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5 Linking S&OP throughout the Supply Chain

# 5 Linking S&OP throughout the Supply Chain

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330  PART IV  • Planning and Controlling Operations and Supply Chains

Figure 10.8

Down the Supply Chain

S&OP

(customer)

S&OP

Pennington

S&OP

(1st-tier

supplier)

S&OP

(2nd-tier

supplier)

Of course, the information can flow downstream as well as upstream. If, for example, a key

supplier increases its capacity, such information would be useful for Pennington’s S&OP effort.

This linking of S&OP throughout the supply chain is shown in Figure 10.8. Sharing of plans

already takes place in many industries, with the results being greater coordination, improved

productivity, and fewer disruptions in the flow of goods and services through the supply chain.

10.6 Applying Optimization Modeling to S&OP

Optimization model

A class of mathematical models

used when the user seeks to optimize some objective function

subject to some constraints.

Objective function

A quantitative function that

an optimization model seeks

to optimize (i.e., maximize or

minimize).

Constraint

A quantifiable condition that

places limitations on the set of

possible solutions. The solution

to an optimization model is

acceptable only if it does not

break any of the constraints.

Example 10.11

S&OP Optimization

Modeling at Bob Irons

Industries

In Chapter 8, we introduced optimization models. As you will recall, optimization models are

a class of mathematical models used when the user seeks to optimize some objective function

subject to some constraints. An objective function is a quantitative function that we hope to

optimize (e.g., we might want to maximize profits or minimize costs). Constraints are quantifiable conditions that place limitations on the set of possible solutions (demand that must be met,

limits on materials or equipment time, etc.). A solution is acceptable only if it does not break any

of the constraints.

In order for optimization modeling to work, the user must be able to state in mathematical terms both the objective function and the constraints. Once the user is able to do this, special

modeling algorithms can be used to generate solutions.

S&OP is ideally suited to such analyses. In particular, managers may be interested in understanding what pattern of resource decisions—labor, inventory, machine time, and so on—will

result in the lowest total cost while still meeting the sales forecast. In Example 10.11, we show

how Microsoft Excel’s Solver function can be used to apply optimization modeling to S&OP.

Bob Irons Industries manufactures and sells DNA testing equipment for use in cancer clinics

around the globe. Bob, the owner and CEO, has developed a spreadsheet (Figure 10.9) to help

calculate the costs associated with various sales and operations plans.

It’s worth taking a few minutes to see how Bob’s spreadsheet works. The cells that contain the planning values are highlighted, as are the columns for the sales forecast, hirings,

and layoffs, indicating that Bob can change these cells. The remaining numbers are all calculated values.

To illustrate, the calculations for January are as follows:

Sales (in labor hours) = B15 * D3 = 500 units * 20 hours per unit

= 10,000 labor hours

Sales (in worker hours) =

C15

10,000 labor hours

=

= 62.5 workers

D4

160 hours per worker

CHAPTER 10  •  Sales and Operations Planning (Aggregate Planning)

B

C

A

2

Labor hrs. per unit:

3

Worker hrs. per month:

4

Beginning & ending workforce:

5

Beginning & ending inventory:

6

7

Production cost per unit:

8

Hiring cost:

9

Layoff cost:

10

Holding cost per unit per month:

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

Month

Sales

Forecast

January

February

March

April

May

June

July

August

September

October

November

December

500

500

600

700

800

900

1,000

1,000

1,100

1,200

1,300

1,400

1,500

Totals:

12,000

Sales (in

labor hrs.)

D

E

F

G

H

331

I

20

160

100

100

Total plan cost

\$6,600,000

\$7,500

\$5,000

\$54,800

\$6,667,300 Grand total

\$550.00

\$300.00

\$200.00

\$4.00

Sales (in

workers)

10,000

12,000

14,000

16,000

18,000

20,000

20,000

22,000

24,000

26,000

28,000

30,000

62.5

75

87.5

100

112.5

125

125

137.5

150

162.5

175

187.5

Average =

125

Actual

Workers

100

125.00

125.00

125.00

125.00

125.00

125.00

125.00

125.00

125.00

125.00

125.00

125.00

Actual

Production

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

1,000.00

12,000.00

Hirings

25.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

25.00

Layoffs

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

25.00

25.00

Ending

Inventory/

Back Orders

100

600.00

1,000.00

1,300.00

1,500.00

1,600.00

1,600.00

1,600.00

1,500.00

1,300.00

1,000.00

600.00

100.00

13,700.00

Figure 10.9  S&OP Spreadsheet for Bob Irons Industries (Level Plan)

Actual workers = E14 + G15 - H15 = 100 beginning workers + 25 hires - 0 layoffs

= 125 workers

Actual production =

125 workers * 160 hours per month

E15*D4

=

= 1,000 units

D3

20 hours per unit

Ending inventory = I14 + F15 - B15 = 100 + 1,000 - 500 = 600 units

The plan shown in Figure 10.9 is, in fact, a level production plan with a total cost of

\$6,667,300. Looking at the plan, Bob wonders if he can do better. As an alternative, Bob

updates the spreadsheet to show a chase plan. The results are shown in Figure 10.10.

The results surprise Bob: The total cost for the chase plan is exactly the same as the cost for

the level plan. He wonders if there is indeed a better solution that meets all of the constraints.

Bob decides to use the Solver function of Excel to find the lowest-cost solution. To

start the process, Bob takes a few moments to identify the objective function, decision variables, and constraints for the optimization model and to match them up to his spreadsheet

(Table 10.14).

As Table 10.14 indicates, Bob will need to set up the Solver function to minimize total

costs (cell F12) by changing the hiring and layoff values (cells G15–H26). At the same time,

the cells containing the ending inventory values must stay at or above 0 for the first 11

months (cells I15–I25), and at or above 100 in the past month (cell I26).

Furthermore, Bob wants to make sure that none of the hiring or layoff numbers (cells

G15–H26) is negative. This may seem like a strange requirement, but unless Bob does this,

the model will try to reduce costs forever by endlessly offsetting a negative hire with a

negative layoff, each iteration of which would “save” +300 + +200 = +500.

332  PART IV  • Planning and Controlling Operations and Supply Chains

B

C

A

2

Labor hrs. per unit:

3

Worker hrs. per month:

4

Beginning & ending workforce:

5

Beginning & ending inventory:

6

7

Production cost per unit:

8

Hiring cost:

9

Layoff cost:

10

Holding cost per unit per month:

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

Month

Sales

Forecast

January

February

March

April

May

June

July

August

September

October

November

December

500

600

700

800

900

1,000

1,000

1,100

1,200

1,300

1,400

1,500

Totals:

12,000

Sales (in

labor hrs.)

D

E

F

G

H

I

20

160

100

100

Total plan cost

\$6,600,000

\$37,500

\$25,000

\$4,800

\$6,667,300 Grand total

\$550.00

\$300.00

\$200.00

\$4.00

Sales (in

workers)

10,000

12,000

14,000

16,000

18,000

20,000

20,000

22,000

24,000

26,000

28,000

30,000

62.5

75

87.5

100

112.5

125

125

137.5

150

162.5

175

187.5

Average =

125

Actual

Workers

100

62.50

75.00

87.50

100.00

112.50

125.00

125.00

137.50

150.00

162.50

175.00

187.50

Actual

Production

500.00

600.00

700.00

800.00

900.00

1,000.00

1,000.00

1,100.00

1,200.00

1,300.00

1,400.00

1,500.00

12,000.00

Hirings

0.00

12.50

12.50

12.50

12.50

12.50

0.00

12.50

12.50

12.50

12.50

12.50

0.00

125.00

Layoffs

37.50

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

87.50

125.00

Ending

Inventory/

Back Orders

100

100.00

100.00

100.00

100.00

100.00

100.00

100.00

100.00

100.00

100.00

100.00

100.00

1,200.00

Figure 10.10  S&OP Spreadsheet for Bob Irons Industries (Chase Plan)

Table 10.14  Description of the Optimization Problem for Bob Irons Industries

Description

Objective function:

Minimize total production, hiring, layoff, and inventory costs

By changing the following decision variables:

Hiring and layoffs

Subject to the following constraints:

Inventory in the last period must be at least 100 units

Inventory cannot go below zero (i.e., the sales forecast

must be met)

Hiring and layoff values cannot be negative

Cell Reference

F12

G15:H26

I26 Ú 100

I15:I25 Ú 0

G15:H26 Ú 0

Figure 10.11 shows the lowest-cost solution, as identified by Solver. The open dialog

box illustrates how the problem stated in Table 10.14 was encoded into Solver. The new

plan is roughly \$18,000 cheaper than either the level or the chase approach. The suggested

solution is to keep the workforce at around 92 workers for the first six months and then

bump it up to around 158 workers for the past six months. Under this plan, the inventory

level falls to zero only once (at the end of June).

CHAPTER 10  •  Sales and Operations Planning (Aggregate Planning)

333

Figure 10.11  Solver-Generated Optimal Solution for Bob Irons Industries

Microsoft® and Windows® are registered trademarks of the Microsoft Corporation in the U.S.A. and other countries. This book

is not sponsored or endorsed by or affiliated with the Microsoft Corporation. Reproduced by permission.

Before making a final decision, Bob has to consider other factors as well. The Solver

solution contains fractional workers—will it still work for whole numbers? If so, will Bob

be able to hire and train nearly 67 workers in July? Does the company have enough space

to store up to 500 units? Is the savings worth the added complexity? Solver can help Bob

identify ways to lower costs, but the final decision is Bob’s, not the spreadsheet’s.

Chapter Summary

S&OP fills the gap between long-term strategic planning and shortterm planning and control. Through S&OP, firms can not only plan

and coordinate efforts in their own functional areas—operations,

marketing, finance, human resources, and so on—but also effectively communicate to other members of the supply chain what

they expect to accomplish over the intermediate time horizon.

In this chapter, we described several approaches to S&OP

and demonstrated the power of the technique. We discussed

when and where top-down versus bottom-up planning can be

used and showed three basic approaches to S&OP: level, chase,

and mixed production.

We also touched on some of the qualitative issues surrounding S&OP: How do we select a plan? How can we use

S&OP to foster agreement and cooperation among the various

parties? How can we organize for S&OP?

We also argued for increased sharing of S&OP information

across the supply chain. As information technologies become

more sophisticated and organizations put more emphasis on

the supply chain, we can expect to see more and more sharing

of S&OP between supply chain partners. Finally, we ended the

chapter with a discussion of how optimization modeling techniques can be applied to the S&OP process.

Key Formulas

Ending inventory level (page 318):

EIt = EIt - 1 + RPt + OPt - St 

where:

EIt

RPt

OPt

St

=

=

=

=

ending inventory for time period t

regular production in time period t

overtime production in time period t

sales in time period t

(10.1)

334  PART IV  • Planning and Controlling Operations and Supply Chains

Net cash flow (page 322):

(10.2)

Net cash flow = cash inflows - cash outflows

Key Terms

Aggregate planning  311

Bottom-up planning  313

Chase production plan  317

Constraint  330

Detailed planning and control  312

Level production plan  316

Mixed production plan  317

Net cash flow  322

Objective function  330

Optimization model  330

Planning values  313

Rolling planning horizon  325

Sales and operations planning

(S&OP)  311

Strategic planning  311

Tactical planning  312

Tiered workforce  328

Top-down planning  313

Yield management  327

Solved Problem

P r o b l e m Hua Ng Exporters

Hua Ng Exporters makes commercial exercise equipment that is sold primarily in Europe and

the United States. Hua Ng’s two major product lines are stair steppers and elliptical machines.

Resource requirements for both product lines, as well as six-month forecasts, are as follows:

Product Line

Stair steppers

Ellipticals

Labor Hours

Per Unit

Fabrication

Hours Per Unit

Assembly Line

Hours Per Unit

2.5

1.0

0.8

1.8

0.15

0.20

Sales Forecast

Month

Stair

Ellipticals

1

2

3

4

5

6

560

560

545

525

525

525

400

400

415

435

435

435

Assuming that Hua Ng follows a chase production plan, develop load profiles for the next six

months for labor, fabrication, and assembly line hours. Interpret the results.

Solution

The first step is to translate the sales forecasts for the two product lines into resource requirements. This will require us to calculate and then combine the resource needs for both product

lines. Table 10.15 shows the results.

To illustrate how we arrived at these results, we calculated the total labor hours for month 1

as follows:

(560 stair steppers)(2.5 hours) + (400 ellipticals)(1 hour) = 1,400 + 400 = 1,800 hours

The remaining numbers are calculated in a similar fashion. Figure 10.12 shows the load

profiles for the three resources.

CHAPTER 10  •  Sales and Operations Planning (Aggregate Planning)

335

Table 10.15  Resource Requirements at Hua Ng Exporters

Sales Forecast

Month

Stair Steppers

Ellipitcals

Total Labor

Hours

Total

Fabrication

Total

Assembly

1

2

3

4

5

6

560

560

545

525

525

525

400

400

415

435

435

435

1,800

1,800

1,777.5

1,747.5

1,747.5

1,747.5

1,168

1,168

1,183

1,203

1,203

1,203

164

164

164.75

165.75

165.75

165.75

2,000

Units

1,500

1,000

Labor hours

Fabrication hours

Assembly hours

500

0

1

2

3

4

Month

5

6

Figure 10.12  Load Profiles for Hua Ng Exporters

Total labor hours are expected to fall somewhat over time, while fabrication hours are

­expected to increase slightly. The reason is the change in the mix of products. Specifically, the

forecast for stair steppers is falling, while the forecast for ellipticals is rising.

Discussion Questions

1.Some people have argued that the process of developing

a sales and operations plan is as important as the final

numbers. How could this be?

2.How does S&OP differ from strategic capacity planning?

From detailed planning and control? What role does S&OP

play in the overall planning activities of an organization?

3.In general, under what conditions might a firm favor a level

production plan over a chase plan? A chase production

plan over a level plan?

4.Services, in general, cannot put “products” in inventory

to be consumed at some later time. How does this limit

service firms’ S&OP alternatives?

5.Why has the implementation of S&OP been described as

a three-phase process? Briefly explain the three different

phases.

6.Yield management is a powerful tool in operations and

supply chain management. It is commonly employed to

handle highly perishable products and/or services. Do you

agree? Give an example.

7.What are the advantages to a firm of coordinating its

S&OP process with key supply chain partners? What are

the potential drawbacks?

Problems

(* = easy; ** = moderate; *** = advanced)

Problems for Section 10.2: Major Approaches to S&OP

1.Consider the following information for Sandy’s Cleaning

Service:

Service

Light cleaning

Medium cleaning

Deep cleaning

Service Mix

Labor Hours

Per Job

25%

50%

30%

0.40

0.27

0.55

336  PART IV  • Planning and Controlling Operations and Supply Chains

a. (*) Calculate the weighted planning value for labor

hours per job.

b. (**) Recalculate the weighted planning value based

on a new service mix of 10%, 65%, and 25% for

light, medium, and deep cleaning, respectively. What

happened?

Month

October

November

December

January

February

March

2.Consider the following information for Covolo Diving

Gear:

Gauge

Set

Product

Mix

Machine

Hours

Per Unit

Labor

Hours

Per Unit

A20

B30

C40

70%

25%

35%

0.30

0.45

0.35

0.15

0.10

0.12

a. (*) Calculate weighted planning values for machine

hours and labor hours per gauge set. Interpret these

planning values.

b. (**) Recalculate the weighted planning values based on

a new product mix of 45%, 30%, and 25% for the A20,

B30, and C40 sets, respectively. What happened?

3.The typical monthly production mix at Bangor Industries

is as follows:

Deluxe models

Regular models

Economy models

55%

40%

35%

Each deluxe model typically requires 5 hours of labor and

10 hours of machine time. Each regular model takes 4

hours of labor and 8 hours of machine time. Finally, the

economy model needs, on average, 3.5 hours of labor and

6 hours of machine time.

a. (**) What should the weighted per-unit planning values be for labor? For machine time? What assumptions

must be made in order to use these values?

b. (**) Suppose that for the next month the mix is expected to change to 30% deluxe, 30% regular, and 40%

economy models. How would this affect the planning

values?

c. (**) When the product mix changes from month to

month, should Bangor Industries use a top-down or a

bottom-up approach to sales and operations planning?

Explain.

4.(**) On average, each unit produced by the Kantor

Company takes 0.90 worker hours and 0.02 hours of

machine time. Furthermore, each worker and machine

is available 160 hours a month. Use these planning values and the following sales forecast to estimate (1) the

number of worker hours and machine hours needed

each month and (2) the number of workers and machines needed each month. Round your estimates of the

number of workers and machines needed to the nearest

whole number.

Sales Forecast

54,000

53,000

78,000

99,000

68,000

56,000

5.Consider the following sales forecasts for products A and B:

Sales Forecasts

Month

Product A

January

February

March

April

May

June

3,500

3,300

3,200

3,000

2,700

2,600

Product B

800

1,200

1,500

1,600

1,900

2,200

Each unit of product A takes approximately 2.5 labor

hours, while each unit of product B takes only 1.8 hours.

a. (**) What is the combined (aggregate) sales forecast

for products A and B? If this were the only information you had, would you expect resource requirements

to increase or decrease from January to June?

b. (**) Use the planning value information to calculate total labor hour requirements in each month. Compare

results.

c. (**) Would top-down planning or bottom-up planning

be better suited to S&OP in this situation? Explain.

6.(**) Complete the level production plan, using the following information. The only costs you need to consider here

are layoff, hiring, and inventory costs. If you complete

the plan correctly, your hiring, layoff, and inventory costs

should match those given here.

Totals

Costs

Cost of plan

Layoff

Hiring

Inventory

25

\$50,000

25

\$75,000

\$318,344

32,224

\$193,344

Planning values

Starting inventory

Starting and ending workforce

Hours worked per month per worker

Hours per unit

Hiring cost per worker

Layoff cost per worker

Monthly per-unit holding cost

1,000

227

160

20

\$3,000

\$2,000

\$6

CHAPTER 10  •  Sales and Operations Planning (Aggregate Planning)

337

Second Table for Problem 6

Month

March

April

May

June

July

August

September

October

November

December

January

February

Forecasted

Sales

Sales in

Worker

Hours

Workers

Needed to

Meet Sales

Average = 252

Actual

Workers

Actual

Production

Layoffs

Hirings

Ending

Inventory

1,592

1,400

1,200

1,000

1,504

1,992

2,504

2,504

3,000

3,000

2,504

1,992

7.(**) Complete the chase production plan, using

the following information. The only costs you

need to consider here are layoff, hiring, and

inventory costs. If you complete the plan correctly, your hiring, layoff, and inventory costs

should match those given here.

Totals

Costs

Cost of plan

Layoff

Hiring

Inventory

250

\$500,000

250

\$750,000

\$1,322,000

12,000

\$72,000

Planning values

Starting inventory

Starting and ending workforce

Hours worked per month per

worker

Hours per unit

Hiring cost per worker

Layoff cost per worker

Monthly per-unit holding cost

1,000

227

160

20

\$3,000

\$2,000

\$6

Second Table for Problem 7

Month

March

April

May

June

July

August

September

October

November

December

January

February

Forecasted

Sales

1,592

1,400

1,200

1,000

1,504

1,992

2,504

2,504

3,000

3,000

2,504

1,992

Sales in

Worker

Hours

Workers

Needed To

Meet Sales

Average = 252

Actual

Employees

Actual

Production

Layoffs

Hirings

Ending

Inventory

338  PART IV  • Planning and Controlling Operations and Supply Chains

8.(**) Consider the following partially completed sales

and operations plan. Using the planning values and

filled-in values as a guide, complete the plan and calculate the layoff, hiring, and inventory costs. Does

this sales and operations plan reflect a chase, level, or

mixed strategy? Explain.

Layoff

Hiring

Inventory

Totals

Costs

Cost of plan

Planning values

Starting inventory

Starting and ending workforce

Hours worked per month per

worker

Hours per unit

Hiring cost per worker

Layoff cost per worker

Monthly per-unit holding cost

500

50

160

4

\$300

\$200

\$4

Second Table for Problem 8

Month

March

April

May

June

July

August

September

October

Forecasted

Sales

1,800

1,800

1,800

1,750

1,640

Sales in

Worker

Hours

Workers

Needed to

Meet Sales

Average = 252

Actual

Workers

Actual

Production

8,000

7,680

7,360

7,200

50

9.(***) (Microsoft Excel problem) Note that Problems 6

through 8 could all be solved by using a single spreadsheet

that allows the user to change the planning, “Forecasted

time the planning, “Forecasted Sales,” or “Actual Workers”

values change. Verify that your spreadsheet works by determining whether it generates the same costs for a level

production plan and a chase production plan shown in

Problems 6 and 7.

10. Castergourd Home Products makes two types of butcherblock tables: the Beefeater and the Deutschlander. The two

tables are made in the same facility and require the same

amount of labor and equipment. In addition, we know the

following:

• Each table costs \$300 to make, and each requires, on

average, 3.2 hours of labor.

• Each employee works 160 hours per month, and there

is no effective limit on the number of employees.

• The cost of hiring or laying off an employee is \$300.

• The monthly holding cost for a table is \$15.

• For planning purposes, Castergourd will begin and end

with 20 employees and 0 tables in inventory.

Layoffs

Hirings

3

0

0

0

0

0

11

0

0

0

0

0

0

0

0

0

0

14

Ending

Inventory

380

Forecasted sales for the tables are as follows:

Month

November 2016

December

January 2017

February

March

April

May

June

July

August

Beefeater

Deutschlander

650

676

624

624

696

475

566

819

754

982

3,048

2,899

3,198

2,671

2,919

3,102

2,964

2,409

3,381

3,965

a. (***) Develop a top-down level production plan for

Castergourd for the 10-month planning period. Calculate the total production, hiring, layoff, and inventory

b. (***) Repeat part a, except in this case develop a chase

production plan.

c. (**) Suppose hiring and layoff costs increase dramatically. In general, will this make a level plan look better

or worse than a chase plan? Explain.

CHAPTER 10  •  Sales and Operations Planning (Aggregate Planning)

11. (**) Consider the level production plan for Pennington

Cabinets shown in Table 10.5. Perform a cash flow analysis for this production plan, using the cash flow analysis

in Example 10.8 as a guide. Assume that each cabinet set

sold generates a cash inflow of \$2,800, while each unit

produced using regular time generates a cash outflow of

\$2,000 and each cabinet set held in inventory at the end of

the month generates a cash outflow of \$40. How does this

cash flow compare with the one for the mixed strategy

(Table 10.10)? Which plan do you think finance would

prefer?

12. Consider the following information:

Month

January

February

March

April

May

June

Forecasted Regular

Overtime

Ending

Sales

Production Production Inventory

900 units

1,100

1,300

1,500

1,700

1,600

1,250 units

1,250

1,250

1,250

1,250

1,250

0 units

0

0

0

150

350

350 units

500

450

200

0

0

Each unit sells for \$500. Regular production and overtime

production costs are \$350 and \$450 per unit, respectively.

The cost to hold a unit in inventory for one month is \$10.

a. (**) Develop a cash flow analysis for this problem. Be

sure to calculate net cash flow and cumulative net cash

flow for each month.

b. (**) Why do the net cash flows for April and May look

so much better than those for the other months? What

are the implications for building up and draining down

inventories under a level production plan?

Problems for Section 10.6: Applying Optimization

Modeling to S&OP

13. (***) (Microsoft Excel problem) Re-create the S&OP

spreadsheet used in Table 10.10 and Example 10.11. (You

do not have to build in the optimization model using the

Solver function.) While your formatting may differ, your

339

generate new results any time any of the planning, sales

forecast, or hiring/layoff values are changed. To test your

spreadsheet, change the planning values to match the

following:

A

3

4

5

6

7

8

9

10

11

C

Labor hrs. per unit:

Worker hrs. per month:

Beginning & ending workforce:

Beginning & ending inventory:

B

Production cost per unit:

Hiring cost:

Layoff cost:

Holding cost per unit per month:

D

24

150

100

100

\$475.00

\$400.00

\$300.00

\$3.00

a level production plan should be \$5,769,100, and for a

chase production plan, it should be \$5,755,600.

14. (***) (Microsoft Excel problem) Kumquats Unlimited

makes large batches of kumquat paste for use in the food

industry. These batches are made on automated production lines. Kumquats Unlimited has the capability to start

up or shut down lines at the beginning of each month, but

at a cost. If a line is up, management has determined that

it’s best to keep the line busy, even if the resulting batches

must be put in inventory.

Management has created the following Excel spreadsheet, which uses the Solver function to find the lowest-cost solution to the S&OP problem. Re-create this

spreadsheet, including the Solver optimization model

(using Example 10.11 as a guide). Your formatting does

not have to be the same, but your answers should be. Your

spreadsheet should allow the user to make changes only to

the planning values, the sales forecast, and the number of

production line start-ups and shutdowns. All other values

should be calculated. Be sure that Solver does not let inventory drop below zero at the end of any month or end June

with less inventory than was available at the beginning of

so that each batch requires 32 hours of production line

time. The new optimal cost should be \$16,215,000.

340  PART IV  • Planning and Controlling Operations and Supply Chains

D

B

E

F

C

A

1 Sales & Operations Planning Spreadsheet for Kumquats Unlimited

2 (with Solver optimization)

3

Production cost per batch: \$

4

2,400

Line hours per batch:

5

16

Production line hours per month:

6

hours

320

Cost to start up a line: \$ 25,000

7

Cost to shut down a line: \$

6,000

8

Inventory holding cost: \$

per batch, per month

300

9

Beginning and ending lines:

production lines

55

10

Beginning and ending inventory:

batches

11

100

12

Actual

Sales

(in production Production

Actual

Sales

Sales

Lines

lines)

Production

Forecast (in line hours)

Month

13

14

55

15

50

55.00

1,000

January

1,100

16,000

16

60

55.00

1,200

February

1,100

19,200

17

60

55.00

1,200

March

1,100

19,200

18

50

50.00

1,000

April

1,000

16,000

19

40

43.00

800

May

860

12,800

20

40

43.00

800

June

860

12,800

55

21

22

Total =

6000

6,020

Average =

23

50

G

H

Production costs:

Line start-up costs:

Line shutdown costs:

Inventory holding costs:

I

\$

\$

\$

\$

125,000

75,000

165,000

Grand total: \$14,964,000

Production Line Production Line

Shutdowns

Start-ups

0

0

0

0

0

0

5

5

0

0

0

5

7

0

0

12.5

Ending

Inventory

100

200

100

0

0

60

120

480

Case Study

Covolo Diving Gear, Part 2

June 15, 2017—It has been two weeks since Covolo Diving

Gear’s contentious semiannual planning meeting, and the senior staff members for Covolo Diving Gear are getting ready

to start their first monthly S&OP meeting. Gina Covolo, CEO,

gets the ball rolling:

I know it’s been a busy two weeks for all of you, and I

­appreciate you working extra time to get ready for this meeting. Production is already set for the next two months, so

we’re going to start by planning for this September through

the following August. I’ve had Patricia from marketing develop a sales forecast for these 12 months, and I’ve also had

David from manufacturing estimate manufacturing costs

and labor requirements, as well as capacity in the plant.

Mary from HR was good enough to come up with some estimates of how much it costs to hire and train new workers, as

well as the cost of laying off folks. Finally, Jack from purchasing was able to get the accounting folks to estimate the cost

of holding a gauge set in inventory for a month. So let’s see

what we’ve got.

Mary passes out the following information to all of the

attendees:

Month

Sales Forecast

September 2017

October

November

December

January 2018

30,000 gauge sets

31,500

35,000

37,000

22,000

(Continued)

Month

Sales Forecast

February

March

April

May

June

July

August

18,000

17,500

27,000

38,000

40,000

42,000

40,000

Manufacturing cost per gauge set: \$74.50

Holding cost: \$8 per gauge set per month

Average labor hours required per gauge set: 0.25 hours

Labor hours available per employee per month: 160

Plant capacity: 35,000 gauge sets per month

Cost to hire and train a new employee: \$1,250

Cost to lay off an employee: \$500

Beginning and ending workforce: 50

Beginning inventory: 10,000

Questions

1. Develop a level production plan for Covolo Diving Gear.

Could Covolo implement a pure chase plan, given the current capacity? Why? If sales continue to grow, what are the

implications for production capacity at Covolo?

2. Patricia Rodriguez, vice president of marketing, states,

“I’ve got to tell you all that I’m pretty comfortable with

the forecasts for September through November, but after

that, a lot could change. It’s just very hard to forecast for

four or more months out in this kind of market.” How will

a monthly S&OP update with rolling planning horizons

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