options

Level Production for Quantum

14-24

Level = 12,000/12 = 1,000

Input by user

Excel calculates

these

Cost of level production

Chase Demand for Quantum

14-25

Input by user

Excel calculates

these

Cost of chase demandNo. workershired in Feb.

LP Solution for Quantum

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Solver foundthis solution

Constraintequationsin these

cells

Optimal solution

Transportation Method

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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

Transportation Tableau

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Transportation Tableau

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Burruss’ Production Plan

14-30

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

Period 2’s endinginventory

Regular productionfor period 1

Cost of solution

Excel and Transportation Method

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Other Quantitative Techniques

• Linear decision rule (LDR)

• Search decision rule (SDR)

• Management coefficients model

14-32

Hierarchical Nature of Planning

14-33

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

Disaggregation

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• Breaking an aggregate plan into more detailed plans

• Create Master Production Schedule for Material Requirements Planning

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

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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 mad available at a

later date

ATP

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ATP

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ATP

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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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Rule Based ATPProduct 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

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

14-43

Yield Management

Yield Management

14-44

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