effective inventory and service management through product and process

8/10/2019 Effective Inventory and Service Management Through Product and Process

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EFFECTIVE INVENTORY AND SERVICE MANAGEMENT THROUGH

PRODUCT AND PROCESS REDESIGN

H U L LEE

Stanford University Stanford California

(Received August 1992; revision received June 1993; accepted February 1994)

One of th e major challenges to operational managers is product proliferation. Product proliferation makes it difficult to forecast

demand s accurately, and con sequently, leads to high inventory investment and poor customer service. Such proliferation is often

a result of the global nature of the market place. Different markets may have different requirements for the product, due to

differences in taste, language, geographical environment, or government regulations. Another reason for product proliferation is

the expansion of the customer base. Different product versions are often developed for different market segments (e.g., educa-

tion, personal, business, or government users ma y have different needs of a produ ct). To gain control of inventory and service,

significant benefits can b e obtained by properly exploring the opportunities in the design of the product or the process by w hich

the product is made. Logistic issues like inventory and service are thus important dimensions that design engineers should

consider, in addition to m easures like functionality, performance, and manufacturability. This paper d escribes how som e simple

inventory models can be used to support the logistic dimensions of productlprocess design. Actual examples are used for

illustration.

R

apid technology changes and increased globaliza-

tion are two common characterizations of the envi-

ronment faced by manufacturing enterprises of high

technology products. The immediate consequence of

such an environment is increased product proliferation.

Product proliferation creates a major operational chal-

lenge to managers of a manufacturing enterprise. It is

difficult to forecast demands accurately, leading to high

inventory investment and poor customer service.

Product proliferation is often unavoidable in a global

market. Different markets may have different require-

ments for the product, due to differences in taste, lan-

guage, geographical environment, or government

regulations. For example, computer products for vari-

ous countries may diEer in the power supply module to

accommodate local voltage, frequency, and plug con-

ventions. Keyboards and manuals must match local

language. Telecommunication products may also be

differentiated by the communication protocols sup-

ported. In some cases, the need for localized versions

of a product results from government-imposed local

content requirements.

Expansion of the customer base may also lead to prod-

uct proliferation. Different product versions are often de-

veloped for different market segments e.g., education,

personal, business, or government users may have differ-

ent needs of a product). Finally, rapid technology

changes mean that a company may be selling multiple

versions of the same product at the same time.

To deal with the operational problems of product pro-

liferation, companies have invested in information tech-

nology, decision support systems, and transportation

modes. These investments aim at improving the

efficiency of the order fulfillment cycle. Another ap-

proach is to redesign the product or the process through

which the product is manufactured and distributed, to

gain control of inventory and customer service for the

product. While this approach is appealing, it often has

not been implemented see Lee and Billington 1992).

Several obstacles exist see Lee 1993 for more details),

which are outlined next.

First, design engineers have to take a broader perspec-

tive than product functionality, performance, and manu-

facturability see Whitney 1988, and Dean and Susman

1989). It also requires enlarging the definition of costs in

the evaluation of alternative designs, which are often

narrowly defined as the material costs of the product and

direct labor for assembly.

Second, redesign of products for inventory and service

improvements often require close collaboration among

multiple functions, such as distribution, sales and mar-

keting, finance, customer support, engineering, R&D,

and manufacturing, within a corporation. The organiza-

tional barriers between these functions can be very high.

Third, design changes may require some investment,

such as investing in additional manufacturing capabilities

at a distribution center, higher component costs, and ad-

ditional vendor management costs.

Hence, management could be reluctant to proceed

with new designs that could result in inventory and ser-

vice improvements, unless there is a concrete estimate of

the corresponding benefits. Logistic costs, such as

freight, customs and duties can easily be quantified. The

benefits in terms of lower inventory, faster response

times to customers, increased availability levels and in-

creased flexibility, are much more difficult to quantify. It

Subject ckussificutio~zs:Inventoryiproduction, applications: product/pro cess design; multi-echelon; supply chain management.

Area

of

review: MANUFACTURING, AND SCHEDULING ISSUEON N EWDIRECTIONS MANAGEMENT)PER.~TIONS (SPECIAL

I N

OPERATIONS

perations Research

0030-364X/9614401-0151$01.25

Vol. 44, No. 1, Jan ua~y -Feb ruar y 1996

1996

I N F O R M S


2/9

is here that inventory theories and models can make a

contribution. There will also be benefits, such as in-

creased worker morale, improved quality, and marketing

values, which one may never be able to quantify

appropriately.

In this paper, we present some simple inventory mod-

els that can be used to support product/process redesigns

for companies to gain control of inventory and service.

These models were used in actual cases, and these appli-

cation cases are also described. Although these models

by themselves are not new innovations to the inventory

literature, the development of the models for product1

process design application is new. Highlighting such de-

velopments will perhaps stimulate inventory researchers

to link their work to productlprocess designs, and moti-

vate design engineers to look into the inventory and ser-

vice dimensions of their designs.

1 LITER TURE REVIEW

We will first give an overview of recent developments

regarding concepts that link design and other elements,

such as logistics and distribution of the manufacturing

enterprise. The literature on such subjects is rapidly

growing, and hence we provide only a sample overview.

Some of the recent works that relate to

product/process

design to improve logistic efficiencies are then described.

The early phases of design have a major impact upon

cost, quality, flexibility, and serviceability, all critical

factors that affect operational performance (Barkan 1991,

1992). The importance of the relationships between de-

sign and the other functional areas of a firm has been

emphasized in recent literature. These relationships, ac-

cording to Calvin and Miller (1989), are consequences of

the many constraints imposed on design teams through

distribution, service, maintenance, marketing, and man-

ufacturing capabilities. Stoll (1986) defined DFM (design

for manufacture) as a process by which a product is de-

signed taking into account all of the important concerns

of both the customer and the corporate organization, and

using this process to define product designs that facilitate

global optimization of the manufacturing system as a

whole.

FM and concurrent engineering concepts emphasize

the importance of considering more than functionality

and performance of a product in its design stage. Thus,

Whitney advocates a larger goal for evaluating design

should be reducing costs over the product's entire life

cycle. Winner et al. (1988) defined concurrent engineer-

ing as a systematic approach to the integrated, concur-

rent design of products and their related processes,

including manufacture and support. This approach is de-

scribed as one intended to cause the developers, from

the outset, to consider all elements of the product life

cycle from conception through disposal, including qual-

ity, cost, schedule, and user requirements.

The product design and development process should

thus involve multiple constituents of a company. Coop-

eration across functional lines (Wheelwright and Sasser

1989), and cross-functional teams (Dean and Susman) are

crucial for successful product development projects.

Sharing and integration of information from different

members that represent different areas of an enterprise in

the design team are also key success factors.

Despite the rapidly growing literature on design for

manufacturability, research that links operational models

to design issues is only emerging. Graves (1988) devel-

oped a model that characterized inventory and output of

a single production site. This approach can be used to

analyze the value of flexibility in the manufacturing pro-

cess as well as parts commonality, both of which are

design issues that can affect the logistical performance of

a product.

A key design concept to gain control of inventory and

service in a global market is delayed product differentia-

tion. It refers to delaying the point in time when a prod-

uct assumes its specific identity, i.e., a particular model

in a particular region for a particular market segment.

Such a strategy increases the company's flexibility in

meeting uncertain and changing customer demands. The

strategy to delay product differentiation to meet different

local region requirements is also known as design for

localization, whereas the strategy to meet the needs of

different modelslmarket segments is sometimes termed

design for customization (see Lee , Billington and

Carter 1993).

Closely related to delayed product differentiation is in-

creased part commonality and interchangeable sub-

assemblies ( design for flexible manufacture7'). Part

commonality can result in cost savings in part number

administration, inventory reduction, and supplier man-

agement. Operations researchers have analyzed the in-

ventory savings that resulted from increased part

commonality (see, for example, Baker 1985, Baker,

Magazine and Nuttle 1986, Gerchak, Magazine and

Gamble 1988, Henig and Gerchak 1986, and Gerchak and

Henig 1989). A more powerful benefit of part commonal-

ity, often ignored in the literature, is that it can be used

as a means to achieve delayed product differentiation.

The manufacturing process of a product and its associ-

ated multiple versions may involve multiple stages, each

requiring different input parts and subassemblies. In-

creasing the level of part commonality at the early stages

of the manufacturing process is similar to postponing the

differentiation of the products until after these early

stages. When used appropriately, part commonality can

provide benefits that go beyond the commonly cited

ones.

Another related concept is product modularity, i.e.,

the division of a product into independent modules. Such

an independence allows a company to standardize com-

ponents and to create product variety from a fmed set of

modules. Hence, modularity is a concept closely linked


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to commonality. The costs and benefits of modularity

have been thoroughly discussed in Ulrich and Tung

(1991) and Ulrich (1991).

As mentioned earlier, the logistics costs of moving ma-

terials and products can be a significant part of the total

product cost. Design for logistics is an emerging con-

cept that is being used at companies such as Digital

Equipment and Hewlett-Packard (Lee). The idea is to

design products that are easy and cost efficient to be

transported.

There is a segment of literature on distribution re-

search that is relevant to product/process design. This

literature is concerned with the impact of changes in the

configuration of the distribution network on the resulting

inventory and service performance of the network. In

many cases, the distribution network can be viewed as

the manufacturing process, so that changes in the config-

uration of the network are similar to the changes in the

design of the product or the process. Notable examples

include Eppen and Schrage (1981), Federgruen and

Zipkin (1984), and Schwarz (1989).

2. INVENTORY MODELS FOR PRODUCT/PROCESS

DESIGN

In this section, we present two inventory models that can

be used to support product/process design. These two

models were all motivated by real application cases.

Both were used to support analysis of product/process

design to delay product differentiation. One deals with an

environment where an intermediate stage of the product

is built to stock, from which this intermediate product is

then customized into different final products on demand.

We term this a build-to-order model, because final prod-

ucts are built on demand. The other deals with an envi-

ronment where immediate delivery of finished products

is critical, so that finished products are built to stock. We

term this a build-to-stock model. Both models assume

stationary demands and costs.

2.1. Build to Order Inventory Model

Consider a production process where products can be

made in batches of any size, and where it takes T time

units for a batch from start to finish. The production

process is such that, for the first t time units, the produc-

tion process is identical for all products. The remaining

T time units are devoted to customize the product

into a distinct end-product. A stockpile of inventory is

held right after the products have completed the first t

time units of the generic process. This intermediate in-

ventory can be used to be customized into any end-

product (see Figure

1 .

Thus, t can be viewed as the

point of product differentiation. The intermediate inven-

tory stockpile is managed as a periodic review order up-

to-S inventory system, with the review period being one

time unit. The amount of customer orders (for all end-

products) in each time unit is an iid random variable. Let

Generic Production

Product Differen-

tiation steps Different

Process

A Product

T Versions

for

I

Customer

Intermediate lnventory

Stockpile Generic Product)

Figure

1

A build-to-order model.

D(r) denote the total demand for all end-products in r

time units, and F(x lr ) denote the probability that D(r ) is

less than or equal to

x.

As a convention, denote

F(xjr) 1 for r a

0.

We assume that demands are

never negative.

The sequence of events at the production site can be

described as follows. At the beginning of each time unit,

customer orders arrive. Intermediate inventory in the

stockpile is then used to customize the products to meet

the customer orders. If there is not sufficient on-hand

inventory in the stockpile to meet all customer orders,

the excess is backlogged until more inventory is available

from upstream production. With respect to customer or-

ders in each time unit, a first-come, first-serve discipline

is used to satisfy their demands. At this point, the

amount of remaining intermediate inventory held at

the stockpile is reviewed. Production to replenish the

intermediate inventory stockpile to bring the inventory

position (inventory on-hand + work in process backlog)

to

S

is then initiated. Note that it takes t time units to

complete production of the intermediate inventory. The

batch of items that began production t time units ago will

then have completed production, and are added to the

intermediate inventory stockpile.

Let Y be the response time to all customer orders ar-

riving in a particular time unit. We will focus on

Y

as our

key measure of performance.

An

individual order arriv-

ing in that particular time unit could have been satisfied

in less than Y time units, and thus

Y

gives the upper

bound (or worst case) to the actual response time to an

individual order. The specific service measure used here

can either be the expected response time to customer

orders, or the probability that the response time to cus-

tomer orders in a time unit is less than or equal to some

target R time units. The first problem is to characterize

the service measures in terms of t,

T

R,

S

and the

demand distribution. Observe first that:

where W is the waiting time if the intermediate stockpile

does not have enough stock on-hand when the customer

orders arrive. The longest waiting time is t , the total

production time of the intermediate product, if produc-

tion has to start from scratch. Now note that, for < t,

the event that W > is equivalent to the event that the

total demand in the previous x

1

time units plus


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the current time unit, i.e., the immediate t

x

time

units, is greater than

S.

Thus:

Prob{W r) Prob{D(t r) S) F(SIt r).

The two service measures can then be written as:

and

Prob{Y R) Prob{W a

R

(T t)) F(SIT R).

Given a target

E Y ,

we can then equate this target to

(I), from which

S

can be found. Alternatively, given a

target reliability (as a probability) of response time being

less than or equal to the target R , we can equate this

target reliability to (2), from which

S

can also be found.

As described earlier, one way to gain control and ser-

vice is through delayed product differentiation. Suppose

that there is a way to make process changes so that the

point of product differentiation t can be delayed, which

means that the point at which intermediate inventory

stockpile is held can also be delayed. Le tg (t ) denote the

unit holding cost rate for intermediate inventory, given

that the intermediate inventory stockpile is held t time

units after initial production. Assuming that there would

be value added during production,

g ( t ) should be a non-

decreasing function in t. Let H( t ) be the expected hold-

ing cost per unit time for such intermediate products,

given that the S value is determined by setting either (1)

or (2) to meet the respective target. In what follows, we

focus on (1) being the service measure used. The analysis

is similar if 2) was considered.

Note first that the total average work in process (prior

to and after product differentiation) would be the same

when t is delayed. We can therefore focus on the inven-

tory level at the intermediate inventory stockpile. Since

the intermediate inventory stockpile is a standard peri-

odic review order-up-to S system, the steady-sta te prob-

ability of the inventory level at the time of inventory

review being higher than

x

is F (S xit) (see Hadley and

Whitin 1963). Hence:

where S is the value that enables (1) to satisfy the service

target. For the sake of illustrating a qualitative property,

we replace the summation sign in (1) and (3) by an inte-

gral, i.e., to treat r as a continuous variable. This is a

common approach used in inventory theory. Differentiat-

ing (1) with respect to (w.r.t.) t and setting it to zero

yields:

This means that when t changes, S should be such that

(4) is satisfied. Now, differentiating the continuous ver-

sion of (3) w.r.t. t , we get:

gr ( t ) F (xl t )

dx

0

From (4), we know that dS/dt 0. Also, aF(xlt)/

dt 0. However, gl (t ) 2 0. Hence, it is not at all clear

if dH/dt

is greater than or smaller than zero. Neverthe-

less, if g'(t) is small and close to zero, then the total inven-

tory cost would decrease as the point of product

differentiation is delayed. To gain the benefits of inventory

savings from delayed product differentiation, the process

change would thus have to be such that gl(t) s small.

2 2

Application of the Build to Order Model

Consider the scenario faced by a disc-drive manufac-

turer. Disc-drive orders come from different computer

manufacturers (OEMs), each of which orders a unique

set of products. Disc-drive manufacturing has a long lead

time, because many time-consuming tests are involved.

Hence, it is necessary to have in-process inventory to

shorten the response time to customer orders. High fore-

cast errors resulted from high demand uncertainty im-

plies that high levels of in-process inventory are needed

to provide a high level of reliability for meeting the target

response time to orders.

The manufacturing process of disc drive can be di-

vided into two parts. All disc drives for any OEMs have

to first go through a generic part of the process. In

the second part, the disc drive is then customized to the

specifications of the different OEMs. Intermediate disc-

drive inventory is held at the end of the first part of the

process. The first part of the manufacturing process,

however, is relatively short. The second part of the pro-

cess begins with some time-consuming tests that require

customized printed circuit boards.

Since the second part of the manufacturing process is

relatively long, a high level of intermediate inventory

stockpile ;s required to support high reliability of order

lead time targets. Based on the model analysis shown in

the last section, it would be ideal to design the process s o

that the point of product differentiation is postponed

without increasing the value of inventory at that later

point. This calls for reconfiguring the process so that

process steps in the second part with little value added

can be made generic and so can be performed before the

differentiation point. It turns out that the testing steps

just described can be carried out using a "coupon"

board (can be viewed as a generic board) without the use

of the customized board on a drive. After the series of

tests are completed, the coupon board is then removed

and the actual printed circuit board is then inserted at


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this point. Hence, the point of product differentiation is

postponed from the beginning of the tests to after the

tests are completed. Since tests do not add significant

value to the product , the delayed product different iat ion

strategy does not incur an increase in the value of inven-

tory investment . Figure 2 i l lustrates such a process de-

sign change.

The biggest resistance for the use of the coupon boards

as a wa y to delay product differentiation cam e from man-

ufacturing management personnel w ho w ere just-in-t ime

purists . T he insert ion and sub sequent removal of a cou-

pon board w as viewed as a nonvalue-added act ivi ty, and

therefore should not be inst i tuted. Th e model helped to

quantify the value of flexibility that resulted from de-

layed product differentiation, in the form of inventory

reduction, and was a key step to sol idify management

support for eventual implementat ion of the process de-

sign change.

2 3

Another App lication of the Bu ild-to-Order Model

A workstat ion manufacturer begins i ts manufacturing

process with the processor board, which involves the

fabrication of ASICs application-specific integrated cir-

cuits). The lead time of this first process is quite long.

The second stage involves bui lding the sheet metal ,

power supply, fan, and cables. The third stage includes

the integration of base memory, floppy drive, hard drive,

and the operat ing system. This is fol lowed by the addi-

tion of application software, add-on memory, video

RAM card , LAN cards, and othe r opt ion cards. The final

stage, which is often performed in distribution sites, in-

cludes the assembly of power cord, keyboard, mouse,

monitor, and documentation.

This workstat ion manufacturer bui lds part ial ly com-

pleted workstat ions based on forecast , and stocks the

wor k in process. Different customers m ay need different

configurations of the system, e.g., different application

softwares, memo ry, hard ver sus floppy drive, and option

cards. Su ch customizat ion steps are performed under the

build-to-order environment, i .e., a system is configured

upon demand. I n the past , s tages 1 and 2 were generic to

all customers, and thus the produc t is bui lt and stocked

up to that point . The rest of the stages const i tute the

customization steps.

Delayed production differentiation has been intro-

duced as a k ey wa y to add flexibi li ty to the m anufactur-

ing proce ss. T o implem ent delayed differentiation, th e

manufacturer considered standardizing the key sub-

assemblies, such as base memory, floppylhard drives,

and the operating system. This way, the point of differ-

ent iat ion can be deferred unti l the third stage is com-

pleted. The number of units of the partially completed

product nee ded to suppo rt the response t ime target could

be reduced by such a change.

On the other hand, a workstat ion that has gone

through stages 1 to 3 of the pro cess is wor th significantly

more than o ne that has gone through only stages

1

and

2

PCB

Insertion

end-product

a

Work-In-Process

lnventory Stockpile

Coupon Board PCB

Insertion Insertion

end-product

Series of Tests

Work-In-Process

lnventory Stockpile

igure

2 Disc drive manufacturing example illustrated.

of the process. Careful analysis of the change using a

simple inventory model such a s the one described in sub-

section 2.1 revealed that reduction in physical units of

inventory held is more than offset by the increased value

of per-unit inventory. Consequently, although delayed

product differentiation is attractive in principle, there

could be a limit to which differentiation should be de-

ferred. Inventory models are useful to help the assess-

ment of the tradeoffs.

2.4. A Build-to-Stock Model

When immediate availability of products is critical, the

servic e meas ure is usually the co nventional fill rate, i .e.,

the fract ion of dema nds that are met from stock without

delay. In this case, inventory is stored in finished goods

form. Consider the following manufacturing process. For

a batch of items that could eventually be customized to

different end-produc ts, it takes time units to process the

items in on e generic form, i.e., all end-produc ts have to

go through these first time units without an y differenti-

ation. Up to this point, all items are identical and can be

customized to any end-products . I t takes

T

time

units to customize the generic items into different end-

products . H ence, the total manufacturing t ime is T time

units. Inven tory is held only in finished good s form see

Figure 3 . All end-products have identical inventory and

backorder costs .

Suppose that each end-product finished goods stock-

pi le is operated as a periodic review inventory system,

where the review period is a t ime unit . Demands for

end-product

i

in each time unit is normally distributed

wi th mean

ki

and standard deviat ion

a .

Assume that

demands of i tems across t ime units are independent ,

but d ema nds for different end-products in a time unit can

be corre la ted . Let p, denote the covar iance of demands

for end-product i and k in a time unit. We further make

the assumption that demands for al l end-products have

an equal coefficient of variation, i .e., ai lp i is constant for

all i Define also that a, /Cjaj . Demands not met

immediately are back ordered. W e a sk a s imilar question


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Point of Product

Differentiation

Generic Production Customization

Process Process

igure 3

build-to-stock model.

as before: How to characterize the operational perfor-

mance of such a system as a function of t , T, the re-

quired fill rate, and the demand distribution of the end-

products. Based on that, we can then explore the costs

and benefits of delaying the point of product differentia-

tion t

At the beginning of each time unit, the inventory status

of all end-products is reviewed, based upon which two

actions will be initiated. First, an allocation decision is

made regarding how items that have just completed the

first

t

time units of processing should be allotted to be

customized for different end-products. Second, the

amount of new items to begin production is determined.

Readers familiar with the distribution literature would

recognize that this manufacturing system resembles the

single warehouse, multiretailer system studied by Eppen

and Schrage (1981), Federgruen and Zipkin (1984), and

Schwarz (1989). Hence, we will only state the key oper-

ating characteristics without detailed proofs here. We

then present the results of our analysis based on these

characteristics.

Eppen and Schrage have shown that, using linear in-

ventory holding and backorder costs and under fairly

mild assumptions, the optimal inventory policy is to op-

erate each end-product stockpile as an order-up-to S sys-

tem. Let S, be the order-up-to level for end-product

i.

Hence, at the beginning of each time unit, the number of

new items to begin production is the total demand of the

previous time unit. Furthermore, an equal fractile alloca-

tion rule is used to allocate the inventory that has just

completed

t

time units of production for the customiza-

tion to different end-products. This rule stipulates that,

after allocation, the inventory position for each end-

product should be the sum of the mean demand for the

end-product over T time units, and a

common

safety-stock factor multiplied by the standard deviation

of demand for the end-product over the

t

time units.

Given such results, the steady-state end-of-period inven-

tory level, I,, has a mean and variance given by (see

Eppen and Schrage, or Schwarz, for details):

where is a function of Si and

pj

but is independent of

t

Based on these two moments, service measures such

as the fill rate can be derived. The value of

Si

is then

determined to satisfy the target service level (see

Schwarz).

We can now consider the value of delayed product

differentiation by considering increasing the value of

t

but keeping

T

constant. Note first that by keeping T

constant the average work-in-process inventory remains

unchanged when

t

changes. Next, note that E(Z,) is inde-

pendent of the value of t. Thus, delayed product differ-

entiation does not affect the expected value of Ii

However, the variance of Iiis a function of

t

Clearly, the

smaller the variance of Ii the lower the

Si

to satisfy

the same level of service.

Differentiating (5) w.r.t.

t

yields:

Since, for all

j

and

k pjk

< qu,, and therefore xj

Cj+,pjk Thus, aVar(Ii)/dt is always nonposi-c ~ ~ ) ~ .

tive. Delayed product differentiation in this case would

always result in less inventory held in finished goods

form. This result is true regardless of whether demands

for the end-products are positively or negatively corre-

lated. However, if pjk is negative, then dVar(I,)ldt is

more negative. Hence, the benefit of delayed product

differentiation in the form of inventory reduction is

greater when demands for different end-products are neg-

atively correlated.

In the special case of

N

independent and identical end-

products with common standard deviation of demand in

a time unit, a , we can simplify

(5)

to:

The value of delayed product differentiation is easy to

see in this simplified form. The first term inside the

bracket on the right-hand side has as a denominator

the number of products

N,

while the second term does

not. Clearly, the variance is reduced by increasing the

numerator in the first term and decreasing a correspond-

ing amount in the second term. Also, the larger the num-

ber of end-products, the greater is the reduction in

variance from delayed product differentiation.

2.5.

Application of the Build to Stock Model

The following application is abstracted from Lee,

Billington and Carter. key computer manufacturer has

one of its printers manufactured centrally in the U.S.,

and distributed globally through the company s three dis-

tribution centers (DCs) for worldwide demands. The

three DCs are located in Europe, the U.S., and the Far

East. Theses printers need to be localized for the re-

quirements of different countries, which involves packag-

ing a printer with the appropriate power supply module,


7/9

with the correct voltage and power cord terminators

(plugs), and a manual with the appropriate language. In

the past, localization was performed at the U.S. factory,

a strategy known as factory localization. Due to com-

petitive pressures, the manufacturer has to provide high

levels of availability for the dealers by maintaining some

target finished goods inventory at the DCs.

Manufacturing at the U.S. factory operates in a pull

mode. Production plans are set to replenish the DCs

just-in-time to maintain the target safety stocks. Un-

der factory-localization, the different versions of the

printers, with different power supplies and manuals, are

shipped to the two non-U.S. DCs by sea, with a transit

time of approximately one month. The consequence of

such a long lead time is that the European and the Far

East DCs have to maintain high levels of safety stocks.

Localization at the DCs provides an attractive alterna-

tive to gain control of inventory and service. Hence, the

factory would be responsible for manufacturing a generic

printer without the power supply module and manual.

Generic products are shipped to the DCs, where the ge-

neric product is then localized to the different specific

country options as they are needed. Such a strategy is

termed DC localization. To implement DC localiza-

tion, some design changes had to be made to the prod-

uct. For example, the product needs to be redesigned so

that the power supply module is the last component to be

added on and can be plugged-in easily at the DC. Some

investment is needed to equip the international DCs with

such a capability. In terms of inventory control with DC

localization, the international power supply modules and

manuals are kept at the remote DCs, instead of at the

factory. Semi-finished goods, i.e., unlocalized version of

the product, are stocked at the European and the Far

East DCs. When actual orders are received, a quick op-

eration localizes the generic version into the specific

product required. Figure 4 shows the difference between

the two localization strategies.

The change from factory localization to DC localiza-

tion is like moving the point of product differentiation

from the factory to the DC, i.e., a postponement of a

month for the non-U.S. markets. The build-to-stock

customers

Point of Product

Differentiation

Factory LocalizationStrategy

mfg

DC

customers

Point of Product

Differentiation

DC Localization Strategy

igure

4

Printer localization example illustrated.

model was used to estimate the inventory savings that

resulted from such a product redesign. In this case, the

correlations among demands of different end-products,

i.e., printers for different countries, are not particularly

high. To illustrate the inventory savings through the

model of subsection 2.4, consider T as the sum of pro-

duction time at the factory (1 week) and the transit time

from factory to the European DC (4 weeks), i.e.,

T

weeks. Factory localization would mean that 1

week. DC localization would almost push to be very

close to T. Let K, be the safety stock factor for end-

product i at the European DC. If the demands for the

different country versions of the printer in Europe are

independent, then the safety stock level for end-product

i is K ~ ~ ( R , ~ c ~ c ~40-3, whereas corresponding safety

stock level under DC localization is

K ; R ; ~ ( ~ Y ; . ; & ) .

he

c \ J J

reduction of safety stock is K,{~(R,~c~.; 40-3

-

4 1.

In addition to inventory, there are many other factors

that should be considered in a comprehensive evaluation

of the localization alternatives. First, a localized printer

contains localization materials, and so it has a higher

value than an unlocalized printer. Hence, the capital tied

up in pipeline inventory (inventory in transit) is also

lower when localization occurs at the end of the chain,

i.e., DC localization. Second, an unlocalized printer is

much less bulky than a localized one, as the localization

materials and many of the final packaging materials that

are needed for the customers do not have to be bundled

with the printer. One can thus ship the unlocalized print-

ers in bulk pallets, and cut the cost of transportation

significantly. Third, increasing local content and local

manu fa~ tur ing~ ~ can make a product moreresence

marketable, which supports doing localization at the non-

U.S. DCs (see Cohen and Lee 1989). There is also a need

to develop a local supply base of the localization materi-

als for the DCs. Finally, since DC localization requires

the DCs to perform some operations that are traditionally

viewed as manufacturing activities, there may be cultural

and organizational barriers to overcome. After consider-

ing both the quantifiable and the nonquantifiable factors

mentioned before, the manufacturer has redesigned the

product, and is designing all future products to support

the DC-localization strategy.

2 6

Another Application of the Build-to-Stock Model

A

printer manufacturer was about to introduce a

new product, a color printer. Demands for the new color

product and the existing monoprinter are probably nega-

tively correlated. To meet high levels of product avail-

ability, the manufacturer has to stock high levels of

finished products. With a high degree of demand uncer-

tainties for the two products, it is easy to have inventory

building up for one product while shortages exist for the

other one.


8/9

The manufacturing processes for the two products are

basically very similar, except for the materials used.

There are two key stages: printed circuit board assembly

and test, and final assembly and test. There are two key

subassemblies that differentiate the color and monoprint-

ers. At the printed circuit board assembly stage, two

distinct head driver boards are used, one for each prod-

uct. At the final assembly stage, two distinct print mech-

anism interfaces are also used. Other differences in the

bill of materials for the two products exist, but these are

minor and can easily be standardized. Here, product dif-

ferentiation in the manufacturing process begins when

the distinct head driver board is inserted into the prod-

uct, i.e., at a relatively early stage of the process.

To address the problem of high forecast errors for the

two distinct end-products, we can again employ the strat-

egy of delayed product differentiation. If a common head

driver board can be designed for both types of printers,

then the point of differentiation can be delayed to after

the printed circuit board assembly stage. Furthermore, if

a common print mechanism interface can also be designed,

then the point of differentiation can be further delayed to

the end of the final assembly stage. Figure shows the

two alternatives of delayed product differentiation.

The operations research literature has addressed the

issue of inventory savings that resulted from commonal-

ity of parts (see, for example, Baker 1985, Baker,

Magazine and Nuttle 1986, Gerchak, Magazine and

Gamble 1988, Henig and Gerchak 1986, Gerchak and

Henig 1989, and others.) The focus of these works, how-

ever, is on the impact of the component inventory as a

result of commonality. In our application here, the val-

ues of the head driver board and the print mechanism

interface are relatively insignificant, compared with the

value of a finished printer. Hence, the major value of

commonality is not on part inventory reduction, but on

the resulting finished goods inventory reduction due to

delayed product differentiation achieved by

commonality.

Besides the technological challenge to standardize the

parts, commonality would result in higher part costs. A

color printer is a product with more functionality than a

monoprinter. Having a standardized part for both means

that the material cost for the monoprinter would proba-

bly go up, because a part with greater capability has been

used. To fully evaluate the effectiveness of commonality

in this case, one would thus have to assess the impact of

1. inventory savings for the parts;

2.

material costs of parts;

3. investment cost for the engineering change; and

4. inventory savings for finished goods.

The model described in subsection 2.4 is useful for esti-

mating the cost item of item

4

No Com mon color printer

Key Parts

mono printer

Common

PC

color printer

Common Head

Driver Board Assembly mono printer

Head

Common

PC

Common color printer

Driver Board,

Common Print ~ ~

~

~

~

~

~

~

~

l

~ ~ b ~ lmono printer

Mech Interface

PCB Assembly Final Assembly

igure 5. Printer commonality example illustrated.

3

CONCLUSIONS

Product and process design changes are powerful means

to enable a company to gain control of inventory and

service in the presence of product proliferation. In many

instances, they are more effective than investing in better

inventory planning and control systems, which assume

given product and process designs. The application ex-

amples in this paper on productlprocess design changes

to effect delayed product differentiation would perhaps

illustrate the importance of expanding the mind set of

inventory modelers from focusing on "optimal" inven-

tory planning and control to exploring alternative prod-

uctiprocess designs to improve inventory and service

performance.

We do see a parallel of our problem here to quality

management. Rather than focusing on quality control

in the form of inspection and process control, the trend in

quality management now is toward designing quality into

the product (see Taguchi and Clausing 1990). There is no

doubt that technical and creative challenges exist for de-

signers to make changes such as the ones described in

this paper. An encouraging note should be mentioned

here. In the many examples cited in references that de-

scribe Taguchi's method of design for quality, it is often

stated that design changes do not always have to be ex-

pensive and difficult undertakings. There often exist sim-

ple design changes that can result in a significant

reduction in product quality variations.

Rapid technological changes and increased globaliza-

tion of markets will continue to result in product prolif-

eration as a major challenge to operations managers of

global companies. It is important for design engineers to

look beyond functionality, performance, and manufac-

turability of a product. Logistic issues such as inventory

and customer service are critical battlegrounds for com-

petitiveness. To this end, inventory models have a lot to

offer.

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