DB – Module 10: Inventory Management and Aggregate Planning

Aggregate Planning
and Master
Scheduling

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11-1

You should be able to:
LO 11.1
LO 11.2
LO 11.3
LO 11.4
LO 11.5
LO 11.6
LO 11.7
LO 11.8

Explain what aggregate planning is and how it is useful
Identify the variables decision makers have to work with in
aggregate planning
Describe some of the strategies that can be used for meeting
uneven demand
Describe some of the graphical and quantitative techniques
planners use
Prepare aggregate plans and compute their costs
Discuss aggregate planning in services
Disaggregate an aggregate plan
Describe the master scheduling process and explain its
importance
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11-2

 Aggregate planning
 Intermediate-range capacity planning that typically

covers a time horizon of 2 to up to 18 months
 Useful for organizations that experience seasonal or
other variations in demand
 Goal:
 Achieve a production plan that will effectively utilize the

organization’s resources to satisfy demand

LO 11.1

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11-3

LO 11.1

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11-4

 Why do organizations need to do aggregate planning?
 Planning
 It takes time to implement plans
 Strategic
 Aggregation is important because it is not possible to predict
with accuracy the timing and volume of demand for individual
items
 It is connected to the budgeting process
 It can help synchronize flow throughout the supply chain; it affects
costs, equipment utilization, employment levels, and customer
satisfaction

LO 11.1

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11-5

 The plan must be in units of measurement that can be

understood by the firm’s non-operations personnel


Aggregate units of output per month



Dollar value of total monthly output



Total output by factory



Measures that relate to capacity such as labor hours

LO 11.1

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11-6

 Most organizations use rolling 3, 6, 9, and 12

month forecasts
 Forecasts are updated periodically, rather than relying

on a once-a-year forecast
 This allows planners to take into account any changes in
either expected demand or expected supply and to
develop revised plans

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11-7

 Strategies to counter variation:
 Maintain a certain amount of excess capacity to handle increases in
demand
 Maintain a degree of flexibility in dealing with changes
 Hiring temporary workers
 Using overtime
 Wait as long as possible before committing to a certain level of
supply capacity
 Schedule products or services with known demands first
 Wait to schedule other products until their demands become
less uncertain

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11-8

Forecast of
aggregate
demand for the
intermediate
range

Develop a
general plan to
meet demand
requirements

Update the
aggregate plan
periodically
(e.g., monthly)

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11-9

 Aggregate planners are concerned with the
 Demand quantity
 If demand exceeds capacity, attempt to achieve balance by
altering capacity, demand, or both
 Timing of demand
 Even if demand and capacity are approximately equal, planners
still often have to deal with uneven demand within the planning
period

LO 11.2

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11-10

 Resources
 Workforce/production rates
 Facilities and equipment
 Demand forecast
 Policies
 Workforce changes
 Subcontracting
 Overtime
 Inventory levels/changes
 Back orders

LO 11.2

 Costs
 Inventory carrying
 Back orders
 Hiring/firing
 Overtime
 Inventory changes
 Subcontracting

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11-11

 Total cost of a plan
 Projected levels of
 Inventory
 Output

 Employment
 Subcontracting
 Backordering

LO 11.2

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11-12

 Proactive
 Alter demand to match capacity

 Reactive
 Alter capacity to match demand

 Mixed
 Some of each

LO 11.2

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11-13

 Pricing
 Used to shift demand from peak to off-peak
periods
 Price elasticity is important
 Promotion
 Advertising and other forms of promotion
 Back orders
 Orders are taken in one period and deliveries
promised for a later period
 New demand
 Create new demand to absorb excess capacity
generated due to peak time demands

LO 11.2

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11-14

 Hire and layoff workers
 Overtime/slack time
 Part-time workers
 Inventories

 Subcontracting

LO 11.2

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11-15

Maintain a level workforce
2. Maintain a steady output rate
3. Match demand period by period
4. Use a combination of decision variables
1.

LO 11.3

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11-16

 Level capacity strategy:
 Maintaining a steady rate of regular-time output while

meeting variations in demand by a combination of
options:
 Inventories, overtime, part-time workers, subcontracting,

and back orders

 Chase demand strategy:
 Matching capacity to demand; the planned output for a

period is set at the expected demand for that period

LO 11.3

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11-17

 Capacities are adjusted to match demand

requirements over the planning horizon
 Advantages
 Investment in inventory is low
 Labor utilization in high

 Disadvantages
 The cost of adjusting output rates and/or workforce levels

LO 11.3

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11-18

 Capacities are kept constant over the planning

horizon
 Advantages
 Stable output rates and workforce

 Disadvantages
 Greater inventory costs
 Increased overtime and idle time
 Resource utilizations vary over time

LO 11.3

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11-19

 General procedure:
1. Determine demand for each period
2. Determine capacities for each period
3. Identify pertinent company or departmental policies

4. Determine unit costs
5. Develop alternative plans and costs
6. Select the plan that best satisfies objectives. Otherwise return to step 5.

LO 11.4

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11-20

 Trial-and-error approaches consist of developing simple

tables or graphs that enable planners to visually compare
projected demand requirements with existing capacity
 Alternatives are compared based on their total costs
 Disadvantage of such an approach is that it does not
necessarily result in an optimal aggregate plan

LO 11.4

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11-21

Period

1

2

3

4

5

Total

Forecast
Output
Regular time
Overtime
Subcontract
Output – Forecast
Inventory
Beginning
Ending
Average
Backlog
Costs Output
Regular
Overtime
Subcontract
Hire/Lay of
Inventory
Back orders
Total

TABLE 11.4 Worksheet/spreadsheet
LO 11.4

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McGraw-Hill Education.

LO 11.4

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11-23

 Linear programming models
 Methods for obtaining optimal solutions to problems

involving the allocation of scarce resources in terms of
cost minimization or profit maximization.
 Simulation models
 Computerized models that can be tested under different

scenarios to identify acceptable solutions to problems

LO 11.4

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11-24

LO 11.5

11-25

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McGraw-Hill Education.

Period

1

2

3

4

5

6

Total

Forecast

200

200

300

400

500

200

1,800

Costs
Output
Regular time = $2 per skateboard
Overtime
= $3 per skateboard
Subcontract = $6 per skateboard
Inventory
= $1 per skateboard per period on average inventory
Back orders
= $5 per skateboard per period
Planners for a company that makes several models of skateboards are about to
prepare an aggregate plan that will cover six periods.

They want to evaluate a plan that calls for a steady rate of regular-time output,
mainly using inventory to absorb the uneven demand but allowing some backlog.
Overtime and subcontracting are not used because they want steady output.
They intend to start with zero inventory on hand in the first period.

LO 11.5

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11-26

Period

1

2

3

4

5

6

Total

Forecast

200

200

300

400

500

200

1,800

Regular time

300

300

300

300

300

300

1,800

Overtime

—

—

—

—

—

—

Subcontract

—

—

—

—

—

—

100

100

0

(100)

(200)

100

Beginning

0

100

200

200

100

0

Ending

100

200

200

100

0

0

Average

50

150

200

150

50

0

600

0

0

0

0

100

0

100

Output

Inventory
Output 2 Forecast

0

Inventory

Backlog

LO 11.5

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11-27

Period

1

2

3

4

5

6

Total

Regular time

$600

$600

$600

$600

$600

$600

Overtime

—

—

—

—

—

—

Subcontract

—

—

—

—

—

—

Hire/Layoff

—

—

—

—

—

—

Inventory

$50

$150

$200

$150

$50

$0

$600

Backlog

$0

$0

$0

$0

$500

$0

$500

$650

$750

$800

$750

$1,150

$600

$4,700

Costs
Output

Total

LO 11.5

$3,600

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11-28

Technique

Solution Approach

Characteristics

Spreadsheet

Heuristic (trial and
error)

Intuitively appealing, easy to understand;
solution not necessarily optimal

Linear programming

Optimizing

Computerized; linear assumptions not always
valid

Simulation

Heuristic (trial and
error)

Computerized model can be examined under a
variety of conditions

TABLE 11.7 Summary of mathematical planning techniques
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11-29

 Hospitals:
 Aggregate planning used to allocate funds, staff, and supplies to meet the

demands of patients for their medical services
 Airlines:
 Aggregate planning in this environment is complex due to the number of

factors involved
 Capacity decisions must take into account the percentage of seats to be
allocated to various fare classes in order to maximize profit or yield
 Restaurants:
 Aggregate planning in high-volume businesses is directed toward

smoothing the service rate, determining workforce size, and managing
demand to match a fixed capacity
 Can use inventory; however, it is perishable

LO 11.6

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11-30

 The resulting plan in services is a time-phased projection

of service staff requirements
 Aggregate planning in manufacturing and services is
similar, but there are some key differences:
1.

2.
3.
4.

LO 11.6

Demand for service can be difficult to predict
Capacity availability can be difficult to predict
Labor flexibility can be an advantage in services
Services occur when they are rendered

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11-31

 Yield management
 An approach to maximizing revenue by using a strategy

of variable pricing; prices are set relative to capacity
availability
 During periods of low demand, price discounts are
offered
 During periods of peak demand, higher prices are
charged
 Users of yield management include
 Airlines, restaurants, hotels, restaurants

LO 11.6

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11-32

Aggregate
Plan

Disaggregation

Master
Schedule

LO 11.7

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11-33

 Master schedule:
 The result of disaggregating an aggregate plan
 Shows quantity and timing of specific end items for a

scheduled horizon

LO 11.7

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11-34

 The heart of production planning and control
 It determines the quantity needed to meet demand from all sources
 It interfaces with
 Marketing
 Capacity planning
 Production planning

 Distribution planning

 Provides senior management with the ability to determine whether

the business plan and its strategic objectives will be achieved

LO 11.8

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11-35

Period

1

2

“frozen”
(firm or
fixed)

LO 11.8

3

4

5

“slushy”
somewhat
firm

6

7

8

9

“liquid”
(open)

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11-36

Inputs

Outputs

Beginning inventory
Forecast

Customer orders

LO 11.8

Projected inventory
Master
Scheduling

Master production schedule
Uncommitted inventory

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11-37

 The master production schedule (MPS) is one of the

primary outputs of the master scheduling process
 Once a tentative MPS has been developed, it must be validated

 Rough cut capacity planning (RCCP) is a tool used in

the validation process
 Approximate balancing of capacity and demand to test the

feasibility of a master schedule
 Involves checking the capacities of production and warehouse

facilities, labor, and vendors to ensure no gross deficiencies exist
that will render the MPS unworkable

LO 11.8

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11-38

LO 11.8

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11-39

LO 11.8

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11-40

LO 11.8

Week

Inventory
from
Previous
Week

Requirements

Inventory
before MPS

1

64

33

31

31

2

31

30

1

1

3

1

30

-29

4

41

30

11

5

11

40

-29

6

41

40

1

7

1

40

-39

+

70

=

31

8

31

40

-9

+

70

=

61

(70)
MPS

+

70

Projected
Inventory

=

41
11

+

70

=

41
1

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11-41

LO 11.8

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11-42

LO 11.8

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11-43

Inventory
Management

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written consent of McGraw-Hill Education.

You should be able to:
LO 12.1
LO 12.2
LO 12.3
LO 12.4
LO 12.5
LO 12.6
LO 12.7
LO 12.8

Define the term inventory
List the different types of inventory
Describe the main functions of inventories
Discuss the main requirements for effective management
Explain periodic and perpetual review systems
Describe the costs that are relevant for inventory management
Describe the A-B-C approach and explain how it is useful
Describe the basic EOQ model and its assumptions and solve typical
problems
LO 12.9 Describe the economic production quantity model and solve typical
problems
LO 12.10 Describe the quantity discount model and solve typical problems
LO 12.11 Describe reorder point models and solve typical problems
LO 12.12 Describe situations in which the fixed-order interval model is appropriate,
and solve typical problems
LO 12.13 Describe situations in which the single-period model is appropriate and
solve typical problems

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12-2

 Inventory
 A stock or store of goods

 Independent-demand items
 Items that are ready to be sold or used
Inventories are a vital part of business: (1) necessary for
operations and (2) contribute to customer satisfaction
A “typical” firm has roughly 30% of its current
assets and as much as 90% of its working capital
invested in inventory

LO 12.1

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12-3

 Raw materials and purchased parts
 Work-in-process (WIP)
 Finished goods inventories or merchandise
 Tools and supplies

 Maintenance and repairs (MRO) inventory
 Goods-in-transit to warehouses or customers (pipeline

inventory)

LO 12.2

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12-4

 Inventories serve a number of functions such as:
1.
To meet anticipated customer demand
2. To smooth production requirements
3. To decouple operations
4. To protect against stockouts
5. To take advantage of order cycles
6. To hedge against price increases
7. To permit operations
8. To take advantage of quantity discounts

LO 12.3

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12-5

 Inventory management has two main concerns:
1. Level of customer service
 Having the right goods available in the right quantity in the
right place at the right time
2. Costs of ordering and carrying inventories
 The overall objective of inventory management is to achieve
satisfactory levels of customer service while keeping
inventory costs within reasonable bounds
1. Measures of performance
2. Customer satisfaction
 Number and quantity of backorders
 Customer complaints
3. Inventory turnover
LO 12.3

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12-6

 Ratio of annual cost of goods sold to average

inventory investment
 How many times a year the inventory is sold
 Higher the better as it implies more efficient use of the

inventory

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12-7

 Requires:
1.
A system keep track of inventory
2. A reliable forecast of demand
3. Knowledge of lead time and lead time variability
4. Reasonable estimates of

Holding costs

Ordering costs

Shortage costs
5. A classification system for inventory items

LO 12.4

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12-8

 Periodic system
 Physical count of items in inventory made at periodic

intervals
 Perpetual inventory system
 System that keeps track of removals from inventory

continuously, thus monitoring current levels of each
item
 An order is placed when inventory drops to a

predetermined minimum level
 Two-bin system
 Two containers of inventory; reorder when the first is empty

LO 12.5

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12-9

 Universal product code (UPC)
 Bar code printed on a label that has information about

the item to which it is attached
 Radio frequency identification (RFID) tags
 A technology that uses radio waves to identify objects,

such as goods, in supply chains

LO 12.5

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12-10

 Purchase cost
 The amount paid to buy the inventory

 Holding (carrying) costs
 Cost to carry an item in inventory for a length of time, usually

a year

 Ordering costs
 Costs of ordering and receiving inventory

 Setup costs
 The costs involved in preparing equipment for a job
 Analogous to ordering costs

 Shortage costs
 Costs resulting when demand exceeds the supply of

inventory; often unrealized profit per unit

LO 12.6

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12-11

 A-B-C approach
 Classifying inventory according to some measure of importance, and

allocating control efforts accordingly
 A items (very important)
 10 to 20 percent of the number of items in inventory and about 60 to 70
percent of the annual dollar value
 B items (moderately important)
 C items (least important)
 50 to 60 percent of the number
of items in inventory but only
about 10 to 15 percent of the
annual dollar value

LO 12.7

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12-12

 Cycle counting
 A physical count of items in inventory

 Cycle counting management
 How much accuracy is needed?
 A items: ± 0.2 percent

 B items: ± 1 percent
 C items: ± 5 percent
 When should cycle counting be performed?
 Who should do it?

LO 12.7

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12-13

 Economic order quantity models identify the optimal

order quantity by minimizing the sum of annual costs
that vary with order size and frequency
1.
2.
3.

LO 12.8

The basic economic order quantity model
The economic production quantity model
The quantity discount model

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12-14

 The basic EOQ model is used to find a fixed order

quantity that will minimize total annual inventory
costs
 Assumptions:
1.

2.
3.
4.
5.

6.

LO 12.8

Only one product is involved
Annual demand requirements are known
Demand is even throughout the year
Lead time does not vary
Each order is received in a single delivery
There are no quantity discounts

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12-15

Profile of Inventory Level Over Time

Q

Usage
rate

Quantity
on hand

Reorder
point

Receive
order

Place
order

Receive
order

Time
Place
order

Receive
order

Lead time

LO 12.8

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12-16

Total Cost = Annual Holding Cost + Annual Ordering Cost
=

Q
H
2

+

D
S
Q

where
Q = Order quantity in units
H = Holding (carrying) cost per unit, usually per year
D = Demand, usually in units per year
S = Ordering cost per order

LO 12.8

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12-17

Annual Cost

The Total-Cost Curve Is U-Shaped
Q
D
TC = H + S
2
Q
Holding Costs

Ordering Costs

QO (optimal order quantity)

LO 12.8

Order Quantity
(Q)

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12-18

 Using calculus, we take the derivative of the total cost

function and set the derivative (slope) equal to zero and
solve for Q.
 The total cost curve reaches its minimum where the
carrying and ordering costs are equal.

 Length of the optimal order cycle = Q0 / D

LO 12.8

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12-19

 The batch mode is widely used in production. In certain

instances, the capacity to produce a part exceeds its usage
(demand rate).
 Assumptions
 Only one item is involved

 Annual demand requirements are known
 Usage rate is constant
 Usage occurs continually, but production occurs periodically
 The production rate is constant
 Lead time is known and constant

 There are no quantity discounts

LO 12.9

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12-20

Q
Production
and usage

Usage
only

Production
and usage

Usage
only

Production
and usage

Qp
Cumulative
production

Imax

Amount
on hand

Time

LO 12.9

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12-21

TC min = Carrying Cost + Setup Cost
æI ö
D
max
=ç
÷H + S
Q
è 2 ø
where
I max = Maximum inventory
=

Qp

p – u)
(
p

p = Production or delivery rate
u = Usage rate

LO 12.9

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McGraw-Hill Education.

12-22

2 DS
Qp =
H

LO 12.9

p
p −u

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12-23

 Other parameters

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consent of McGraw-Hill Education.

12-24

 Quantity discount
 Price reduction for larger orders offered to customers to

induce them to buy in large quantities
Total Cost = Carrying Cost + Ordering Cost + Purchasing Cost
Q
D
= H + S + PD
2
Q
where
P = Unit price

LO 12.10

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McGraw-Hill Education.

12-25

LO 12.10

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12-26

The total-cost curve
with quantity discounts
is composed of a
portion of the total-cost
curve for each price

LO 12.10

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12-27

 Reorder point
 When the quantity on hand of an item drops to this amount, the
item is reordered.
 Determinants of the reorder point
1.
The rate of demand
2. The lead time
3. The extent of demand and/or lead time variability
4. The degree of stockout risk acceptable to management

LO 12.11

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12-28

ROP = d  LT
where
d = Demand rate (units per period, per day, per week)
LT = Lead time (in same time units as d )

LO 12.11

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12-29

 Demand or lead time uncertainty creates the possibility

that demand will be greater than available supply
 To reduce the likelihood of a stockout, it becomes
necessary to carry safety stock
 Safety stock

 Stock that is held in excess of expected demand due to variable

demand and/or lead time

Expected demand
ROP =
+ Safety Stock
during lead time
LO 12.11

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12-30

LO 12.11

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12-31

 As the amount of safety stock carried increases, the

risk of stockout decreases.
 This improves customer service level

 Service level
 The probability that demand will not exceed supply during lead
time
 Service level = 100% − stockout risk

LO 12.11

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12-32

 The amount of safety stock that is appropriate for a

given situation depends upon:
The average demand rate and average lead time
2. Demand and lead time variability
3. The desired service level
1.

Expected demand
ROP =
+ z dLT
during lead time
where
z = Number of standard deviations

 dLT = The standard deviation of lead time demand
LO 12.11

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12-33

The ROP based
on a normal
distribution of lead
time demand

LO 12.11

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12-34

ROP = d  LT + z d LT
where
z = Number of standard deviations
d = Average demand per period (per day, per week)

 d = The stdev. of demand per period (same time units as d )
LT = Lead time (same time units as d )
Note: If only demand is variable, then  dLT =  d

LO 12.11

LT

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12-35

ROP = d  LT + zd LT
where
z = Number of standard deviations
d = Demand per period (per day, per week)

 LT = The stddev. of lead time (same time units as d )
LT = Average lead time (same time units as d )
Note: If only lead time is variable, then  dLT = d LT

LO 12.11

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12-36

 Fixed-order-interval (FOI) model
 Orders are placed at fixed time intervals
 Reasons for using the FOI model
 Supplier’s policy may encourage its use
 Grouping orders from the same supplier can produce savings in
shipping costs
 Some circumstances do not lend themselves to continuously
monitoring inventory position

LO 12.12

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McGraw-Hill Education.

12-37

Fixed Quantity

Fixed Interval

LO 12.12

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12-38

Expected demand
Amount = during protection + Safety − Amount on hand
to Order
at reorder time
stock
interval
= d (OI + LT) + z d OI + LT − A
where
OI = Order interval (length of time between orders)
A = Amount on hand at reorder time

LO 12.12

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12-39

 Single-period model
 Model for ordering of perishables and other items with limited
useful lives
 Shortage cost
 Generally, the unrealized profit per unit
 Cshortage = Cs = Revenue per unit – Cost per unit
 Excess cost
 Different between purchase cost and salvage value of items left
over at the end of the period
 Cexcess = Ce = Cost per unit – Salvage value per unit

LO 12.13

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12-40

 The goal of the single-period model is to identify the order

quantity that will minimize the long-run excess and
shortage costs
 Two categories of problem:
 Demand can be characterized by a continuous distribution

 Demand can be characterized by a discrete distribution

LO 12.13

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12-41

Cs
Service level =
C s + Ce
where
Cs = shortage cost per unit
Ce = excess cost per unit
Ce

Cs

Service level
Quantity
So
Balance Point

LO 12.13

So =Optimum
Stocking Quantity

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McGraw-Hill Education.

12-42

MRP and ERP

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written consent of McGraw-Hill Education.

12-1

You should be able to:
LO 13.1
LO 13.2
LO 13.3
LO 13.4
LO 13.5
LO 13.6
LO 13.7
LO 13.8

Describe the conditions under which MRP is most appropriate
Describe the inputs, outputs, and nature of MRP processing
Explain how requirements in a master production schedule are
translated into material requirements for lower-level items
Discuss the benefits and requirements of MRP
Describe some of the difficulties users have encountered with MRP
Describe MRP II and its benefits
Explain how an MRP system is useful in capacity requirements
planning
Describe ERP, what it provides, and its hidden costs

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13-2

 Material requirements planning (MRP):
 A computer-based information system that translates

master schedule requirements for end items into timephased requirements for subassemblies, components,
and raw materials
 The MRP is designed to answer three questions:
What is needed?
2. How much is needed?
3. When is it needed?
1.

LO 13.2

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13-3

LO 13.2

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13-4

 Master schedule:
 One of three primary inputs in MRP; states which end items are to

be produced, when these are needed, and in what quantities
 Managers like to plan far enough into the future so they have

reasonable estimates of upcoming demands
 The master schedule should cover a period that is at least equivalent

to the cumulative lead time
 Cumulative lead time
 The sum of the lead times that sequential phases of a process

require, from ordering of parts or raw materials to completion of
the final assembly

LO 13.2

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McGraw-Hill Education.

13-5

LO 13.2

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13-6

 Bill of Materials (BOM)
 A listing of all of the assemblies, subassemblies, parts,

and raw materials needed to produce one unit of a
product
 Product structure tree
 A visual depiction of the requirements in a bill of materials,

where all components are listed by levels

LO 13.2

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McGraw-Hill Education.

13-7

LO 13.2

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13-8

 Low-level coding
 Restructuring the bill of materials so that multiple

occurrences of a component all coincide with the lowest
level at which the component occurs
X

Level 0
Level 1

LO 13.2

B(2)

Level 2

D(3)

Level 3

E(4)

C
F(2)
E

E(2)

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13-9

 Inventory records
 Includes information on the status of each item by time period,
called time buckets
 Information about
 Gross requirements
 Scheduled receipts

 Expected amount on hand
 Other details for each item such as
 Supplier
 Lead time
 Lot size policy

 Changes due to stock receipts and withdrawals
 Canceled orders and similar events

LO 13.2

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13-10

LO 13.2

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13-11

 Primary Outputs
 Planned orders
 A schedule indicating the amount and timing of future
orders
 Order releases
 Authorizing the execution of planned orders
 Changes
 Revisions of the dates or quantities, or the cancellation of
orders

LO 13.2

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13-12

 Secondary Outputs
 Performance-control reports
 Evaluation of system operation, including deviations from plans
and cost information
 e.g., missed deliveries and stockouts

 Planning reports
 Data useful for assessing future material requirements
 e.g., purchase commitments

 Exception reports
 Data on any major discrepancies encountered
 e.g., late and overdue orders, excessive scrap rates, requirements for

nonexistent parts

LO 13.2

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McGraw-Hill Education.

13-13

 MRP processing takes the end item requirements

specified by the master schedule and “explodes” them
into time-phased requirements for assemblies, parts,
and raw materials offset by lead times

LO 13.3

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13-14

Week Number

1

2

3

4

5

6

Gross Requirements
Scheduled Receipts
Projected on hand
Net requirements
Planned-order-receipt
Planned-order release

Gross requirements
• Total expected demand

Scheduled receipts
• Open orders scheduled to arrive

Projected Available
• Expected inventory on hand at the beginning of each time
period
LO 13.3

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McGraw-Hill Education.

13-15

Week Number

1

2

3

4

5

6

Gross Requirements
Scheduled Receipts

Projected on hand
Net requirements
Planned-order-receipt

Planned-order release

Net requirements
• Actual amount needed in each time period

Planned-order receipts
• Quantity expected to received at the beginning of the period
offset by lead time

Planned-order releases
• Planned amount to order in each time period
LO 13.3

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13-16

 The MRP is based on the product structure tree diagram
 Requirements are determined level by level, beginning

with the end item and working down the tree
 The timing and quantity of each “parent” becomes the basis for

determining the timing and quantity of the “children” items directly
below it
 The “children” items then become the “parent” items for the next
level, and so on

LO 13.3

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McGraw-Hill Education.

13-17

Shutter

Frames (2)

LO 13.3

Wood
sections (4)

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13-18

LO 13.3

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13-19

 Pegging
 The process of identifying the parent items that have

generated a given set of material requirements for an
item

LO 13.3

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13-20

 An MRP is not a static document
 As time passes
 Some orders get completed
 Other orders are nearing completion
 New orders will have been entered
 Existing orders will have been altered
 Quantity changes
 Delays
 Missed deliveries

LO 13.3

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McGraw-Hill Education.

13-21

 Two basic systems
 Regenerative system
 Approach that updates MRP records periodically
 Essentially a batch system that compiles all changes that occur

within the time interval and periodically updates the system
 A revised production plan is developed in the same way the
original plan was developed

 Net-change system
 Approach that updates MRP records continuously
 The production plan is modified to reflect changes as they occur

 Only the changes are exploded through the system

LO 13.3

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McGraw-Hill Education.

13-22

 Safety Stock
 Theoretically, MRP systems should not require safety stock
 Variability may necessitate the strategic use of safety stock
 A bottleneck process or one with varying scrap rates may cause
shortages in downstream operations
 Shortages may occur if orders are late or fabrication or assembly
times are longer than expected
 When lead times are variable, the concept of safety time is often
used
 Safety time
 Scheduling orders for arrival or completion sufficiently ahead of

their need so that the probability of shortage is eliminated or
significantly reduced

LO 13.3

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McGraw-Hill Education.

13-23

 Lot-for-Lot (L4L) ordering

 The order or run size is set equal to the demand for that period
 Minimizes investment in inventory
 Results in variable order quantities
 A new setup is required for each run
 Economic Order Quantity (EOQ)
 Can lead to minimum costs if usage of item is fairly uniform
 This may be the case for some lower-level items that are common to different

‘parents’
 Less appropriate for ‘lumpy demand’ items because inventory remnants often
result

 Fixed Period Ordering
 Provides coverage for some predetermined number of periods

LO 13.3

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McGraw-Hill Education.

13-24

 Material goods that form a part of

product – service
 Food catering service
 Estimating quantities of ingredients
 Estimating delivery times

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consent of McGraw-Hill Education.

13-25

 Enables managers to easily
 Determine the quantities of each component for a given order size
 Know when to release orders for each component
 Be alerted when items need attention

 Additional benefits
 Low levels of in-process inventories
 The ability to track material requirements
 The ability to evaluate capacity requirements
 A means of allocating production time
 The ability to easily determine inventory usage via backflushing
 Exploding an end item’s BOM to determine the quantities of the components
that were used to make the item

LO 13.4

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McGraw-Hill Education.

13-26

 To implement an effective MRP system requires:
 A computer and the necessary software to handle computations and
maintain records
 Accurate and up-to-date
 Master schedules
 Bills of materials
 Inventory records
 Integrity of data files

LO 13.4

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McGraw-Hill Education.

13-27

 Consequence of inaccurate data
 Missing parts
 Ordering incorrect numbers of items
 Inability to stay on schedule

 Other problems
 Assumptions of constant lead times
 Products being produced differently from the BOM
 Failure to alter a BOM when customizing a product

 Inaccurate forecasts

LO 13.5

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McGraw-Hill Education.

13-28

 Manufacturing resources planning (MRP II)
 Expanded approach to production resource planning, involving

other areas of the firm in the planning process and enabling
capacity requirements planning
 Most MRP II systems have the capability of performing simulations to

answer a variety of “what if” questions so they can gain a better
appreciation of available options and their consequences

LO 13.6

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McGraw-Hill Education.

13-29

LO 13.6

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McGraw-Hill Education.

13-30

 When MRP II systems began to include feedback loops,

they were referred to as Closed Loop MRP
 Closed Loop MRP
 Systems evaluate a proposed material plan relative to available

capacity
 If a proposed plan is not feasible, it must be revised
 This evaluation is referred to as capacity requirements planning

LO 13.6

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McGraw-Hill Education.

13-31

 Capacity requirements planning (CRP)
 The process of determining short-range capacity requirements.
 Inputs to capacity requirement planning
 Planned-order releases for the MRP
 Current shop loading
 Routing information
 Job time
 Key outputs
 Load reports for each work center

LO 13.7

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McGraw-Hill Education.

13-32

 Load reports
 Department or work center reports that compare known

and expected future capacity requirements with
projected capacity availability

LO 13.7

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McGraw-Hill Education.

13-33

 Enterprise resource planning (ERP)
 ERP was the next step in an evolution that began with MRP and

evolved into MRPII
 ERP, like MRP II, typically has an MRP core
 ERP provides a system to capture and make data available in real

time to decision makers and other users throughout an
organization
 ERP systems are composed of a collection of integrated modules

LO 13.8

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McGraw-Hill Education.

13-34

Module

Brief Description

Accounting/Finance

A central component of most ERP systems. It provides a range of financial reports,
including general ledger, accounts payable, accounts receivable, payroll, income
statements, ad balance sheets

Marketing

Supports lead generation, target marketing, direct mail, and sales

Human Resources

Maintains a complete data base of employee information such as date of hire,
salary, contact information, performance evaluations, and other pertinent
information

Purchasing

Facilitates vendor selection, price negotiation, making purchasing decisions, and
bill payment

Production Planning

Integrates information on forecasts, orders, production capacity, on-hand
inventory quantities, bills of material, work in process, schedules, and production
lead times

Inventory Management

Identifies inventory requirements, inventory availability, replenishment rules, and
inventory tracking

Distribution

Contains information on third-party shippers, shipping and delivery schedules,
delivery tracking

Sales

Information on orders, invoices, order tracking, and shipping

Supply Chain Management

Facilitates supplier and customer management, supply chain visibility, and event
management

LO 13.8

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McGraw-Hill Education.

13-35

 The ‘big bang’
 Companies cast off all of their legacy systems at once and implement a

single ERP system across the entire company
 The most ambitious and difficult implementation approach
 Franchising strategy
 Independent ERP systems are installed in each business unit of the

enterprise while linking common processes across the enterprise
 Suits large or diverse companies that do not share many common processes
across business units
 Slam dunk
 ERP dictates the process design where the focus is on a few key processes

 More appropriate for smaller companies expecting to grow into ERP

LO 13.8

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McGraw-Hill Education.

13-36

 How can ERP improve a company’s business performance?
 How long will an ERP implementation project take?
 How will ERP affect current business processes?
 What is the ERP total cost of ownership?

 What are the hidden costs of ERP ownership?

LO 13.8

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McGraw-Hill Education.

13-37

DB – Module 10: Inventory Management and Aggregate Planning
In this module, you will learn about inventory management and aggregate planning. The focus
of aggregate planning is intermediate-range capacity planning. Usually, the intermediate-range
covers the 2- to 12-month time horizon. It is important to consider aggregate planning so as to
balance supply with the demand an organization expects in the intermediate time horizon.

Question Requirements:
Discussion Topic

Enterprise Resource Planning
Enterprise resource planning (ERP) is a computerized system designed to connect all parts of a
business organization as well as key portions of its supply chain to a single database for the
purpose of information sharing.
Telecomm Systems is a small organization offering satellite internet and mobile phone services
that wants to expand their reach internationally. Their decision making process is long and
time-consuming because they rely on paper reports created by various individuals throughout
the organization to evaluate decisions. Before expanding their service internationally, they have
decided to implement an ERP system.
• Discuss three benefits the organization will achieve by using ERP.
• Discuss three disadvantages the organization might face while implementing ERP.
• Discuss how the use of ERP impacts planning and scheduling in the organization.
Directions:
• Discuss the concepts, principles, and theories from your textbook. Cite your textbooks
and cite any other sources if appropriate.
• Your initial post should address all components of the question with a 500 word limit.
Learning Outcomes
• Analyze how to manage resources to match supply and demand using inventory
management and scheduling.
• Examine the use of enterprise resource planning (ERP) systems in an organization.
• Evaluate the use of aggregate planning in an organization.
Readings
Required:
• Chapters 11, 12, & 13 in Operations Management
• Chapters 11, 12, & 13 PowerPoint Presentations
• Corban, T., & Jun Liu. (2023). Accounting Digital Transformation: As the ERP landscape
evolves, organizations can implement a digital transformation that accounts for changing
business needs. Strategic Finance, 105(5), 65–67.
Recommended:
• Leseure, M. (2024). From Aggregate Production Planning to Aggregate Energy Industrial
Consumption Plans. Energies, 17(24), 6388.
• Leong, W. Y., Wong, K. Y., & Anjomshoae, A. (2025). A systematic literature review of
Aggregate Production Planning (APP): Social and economic perspectives. Journal of
Industrial Engineering and Management, 18(1), 48-71.

Operations Management

Operations Management
FOURTEENTH EDITION

William J. Stevenson
Saunders College of Business

Rochester Institute of Technology

OPERATIONS MANAGEMENT, FOURTEENTH EDITION
Published by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121. Copyright © 2021 by McGraw-Hill
Education. All rights reserved. Printed in the United States of America. Previous editions © 2018, 2015, and
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Library of Congress Cataloging-in-Publication Data
Library of Congress Cataloging-in-Publication Data
Names: Stevenson, William J., author.
Title: Operations management / William J. Stevenson, Saunders College of
Business, Rochester Institute of Technology.
Description: Fourteenth edition. | New York, NY : McGraw-Hill Education,
[2021] | Includes bibliographical references and index.
Identifiers: LCCN 2019044799 | ISBN 9781260238891 (bound edition ;
acid-free paper) | ISBN 126023889X (bound edition ; acid-free paper) |
ISBN 9781260718423 (loose-leaf edition ; acid-free paper) | ISBN
1260718425 (loose-leaf edition ; acid-free paper)
Subjects: LCSH: Production management.
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LC record available at

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v

Preface
The material in this book is intended as an introduction to the
field of operations management. The topics covered include
both strategic issues and practical applications. Among the
topics are forecasting, product and service design, capacity
planning, management of quality and quality control, inventory management, scheduling, supply chain management, and
project management.
My purpose in revising this book continues to be to provide
a clear presentation of the concepts, tools, and applications of
the field of operations management. Operations ­management
is evolving and growing, and I have found updating and
­integrating new material to be both rewarding and challenging, particularly due to the plethora of new developments in
the field, while facing the practical limits on the length of
the book.
This text offers a comprehensive and flexible amount
of content that can be selected as appropriate for different
courses and formats, including undergraduate, graduate, and
executive education.
This allows instructors to select the chapters, or portions
of chapters, that are most relevant for their purposes. That
flexibility also extends to the choice of relative weighting
of the qualitative or quantitative aspects of the material, and
the order in which chapters are covered, because chapters do
not depend on sequence. For example, some instructors cover
project management early, others cover quality or lean early,
and so on.
As in previous editions, there are major pedagogical f­ eatures
designed to help students learn and understand the material.
This section describes the key features of the book, the ­chapter
elements, the supplements that are available for teaching the
course, highlights of the fourteenth edition, and suggested
applications for classroom instruction. By providing this support, it is our hope that instructors and students will have the
tools to make this learning experience a rewarding one.

What’s New in This Edition
In many places, content has been rewritten or added to
improve clarity, shorten wording, or update information. New
material has been added on supply chains, and other topics.
Some problems are new, and others have been revised. Many
new readings and new photos have been added.
Some of the class preparation exercises have been revised.
The purpose of these exercises is to introduce students to the
subject matter before class in order to enhance classroom

learning. They have proved to be very popular with students, both as an introduction to new material and for study
purposes. These exercises are available in the Instructor’s
Resource Manual. Special thanks to Linda Brooks for her
help in developing the exercises.

Acknowledgments
I want to thank the many contributors to this edition. Reviewers and adopters of the text have provided a “continuously
improving” wealth of ideas and suggestions. It is encouraging to me as an author. I hope all reviewers and readers will
know their suggestions were valuable, were carefully considered, and are sincerely appreciated. The list includes post-­
publication reviewers.
Jenyi Chen
Eric Cosnoski
Mark Gershon
Narges Kasiri
Nancy Lambe
Anita Lee-Post
Behnam Nakhai
Rosa Oppenheim
Marilyn Preston
Avanti Sethi
John T. Simon
Lisa Spencer
Nabil Tamimi
Oya Tukel
Theresa Wells
Heath Wilken

Cleveland State University
Lehigh University
Temple University
Ithaca College
University of South Alabama
University of Kentucky
Millersville University of Pennsylvania
Rutgers Business School
Indiana University Southeast
University of Texas at Dallas
Governors State University
California State University, Fresno
University of Scranton
Cleveland State University
University of Wisconsin-Eau Claire
University of Northern Iowa

Additional thanks to the instructors who have contributed extra
material for this edition, including accuracy ­checkers: Ronny
Richardson, Kennesaw State University and Gary Black,
­University of Southern Indiana; Solutions and ­SmartBook:
Tracie Lee, Idaho State University; PowerPoint Presentations:
Avanti Sethi, University of Texas-Dallas; Test Bank: Leslie
Sukup, Ferris State University.
Special thanks goes out to Lisa Spencer, California State
University-Fresno, for her help with additional readings and
examples.

vii

viii

Preface

Finally, I would like to thank all the people at ­McGraw-Hill
for their efforts and support. It is always a pleasure to work
with such a professional and competent group of p­eople.
Special thanks go to Noelle Bathurst, Portfolio Manager;
Michele Janicek, Lead Product Developer; Fran Simon and
Katie Ward, Product Developers; Jamie Koch, Assessment
Content Project Manager; Sandy Ludovissy, Buyer; Matt Diamond, Designer; Jacob Sullivan, Content Licensing Specialist; Harper Christopher, Executive Marketing Manager; and
many others who worked behind the scenes.
I would also like to thank the many reviewers of previous
editions for their contributions: Vikas Agrawal, Fayetteville
State University; Bahram Alidaee, University of Mississippi;
Ardavan Asef-Faziri, California State University at Northridge; Prabir Bagchi, George Washington State University;
Gordon F. Bagot, California State University at Los Angeles;
Ravi Behara, Florida Atlantic University; Michael Bendixen,
Nova Southeastern; Ednilson Bernardes, Georgia Southern
University; Prashanth N. Bharadwaj, Indiana University of
Pennsylvania; Greg Bier, University of Missouri at Columbia;
Joseph Biggs, Cal Poly State University; Kimball Bullington,
Middle Tennessee State University; Alan Cannon, University
of Texas at Arlington; Injazz Chen, Cleveland State University; Alan Chow, University of Southern Alabama at Mobile;
Chrwan-Jyh, Oklahoma State University; Chen Chung, University of Kentucky; Robert Clark, Stony Brook University;
Loretta Cochran, Arkansas Tech University; Lewis Coopersmith, Rider University; Richard Crandall, Appalachian State
University; Dinesh Dave, Appalachian State University; Scott
Dellana, East Carolina University; Kathy Dhanda, DePaul
University; Xin Ding, University of Utah; Ellen Dumond,
California State University at Fullerton; Richard Ehrhardt,
University of North Carolina at Greensboro; Kurt Engemann,
Iona College; Diane Ervin, DeVry University; Farzaneh
Fazel, Illinois State University; Wanda Fennell, University of
Mississippi at Hattiesburg; Joy Field, Boston College; Warren Fisher, Stephen F. Austin State University; Lillian Fok,
University of New Orleans; Charles Foley, Columbus State
Community College; Matthew W. Ford, Northern Kentucky
University; Phillip C. Fry, Boise State University; Charles
A. Gates Jr., Aurora University; Tom Gattiker, Boise State
University; Damodar Golhar, Western Michigan University;
Robert Graham, Jacksonville State University; Angappa
Gunasekaran, University of Massachusetts at Dartmouth;
Haresh Gurnani, University of Miami; Terry Harrison, Penn
State University; Vishwanath Hegde, California State University at East Bay; Craig Hill, Georgia State University;
Jim Ho, University of Illinois at Chicago; Seong Hyun Nam,
University of North Dakota; Jonatan Jelen, Mercy College;

Prafulla Joglekar, LaSalle University; Vijay Kannan, Utah
State University; Sunder Kekre, Carnegie-Mellon University;
Jim Keyes, University of Wisconsin at Stout; Seung-Lae Kim,
Drexel University; Beate Klingenberg, Marist College; John
Kros, East Carolina University; Vinod Lall, Minnesota State
University at Moorhead; Kenneth Lawrence, New Jersey
Institute of Technology; Jooh Lee, Rowan University; Anita
Lee-Post, University of Kentucky; Karen Lewis, University of
Mississippi; Bingguang Li, Albany State University; Cheng
Li, California State University at Los Angeles; Maureen P.
Lojo, California State University at Sacramento; F. Victor
Lu, St. John’s University; Janet Lyons, Utah State University; James Maddox, Friends University; Gita Mathur, San
Jose State University; Mark McComb, Mississippi College;
George Mechling, Western Carolina University; Scott Metlen,
University of Idaho; Douglas Micklich, Illinois State University; Ajay Mishra, SUNY at Binghamton; Scott S. Morris,
Southern Nazarene University; Philip F. Musa, University of
Alabama at Birmingham; Roy Nersesian, Monmouth University; Jeffrey Ohlmann, University of Iowa at Iowa City; John
Olson, University of St. Thomas; Ozgur Ozluk, San Francisco
State University; Kenneth Paetsch, Cleveland State University; Taeho Park, San Jose State University; Allison Pearson,
Mississippi State University; Patrick Penfield, Syracuse University; Steve Peng, California State University at Hayward;
Richard Peschke, Minnesota State University at Moorhead;
Andru Peters, San Jose State University; Charles Phillips,
Mississippi State University; Frank Pianki, Anderson University; Sharma Pillutla, Towson University; Zinovy Radovilsky, California State University at Hayward; Stephen A.
Raper, University of Missouri at Rolla; Pedro Reyes, Baylor
University; Buddhadev Roychoudhury, Minnesota State University at Mankato; Narendra Rustagi, Howard University;
Herb Schiller, Stony Brook University; Dean T. Scott, DeVry
University; Scott J. Seipel, Middle Tennessee State University; Raj Selladurai, Indiana University; Kaushic Sengupta,
Hofstra University; Kenneth Shaw, Oregon State University;
Dooyoung Shin, Minnesota State University at Mankato;
Michael Shurden, Lander University; Raymond E. Simko,
Myers University; John Simon, Governors State University;
Jake Simons, Georgia Southern University; Charles Smith,
Virginia Commonwealth University; Kenneth Solheim,
DeVry University; Young Son, Bernard M. Baruch College;
Victor Sower, Sam Houston State University; Jeremy Stafford, University of North Alabama; Donna Stewart, University of Wisconsin at Stout; Dothang Truong, Fayetteville State
University; Mike Umble, Baylor University; Javad Varzandeh, California State University at San Bernardino; Timothy
Vaughan, University of Wisconsin at Eau Claire; Emre Veral,

Preface

Baruch College; Mark Vroblefski, University of Arizona;
Gustavo Vulcano, New York University; Walter Wallace,
Georgia State University; James Walters, Ball State University; John Wang, Montclair State University; Tekle Wanorie,
Northwest Missouri State University; Jerry Wei, University
of Notre Dame; Michael Whittenberg, University of Texas;

ix

Geoff Willis, University of Central Oklahoma; Pamela Zelbst,
Sam Houston State University; Jiawei Zhang, NYU; Zhenying Zhao, University of Maryland; Yong-Pin Zhou, University of Washington.
William J. Stevenson

Walkthrough
MAJOR STUDY AND LEARNING FEATURES
A number of key features in this text have been specifically
designed to help introductory students learn, understand, and
apply operations concepts and problem-solving techniques.
Examples with Solutions
Rev.Confirming Pages

Throughout the text, wherever a quantitative or
analytic technique is introduced, an example is
included to illustrate the application of that technique. These are designed to be easy to follow.
Chapter Three Forecasting

EXAMPLE

Determining a Regression Equation
Sales of new houses and three-month lagged unemployment are shown in the following
table. Determine if unemployment levels can be used to predict demand for new houses
and, if so, derive a predictive equation.
Period . . . . . . . . . . . . . 1
Units sold . . . . . . . . . . 20
Unemployment %
(three-month lag)
7.2

1.

2
41

3
17

4
35

5
25

6
31

7
38

8
50

9
15

10
19

11
14

4.0

7.3

5.5

6.8

6.0

5.4

3.6

8.4

7.0

9.0

Plot the data to see if a linear model seems reasonable. In this case, a linear model
seems appropriate for the range of the data.
50

Units sold, y

40
30
20
10
0

2

4

6

8

10

Level of unemployment (%), x

2.

Check the correlation coefficient to confirm that it is not close to zero using the website template, and then obtain the regression equation:
r = −.966
This is a fairly high negative correlation. The regression equation is
y = 71.85 − 6.91x
Note that the equation pertains only to unemployment levels in the range 3.6 to 9.0, because
sample observations covered only that range.

x

103

8

mhhe.com/stevenson14e

S O L U T I O N

Solved Problems
At the end of chapters
and chapter ­supplements,
“Solved Problems” are
­provided to illustrate
­problem solving and the
core ­concepts in the chapter.
These have been carefully
prepared to help students
understand the steps
involved in solving different
types of problems. The Excel
logo indicates that a spreadsheet is available on the
text’s website.

2.

Strategy formulation is critical because strategies provide direction for the organization, so they
can play a role in the success or failure of a business organization.

3.

Functional strategies and supply chain strategies need to be aligned with the goals and strategies
of the overall organization.

4.

The three primary business strategies are low cost, responsiveness, and differentiation.

5.

Productivity is a key factor in the cost of goods and services. Increases in productivity can
become a competitive advantage.

6.

High productivity is particularly important for organizations that have a strategy of low costs.

competitiveness, 42
core competencies, 46
environmental scanning, 48
goals, 44
mission, 44

mission statement, 44
operations strategy, 51
order qualifiers, 48
order winners, 48
productivity, 56

quality-based strategies, 52
strategies, 44
SWOT, 48
tactics, 45
time-based strategies, 53

SOLVED PROBLEMS

Computing Productivity

A company that processes fruits and vegetables is able to produce 400 cases of canned peaches in
one-half hour with four workers. What is labor productivity?
400 cases
Quantity produced
Labor productivity = ________________ = ________________________
Labor hours
4 workers × 1 / 2 hour / worker

Problem 1
mhhe.com/stevenson14e

Solution

= 200 cases per labor hour

Computing Multifactor Productivity

A wrapping-paper company produced 2,000 rolls of paper in one day. Labor cost was $160, material
cost was $50, and overhead was $320. Determine the multifactor productivity.
Quantity produced
Multifactor productivity = ______________________________
Labor cost + Material cost + Overhead

Problem 2
mhhe.com/stevenson14e

Solution

2,000 rolls
= _______________ = 3.77 rolls per dollar input
$160 + $50 + $320
A variation of the multifactor productivity calculation incorporates the standard price in the
numerator by multiplying the units by the standard price.Rev.Confirming Pages

Computing Multifactor Productivity

Compute the multifactor productivity measure for an eight-hour day in which the usable output was
300 units, produced by three workers who used 600 pounds of materials. Workers have an hourly
wage of $20, and material cost is $1 per pound. Overhead is 1.5 times labor cost.

TABLE 16.5 Excel solution for Example 2a

KEY TERMS

Chapter Sixteen Scheduling Usable output
707
Multifactor productivity = __________________________________
Labor cost + Material cost + Overhead cost
300 units
= _____________________________________________________
(3 workers × 8 hours × $20 / hour) + (600 pounds × $1 / pound) +
(3 workers × 8 hours × $20 / hour × 1.50)
300 units
= ________________
$480 + $600 + $720
= .167 units of output per dollar of input

Problem 3
mhhe.com/stevenson14e

Solution

Excel Spreadsheet
Solutions

ste3889X_ch02_040-073.indd

63

Where applicable, the
­examples and solved
­problems include screen
shots of a spreadsheet
solution.

09/04/19 09:59 AM

Source: Microsoft

c.

Using earliest due date as the selection criterion, the job sequence is C-A-E-B-D-F.
The measures of effectiveness are as follows (see table):
(1) Average flow time: 110/6 = 18.33 days
(2) Average tardiness: 38/6 = 6.33 days
(3) Average number of jobs at the work center: 110/41 = 2.68

xi

CHAPTER ELEMENTS
Within each chapter, you will find the following elements
that are designed to facilitate study and learning. All of
these have been carefully developed over many editions and
have proven to be successful.
Learning Objectives
Every chapter and supplement lists the ­learning
objectives to achieve when studying the ­chapter
material. The learning objectives are also
included next to the specific material in the
­margins of the text.

Rev.Confirming Pages

Rev.Confirming Pages

4

Product and Service
Design

C H A P T E R

LEARNING OBJECTIVES
After completing this chapter, you should be able to:
LO4.1

Explain the strategic importance of product and service design.

LO4.2

Describe what product and service design does.

LO4.3

Name the key questions of product and service design.

LO4.4

Identify some reasons for design or redesign.

LO4.5

List some of the main sources of design ideas.

LO4.6

Discuss the importance of legal, ethical, and sustainability considerations in product and service design.

LO4.7

Explain the purpose and goal of life-cycle assessment.

LO4.8

Explain the phrase “the 3 Rs.”

LO4.9

Briefly describe the phases in product design and development.

LO4.10

Discuss several key issues in product or service design.

LO4.11

Discuss the two key issues in service design.

LO4.12

List the characteristics of well-designed service systems.

LO4.13

List some guidelines for successful service design.

C H A P T E R
4.1

Mark Lennihan/AP Images

4.11 Service Design 165
Overview of Service Design 166
Differences between
Service Design and
Product Design 166
Phases in the Service Design
Process 167

Service Blueprinting 168
Characteristics of WellDesigned Service Systems 168
Challenges of Service
Design 169
Guidelines for Successful
Service Design 169

4.12 Operations Strategy 170
Operations Tour: High Acres
Landfill 174
Chapter Supplement:
Reliability 176

O U T L I N E

Introduction 140

4.7

What Does Product and Service
Design Do? 140
Objectives of Product and
Service Design 141
Key Questions 141
Reasons for Product or Service
Design or Redesign 141

4.2

Idea Generation 142

4.3

Legal and Ethical
Considerations 144

4.4

Human Factors 145

4.5

Cultural Factors 145

4.6

Global Product and Service
Design 146

4.8

Environmental Factors:
Sustainability 146

Designing for Mass
Customization 154
Reliability 156
Robust Design 157
Degree of Newness 158
Quality Function Deployment 158
The Kano Model 160

Cradle-to-Grave Assessment 146
End-of-Life Programs 147
The Three Rs: Reduce, Reuse,
and Recycle 147
Reduce: Value Analysis 147
Reuse: Remanufacturing 148
Recycle 149

4.9

Other Design
Considerations 151

4.10 Designing for Production 163

Strategies for Product or
Service Life Stages 151
Product Life Cycle
Management 153
Degree of Standardization 153

Phases in Product Design
and Development 162
Concurrent Engineering 163
Computer-Aided Design
(CAD) 164
Production Requirements 165
Component Commonality 165

The essence of a business organization is the products and services it offers, and every
LO4.1 Explain the strateaspect of the organization and its supply chain are structured around those products
gic importance of product
and services. Organizations that have well-designed products or services are more
and service design.
likely to realize their goals than those with poorly designed products or services. Hence,
organizations have a strategic interest in product and service design. Product or service design should be closely tied
to an organization’s strategy. It is a major factor in cost, quality, time-to-market, customer satisfaction, and competitive
advantage. Consequently, marketing, finance, operations, accounting, IT, and HR need to be involved. Demand forecasts and projected costs are important, as is the expected impact on the supply chain. It is significant to note that an
important cause of operations failures can be traced to faulty design. Designs that have not been well thought out, or
are incorrectly implemented, or instructions for assembly or usage that are wrong or unclear, can be the cause of product and service failures, leading to lawsuits, injuries and deaths, product recalls, and damaged reputations.
continued

138

ste3889X_ch04_138-175.indd 138

139

08/01/19 07:17 AM

ste3889X_ch04_138-175.indd

139

Chapter Outlines

Opening Vignettes

Every chapter and supplement includes an
outline of the topics covered.

Each chapter opens with an introduction to the
important operations topics covered in the ­chapter.
This enables students to see the relevance of
­operations management in order to actively engage
in learning the material.

xii

08/01/19 07:17 AM

Figures and Photos
The text includes photographs and
graphic illustrations to support
­student learning and provide interest
and motivation. Approximately 100
­carefully selected photos highlight
the 14th edition. The photos illustrate
applications of operations and supply
chain concepts in many successful
companies. More than 400 graphic
illustrations, more than any other
text in the field, are included and all
are color coded with ­pedagogical
­consistency to assist students in
understanding concepts.
56

Chapter Two

A major key to Apple’s continued
success is its ability to keep pushing
the boundaries of innovation. Apple
has demonstrated how to create
growth by dreaming up products so
new and ingenious that they have
upended one industry after another.

Rev.Confirming Pages

246

Chapter Six

Process Selection and Facility Layout

FIGURE 6.1

Process selection and
capacity planning influence
system design

Inputs

Outputs

Forecasting

Facilities and
equipment
Capacity
Planning

Product and
service design

Layout

Rev.Confirming Pages
Process
Selection
Technological
change

Work
design

Competitiveness, Strategy, and Productivity

LO6.1 Explain the
strategic importance of
process selection and the
influence it has on the
organization and its supply
chain.

6.1 INTRODUCTION
Process selection refers to deciding on the way production of goods or services will be organized. It has major implications for capacity planning, layout of facilities, equipment, and
design of work systems. Process selection occurs as a matter of course when new products or
services are being planned. However, it also occurs periodically due to technological changes
in products or equipment, as well as competitive pressures. Figure 6.1 provides an overview
of where process selection and capacity planning fit into system design. Forecasts, product
and service design, and technological considerations all influence capacity planning and process selection. Moreover, capacity and process selection are interrelated, and are often done in
concert. They, in turn, affect facility and equipment choices, layout, and work design.
How an organization approaches process selection is determined by the organization’s process strategy. Key aspects include:
• Capital intensity: The mix of equipment and labor that will be used by the organization.
• Process flexibility: The degree to which the system can be adjusted to changes in
processing requirements due to such factors as changes in product or service design,
changes in volume processed, and changes in technology.

Pieter Beens/Shutterstock

Moreover, this approach pays little attention to suppliers and government regulations, and
community, environmental, and sustainability issues are missing. These are closely linked,
theoftwo
and business organizations LO6.2
need to Name
be aware
the impact they are having in these areas and
Process
choice
demand-driven.
main factors
that influence
respond accordingly. Otherwise,
organizations
may be subject
to attack
by is
pressure
groups The two key questions in process selection are:
process selection.
and risk damage to their reputation.

6.2 PROCESS SELECTION
1.
2.

LO2.6 Define the term
productivity and explain
why it is important to companies and to countries.
Productivity A measure of
the effective use of resources,
usually expressed as the ratio
of output to input.

How much variety will the process need to be able to handle?
How much volume will the process need to be able to handle?

Answers to these questions will serve as a guide to selecting an appropriate process. Usually, volume and variety are inversely related; a higher level of one means a lower level of the
other. However, the need for flexibility of personnel and equipment is directly related to the
One of the primary responsibilities of a manager is to achieve productive use of an organizalevel
of variety the
will need to handle: The lower the variety, the less the need for
tion’s resources. The term productivity is used to describe this.
Productivity
is anprocess
index that
flexibility,
while
the higher
the variety, the greater the need for flexibility. For example, if a
measures output (goods and services) relative to the input (labor,
materials,
energy,
and other
worker’s
job to
in input:
a bakery is to make cakes, both the equipment and the worker will do the same
resources) used to produce it. It is usually expressed as the ratio
of output
thing day after day, with little need for flexibility. But if the worker has to make cakes, pies,
Output
cookies, brownies, and croissants,
both the worker and the equipment must have the flexibilProductivity = ______
(2–1)
Input
ity to be able to handle the different requirements of each type of product.
Thereitisisanother
aspect
of variety that is important. Variety means either having dedicated
Although productivity is important for all business organizations,
particularly
impordifferentthe
product or service, or if not, having to get equipment ready every
tant for organizations that use a strategy of low cost, becauseoperations
the higherfor
theeach
productivity,
time there is the need to change the product being produced or the service being provided.
lower the cost of the output.

2.7 PRODUCTIVITY

A productivity ratio can be computed for a single operation, a department, an organization, or an entire country. In business organizations, productivity ratios are used for planning
workforce requirements, scheduling equipment, financial analysis, and other important tasks.
Productivity has important implications for business organizations and for entire nations.
For nonprofit organizations, higher productivity means lower costs; for profit-based organizations, productivity is an important factor in determining how competitive a company is. For
a nation, the rate of productivity
growth is of great importance. Productivity growth is the
ste3889X_ch06_244-299.indd 246
increase in productivity from one period to the next relative to the productivity in the preceding period. Thus,
Current productivity − Previous productivity
Productivity growth = _____________________________________ × 100
Previous productivity

(2–2)

08/01/19 07:28 AM

xiii

Rev.Confirming Pages

Chapter Five

Strategic Capacity Planning for Products and Services

213

Operations Strategies

5.12 OPERATIONS STRATEGY

An Operations Strategy section
The strategic implications of capacity decisions can be enormous, impacting all areas of the
organization. From an operations management standpoint, capacity decisions establish a set
is included at the end of most
of conditions within which operations will be required to function. Hence, it is extremely
­chapters. These sections discuss
important to include input from operations management people in making capacity decisions.
how the chapters’ concepts can
Flexibility can be a key issue in capacity decisions, although flexibility is not always an
option, particularly in capital-intensive industries. However, where possible, flexibility allows
be applied and how they impact
an organization to be agile—that is, responsive to changes in the marketplace. Also, it reduces
the operations of a company.
to a certain extent the dependence on long-range forecasts to accurately predict demand. And
flexibility makes it easier for organizations to take advantage of technological and other innovations. Maintaining excess capacity (a capacity cushion) may provide a degree of flexibility,
albeit at added cost.
Some organizations use a strategy of maintaining a capacity cushion for the purpose of
blocking entry into the market by new competitors. The excess capacity enables them to produce at costs lower than what new competitors can. However, such a strategy means higherthan-necessary unit costs, and it makes it more difficult to cut back if demand slows, or to
shift to new product or service offerings.
Efficiency improvements and utilization improvements can provide capacity increases.
Such improvements can be achieved by streamlining operations and reducing waste. The
chapter on lean operations describes ways for achieving those improvements.
Bottleneck management can be a way to increase effective capacity, by scheduling nonbottleneck operations to achieve maximum utilization of bottleneck operations.
In cases where capacity expansion will be undertaken, there are two strategies for determining the timing and degree of capacity expansion. One is the expand-early strategy (i.e.,
before demand materializes). The intent might be to achieve economies of scale, to expand
Rev.Confirming Pages
market share, or to preempt competitors from expanding. The risks of this strategy include
an oversupply that would drive prices down, and underutilized equipment that would result in
higher unit costs.
The other approach is the wait-and-see strategy (i.e., to expand capacity only after demand
materializes, perhaps incrementally). Its advantages include a lower chance of oversupply due
to more accurate matching of supply and demand,
and higher capacity utilization. The key
READING
DUTCH BOY BRUSHES UP ITS PAINTS
risks are loss of market share and the inability to meet demand if expansion requires a long
lead time.
Sherwin-Williams’ Dutch Boy Group put a revolutionary spin on
In cases where capacity contraction will paint
be undertaken,
capacity
disposal Twist
strategies
cans with its innovative
square-shaped
& PourTM
become important. This can be the result of thepaint-delivery
need to replace
equipment
with
container aging
for the Dirt
Fighter interior
latexnewer
paint line.
The four-piece
square containeroperations.
could be the first
major
change
equipment. It can also be the result of outsourcing
and downsizing
The
cost
or in
how house paint is packaged in decades. Lightweight but sturdy,
benefit of asset disposal should be taken into account
when
contemplating
these
actions.
the Twist & Pour “bucket” is packed with so many conveniences, it

Readings

is next to impossible to mess up a painting project.
Winning Best of Show in an AmeriStar packaging competition sponsored by the Institute of Packaging Professionals, the
exclusive,
paint services
container stands
7½ in. time
tall and
Capacity refers to a system’s potential for producing goods orall-plastic
delivering
over aalmost
specified
holds 126isoz.,
a bit lesson
than
1 gal. Rust-resistant
moistureinterval. Capacity decisions are important because capacity
a ceiling
output
and a majorand
determiresistant, the plastic bucket gives users a new way to mix, brush,
nant of operating costs.
and store paint.
Three key inputs to capacity planning are the kind ofA capacity
thatonwill
muchtowill
hollow handle
one be
sideneeded,
makes it how
comfortable
pourbe
and
needed, and when it will be needed. Accurate forecasts
areA critical
to the
planning
process.
carry.
convenient,
snap-in
pour spout
neatly pours paint into
a trayimportant
with no dripping
but canthat
be removed
if desired,
allow
The capacity planning decision is one of the most
decisions
managers
make.toThe
a wide
brushinvolving
to be dipped
into the 5¾-in.-diameter
mouth. Capcapacity decision is strategic and long term in nature,
often
a significant
initial investment
ping
the
container
is
a
large,
twist-off
lid
that
requires
no
tools
of capital. Capacity planning is particularly difficult cases where returns will accrue over a lengthyto
open or close. Molded with two lugs for a snug-finger-tight closperiod, and risk is a major consideration.
ing, the threaded cap provides a tight seal to extend the shelf life
A variety of factors can interfere with effective capacity,
so effective capacity is usually somewhat
of unused paint.
less than design capacity. These factors include facilities
and layout,
product/
Whiledesign
the lid requires
no tools human
to access,factors,
the snap-off
carry bail
is assembled
on theconsiderations.
container in a “locked-down position” and
service design, equipment failures, scheduling problems,
and quality
can
be
pulled
up
after
purchase
for
toting
or
hanging
on
a ladder.
Capacity planning involves long-term and short-term considerations. Long-term considerations relate
Large, nearly 4½-inch-tall label panels allow glossy front and back
to the overall level of capacity; short-term considerations relate to variations in capacity requirements
labels printed and UV-coated to wrap around the can’s rounded
due to seasonal, random, and irregular fluctuations corners,
in demand.
Ideally, display.
capacity will match demand.
for an impressive
Jim MacDonald, co-designer of the Twist & Pour and a packaging engineer at Cleveland-based Sherwin-Williams, tells Packaging
Digest that the space-efficient, square shape is easier to ship and
easier to stack in stores. It can also be nested, courtesy of a recess

Readings highlight important
real-world applications, ­provide
examples of production/­
operations issues, and offer
further elaboration of the text
material. They also provide a
basis for classroom discussion
and generate interest in the
subject matter. Many of the
end-of-chapter readings include
assignment questions.

ste3889X_ch05_190-221.indd 213

xiv

LO4.5 List some of the
main sources of design
ideas.

SUMMARY

Jerry Simon

in the bottom that mates with the lid’s top ring. “The new design
allows for one additional shelf facing on an eight-foot rack or
shelf area.”
The labels are applied automatically, quite a feat, considering
their complexity, size, and the hollow handle they likely encounter
during application. MacDonald admits, “Label application was a
challenge. We had to modify the bottle several times to accommodate the labeling machinery available.”
Source: “Dutch Boy Brushes Up Its Paints,” Packaging Digest, October 2002.
Copyright ©2002 Reed Business Information. Used with permission.

4.2 IDEA GENERATION

08/01/19 07:22 AM

Ideas for new or redesigned products or services can come from a variety of sources, including customers, the supply chain, competitors, employees, and research. Customer input can
come from surveys, focus groups, complaints, and unsolicited suggestions for improvement.
Input from suppliers, distributors, and employees can be obtained from interviews, direct or
indirect suggestions, and complaints.
One of the strongest motivators for new and improved products or services is competitors’ products and services. By studying a competitor’s products or services and how the
competitor operates (pricing policies, return policies, warranties, location strategies, etc.), an
organization can glean many ideas. Beyond that, some companies purchase a competitor’s

∑ y − b∑ t
a = ______ or ¯y − b¯t
n
Trend-adjusted
forecast

Linear regression
forecast

TAF t+1 = S t + T t
where
S t = TAF t + α( A t − TAF t)
T t = T t−1 + β( TAF t − TAF t−1 − T t−1)

t = Current period
TAF t+1 = Trend-adjusted forecast for
next period
S = Previous forecast plus
smoothed error
T = Trend component

Y c = a + bx
where
n (∑ xy ) − (∑ x) (∑ y)
b = _____________________
n(∑ x 2) − (∑ x 2)

y c = Computed value of dependent
variable
x = Predictor (independent) variable
b = Slope of the line
a = Value of y c when x = 0

∑ y − b∑ x
a = ______ or ¯y − b¯x
n

END-OF-CHAPTER RESOURCES
Standard error of
estimate

√

________

Se =

(y − y c) 2
∑
_______
n−2

S e = Standard error of estimate
y = y value of each data point
n = Number of data points

For student study and review, the following items are
√
√
√
­provided at the end
of each chapter or chapter supplement.
t

Tracking signal

∑e
TS t = _____
MAD t

Control limits

UCL = 0 + z MSE
_____
LCL = 0 − z MSE

_____

_____

MSE = standard deviation
z = Number of standard deviations;
2 and 3 are typical values

Microsoft

1.
2.
3.
4.

Demand forecasts are essential inputs for many business decisions. They help managers decide
how much supply or capacity will be needed to match expected demand, both within the organization and in the supply chain.
Because of random variations in demand, it is likely that the forecast will not be perfect, so managers need to be prepared to deal with forecast errors.
Other, nonrandom factors might also be present, so it is necessary to monitor forecast errors to
check for nonrandom patterns in forecast errors.
It is important to choose a forecasting technique that is cost-effective and one that minimizes forecast error.

associative model, 80
judgmental forecasts, 80
regression, 98
bias, 109
least squares line, 99
seasonality, 82
centered moving average, 96
linear trend equation, 89
seasonal relative, 94
Chapter
One deviation
Introduction to Operations
Management
control chart, 107
mean absolute
seasonal variations,
93
correlation, 102
(MAD), 106
standard error of estimate, 100
cycle, 82
mean absolute percent error
time series, 82
7. What
are models
Delphi
method,and
81why are they important?
(MAPE), 106
time-series forecasts, 80
8. Why
is the
degree of customization an mean
important
consideration
in process
error,
105
squared
error (MSE),
106 planning?
tracking signal, 109
smoothing,
87consider for
moving
trend, 82
9. Listexponential
the trade-offs
you…
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