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Supply chain reengineering using a core process analysismatrix and object-oriented simulation

S. Wesley Changchien*, Hsiao-Yun Shen Department of Information Management, Chaoyang University of Technology, 168 GiFeng E. Road, WuFeng, Taichung County, Taiwan, ROC

Received 30 June 1999; received in revised form 13 April 2000; accepted 16 March 2001

Abstract

To satisfy and respond quickly to customers' demand, many companies are now aggressively focusing on supply chain

management in order to strengthen their competitiveness. This paper proposes an integrated business process reengineering

(BPR) framework for improving performance. There are several steps in this framework: creating vision, identifying core

processes to be redesigned, analyzing current core processes, designing for innovation, evaluating the new processes, selecting

the best, and transforming and implementing the resulting design. A core process analysis matrix is proposed for identifying

the critical processes. System simulation is useful in measuring the performance and predicting the effect of change on the

system. To reduce the risk of BPR, an object-oriented simulation framework is developed for evaluating and analyzing the

reengineering proposals. This paper uses a case study to show the value of the method. # 2002 Elsevier Science B.V. All

rights reserved.

Keywords: Supply chain management; Business process reengineering; Strategic alliances; Object-oriented simulation

1. Introduction

Today, companies face severe competitive

challenges. The agility of a company's response to

customer demand has been recognized as a critical

success factor in meeting competition. Supply chain

management (SCM) is an effective way to do this.

The scope of a supply chain depends on the numberof ®rms involved.

Stronger and more sophisticated customer de-

mands, increasing competitive pressure, and the

ever-changing market environment are forcing com-

panies to rethink the way they perform operations.

One modern management strategy is business process

reengineering (BPR). A number of similarities exist

between BPR and SCM [10]. Both need fundamental

rethinking and consideration of strategies and are

process-based; also they generally reduce the duration

of the processes. Of course, information technology is

used as a catalyst for both. Supply chain reengineering

aims to overcome the uncertainty associated with

various aspects of the chain, including the changingneeds and demands of customers, the quality of the

information, and inherent delays that affect purchas-

ing and ordering decisions.

2. Supply chain management and business

process reengineering

BPR is `̀ the fundamental rethinking and radi-

cal redesign of an entire business systemÐbusiness

Information & Management 39 (2002) 345±358

* Corresponding author. Tel.: �886-4-23323000x4204;

fax: �886-4-23742337.

E-mail address: [email protected] (S.W. Changchien).

0378-7206/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved.

PII: S 0 3 7 8 - 7 2 0 6 ( 0 1 ) 0 0 1 0 2 - 1



processes, job de®nitions, organizational structures,

management and measurement systems, values and

beliefÐto achieve dramatic improvements in critical

measures of performance (cost, quality, capital, ser-vice, speed)'' [15]. Davenport and Short [8] regard

business process redesign as `̀ the analysis and design

of work ¯ows and processes within and between

organizations.''

A great number of BPR methodologies have been

presented [21,29]; most of them involve a series of

procedural stages, including envisioning, identifying

processes, evaluating processes, designing, and imple-

menting, etc. [8,14]. In the context of BPR evolution,

Stephens et al. [25] say that BPR passes through three

stages. Stage 1 is department focused; enterprise-wide

solutions are emphasized at stage 2; and the efforts are

supply chain focused to go outside the organization in

stage 3. Due to the high risk of BPR, Kim and Kim

[20] use a computerized simulation method of BPR

model to estimate changes.

SCM is de®ned in many ways [3]. The International

Center for Competitive Excellence de®ned it to be [7]:

` .̀ . . the integration of business processes from end

user through original suppliers that provides pro-

ducts, services and information that add value for

customers.''

The supply chain can be regarded as a businessprocess to construct enterprise-wide schemes [5].

Hewitt [16] believes that the supply chain is of parti-

cular interest, because it is regarded as `core' or

`strategic' within the overall enterprise process. A

number of researchers have presented methods for

supply chain redesign [4,17]. Stevens [26] addressed a

supply chain integration model, Abrahamsson and

Brege [1] focused on structural changes on supply

chain of a single ®rm, Towill [27] used systems

dynamics modeling, analysis, and simulation to

develop a methodology for supply chain reengineer-ing.

3. Inter-organizational relations

Recently, more companies have joined inter-organi-

zational relationships to cooperate by sharing either

market or resources to enhance their competitiveness

and better to service customers. The relationships occur

in several ways such as strategic alliances, partnerships,

jointventures,cooperative agreement, outsourcingcon-

tract, network organizations, and coalitions.

3.1. Virtual organization

In a virtual organization, complementary resources

exist in a number of cooperating companies; they

support a particular product effort for as long as it

is a pro®table endeavor. Business Week de®ned a

virtual company or organization as a new model that

uses technology to link people, assets, and ideas

dynamically. It is ideal for cooperation between com-

panies. However, a number of factors must be

addressed to implement a virtual organization: oppor-

tunism, excellence, technology, no borders, and trust.

One of the advantages of forming a virtual organi-

zation (VO) is its ¯exibility [19,22]. The ability to

respond quickly is a critical goal. Goldman et al. [12]

say that a virtual organization provides for three major

needs of agile competition:

1. Creation or assembly of new production resources

very quickly.

2. Creation or assembly of new productive resources

frequently and concurrently.

3. Access to a wider range of world-class compe-

tenciesWilliams [30] suggested that there were four types

of inter-organizational relationships: hierarchical,

solar, centreless, and swingle (sic).

Besides the transformation of organization and

management structure, the technology which enables

the realization of VO is IT. The collaborative advan-

tage of VO is based on the performance of complex

activities conducted frequently and concurrently.

Accordingly, the introduction of a VO cannot be

successfully implemented in companies without

advanced information systems and extensive use of computer networks.

3.2. Strategic alliances

Strategic alliances provide a number of advantages,

including faster market penetration, sharing of ®nan-

cial risk, possibilities of technology transfer, and

increased production ef®ciencies [24]. Kanter [18]

concluded that the best inter-organizational relation-

ship to promote collaborative advantages tends to

346 S.W. Changchien, H.-Y. Shen / Information & Management 39 (2002) 345±358



meet an eight I's criteria: Individual excellence,

Important, Interdependence, Investment, Information,

Integration, Institutionalization, and Integrity. Appar-

ently, strategic alliances require complementary corecompetencies in the individual alliances so that each

can bene®t from collaboration.

4. Approach

4.1. A BPR framework

A BPR framework based on OOS is depicted in

Fig. 1. Steps should be cyclically performed as a

routine improvement procedure.

1. Vision and objectives creation: Envisioning is the

®rst stage. The enterprise should review its current

pro®le and develop a broad strategic vision. Key

activities include evaluating organizational struc-

ture and the environment, recognizing needs, and

setting reengineering goals.

2. Core process identi®cation: The building blocks of

a business are its processes. However, not all of

them should be reengineered at the same time.

When companies proceed with BPR, only a fewkey processes should be selected for the initial

effort. A core process analysis matrix (CPAM) can

help managers identify critical processes by

relating the candidates to the goals.

3. Current processes analysis: Understanding and

analyzing the current processes follows. It is

necessary that the processes are diagnosed and

correctly understood. A proposed OOS framework

can be employed for modeling and analyzing the

new processes, as well as the processes to be

reengineered.

4. Innovative reengineering: The IT has been identi-

®ed as an enabler of process redesign. Its diffusion

effects in BPR have been demonstrated by Grover

et al. [13]. Organizational structure is generally

believed to be associated with the ®rm perfor-

mance. Also, process innovation occurs as a major

aspect of BPR [6,23].

Fig. 1. A proposed business process reengineering framework.

S.W. Changchien, H.-Y. Shen / Information & Management 39 (2002) 345±358 347



5. Evaluate new processes: New processes are next

simulated, using the OOS framework. The perfor-

mance of all candidate processes is recorded.

6. New process selection: An appropriate multi-criteria decision-making method or group decision

making method can be employed to select the

processes for implementation.

7. Transformation and implementation: Finally, man-

agement personnel must be involved in the post

implementation assessment. The new performance

results should be benchmarked and compared

against those of the original process.

The seven-step procedure should be repeated cycli-

cally to provide continuous improvement.

4.2. The core process analysis matrix

A CPAM for identifying the core processes of a

reengineering project is shown in Fig. 2.

4.2.1. WHATs criteria and viewpoints affecting

business vision

WHATs are the list of the concerned criteria of

BPR. In supply chain reengineering, these may in-

clude: the strategic, function, logistics-transportation,

and information management views.

4.2.2. HOWs candidate business processes

HOWs represent the processes that may need to be

reengineered. A set of WHATs can be achieved

through the reengineering of a set of selected HOWs.

The initial business processes of supply chain were

identi®ed as seven processes by the International

Center for Competitive Excellence. These are: custo-mer relationship, customer service, demand, order

ful®llment, manufacturing ¯ow, procurement, and

development and commercialization.

4.2.3. WHYs weighting factors on WHATs

WHYs de®ne the relative importance of the

WHATs. For each criterion, they take into account

current evaluation of the main competitors and assess-

ment of the company itself. A typical set is a list of

`̀ overall importance'' of concerned business view-

points (the WHATs). The relative importance can

be obtained using the following formulae:

1. The relative evaluation value:

RV �current evaluation for us

current average evaluation for competitors

2. The adjusted criteria (WHATs) importance:

ACI �criteria importance

RV

4.2.4. WHATs versus HOWsTo obtain the relationships between business pro-

cesses and concerned business perspectives, a correla-

tion matrix is established by marking relationship

level on each WHAT versus HOW. The relationships

Fig. 2. The structure of core process analysis matrix (CPAM).




can be rated at several levels, such as strong, medium,

weak, and none.

4.2.5. Target matrixAn index of importance for each business process

can next be calculated. The formulae for calculating

the target importance are

1. The raw importance index:

RI �X

column

CI Â CO

where CI is criteria importance and CO is the

correlation between business processes and per-

spectives.

2. The importance index for business process:

I �RIP

row

RI

4.3. Object-oriented simulation framework

An OOS framework consists of a simulation

scheme and OO modeling method. Here, an object-

oriented simulation world-view is used to present the

progress of system advance over time in terms of objects and their interactions. The simulation is based

on an object list. The object list maintains objects,

each of which represents one of the system members

to be processed as the simulation proceeds. Further-

more, each object contains an attribute `time' which

indicates the system time when the object needs to be

activated in the list. The procedure is:

Step 1 Initialize objects in the system.

Step 2 Put objects into the object list ordered by

their time attribute.

Step 3 Get the most recent object from the objectlist.

Step 4 Check its type.

Step 5 Process the object and perform tasks

according to its type.

Step 6 Delete the processed object or add it into

the object list, if necessary.

Step 7 Ifneeded,create new objects and goto Step2.

Step 8 Check the condition for termination. If not

termination, go to Step 3.

Step 9 Terminate.

A system consists of objects and processes in

accordance with business rules. The system component

perspective describes the static, structural components

of the system. The system work¯ow perspectiverepresents the processes during system execution.

The system control perspective describes dynamic

system state changes. Herein the UML [9,11] notation

is used for implementing the simulation modeling

method.

The system components should capture those con-

cepts from the real world that are important to system

simulation. The components are represented graphi-

cally, with class diagrams that show the static view of a

system in terms of classes. The System Work¯ow

represents the system process ¯ow. It is represented

graphically through activity and interaction diagrams.

These capture tasks and activities that will be per-

formed and illustrate how objects interact (the inter-

action diagram focuses on how messages are sent and

received among objects). System control represents

dynamic, behavioral, temporal, and control perspec-

tive of a system. The system component is represented

graphically, with state diagrams that describe all the

possible states a particular object can enter and how

the object's state changes.

5. A case study of a motorcycle manufacturer

This studies the supply chain activities of a motor-

cycle manufacturer in Taiwan. The production man-

agement division of the manufacturer is the main

concern here. Thus this example only focuses on Steps

2±6 of the framework. Figs. 3 and 4 present a portion

of the components and work¯ow using the OOS

modeling method.

5.1. Identify core processes

In conducting the CPAM, the WHATs and HOWs

were stated and the correlation matrix and WHYs

were provided by the top and middle level managers.

Five members of the decision group contribute their

expertise toward identifying the core processes.

Table 1 shows the opinion of one member of the

decision group about the correlation matrix, criteria

weights, evaluation for the ®rm for the criteria, and

evaluation of competitors. The target matrix contains




the importance indices for the processes of the supply

chain. Because of the inter-organizational processes, a

group decision making method helped to take into

account the opinions of diverse experts.The importance of the ®ve members is averaged in

Table 2, which shows that they tend to consider

Product Development, Procurement and Demand

Management the three core processes.

5.2. Analyze current core processes

We collected data on one speci®c motorcycle

model. In the forecasting process, the manufacturer

forecasts demand based on its franchisees' forecast

based on retailers' experiences. Since the stable stageof the product life cycle is the concern of this case

study, only limited data was available for investiga-

tion. Based on the data over a 26-month period, the

mean absolute difference (MAD) between market

sales and manufacturer forecasting is 346 units and

the MAD between manufacturing forecasting and

sales to franchisee is 321 units.

In the procurement process, the manufacturer ®rst

surveys and forecasts the demand. A decision making

group is then formed of people from the production

and marketing divisions. This takes responsibility for

all aspects of the production schedule.

5.3. Design innovation

New process designs of the forecasting and pro-

curement process were reengineered as de®ned below.

5.3.1. Forecasting activity

In order to improve the forecasting activity, sys-

tematic forecasting methods were introduced, thereby

abandoning the old multi-stage forecasting process.

Well known moving average, exponential Smoothing,

factors decomposition, and Bayesian methods [2]

were considered to show the value of each. The Bayesian forecasting method assumed that the past

sales follow a known probability distribution; we used

a goodness test for the past sales data, assuming that

the market demand follows a normal distribution with

a mean of 490 and standard deviation of 85.

5.3.2. Procurement process

In the case study, the original monthly procurement

policy was changed to bi-weekly procurement. Pre-

viously, the manufacturer placed purchasing orders to

Fig. 3. The components of a simulation system of this case study.




suppliers according to an agreement resulting from a

production±marketing joint meeting. Due to uncer-

tainty of sales, the manufacturer frequently faced

addition or cancellation of orders. When that situation

occurred, the manufacturer adjusted purchasing orders

in the next period so that any stock shortage or super-

¯uity would occur then. Design innovation includedquick response by adjusting purchasing orders or

shortening the cycle time of the joint meeting during

the procurement process.

5.4. Evaluate new processes

Based on the calculated MADs between real market

demand and forecasting, it is possible from computa-

tions using moving average, exponential smoothing,

factor decomposition, and Bayesian methods, to

reduce MADs to at least 50% of the MAD without

forecasting, as Fig. 5. Of all these, the Bayesian

method had the smallest MAD.

Fig. 6 shows the forecasting values using exponen-tial smoothing versus real market demand per month

during the prior 5-year period. The simulation of new

procurement processes is based on these data. Fig. 7

presents the comparisons of the procurement pro-

cesses. Policies represent: (1) current procurement;

(2) adjusting orders in the current period; and (3)

shortening the cycle time of production±marketing

joint meeting and purchasing. In this case, the pur-

chase lead times of parts are classi®ed into (a) those

between 15 and 30 days, which can be shortened to 7±

15 days and (b) those greater than 30 days. For parts

having shorter lead times, the manufacturer has to

negotiate the adjustment of orders with suppliers in

response to the change of the market. The X -axis

represents purchasing costs items of two types of

parts, ®nished goods, shortages, and total costs. The

Y -axis shows the purchasing costs.

5.5. Select a new process

The manufacturer next considered the implementa-

tion cost, the applicability of the process, and whether

suppliers could accommodate the new process. An

appropriate multi-criteria decision making method

was required.

Let A � f A1; A2; . . . ; Ang be a set of alternatives

and C � fC 1;C 2; . . . ;C mg be a set of criteria char-

acterizing the decision situation. Moreover, W �fw1;w2; . . . ;wmg is a set of weights that indicates

the relative importance of criteria set C . The universe

of discourse, U , is a ®nite set of fuzzy numbers within

[0, 1]; they are used to express an imprecise concept or

level. They allow the following analysis:

1. Universe of discourse domain

Let

~u1 � very low�VL�~u2 � low �L�~u3 � medium low �ML�~u4 � medium �M�~u5 � medium high �MH�~u6 � high �H�~u7 � very high�VH�

Fig. 4. Process of this case study described with an activity

diagram.




Table 1

An example of CPAM (by a group member) associated with seven processes and four criteria views

WHATs HOWs

Customer

relationship

management

Customer

service

management

Demand

management

Order

fulfillment

Manufacturing

flow

management

Procurement Product

developme

Strategic view Product sales M M M M S S S

Function view Procurement cost M M S S M S M

Manufacturing cost M M S S S S M Logistics view Transportation cost M M S M M M M

Information

management view

Information process cost M M M M M M M

Raw importance 165 165 240 228 223 269 205

Importance (%) 11.00 11.00 16.08 15.28 14.94 17.95 13.74

Strong, 9; medium, 5; weak, 1.



2. Membership functions for ~u:

i~u1�

0; r < 0 or r > 16

1 À 6r ; 0 r 16

(£g7 �

0; r 56

or r > 1

6r À 5; 56< r 1

(

for k � 2, 3, 4, 5, 6

£gk �

0; r k À 2

6or r !

k

6

6r À �k À 2�; k À 26

r k À 16

k À 6r ;k À 1

6 r

k

6

8>>>>>><>>>>>>:

Table 2

Averaged importance for each process

Member #1 Member #2 Member #3 Member #4 Member #5 Average

Customer relationship management 11.02 14.60 8.19 11.39 8.6 10.76

Customer service management 11.02 14.60 17.47 12.90 14.67 14.13

Demand management 16.07 16.07 18.08 15.20 11.86 15.46

Order fulfillment 15.27 16.07 18.08 11.81 11.86 14.62

Manufacturing flow management 14.93 12.64 6.34 14.86 18.41 13.44

Procurement 17.97 10.43 16.23 17.29 18.41 16.07

Product development 13.73 15.58 15.61 16.56 16.20 15.54

Fig. 5. The MADs for current process and a number of forecasting methods.




Fig. 8 shows membership functions for the uni-

verse of discourse. The summary of ®ve multi-

attribute methods by Triantaphyllou and Lin [28],

leads to the basic operations on fuzzy triangular

numbers and a ranking method by Zhu and Lee

along with the evaluations provided by a middle

manager for selecting the new procurement process.

Fig. 9 displays the membership functions of the

®nal results, and speci®cally, a new process that

shortens the purchasing and production±marketingcycle time to 2 weeks is selected for implementa-

tion.

5.6. The next BPR cycle focusing on strategic

alliance

Repeated implementation of the seven-step proce-

dure is required for continuous improvement. During

the ®rst cycle, two major processes (forecasting and

order procurement) were investigated and new pro-

cesses were suggested. According to the future plan of

BPR and strategic planning of the ®rm, new strategies

of collaboration in SCM have long been under con-

sideration by most of the manufacturers, including the

®rm being studied.

To increase the utilization of capacity, share the

costs and risk, mutually bene®t from core competen-

cies, and satisfy customers, a number of order sharing

policies were presented. The order sharing policies for

a virtual organization imply:

1. All orders are allocated to companies on the basis

of equal capacity utilization (policy 1).

2. All orders are allocated to companies on the basis

of prede®ned percentages (policy 2).

3. Each order is ®rst allocated to the company that

originally received the order. If that company's

capacity is inadequate, the excess portion is

reallocated to a company that has the least current

capacity utilization (policy 3).

Fig. 6. Simulation data with exponential smoothing forecasting and real market demand (normal distribution) per month during 5 years.




Fig. 7. Cost impacts for current procurement process and two new policies at current safety stock level.

Fig. 8. Membership function for universe of discourse in this study.




4. If a company capacity is inadequate, the excess

portion of the order is reallocated to a company

that has the least current accumulated capacity

utilization (policy 4).

For each policy of the above, assume that the lost

orders were entirely reallocated by the virtual orga-

nization to alliances. Any particular company is not

responsible for the lost order.

Fig. 9. Membership functions of the two alternatives of the new procurement processes according to the fuzzy approach.

Table 3

Comparisons of capacity utilization for strategic alliance policies

Capacity Mean Deviation Utilization

Policy 0 Policy1 Policy 2 Policy 3

Case 1 Manu. 1 40 50 20 0.949 0.930 0.949 0.955

Manu. 2 60 60 10 0.959 0.930 0.941 0.949

Manu. 3 80 60 5 0.756 0.930 0.910 0.881

Case 2 Manu. 1 80 70 20 0.853 0.848 0.856 0.854

Manu. 2 60 50 10 0.840 0.848 0.861 0.858

Manu. 3 40 30 5 0.761 0.848 0.806 0.822

Case 3 Manu. 1 80 70 20 0.853 0.847 0.856 0.853

Manu. 2 60 50 5 0.837 0.847 0.861 0.863Manu. 3 40 30 3 0.757 0.847 0.805 0.808

Case 4 Manu. 1 80 85 5 1.000 0.973 0.981 1.000

Manu. 2 60 60 3 0.987 0.973 0.984 0.994

Manu. 3 40 30 3 0.757 0.973 0.926 0.886

Case 5 Manu. 1 80 85 20 0.953 0.950 0.957 0.956

Manu. 2 60 60 5 0.979 0.950 0.961 0.990

Manu. 3 40 30 3 0.756 0.950 0.917 0.878

Case 6 Manu. 1 80 85 20 0.953 0.947 0.955 0.959

Manu. 2 60 60 10 0.959 0.947 0.959 0.977

Manu. 3 40 30 3 0.757 0.947 0.913 0.879




Each of the three policies 1, 2, and 3 was employed

to process orders for a number of periods in the case

study. The simulation results are presented in Tables 3and 4. Compared with the case without strategic

alliance (policy 0), the results show that better capa-

city utilization, less lost orders, and better due date

satisfaction are achieved, as well as possible reduced

marketing and other related costs under a variety of

scenarios.

6. Discussions and conclusions

A BPR framework and its associated implementingmethods are proposed here and applied to the supply

chain reengineering of a motorcycle manufacturer. A

CPAM and the proposed OOS schema are integrated

into the BPR framework. Once ®rms have decided on

their business vision and objectives, they can identify

the core business processes to be redesigned through

the CPAM. Using the proposed object-oriented world-

view simulation framework, ®rms can analyze and

compare the probable in¯uence of reengineering prior

to its implementation to reduce high risks.

It is very important that good communication exists

between the business personnel collecting the data and

the decision makers. Interaction is required in eachstep of the proposed framework.

In conclusion, through the proposed BPR frame-

work and associated implementing methods, we pro-

vide a systematic approach for industrial practice.

Most importantly, the BPR framework takes advan-

tages of the OOS, which can evaluate the reengineer-

ing in advance of the implementation, and this is

expected to reduce the high failure rate of BPR

projects.

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Table 4

Comparisons of lost quantities for strategic alliance policies

Capacity Mean Deviation Lost quantity

Policy 0 Policy1 Policy 2 Policy 3

Case 1 Manu. 1 40 50 20 458 51 69 197

Manu. 2 60 60 10 87 77 91 33

Manu. 3 80 60 5 0 102 76 0

Case 2 Manu. 1 80 70 20 179 32 39 71

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Manu. 3 40 30 3 0 57 31 0

Case 6 Manu. 1 80 85 20 389 125 137 236

Manu. 2 60 60 10 87 94 109 45

Manu. 3 40 30 3 0 62 37 0




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S. Wesley Changchien is an Associate

Professor with the Department of In-

formation Management at Chaoyang

University of Technology, Taiwan,

ROC. He received a BS degree in

Mechanical Engineering (1989) and

completed his MS (1993) and PhD

(1996) degrees in Industrial Engineering

at State University of New York at

Buffalo. His current research interests

include knowledge management, knowledge discovery, data

mining, bio-informatics, agent technology, intelligent systems,

genetic algorithms.

Hsiao-Yun Shen is a candidate for doctorate

degree in National Chiao Tung University in

Taiwan. She received her MBA degree in

1999 with major in information manage-

ment from Chaoyang University of Tech-

nology. Currently, she is doing research on

the subject of information security manage-

ment in electronic commerce.


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