Planning Demand and Supply in a Supply Chain

Andy Guo

Planning Demand and Supply in a Supply Chain

Planning Demand and Supply in a Supply Chain

第二單元 (3) ： Planning Demand and Supply in a Supply Chain

郭瑞祥教授【本著作除另有註明外，採取創用CC「姓名標示－非商業性－相同方式分享」台灣3.0版授權釋出】

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Andy Guo

Outline

►Part I: Aggregate planning

►Part II: Managing predictable variability

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Aggregate Planning► A process by which a company determines levels of capacity, production,

subcontracting, inventory, stockouts, and pricing to maximize the firm’s profit over the planning horizon (3-18 months) given the demand forecast for each period.

► Focus on aggregate decisions rather than SKU level decisions.

► Identify operational parameters:

– Production rate

– Workforce

– Overtime

– Machine capacity level

– Subcontracting

– Backlog

– Inventory on hand3

Andy Guo

Information Required for Aggregate Planning

► Demand forecast for each period in the planning horizon

► Production costs

► Labor/machine hours required per unit

► Inventory holding cost

► Stockout or backlog cost

► Constraints: limits on overtime, layoffs, capital, stockouts/backlogs

– Labor costs: regular time and overtime costs

– Subcontracting cost

– Cost of changing capacity: hiring/laying off labor, machine capacity change

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Andy Guo

Aggregate Planning

► Production quantity from regular time, overtime, and subcontracted time

► Inventory held► Backlog/stockout quantity► Workforce hired/laid off► Machine capacity increase/decrease

► Capacity (regular time, overtime, subcontracted)► Inventory► Backlog/lost sales

Determinations

Tradeoffs

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Basic Strategy

► Use capacity as the lever

► Production rate synchronized with demand rate by

varying capacity of employee and machine

► Result in low inventory and high level of change in

capacity and workforce► Used when the cost of carrying inventory is very

expensive and cost to change levels of capacity and workforce are low

Chase Strategy

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Andy Guo

Basic Strategy

Time Flexibility from Workforce or Capacity Strategy

► Use utilization as the lever

► Workforce is kept stable but the number of hours

worked is varied over time

► Result in low inventory and lower average utilization

► Used when inventory carrying cost are high and

capacity is inexpensive

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Andy Guo

Basic Strategy

► Use inventory as the lever

► Stable machine capacity and workforce are maintained with

a constant output rate

► Result in large inventory and backlogs

► Used when inventory carrying costs and backlog costs are

low

Level Strategy

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Andy Guo

Scenario 1: Aggregate Planning at Red Tomato Tools

Month Demand Forecast

January 1,600

February 3,000

March 3,200

April 3,800

May 2,200

June 2,200

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Andy Guo

Costs for Red Tomato

Item Cost

Material cost $10/unit

Inventory holding cost $2/unit/month

Marginal cost of stockout/backlog $5/unit/month

Hiring and training costs $300/worker

Layoff cost $500/worker

Labor hours required 4/unit

Regular time cost $4/hour

Overtime cost $6/hour

Cost of subcontracting $30/unit

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Red Tomato

► Sell gardening tool which is highly seasonal– Peak in spring– Main capacity is “size of workforce”

► Sell each tool at $40► Starting inventory in January is 1000 tools► Starting employees in January is 80 persons► The plant has a total of 20 working days/month and 8 regular

hours/day► Ending inventory is 500► All demand must be satisfied; no stock out in the last period

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Andy Guo

Costs for Red Tomato

Item Cost

Material cost $10/unit

Inventory holding cost $2/unit/month

Marginal cost of stockout/backlog $5/unit/month

Hiring and training costs $300/worker

Layoff cost $500/worker

Labor hours required 4/unit

Regular time cost $4/hour

Overtime cost $6/hour

Cost of subcontracting $30/unit

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Andy Guo

Aggregate Planning Model

Wt = Workforce size for month t, t = 1, ...,6

Ht = Number of employees hired at the beginning of month t, t = 1, ...,6

Lt = Number of employees laid off at the beginning of month t, t = 1, ...,6

Pt = Production in month t, t = 1, ...,6

It = Inventory at the end of month t, t = 1, ...,6

St = Number of units stocked out/backlogged at the end of month t, t = 1, ...,6

Ct = Number of units subcontracted for month t, t = 1, ...,6

Ot = Number of overtime hours worked in month t, t = 1, ...,6

Define Decision Variables

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Define Objective Function

6

1

6

1

6

1

6

1

6

1

6

1

6

1

6

13010525003006640

tt

tt

tt

tt

tt

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tt CPSILHOWMin

Regular time labor cost

Overtime labor cost

Cost of hiring and layoffs

Cost of inventory and stockout

Cost of materials and subcontracting


Overtime labor cost



Regular time labor cost = 4/hr * 8 hr/day * 20 day/month= 640

Since all demands is met, revenue is fixed

maximizing profit = minimizing cost

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Andy Guo

► Workforce size for each month is based on hiring and layoffs

► Production for each month cannot exceed capacity

► Inventory balance for each month

► Overtime limit for each month

Define Constraints

80 where6,...,1fo r 01 WtLHWW tttt

6,...,1fo r 440 tOWP ttt

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Define Constraints




20*8=160 hrs4 hours/unit

160

4

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Define Constraints



0 ,0 ,500 ,000,1where

6,...,1for

600

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6

SSII

tSISDCPI ttttttt

6,...,1fo r 11 tSISDCPI ttttttt

Net supply in current

period

Net supply in previous

period

Supply Demand

DCPSISI ttttttt )()( ) ( 11

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Define Constraints



0 ,0 ,500 ,000,1where

6,...,1for

600

11

6

SSII

tSISDCPI ttttttt

6,...,1fo r 10 tWO tt

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Aggregate Planning Model









Define Decision Variables

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Defining Constraints


1604

20*8=160 hrs4 hours/unit

6,...,1fo r 11 tSISDCPI ttttttt

DCPSISI ttttttt )()( ) ( 11

Net supply in current

period

Net supply in previous

period

Supply Demand

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Evaluation of Performance

TIIIT

ttT /2/)(

1

10

Little’s law: average flow time = average inventory / throughput

► Average inventory =

► Average flow time =

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Andy Guo

Evaluation of Performance

TIIIT

ttT /2/)(

1

10

T

tt

T

ttT TDTIII

1

1

10 //2/)(

Little’s law: average flow time = average inventory / throughput

► Average inventory =

► Average flow time =

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EXCEL-DEMO









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EXCEL-DEMO

300 X B5

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EXCEL-DEMO2

6

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6

1

6

1

6

1

6

1

6

1

6

1

6

13010525003006640

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tt CPSILHOWMin


6

1

6

1

6

1

6

1

6

1

6

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6

1

6

13010525003006640

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tt

tt

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tt CPSILHOWMin


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EXCEL-DEMO3

cost

Decision Variables

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EXCEL-DEMO4

6

1

6

1

6

1

6

1

6

1

6

1

6

1

6

13010525003006640

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tt

tt

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tt CPSILHOWMin


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EXCEL-DEMO5

6

1

6

1

6

1

6

1

6

1

6

1

6

1

6

13010525003006640

tt

tt

tt

tt

tt

tt

tt

tt CPSILHOWMin

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EXCEL-DEMO6

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Define Constraints



0 ,0 ,500 ,000,1where

6,...,1for

600

11

6

SSII

tSISDCPI ttttttt

6,...,1fo r 10 tWO tt

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EXCEL-DEMO7

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Optimal Aggregate Plan for Scenario 1

Periodt

No.Hired

Ht

No. LaidOff Lt

WorkforceSize Wt

OvertimeOt

InventoryIt

StockoutSt

SubcontractCt

TotalProduction

Pt

0 0 0 80 0 1,000 0 0

1 0 15 65 0 1,983 0 0 2,583

2 0 0 65 0 1,567 0 0 2,583

3 0 0 65 0 950 0 0 2,583

4 0 0 65 0 0 267 0 2,583

5 0 0 65 0 117 0 0 2,583

6 0 0 65 0 500 0 0 2,583

► Total cost over planning horizon = $422,275► Revenue over planning horizon = 40 16,000 = $640,000► Average seasonal inventory = 895► Average flow time = 895 / 2,667 = 0.34 months

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Andy Guo

6

1

6

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6

1

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6

1

6

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1

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13010525003006640

tt

tt

tt

tt

tt

tt

tt

tt CPSILHOWMin


Overtime labor cost



Cost of materials and subcontracting


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Define Constraints



0 ,0 ,500 ,000,1where

6,...,1for

600

11

6

SSII

tSISDCPI ttttttt

6,...,1fo r 10 tWO tt

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Andy Guo


Periodt

No.Hired

Ht

No. LaidOff Lt

Workforce

Size Wt

OvertimeOt

InventoryIt

StockoutSt

SubcontractCt

TotalProducti

onPt

0 0 0 80 0 1,000 0 0

1 0 15 65 0 1,983 0 0 2,583

2 0 0 65 0 1,567 0 0 2,583

3 0 0 65 0 950 0 0 2,583

4 0 0 65 0 0 267 0 2,583

5 0 0 65 0 117 0 0 2,583

6 0 0 65 0 500 0 0 2,583

► Total cost over planning horizon = $422,275► Revenue over planning horizon = 40 16,000 = $640,000► Average seasonal inventory = 895► Average flow time = 895 / 2,667 = 0.34 months

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Andy Guo

Scenario 2: Increased Demand Fluctuation

The same overall demand (16,000 units) as scenario 1


January 1,000

February 3,000

March 3,800

April 4,800

May 2,000

June 1,400

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 15 65 0 2,583 0 0 2,583

2 0 0 65 0 2,167 0 0 2,583

3 0 0 65 0 950 0 0 2,583

4 0 0 65 0 0 1,267 0 2,583

5 0 0 65 0 0 683 0 2,583

6 0 0 65 0 500 0 0 2,583

► Total cost over planning horizon is higher = $432,858

► Average seasonal inventory = 1,075

► Average flow time = 1,075 / 2,667 = 0.40 months

► Inventories and stockouts go up compared with the plan for scenario 1

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 23 57 0 1,667 0 0 2,267

2 0 0 57 0 933 0 0 2,267

3 0 0 57 0 0 0 0 2,267

4 0 0 57 0 0 67 1,467 2,267

5 0 0 57 0 0 0 0 2,267

6 0 0 57 0 500 0 433 2,267

► Suppose holding cost is increased from $2 to $6 compared to scenario 1► Total cost over planning horizon is higher = $441,200► Average seasonal inventory = 558► Average flow time = 558 / 2,667 = 0.21 months► Inventories carried is reduced while subcontracted amount is increased

compared with the plan for scenario 1

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Andy Guo

Handle Forecast Error in Aggregate Plans

► Use safety stock or safety capacity

– Use overtime (safety capacity)

– Carry extra workforce (safety capacity)

– Use subcontractors (safety capacity)

– Build and carry extra inventory (safety inventory)

– Purchase capacity or product from open market (safety capacity)

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Andy Guo

Outline

►Part I: Aggregate planning

►Part II: Managing predictable variability

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Andy Guo

Managing Predictable Variability- Managing Supply -

► Managing capacity– Time flexibility from workforce– Use of seasonal workforce– Use of subcontracting– Use of dual facilities – dedicated and flexible– Designing product flexibility into the production

processes

► Managing inventory– Using common components across multiple products– Building inventory of high demand or predictable

demand products

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Andy Guo

Managing Predictable Variability- Managing Demand -

► Demand can be influenced using pricing and other forms of promotions.

► Four key factors influence the timing of a trade promotion:

► Demand increase from promotion results from three factors:– Market growth– Stealing market share– Forward buying

– Impact of the promotion on demand– Product margins– Cost of holding inventory– Cost of changing capacity

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Andy Guo

Scenario 4: Aggregate Planning and Promotion at Red Tomato

► Discounting a unit from $40 to $39 results in the period demand’s increasing by 10 percent because of increased consumption or substitution. Further, 20 percent of each of the two following months demand is moved forward.

► Consider the discount offering in off-peak month of January. The demand forecast is shown below:


January 3,000

February 2,400

March 2,560

April 3,800

May 2,200

June 2,200

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 15 65 0 610 0 0 2,610

2 0 0 65 0 820 0 0 2,610

3 0 0 65 0 870 0 0 2,610

4 0 0 65 0 0 320 0 2,610

5 0 0 65 0 90 0 0 2,610

6 0 0 65 0 500 0 0 2,610

► Total cost over planning horizon = $421,915► Revenue over planning horizon = $643,400► Profit over planning horizon = $221,485

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Andy Guo


Demand fluctuation has increased relative to the profile in scenario 1.


► Consider the discount offering in peak month of April.

The demand forecast is shown below:


January 1,600

February 3,000

March 3,200

April 5,060

May 1,760

June 1,760

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 14 66 0 2,047 0 0 2,647

2 0 0 66 0 1,693 0 0 2,647

3 0 0 66 0 1,140 0 0 2,647

4 0 0 66 0 0 1,273 0 2,647

5 0 0 66 0 0 387 0 2,647

6 0 0 66 0 500 0 0 2,647


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Andy Guo

Conclusions based on Scenarios 1, 4 & 5

► A price promotion in January (scenario 4) results in a higher profit than no promotion (scenario 1). A promotion in April (scenario 5) results in a lower profit than no promotion (scenario 1).

► Even though revenues are higher when promotions is offered in April, the increase in operating costs makes it a less profitable option.

► Red Tomato should offer the discount in the off-peak month of January.

► The above conclusions could be different if Red Tomato were in a situation in which most of the demand increase comes from market growth or stealing market share rather than forward buying (see scenarios 6 & 7)

► It is not appropriate for a firm to leave pricing decisions solely in the domain of marketing and aggregate planning solely in the domain of operations. It is crucial that forecasts, pricing, and aggregate planning be coordinated in the supply chain.47

Andy Guo



► Consider the discount offering in off-peak month of January. The demand forecast is shown below:


January 4,440

February 2,400

March 2,560

April 3,800

May 2,200

June 2,200

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 0 80 0 0 240 0 3,200

2 0 11 69 0 140 0 0 2,780

3 0 0 69 0 360 0 0 2,780

4 0 0 69 0 0 660 0 2,780

5 0 0 69 0 0 80 0 2,780

6 0 0 69 0 500 0 0 2,780


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Andy Guo


Demand fluctuation has increased relative to the profile in scenario 1.


► Consider the discount offering in peak month of April. The demand forecast is shown below:


January 1,600

February 3,000

March 3,200

April 8,480

May 1,760

June 1,760

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Andy Guo


Period

t

No.

Hired

Ht

No. Laid

Off Lt

Workforce

Size Wt

Overtime

Ot

Inventory

It

Stockout

St

Subcontract

Ct

Total

Production

Pt

0 0 0 80 0 1,000 0 0

1 0 0 80 0 2,600 0 0 3,200

2 0 0 80 0 2,800 0 0 3,200

3 0 0 80 0 2,800 0 0 3,200

4 0 0 80 0 0 2,380 100 3,200

5 0 0 80 0 0 940 0 3,200

6 0 0 80 0 500 0 0 3,200

► Total cost over planning horizon = $536,200► Revenue over planning horizon = $783,520► Profit over planning horizon = $247,320► When forward buying is a small part of the increase in demand from

discounting, Red Tomato should offer the discount in the peak demand month of April.

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Andy Guo

Performance Under Different Scenarios

Regular Price

Promotion Price

Promotion Period

Percent Increase in

Demand

Percent Forward Buy

Profit Average Inventory

$40 $40 NA NA NA $217,725 895

$40 $39 January 20 % 20 % $221,485 523

$40 $39 April 20% 20% $211,283 938

$40 $39 January 100% 20% $242,810 208

$40 $39 April 100% 20% $247,320 1,492

$31 $31 NA NA NA $73,725 895

$31 $30 January 100% 20% $84,410 208

$31 $30 April 100% 20% $69,120 1,492

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Conclusions Regarding Promotions

► Pricing and aggregate planning must be done jointly.

► Average inventory increases if a promotion is run during the peak period and decreases if run during off-peak period.

► Promotion during the peak period may decrease overall profitability if a significant fraction of the demand increase results from a forward buy.

► Promotion during the peak period may increase overall profitability if forward buying becomes a smaller fraction of the demand increase.

► As product margin declines, promotion during the peak period becomes less profitable.

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Andy Guo

Summary of Impact on Promotion Timing

Factor Favored timing

High forward buying Low demand period

High stealing market share High demand period

High growth of market High demand period

High margin High demand period

Low margin Low demand period

High holding costs Low demand period

High cost of changing capacity Low demand period

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Andy Guo

頁碼作品授權條件作者 /來源

9, 36本作品轉載自Microsoft Office 2007多媒體藝廊，依據Microsoft 服務合約及著作權法第 46 、 50 、 52 、 65條合理使用。

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Planning Demand and Supply in a Supply Chain

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