AN ANALYSIS BETWEEN ORGANIZATIONAL STRUCTURE
AND ENTERPRISE RESOURCE PLANNING SYSTEM
IMPLEMENTATION SUCCESS
by
MURAT COLAK, B.S.
A THESIS
IN
SYSTEMS AND ENGINEERING MANAGEMENT
Submitted to the Graduate Faculty
of Texas Tech University in
Partial Fulfillment of
the Requirements for
the Degree of
MASTER OF SCIENCE
IN
SYSTEMS AND ENGINEERING MANAGEMENT
Approved
Chaj^erson of the Committee
Accepted
Dean of the Graduate School
December, 2004
ACNOWLEDGEMENTS
Throughout the course of my master's research, I have gained tremendous insight
into experimental study. I want to thank my mentors who assisted me in along the ways
in accomplishing my goals while holding onto values, personal integrity and intellectual
honesty.
I am deeply grateful to Dr. Elliot J. Monies for his advice, guidance and kind
support during my studies. His encouragement and valuable suggestions especially
helped me during the completion of this research.
I would like to thank other members of my defense committee: Dr. Mario G.
Beruvides and Dr. Terry R. Collins. Their encouragement and advice have been
invaluable.
And also I would like to thank Dr. Atila Ertas and Atilla Filizler, ISIS General
Manager, for their help, guidance and advice during my research.
Finally, I am deeply indebted to my mother and father, Serpil and Ramazan
Colak, without whom I would not be what I am today. I am also lucky that I have a
loving and caring brother, Gokhan Colak. My family members have been my strongest
source of strength and inspiration, and I thank them for their patience, love and support
through the years.
n
LIST OF CONTENTS
ACNOWLEDGEMENTS
ii
LIST OF TABLES
vi
LIST OF FIGURES
ix
CHAPTER
1
L INTRODUCTION
1
1.1 Introductory Remarks
1
1.2 Critical Success Factors
4
1.3 Research Question
8
II. LITERATURE REVIEW
9
2.1 Introductory Remarks
9
2.2 Organizational Structure Types
9
2.3 Relationship between ERP Systems and Organizational Structure
16
2.4 Effects of Organizational Structure
19
in. EXPERIMENTAL DESIGN
21
3.1 Introduction to Experimental Design
21
3.2 Hypothesis
23
3.3 Experiment Tool
27
IV. DATA ANALYSIS
33
4.1 Introduction to Data Analysis
33
4.2 Methods Used in Analyzing the Survey
33
4.3 General Properties of the Companies
34
4.4 Reliability Test of the Survey
39
4.5 Statistical Analysis
40
4.6 Hypothesis Testing
44
4.7 Interpretation of the Results
75
V. CONCLUSION
80
BIBLIOGRAPHY
83
ni
APPENDICES
86
A: CODE BOOK FOR THE SURVEY DATA
87
B: SURVEY
92
C: RAW DATA
96
IV
ABSTRACT
In the past decade, the business environment has changed dramatically.
The
world has become a small and very dynamic marketplace and the evolution of Enterprise
Resource Planning (ERP) systems has been a highlight in the information systems arena.
While the growth of ERP systems has been enormous, cost and failures have undermined
its true capabilities. With respect to the high percentage of implementation failures, it is
very important to study all of the critical success factors in order to increase the ratio of
successful implementations.
This research presents an experimental design for a survey that will be utilized to
investigate what effect that organizational structure has on the success of ERP
implementation. First the organizational structures are described and possible effects of
these structures are identified. Then, the necessary tests to analyze the survey are
described. Finally, the results of the statistical analysis take place.
After getting the results, the expected and actual relationship between the
variables are discussed. Finally, conclusions about these results and fiature research that
may take place after this study is described.
LIST OF TABLES
1.1
Critical success factors
5
1.2
CSF's in the literature according to Jens Laurits Nielsen's research
6
2.1
Natural matches between predominant CBIS configuration and organizational
structure
18
3.1
Expected relationships between significance levels of organizational structures
in terms of in achieving the success factors
24
3.2
Example for coding the data
32
4.1
Sector that the company works for
34
4.2
Product type of the company
35
4.3
Annual sales company in year 2003 (sales)
36
4.4
Number of the employees
36
4.5
Which ERP software does the company use?
36
4.6
What was the implementation time that was planned before
starting? (in months)
37
4.7
How long did the implementation take? (in months)
38
4.8
Percentages of the companies that exceed the planned implementation time
38
4.9
4.10
Percentage of the old data which is transferred to the new system
Percentage of the work processes which are redefined during BPR (Business
Process Reengineering)
38
4.11
Reliability statistics
40
4.12
Normality test
41
4.13
Crosstabulation results for the success factor SI
44
4.14
The Kruskal-Wallis H test results for the success factor SI
46
4.15
The Mann Whitney U test between the Functional Structure and
Matrix Structure in terms of the success factor flexibility (SI)
The Mann Whitney U test between the Matrix Structure and
Pure Project Structure in terms of the success factor flexibility (SI)
48
The Mann Whitney U test between the Functional Structure and
Pure Project Structure in terms of the success factor flexibility (SI)
49
Crosstabulation results for the success factor S2
50
4.16
4.17
4.18
VI
39
47
4.19
The Kruskal-Wallis statistical analysis for success factor S2
52
4.20
Crosstabulation results for the success factor S3
53
4.21
The Kruskal-Wallis statistical test for success factor S3
54
4.22
The Mann-Whitney U test, functional structure vs matrix structure
55
4.23
The Mann-Whitney U test between matrix and pure project organization for
success factor, S3
55
4.24
The Mann-Whitney U test between functional and pure project organization for
success factor, S3
56
4.25
Crosstabulation test for the success factor, S4
58
4.26
Symmetric measures and Cramer's V for success factor S4
58
4.27
The Kruskal Wallis test for the success factor S4
59
4.28
The Mann-Whitney U test between functional structure and matrix
structure for standardization
59
The Mann-Whitney U test between matrix and pure project structure for
standardization
60
The Mann-Whitney U test between functional and pure project structure for
standardization
60
4.31
Crosstabulation between organizational structure and success factor S5
61
4.32
The Kruskal-Walhs test for success factor S5
62
4.33
Crosstabulation table for success factor S6
64
4.34
The Kruskal Wallis test for success factor, S6
65
4.35
Crosstabulation for success factor S7
66
4.36
The Kruskall Wallis test for success factor S7
67
4.37
The Mann-Whitney U test between functional structure and the matrix
structure for success factor S7
67
The Mann-Whitney U test between matrix structure and pure project
structure for success factor S7
68
The Mann-Whitney U test between functional structure and pure project
structure for success factor, S7
69
4.40
Crosstabulation for success factor SB, time
70
4.41
The Kruskal Wallis test for success factor S8
71
4.42
Crosstabulation for the total success of the ERP implementation
72
4.43
The Kruskal Wallis test for total success of the ERP implementation
73
4.29
4.30
4.38
4.39
Vll
4.44
4.45
4.46
4.47
The Mann-Whitney U test between functional and matrix structure
for the total success of the ERP implementation
73
The Mann-Whitney U test between matrix structure and pure project
structure for the total success of the ERP implementation
74
The Mann-Whitney U test between fiinctional structure and pure project
structure for the total success of the ERP implementation
75
Actual relationships between significance levels of organizational structures
in terms of achieving the success factors
76
Vlll
LIST OF FIGURES
2.1
Traditional Management Structure
12
2.2
Pure Project Organization Structure
12
2.3
A typical matrix structure
15
4.1
Location of the companies involved to this research
34
4.2
Positions of the individuals who took the survey
35
IX
CHAPTER I
INTRODUCTION
1.1 Introductorv Remarks
In recent years, business environment has transformed dramatically and continues
to do so every day, as the global marketplace keeps pace with a shrinking worid.
Organizations today deal with new markets, new competition and increasing customer
expectations. This has placed an incredible demand on manufacturers in seven main areas
in order to: 1) Lower total costs in the complete supply chain, 2) Minimize the stock level
3) Shorten throughput times, 4) hicrease product variety, 5) hnprove the quality of
product 6) Provide more reliable delivery dates and higher standard service to the
customer, and 7) Efficiently organize global demand, supply and production. As a result,
today's companies have to re-engineer their business practices and procedures if they
want to be more responsive to customers and competition. In the past decade, information
technology and business process re-engineering, used in combination with each other,
have emerged as important tools which give organizations the leading edge. As a solution
to these problems, organizations have begun to use software packages to integrate all
their needs and work in the same data base. These packages are called Enterprise
Resource Planning Systems.
As Bradley stated, "ERP systems promise to meet the information needs of
organizations with an off-the-shelf solution for replacing legacy information systems"
(Bradley, 2003,pp. 1023). ERP systems attempt to integrate all departments and functions
across a company onto a single computer system that can serve all those different
departments' particular needs. Emerging in the 1960's, Enterprise Resource Planning
Systems have gone through a long journey throughout their development. The focus of
manufacturing systems in the 1960's was on Inventory control. Software packages were
designed to handle inventory based on traditional inventory concepts. From the beginning
of the 1970's, the focus changed to Material Requirement Planning (MRP) Systems
which translated the Master Schedule built for the end items into time-phased net
requirements for the sub-assemblies, components and raw materials planning, and
procurement. Then, in the 1980's, the concept of Manufacturing Resources Planning
(MRP-II), which was nothing but an extension of MRP to shop floor and distribution
management activities, grew in importance. At the beginning of the 1990's, the increased
complexity of business and the need for integration of all of the functions, especially for
global companies, within an enterprise designed to keep up in the dynamic environment,
led to the development of Enterprise Resource Planning (ERP) tools. ERP was an
extension of MRP II to cover the range of activities within any enterprise. Furthermore, it
addressed technical aspects like client/server-distributed architecture and object oriented
programming.
ERP packages
supply talented means for
companies to get business
breakthroughs. As Slater said, the target of these packages is to provide a single,
integrated software system that handles a host of corporate functions, including finance,
human resources, materials management, and sales and distribution (Slater, 1998). In
fact, companies usually implement ERP systems for five main reasons. Koch (2002)
stated these reasons as follows;
• Integration of the financial information: Examining the company's overall performance
depends on the identification of financial information. In some companies, the financial
indicators change from unit to unit. An ERP system uses one common version for all
the units thus the results can be questioned easily.
• Integration of the customer order information: ERP systems can become the place
where the customer order lives fi-om the time a customer service agent receives it until
the loading dock ships the products and finance sends an invoice. By having this
information in one software system that can communicate with other available systems,
companies can keep track of orders more easily, as well as coordinate manufacturing,
inventory and shipping among many different locations at the same time.
• Standardizing
and speeding up manufacturing processes: Most manufacturing
companies find that the various business units in the company make the same widget by
using different systems and tools. ERP systems standardize the methods for automating
several steps of a manufacturing process. With this standardization and by using a
single, integrated computer system, companies are able to save time, increase
productivity, and reduce head count.
• Reducing Inventory: ERP systems give more control within the manufacturing process
and they help to improve visibility of the order completion process inside the company.
This can reduce inventory and help to come up with a better delivery plan for customers
by reducing the finished good inventory at warehouses and shipping docks.
• Standardize HR Information: In companies that have multiple business units, HR may
not have a standardized and simple method for communicating with and tracking
employees. ERP systems can fix that problem by standardizing these methods and
simplifying them.
Based on the reasons listed above, it can be seen that the word "standardization"
and "integration" are clues to answering the question, "Why would companies want to
implement ERP Systems?" In such a dynamic business world companies and especially
employees have to know precisely what they are doing. These systems allow
organizational standardization across different locations. Without standardizing methods,
tools and processes, companies cannot run away fi-om the chaos they experience from a
disruptive change.
O'Leary (2000) lists the most important dimensions of the ERP systems;
• ERP affects the predominant corporations in the market.
• ERP affects many small and medium companies.
• ERP affects competitors' behavior.
• ERP affects business associates necessities.
• ERP changes the character of consulting companies.
• ERP provides one of the most important tools for reengineering.
• ERP changes the characteristics of jobs in all areas.
• ERP cost is high.
• ERP increases its market share incredibly.
If these dimensions are examined carefully it can be seen that ERP systems have a
deep impact on organizations in terms of many features such as business reengineering,
job definitions, information flows, costs, partner requirements, etc. For nearly all
companies, the cost dimension, expressed in the hst above as "ERP cost is high", is the
most important and also daunting characteristic of ERP systems. According to META
group, a company that provides IT and business guidance to companies, the average cost
of the implementation of an ERP System is $15 miUion, at a cost of $53,320 per user.
These costs include hardware, software, professional services and internal staff costs for
the full implementation in addition to 2 years of post-implementation support (META
Group).
1.2 Critical Success Factors
In spite of the benefits that can be achieved after a successful ERP
implementation, there is a high risk of failure in these implementation projects. The
percentage of ERP implementations that can be classified as "failures" ranges from 40%
to 60% or higher (Sousa and CoUado, 2000). These percentages are really high for a
project with such a very high cost. Therefore, one of the major research issues in ERP
systems today is the study of ERP implementation success. Successful implementation
focuses on technical, financial, and non-technical issues. The definition and measurement
of ERP implementation success is a very difficult subject. Sousa (2000) says, "Some
authors have shown that this success definition and measurement depends on the points
of view of the involved stakeholders" (pp.12). The most typical definition and
measurement approach is the critical success factors approach. Sousa et al. (2000) defines
these CSFs in Table 1.1.
This model shows ahnost all critical success factors found in the ERP literature.
Because of the high cost and high risk of failure, it is always worthwhile to examine the
factors that determine whether or not the implementation will be successfiil. ft is better
for organizations to know their ability to achieve the goals during implementation. Thus,
they know their capacity and are prepared before failures happen.
Table 1.1 Critical success factors (Souza, 2000).
Organizational
Strategic
Tactical
• Sustained management support
• Dedicated staff and
• Effective organizational change
management
• Good project scope management
• Adequate project team composition
• Comprehensive business process
reengineering
• Adequate project champion role
• User involvement and participation
• Trust between partners
consultant
• Strong communication
inwards and outwards
• Formalized project
plan/schedule
• Reduced trouble shooting
• Appropriate usage of
consultants
• Empowered decision
makers
Teclinological
• Adequate ERP implementation
strategy
• Avoid customization
• Adequate software
configuration
• Legacy systems
• Adequate ERO version
In order to manage implementation successfully, project managers must have both
strategic and tactical management capabilities. As seen fi-om the table 1.1, one of the
strategic organizational factors is the effective organizational change management. ERP
implementation forces companies to make business process reengineering.
Umble et al (2003) states that "The existing organizational structure and processes
found in most companies are not compatible with the structure, tools and types of
information provided by ERP systems" (pp.246). Some companies that implement even
the most flexible ERP systems are forced to change their strategy, organization and
culture.
Critical success factors in the literature can also be listed as follows:
Table 1.2 CSF's in the literature according to Jens Laurits Nielsen's research (2002).
Critical Success Factors
1
Minimal customization
2
Business process reengineering
3
Discipline and standardization
4
Business integration
5
Use of tools for the development
6
Interdepartmental cooperation and communication
7
Customer satisfaction
8
Reporting functionality
9
Appropriate decision making fi-amework
10
Top management support
11
External expertise (use of consultants)
12
Change management
13
User participation
14
Education and training
15
Effective communications
16
Technical and business knowledge
17
Hardware issues
18
Information and access security
19
Implementation approach
Therefore, implementing an ERP system may force companies to experience the
reengineering of their most important business processes and/or develop new business
processes that are in line with the organization's goals (Umble et al. 2003). In fact, most
managers mistakenly think that ERP is a simple software system and implementing this
system is only a technological challenge. Thinking in this manner causes most of the
failures because implementing ERP systems is a very serious project that all chief
executives have to pay attention to and spend time on accordingly, hnplementing ERP
systems can redesign processes and these processes need corresponding realignment in
organizational control to continue the effectiveness of the reengineering efforts. Umble et
al. (2003) says that the resulting changes from this reengineering process may
considerably affect organizational structures, processes, policies, employees and the
culture.
The ultimate goal of this project should be to improve the business, not just
focusing on implementing the software. The implementation should be business driven
and directed by the managers, as opposed to the IT department. ERP system
implementation has a very deep impact on business processes and also on employees. If
people are not ready for these significant changes, then rejection, confrontation and chaos
will be appear as a result of the implementation. However, when the change management
techniques are used, the company will be prepared for opportunities provided by the new
ERP system. The organizations have to be flexible enough to achieve all of the
advantages of these benefits (Sherrard, 1998). So, a question that might occur fi-om as a
result, "Is the organization flexible enough to implement the system and achieve the
benefits?"
Allen et al. (2002) states that organizational culture has a significant impact on the
implementation. Shein (1992) defines the organizational culture as an objective entity
consisting of a set of behavioral and cognitive characteristics:
a pattern of basic assumptions- invented, discovered or developed by a
given group as it learns to cope with its problems of extemal
adaptations and internal integration- that has worked well enough to be
considered valid and therefore to be taught to new members as the
correct way to perceive, think and feel in relation to those problems.
(pp.112)
Organizational structure produces an effect on the organizational cultiare. For
example, if a hierarchical structiire restiicts cross-fimctional communications, then close
relationships between interrelated fiinctions will be more difficult. Similarly, in a
unionized organization the relationship between management and the union will set the
stage for how cooperatively people are able to work together toward common goals.
Therefore, one of the factors that determines the flexibility and culture of an organization
is the organizational structure (Gulla, 1999).
There are many parameters in achieving the successful in ERP implementations.
It would be very useful to know which one of these uses is the most effective in
successful ERP implementation so that whether or not a company might achieve its
objectives could be determined. The lack of the information in the Hterature about the
parameters which are mentioned above will be flilfilled by the resuUs of this research.
Low complexity, low formalization, decentralized decision making and problem
solving are the key elements of easy implementation. For a complex process such as ERP
software implementation, these elements are more important. So, for expected outcome
of this research matrix strucmre, flat organizations and pure project structure have an
advantage in terms of the elements that are mentioned above.
1.3 Research Question
How does organizational stioicture effect ERP implementation success? The goal
of this research is to find the possible "'Relationship between ERP Implementation
Success and Organizational Structure ".
CHAPTER II
LITERATURE REVIEW
2.1 Introductorv Remarks
Organizational structure and information systems are highly interconnected with
each other. Over the years, information systems architectures as well as organization
strucmres have been changed from centralized to more decentralized forms. ERP
systems, when implemented successfully, make information more easily accessible,
which helps to create decentralized communication and control in companies.
Early ti-ends developed single business that kept overall control by vertical
integration (Mukherji, 2002). Organizational structures have been changed dramatically
in the last 30-40 years. The direction of these changes has been fi-om centralized forms to
decentralized forms. Mukherji (2002) says, "This was a movement away from functional
control to divisionalized control" (pp.501). It is very important that organizations realize
that in many situations a decentralized form more effectively manages changes in the
environment. This form leads organizations to be more flexible.
2.2 Organizational Structure Types
Decentralization is still moving further and the latest structure types are in the
forms of matrix, hybrid and network, says Daft (2001). Each of them helps to cope with
increasing turbulence in the extemal environment. Organizations are continually
restructured to meet the demands imposed by the environment. This can change the role
of individuals in the formal and the informal organization. No matter which
organizational structure is finally selected, formal channels must be developed so that
people have a clear explanation of the authority, responsibility and accountability
necessary for the work to proceed (Kerzner, 2003). Kerzner identifies these three issues
as follows;
• Authority is the power granted to individuals (possibly by their position) so that
they can make final decisions.
• Responsibility is the obligation incurred by individuals in their roles in the
formal organization to effectively perform assignments.
• Accountability is being answerable for the satisfactory completion of a specific
assignment. (Accountability = authority + responsibility) (pp.90-91).
hi this study, three types of organizational structures will be studied which are the
most popular today.
2.2.1 Functional (Classical) Structure
At the beginning of the 20"" century a German sociologist Max Weber described
an ideal organization and mentioned the following characteristics:
•
Division of labor: Each employee's job is well-defined and broken into simple
and routine tasks.
•
Well defined authority hierarchy: A multilevel formal structure with a hierarchy
of positions where each lower level is under the control of a supervisor.
•
Impersonal nature: Authorizations are applied uniformly and impersonally to
avoid undue bias.
•
High formalization: There are formal rules and procedures to guarantee
uniformity and to control the behavior of the employees.
•
Employment decision based on merit: Employment decisions are based on
technical qualifications and performance of the candidates.
•
Career tracks for employees: All the employees are expected to pursue a career
in the company.
•
Distinct separation of members' organizational and personal lives: Anxiety and
the interests of the individuals are kept completely separate to stop them
interfering with the organization's activities.
In this kind of stiiicture that Weber described, positions are arranged in a
pyramidal hierarchy. Authority increases as one climbs the organizational ladder, which
characterizes general bureaucracy (Robbins, 1983).
10
This traditional management structure has survived for more than two centuries.
However, recent developments in the business world, such as the change in technology
and increased stockholder demands, have created strain on existing organizational forms.
An example of a traditional management structure is shown in figure 2.1. Where the
general manager has all the functional entities necessary to perform R&D or develop and
manufacture a product (Kerzner, 2003). All jobs take place within the functional groups
and are headed by a department head. Very strong concentration of technical expertise is
maintained by each department. While all projects must flow through the functional
departments, each of them can make use of the most advanced technology. This makes
this type of structure well suited to mass production. According to Kerzner the
advantages and disadvantages of the classical structure are hsted as follows;
Advantages;
• Easier budgeting and cost control are available,
• better technical control (knowledge and responsibility sharing),
• flexibility in the use of manpower,
• easily
defined
and understandable poUcies, procedures
and
lines of
responsibility,
• good control over personnel,
• established communication in a vertical pattern, and
• quick reaction capability, but dependent on the priorities.
Disadvantages;
• No one individual is directly responsible for total.
• no customer focal point,
• complex coordination, with additional time required for approval decisions,
• slow response to customer needs,
• decreased motivation and innovation, and
. decisions normally favor the strongest fiinctional groups.
11
Executive
Office
+
Division
Engineering
Operations
Financial
Administration
Marketing
1
1
1
Department
Section
7-—I
Functional
Responsibility
Figure 2.1 Traditional Management Structure
2.2.2 Pure Product (Project) Organization Structure
This kind of structure develops as a division within the division. If projects flow
continuously than work is stable and conflicts are at minimum level. The most important
benefit of this type of structure is that one individual maintains complete authority over
the whole project (Kerzner, 2003). Pure project organization structure has strong
communication abilities that result in a very quick reaction time. An example for the pure
product (project) organization structure is given in the following figure.
General
Manager
r
Product A
Manager
ENG.
MANU.
Product B
Manager
MANU.
ENG.
1
Product C
Manager
ENG.
MANU.
Figure 2.2 Pure Project Organization Structure
12
The major downside of this kind of structure is the cost of maintaining the
organization. There is not possibility to share an individual with another project with the
purpose of reducing costs.
As compared to traditional structure, pure project structure keeps activities on
schedule with fast reaction times. But the technology is not as well developed as in the
tiaditional structure because of the lack of strong functional groups which create
technical communication in the company. Some advantages and disadvantages of the
pure project organization sti-ucture are listed as follows:
Advantages:
• Provides complete line authority over the project,
• strong communication ability,
• very fast reaction times,
• unprofitable product lines can be determined and eliminated easily,
• a focal point develops for outside company customer relations,
• interface management becomes easier as unit size is decreased, and
• upper-level management has more time for executive decision making.
Disadvantages:
• In multiproduct companies the cost is high to maintain this kind of form in
terms of effort, facilities and personnel,
• technical interchange between projects is not possible,
• technology suffers because of the lack of the strong functional groups, and
• upper-level management is needed to balance the workloads as projects start up
and phased out, especially in terms of the controlling the facilities and
equipment,
2.2.3 Matrix Organizational Structure
This kind of structure is developed to combine the advantages of the two types of
forms that are mentioned above; pure functional structure and the pure project structure.
In figure 2.3, the direction of project responsibility and the functional responsibility can
13
be seen. Functional departments are responsible for maintaining technical excellence on
the project. Project managers have responsibility and the accountability for project
success.
Warren G. Bennis, cited by Robbins (1983), defines a matrix structure as follows,
"a rapidly changing, adaptive, temporary system organized around problems to be solved
by groups of relative strangers with diverse professional skills." This form of structure
has the characteristics of low complexity, low formalization, and decentralized decision
making. It has a high degree of horizontal differentiation based on formal training. The
most important sti-ength of the matrix stixicture is the abihty to respond rapidly to changes
in the environment.
The matrix has a dual chain of command. In this type of structure, every
employee has two bosses, a department manager, and a project manager, to report. As
Mukherji (2002) stated, for a matrix to function mutual coordination and cooperation are
critical factors. Thus, these organizations act like project teams. They are basically
organic with little formalization.
This kind of sti-ucture eliminates ahnost all of the
disadvantages of the traditional structure.
According to Harold Kerzner, the advantages of the matrix structure are listed as
follows;
• The project manager has maximum control of the project resources, including
cost and personnel.
• For each project, policies and procedures are developed independently.
• Quick responses are available for changes, inconsistency resolution, and project
needs.
• The functional groups stand mainly as support for the project.
• Due to the sharing of key people, the program cost is minimized. People can
work on different problems, thus better control on people is possible.
• A strong technical base can be developed, and much more time can be directed
to complex problem-solving. Knowledge exists for all projects equally.
• There is a better balance between cost, time, and performance.
14
• There is a fast development of specialists and generalists.
• Authority and responsibility are shared.
In the following figure a typical matrix structure can be seen.
General
Manager
1
Engineering
1
isibility
s
Project Mgr.
Y
Operations
Financial
Others
i
T
•
Functional
Project Mgr.
X
1
Project Mgr.
Z
'
Figure 2.3 A typical matrix structure.
The disadvantages of this kind of structure can be listed as follows;
• Multidimensional information and work flow.
• Double reporting.
• Constantly changing priorities.
• Difference between management goals and project goals.
• Difficulty monitoring and controlling.
• Every project organization works independently. Thus, duplication of efforts
does not exist.
• Compared to the tt-aditional structiire, more time and effort are necessary to
define policies and procedures.
• Possibility that the functional manager is biased to their own priorities.
• Balance between organizations (project and management) and between time,
cost, and performance must be monitored.
• Because of dual reporting people do not feel that they have any control over
their own fate.
15
2.3 Relationship between ERP Systems and Organizational Structure
Terry Lister of IBM Consulting Service says that 61.9% of the ERP
implementations range between somewhat successful and not very successful. Only
32.1% of the implementations are between very successful and successful. He also stated
that 52% of the barriers to ERP success include two main challenges, change
management and communication. These two problems are directiy related to the structure
of the organization in terms of its communication capability and flexibility for the change
management. Organizational structure is a performance-driven
feature in ERP
implementations, whether it gives the flexibility and the capability of response to the
transformation.
Krumbholz (2001) stated that, "ERP implementations in North America have
been more effective because of the more complex European organizational and national
sti-ucture and cultiu-es." Successful implementations are expected to increase because
companies move fi-om complex ones to simpler structures.
Lee and Leifer (1992) summarize natural matches between Computer Based
Information Systems (CBIS) and organizational design in the following table in the sense
of actions and behaviors required by CBIS (Table2.1).
Boudreau (1999) said that because ERP systems require business process
reengineering, many companies are attracted to these systems because of their need to
change not only the technology but also the processes through which business is
conducted. Because of the dramatic change of the business process reengineering, ERP
implementations have enormous effects on organizational structures.
Thus, it is not surprising that making the transition to ERP is neither easy nor
quick. So, the question arises "What if our organizational structure does not need to
change as much as others or it is flexible enough to respond to BPR easily?" Companies
can change their structiires before implementation in order to be more flexible and, in this
way, they can achieve the goals for the implementation and business process
reengineering more effectively without wasting money and time. Reporting the findings
of a large survey undertaken in the eariy 1990s, it is found that the organizations are
16
moving a "hybrid" model that is a combination of the form of the hierarchical
bureaucratic model with alternative, more flexible structure types. Avgerou (2000) stated
that.
On the contrary, the merits of the bureaucratic organizational form
have been challenged, and various different ways of organizing human
activity within the prevailing market driven socio-economic regime
came to be seen as legitimate alternatives. The quest for and adoption
of new organizational features, more suitable for their changing
environment, constitutes a deinstitutionalization process. In most
organizations, the effectiveness of their management structure and
work processes, the merits of their culture, and often the wisdom of
their mission are questioned, and innovation efforts permeating all
such organizational elements are frequently attempted (pp.304).
Yet, technology-driven approaches are often obviously pursued in some countries
with visible economic success, and in the developing world, IT modernization is often
advocated as a requirement for achieving the organizational structures and activities
which are necessary for contribution to the global economy (Schware and Kimberley,
1995).
Markus and Robey (1988) have identified three conceptions of causal agency in
the literature on information technology and organizational change. These are as follows:
the technological imperative, the organizational imperative, and the emergent imperative.
In the technological imperative, information technology appears to be the reason for
organizational structure change. In the organizational imperative, the motives and actions
of the producers of information technologies are reasons for the change in the
organizational structure.
With respect to identifying the critical success factors, an attempt has to be
undertaken. For this purpose, special attention should be directed towards the
organizational structure of the institutions. The reason for this emphasis is that the
organizational structure and processes are often stated as a major critical success factor in
many arguments (Wall and Seifert, 2002).
17
Table 2.1 Natural matches between predominant CBIS configuration and Organizational
structure
Categorization of CBIS
Type of Organizational
Structure
Simple Structures
(small, young,
centralized, little
formalization, CEO
control)
Machine Bureaucracy
(old, large, centralized,
formalized, functional,
bureaucratic,
standardization of work)
Professional
Bureaucracy (little
formalization,
bureaucratic
standardization of skills,
decentralized, high skill
specialization)
Divisionalized Form - A
(old, large, machine
bureaucratic division
oriented to markets,
standardization of
outputs, loosely coupled
to administration)
Stand Alone
PC's
(independent
processors not
linked to each
other
Supports CEO
with limited
amounts of
information
processing
capabilities
Centralized
Systems
(Mainframe with
dumb terminals)
Distributed Systems
(central host linked
with smart terminals,
many to one
communications)
Decentralized
Systems (linked
independent terminals
or processors, many
to many
communications)
Need for
centralized
fmancial and
operational
control.
Access to
mainframe
processing
capabilities, data
bases or libraries,
time sharing
Local individual
processing to support
individual needs and
linked to specialized
or large data bases.
Intra division
needs
Characteristics
same as machine
bureaucracy
Division processing
linked to the
administrative unit's
centralized processor.
Little interdivision
communication, need
for control by central
administration.
Divisionalized Form -B
(large, bureaucratic or
organic division
converted to markets,
tightly coupled to
administration by strong
culture)
Large amounts of
information sharing,
access to distributed
data bases, LAN or
email, enhances
information
processing
capabilities both
horizontally and
vertically.
Adhocracy (young,
decentralized, low
formalization, small,
coordinated by mutual
adjustment, organic,
high specialization of
skills
Requires high
information processing
capabilities supports
team functioning.
Allows adhoc
"synthetic" groups for
specific problem sharing
and coordination.
Supports complex task
driven relationships. Fast
interpersonal
communication
18
2.4 Effects of Organizational Structure
A major research question for this work is to prove whether organizational
structure has an influence on ERP success or not. For Wall and Seifert (2002), there are
three different perspectives that influence ERP implementation success: organizational
flexibility, organizational fit, and informational power.
Organizational flexibility, as mentioned before, is one of the most important
features that helps organizations to respond to significant and unpredictable changes.
From the technological imperative view, ERP systems do not force a definite
organizational sti-ucture on the whole but they cause process changes in many cases. Wall
and Seifert made a statement about these process changes, "organizational structure
appears to be an influence factor on the ERP system success in so far as structiire
influences the flexibility and innovative ability of an organization." Regarding this
statement it can be said that organic structures allow a greater capacity for independence,
show a creative direction of information flow as well as a small importance of
formalization and programming.
According to the statement above, it seems that organizations which have organic
and flexible structures are able to deal better with the changes that ERP systems cause
and thus they may be able to take advantage of these systems more easily.
From the view of organizational fit, Markus and Robey (1983) point out that a
good fit of the information system does not necessarily ensure the success of the system.
A system with a good organizational fit may be easier because of less resistance in the
organization but, with that, inefficient organizational structures may be "cemented."
Formal organizational structures affect the organization success to a high degree.
The nature of organizations determines their activities, the information support they need,
and the type of information system they use. Therefore, their structures influence all the
important performance measures of the organizations. In terms of the success of ERP
systems implementation, organizational structure effect should be examined to achieve
the best results from the implementation and get the benefits of these systems
19
immediately. Returning of investments on these systems is really important for
companies in such a turbulent business world.
20
CHAPTER III
EXPERIMENTAL DESIGN
3.1 Introduction to Experimental Design
In this study, a possible influence of organizational structure on ERP
implementation success will be investigated. There are many parameters in achieving
success in ERP implementation for a company, which include software flexibility,
appropriate tool selection, simplicity of reaching data, storing the data in the appropriate
format, ease of reporting, in addition to financial, management, or resource control. Of
course, in terms of the companies' own expectations the importance of these uses varies
between companies. It is very useful to know which one of these uses is the most
effective in the success of ERP implementations so it can be more accurately determined
if the company achieves its objectives or not.
On the other hand, in this study organizational structure is one of the most
important variables that will be discussed. With respect to the goals of this study,
organizational structure in the companies that use ERP systems is a parameter which is
will be determined. Today, the most common existing organizational structure types in
are fimctional structure, matrix structure, and pure project structure.
3.1.1 Bias
From a scientific standpoint, bias is just a tendency to examine the phenomenon
in a way that differs fi-om "true" observation in some reliable fashion. Most biases in the
social sciences are social. Social-scientific issues are affected by the observer's beliefs,
emotions, and other mental specifications (Simon, 1969).
In this research, every aspect of the survey and the hypothesis is based on the
literature review. In the literature review, ERP success factors and the organizational
structure types are explained in detail. Furthermore, an interpretation by the researcher
does not exist in any of the success factors mentioned in the literature review or in the
survey. In fact, according to the research question and the survey, it can be observed that
21
no personal or ethnic issues which can cause bias exist. All the samples are selected
randomly and they all are related to the research question.
3.1.2 Validitv
The core meaning of validity is explained entirely by accuracy. From this
perspective, a researcher's data are valid to the extent that the results of the measurement
process are accurate. In other words, a measuring instrument is valid to research when it
measures what it is supposed to measure (Huck and Cormier, 1996).
A survey is used for the research topic and the hypothesis. It is explained that the
questions in the survey are directly related to the research topic. Surveys are one of the
best tools to observe for the relationships between variables in the social science. A key
part of the survey is the analysis which obtains accurate results for the research.
Statistical analyses that are used for this research are explained in detail in the analysis
section.
A survey is sent to companies that use ERP systems. A key variable that is
controlled is whether the survey is answered by a qualified (authorized) person or not. So,
by this controlling mechanism survey, responses can be trusted in terms of if the answers
are given by the qualified people. The positions of the people answering this survey are
described in detail in the analysis section.
3.1.3 Reliability
Rehability is one of the basic elements of establishing vahdity. Rehability is the
degree of random variation in the results of the study. An important cause of overall
unreliability is a too-small sample size, hi this stiidy, the sample size is significant
enough to be representative. Reliability is roughly the same as consistency and
repeatability (Simon, 1969). The concept applies to either operational definitions or to
measuring devices.
Different statistical procedures have been developed to evaluate the degree to
which a researcher's data are reliable. These reliability techniques have led to a single
22
numerical index, called the reliability coefficient. For this purpose, internal consistency
reliability will be examined for the survey results which are applied one time to one
group; and these tests are explained in detail in the analysis section of the survey.
3.1.4 Representativeness
Representativeness is an important issue in research that uses surveys as a tool.
This feature is about the sample, not the method, hi this study, sample size is selected
from 100-120 responses. Thus, it is enough sample size to get the correct results fi-om the
research. Because the survey was sent only to companies which have ERP systems, the
expected results will be rehable. In other words the sample is chosen from a target
population so that any findings about the sample can be applied (generalized) to the
population. The survey contains question which looks for the position of the person who
takes the survey. So, the data can be discarded if the survey was answered by an
unauthorized or unqualified person.
A sample which is biased would not be
representative and this is one of the most important issues in representativeness. As
mentioned previously, in this study there is no bias problem.
3.2 Hypothesis
The research question is how does the organizational structure effect ERP
implementation success?
The goal of this research is to find out the possible
"Relationship between ERP implementation success and organizational structure. " The
following hypotheses have been developed to assess the possible relationship between
organizational structure and ERP implementation success:
Hypothesis 1: In comparing the organizational structure types. Functional Structure, Pure
Project Structure, and Matrix Structure are not equal in terms of achieving ERP Success
(SltoSS).
23
Hypothesis
la
Null Hypothesis: The significance level of Functional Structure (|LIF). Pure Project
Structure (^p), and Matrix Structure (^M) are equal in terms of achieving ERP
Success factor; Flexibility (f).
Ho: |iMf= I^Ff
Hi: ^Mf ?^^Ff
H o: \i-m = |ipf
H i : fx^f ?i^pf
Ho: |Xpf = i^Ff
H i : |ipf ?i|a,Ff
For any where Ho is rejected (according to the given matrix below);
H"O:
^xf :^^Yf
for X: M, F, P and Y: M, F, P
H 1: \ixi > |LtYf
Table 3..1 Expected relationships between significance levels of organizational
tructiires in terms of in achieving the success factors. (H:High, M:Medium, L:Low)
Functional
Matrix
Project Structure
Success Factors
L
H
M
Flexibility
L
H
M
Having the proper tools
L
H
M
Integration
H
L
M
Standardization
L
H
M
Ease of use of the ERP modules
H
M
L
Reporting
M
L
H
Satisfy customer demands
L
H
M
Implementation time
L
H
M
Total Success of the implementation
Hypothesis
lb
Null Hypothesis: The significance level of Functional Structure (|IF), Pure Project
Structure (|Up), and Matrix Structure (fiM) are equal in terms of achieving ERP
Success factor; Having the proper tools (pt).
Ho: i^Mpt^ ^Fpt
Hi: ^Mpt J^IiFpt
Ho: l^Mpt = M'Ppt
H i : UMpt 5^^Ppt
H Q: uppt = l^Fpt
H i: )Xppt ?^|iFpt
24
For any where HQ is rejected;
H o: ^xpt ^^Ypt
for X: M, F, P and Y: M, F, P
H 1: ^xpt > I^Ypt
Hypothesis Ic
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Structure (^p), and Matrix Structure (^M) are equal in terms of achieving ERP
Success factor; Integration (i).
HQ:
^Mi= HFi
Hi: \iu\
T^^FI
Ho: I^Mi = ^pi
Hi: ^IMI J^l^pi
Ho: |ip, = HFI
H I : |xpj j^iipi
For any where HQ is rejected;
H"O:
^ixi ^^Yi
for X: M, F, P and Y: M, F, P
H i: |ixi>^Yi
Hypothesis Id
Null Hypothesis: The significance level of Functional Structure (HF), Pure Project
Structure (jip), and Matrix Stincture
(|4.M)
are equal in terms of achieving ERP
Success factor; Standardization (s).
H o : jJ-Ms = P-Fs
H i : |IMS J^^FS
HQ: M^MS = P-PS
H I : |J,MS J^PPS
Ho: M^Ps = PFS
H I : UPS ?^PFS
For any where Ho is rejected;
H"O: |XXS ^PYS
for X: M, F, P and Y: M, F, P
H"i: fixs > PYS
Hypothesis le
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Structure (^p) and Matrix Structure (PM) are equal in terms of achieving ERP Success
factor; Ease of use of the ERP modules (eu).
H Q : M-Meu^PFeu
H ^ (iMeu J^^Feu
H Q : )LlMeu ~ MPeu
H ^ JiMeu 5^PPeu
25
H o: PPeu - PFeu
H i: |Ipeu ?i|iFeu
For any where Ho is rejected;
H o: Pxeu ^PYeu
for X: M, F, P and Y: M, F, P
H 1: PXeu > PYeu
Hypothesis If
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Stinctiire (PP), and Matrix Structure (PM) are equal in terms of achieving ERP
Success factor; Reporting (r).
Ho: HMr= PFr
H i : ^Mr T^V^Vx
H o : |iMr ^\i.?r
H i : I^Mr ?^M.Pr
H o: HPr = HFr
H i : Upr ?^|XFr
For any where Ho is rejected;
H"O: pxr ^liYr
for X: M, F, P and Y: M, F, P
H 1: Pxr > PYr
Hypothesis Ig
Null Hypothesis: The significance level of Functional Structure
(|IF),
Pure Project
Structure (|ip), and Matrix Structure (JXM) are equal in terms of achieving ERP
Success factor; Satisfying the customer demands (scd).
H o : PMscd= f^Fscd
H ^ I^Mscd J^^Fscd
H o : I^Mscd ~ M-Pscd
H i : jiMscd J^^Pscd
H o: M-Pscd = M^Fscd
H 1: Upscd 5^M-Fscd
For any where Ho is rejected;
H"O: nxscd ^PYscd
for X: M, F, P and Y: M, F, P
H 1: [ixscd > M^Yscd
Hypothesis Ih
Null Hypothesis: The significance level of Functional Structure (^F). Pure Project
Structure (|Xp), and Matrix Structure (|IM) are equal in terms of achieving ERP
Success factor; Implementation time (it).
Ho: UMit = PFit
H i : ^Mit J^^Fit
26
HO: PMit-|Xp,t
H'I: ^Mit 5^PPit
Ho:Hpit = pFit
H"I: lipit ?i^Fit
For any where Ho is rejected;
H o: pxit ^ILiYit
for X: M, F, P and Y: M, F, P
H 1: pxit > IiYit
Hypothesis 2: hi comparing the organizational structure types. Functional Structure, Pure
Project Sti-ucture, and Matrix Structure are not equal in terms of achieving the total
success of the ERP implementation
Null Hypothesis: Ho: The significance level of Functional Structure, Pure Project
Stinctiire and Matrix Stincture are equal in terms of total success (ts) of the ERP
implementation.
Ho: PMts= PFts
Hi: |iMts J^Iipts
Ho: l^Mts - ^pts
Hi: |iMts ^l^-Pts
H Q: \ipts= ^Fts
H i: \ipts J^Fts
For any where Ho is rejected;
H"O: pxts ^^Yts
for X: M, F, P and Y: M, F, P
H 1: pxts > M-Yts
3.3 Experiment Tool
To find the relation between these two variables, a survey is used for this research
to examine the correlation between different types of organizational structures and their
corresponding ERP implementation results. Two types of surveys are utilized in this
study; emailed questionnaire and Web-based fill-in form. They are fast, easy, interactive,
and accurate. They are also more effective in terms of results because data entry mistakes
will not occur.
27
3.3.1 Survey Structure
In order to assess the effect that organizational structure has on ERP implementation
success, a questionnaire has been developed to capture the following:
• Company respondent demographics such as company size, industry, and sales.
• Organizational structure type.
• ERP implementation success ratings.
The organizational structure types used in this survey questionnaire are:
• Functional structure (classical hierarchical structured organization having several
levels arranged in a tree-like structure)
• Pure project structure (project manager maintains complete line authority over the
entire project and associated resources)
• Matrix structure (combination of the functional and pure project organization where
resources are shared and managed across functions)
The survey consists of seventeen questions. All questions are closed-ended
questions. Closed-ended questions are quick to answer, easy to code and there are no
differences between articulate and inarticulate respondents. There are two types of scales
of measurement used in this survey, namely nominal scale and ordinal scale.
Observations of unordered variables, such as product type, ERP software name,
and sector that the company works for, are one of the most primitive forms of
measurement and are described as constituting a nominal scale (Edwards, 1958). In
nominal scales, numbers may be substituted for the names of the various classes of
variable. The numbers serve only to identify the classes and do not indicate anything
about the classes other than their difference. Thus, for example, in the first question, the
data labeled public can be identified with the number 0 and the data labeled private can
be identified with the number 1. This coding allows identification of variables during
statistical analysis.
In some cases, observations may be ordered in such a way that one observation
represents more of a given variable than any other observation. For example, in questions
15, 16, and 17, we have the degree of obtaining uses and the degree of importance of the
28
uses for the companies. They are scaled from very important to not important and from
totally to none. If very important and totally are identified by assigning 5 and not
important and none are identified by assigning 1, then this observation would be
described as constituting an ordinal scale, hi fact, a scale that is used in this survey for the
last three questions has a special name which is the Likert scale. A Likert scale is a type
of ordinal scale. The numbers used in identifying the observations are called ranks. Ranks
tell about the degree of the variable within the set of observations at hand (Edwards,
1958). These numbers will be discussed in more detail in the code book where the
numbers of codes that are used in this survey are explained.
All respondents' confidentiality will be maintained since such identifiers are not
requested within the questionnaire. According to the literature, there are many factors
that can be used to measure ERP implementation success. The following eight success
factors will be utilized within the survey questionnaire:
(51) Flexibility of the software in responding to the changes in the company's processes
or how adaptable is the ERP software in accommodating business process changes?
(Question 15 a)
(52) Having the proper tools for the company; does the ERP software fiinctionality
satisfy the company's business processing requirements? (Question 15b)
(53) What degree of business process integration has been achieved (i.e., common
accessibility of data, reports, and performance measures)? (Question 15c)
(54) Standardization of the processes; what degree of business process standardization
did you achieve? (Question 15d)
(55) The "ease of use" of the ERP modules (Question 15e)
(56) Effectiveness and completeness of the reporting functionality within the system
(Question 15f)
(57) The ability to satisfy customer demand (Question 15g)
(58) Implementation time of your system (i.e., fi-om system purchase to final
implementation or "go live") (Questions 8-9)
29
The objective of the study is to find out if there is a relationship between
organizational structure and ERP implementation success. So, to achieve this goal
statistical analysis has to be made regarding observation of relationship.
Human subject approval has been received from Texas Tech University
Institutional Review Board for the Protection of Human Subjects.
There are many ways to search for a possible relationship between two variables.
These solutions depend on the types of the variables that we have. It is important to
specify the scale of measurement of each of the two variables when examining the
relationship between two variables because these determine the type of analysis and
summary to be performed upon the data.
3.3.2 Types of Data
Data comes in various sizes and shapes and it is important to know about these so
that proper analysis can be conducted on the data. There are usually 4 scales of
measurement that must be considered:
Nominal Data
•
classification data, e.g. m/f
•
no ordering, e.g. it makes no sense to state that M > F
•
arbitrary labels, e.g., m/f, 0/1, etc
Ordinal Data
• ordered but differences between values are not important
•
e.g., political parties on left to right spectirun given labels 0, 1, 2
•
e.g., Likert scales, rank on a scale of 1 ..5 your degree of satisfaction
•
e.g., restaurant ratings
Interval Data
•
ordered, constant scale, but no natural zero
.
differences make sense, but ratios do not (e.g., 30°-20°=20°-10°, but
20°/10° is not twice as hot!
•
e.g., temperature (C,F), dates
30
Ratio Data
• ordered, constant scale, natural zero
•
e.g., height, weight, age, length
Only certain operations can be performed on certain scales of measurement. The
following list summarizes which operations are legitimate for each scale. Operations can
always be applied fi-om a 'lesser scale' to any particular data, e.g. nominal, ordinal, or
interval operations can be applied to an interval scaled datum.
•
Nominal Scale. Allowed to examine if a nominal scale datum is equal to some
particular value or to count the number of occurrences of each value. For
example, gender is a nominal scale variable. You can examine if the gender of a
person is F or count the number of males in a sample.
•
Ordinal Scale. Allowed to examine if an ordinal scale datum is less than or greater
than another value. Hence, you can 'rank' ordinal data, but you cannot 'quantify'
differences between two ordinal values. For example, political party is an ordinal
datum with the NDP to the left of Conservative Party, but you cannot quantify the
difference.
Another
example, preference
scores, e.g. ratings
establishments where 10=good, l=poor, but the difference
at
eating
between an
establishment with a 10 ranking and an 8 ranking cannot be quantified.
•
Interval Scale. Allowed to quantify the difference between two interval scale
values but there is no natural zero. For example, temperature scales are mterval
data which are 25C warmer than 20C, where 5C difference has some physical
meaning. Note that OC is arbitrary, so that it does not make sense to say that 20C
is twice as hot as IOC.
•
Ratio Scale. Allowed to take ratios among ratio-scaled variables. Physical
measurements of height, weight, and length are typically ratio variables. It is now
meaningful to say that 10 m is twice as long as 5 m. This ratio holds tine
regardless of which scale the object is being measured in (e.g. meters or yards).
This is because there is a natural zero.
31
3.3.3 Coding the Data to Analyze
Before the statistical tests take place, the data gathered from the survey should be
converted to a proper form that allows the data to be analyzed (Diamond and Jefferies,
2001). A code book gives information about each variable, such as name and type, along
with the units of measurement or categories as in the following example for the survey
that takes place in this study.
hi this example, every variable can be coded and converted to a proper form that
allows for analysis. After coding the survey, the data is ready to be analyzed for the
relationships between variables.
So, after the analysis any relationship between ERP implementation success and
organizational shncture will be seen. SPSS software will take place in the analysis of this
data. The whole codebook is given in the appendix.
Table 3.2 Example for coding the data
Variable Name
Variable Type
(Ql)Sector that the company
works for
Categorical
Codes
1-Pubhc
2=Private
1= Hierarchical Structure
(Q7)Which organizational
structure exists in your
2= Matrix Structure
Categorical
company?
3= Flat Organization
4= Simple Structure
5= Divisional Structure
l^None
2= Very Little
(Q16a) Evaluate these uses of
ERP in terms of the degree of
Categorical
3= Little
4= Partially
obtaining Flexibility
5= Totally
32
CHAPTER rv
DATA ANALYSIS
4.1 Introduction to Data Analysis
hi this chapter, the survey that was developed to search for a possible relationship
between organizational structure and ERP implementation success is analyzed by using a
statistical analyzing software package called SPSS.
Some of the contacts for this survey are gathered fi-om consulting firms and some
of them are found by searching on the web for companies that have implemented ERP
system and are already using the package. The survey was posted on the web and was
designed in such a way that the respondents have to answer all of the questions in order
to submit the survey. The issues about bias, validity, reliability, replicability and
representativeness are mentioned in the previous chapter. The reliability issue is also
going to be discussed with the necessary statistical analysis in the following sections.
4.2 Methods Used in Analyzing the Survey
At the begirming of the survey analysis, the situation of the companies is analyzed
and the general information is represented in the tables. For this purpose frequency
analysis is used.
After fi-equency analysis, a statistical test was performed to decide whether this
survey is reliable or not. For this study, inter-correlation analysis is used to find out the
reliability of the survey that is used for this research. The Reliability Analysis procedure
calculates a number of commonly used measures of scale reliability and also provides
information about the relationships between individual items in the scale. There are many
models of reliability and the Alpha (Cronbach) model takes place in this study. This is a
model of internal consistency, based on the average inter-item correlation and this fits
into our data properties.
Following the reliability analysis, a normality test is going to be applied on the
survey data and then according to the resuhs of this analysis parametric or non parametric
33
is used to test the hypothesis. Because our survey data is not normal, a non parametric
test is used to search for relationships between the variables.
4.3 General Properties of the Companies
The survey was sent to 230 companies and 118 of them were returned. From these
120 results, 19 of them were ehminated because of the position of the individual who
took the survey. The companies that were involved to this research represented different
counhies and also continents. This is to provide representativeness of the research in
terms of generalizability. Figure 4.1 shows the distribution of the companies.
Location of the C o m p a n i e s
United
States
4
Australia
13
Figure 4.1 Location of the companies involved in this research
In the following table, sectors of the companies are listed with the frequency
numbers. As seen from the table, most of the companies are private companies.
Table 4.1 Sector that the company works for
Frequency Valid Percent
Cumulative
Percent
Public
26
26.26
26.26
Private
73
73.74
100
Total
99
100
34
Figure 4.2 Positions of the individuals who took the survey
12 of the responses were eliminated because what they wrote in the blank box
does not make sense or they are only the users working in these companies.
In the following tables, the product type and the armual sales of the companies for
the year 2003 can be observed. Company types are almost evenly distributed and this
helps with the issue of generalization.
Table 4.2 Product type of the company
Frequency Valid Percent
Cumulative
Percent
Public
26
26.26
26.26
Private
73
73.74
100
Total
99
100
The number of the employees and the annual sales of the companies have always
been an important issue in ERP implementation. This statistical data is also an important
factor for the ERP system in terms of cost and effectiveness. The number of the
employees of the companies is listed in table 4.4.
35
Table 4.3 Annual sales company in year 2003 (sales)
Frequency Valid Percent
Cumulative Percent
<$10mil
15
15.15
15.15
$10-$24mil
11
11.11
26.26
$25-$49mil
13
13.13
39.39
$50-$74mil
7
7.07
46.46
$75-$99mil
12
12.12
58.59
$100-$500mil
28
28.28
86.87
>$500mil
13
13.13
100
Total
99
100
Table 4.4 Number of the employees
Frequency Valid Percent
Cumulative Percent
<50
7
7.07
7.07
51-150
8
8.08
15.15
151-500
28
28.28
43.43
501-1500
24
24.24
67.68
1501-5000
20
20.20
87.88
>5000
12
12.12
100
Total
99
100
Fable 4.5 Wl lich ERP software does the company use?
Frequency Valid Percent
Cumulative Percent
SAP
29
29.29
29.29
Oracle App.
10
10.10
39.39
Baan
5
5.05
44.44
J.D. Edwards
21
21.21
65.66
Link
5
5.05
70.71
Adonix
1
1.01
71.72
Other
28
28.28
100
Total
99
100
36
In the previous table, the ERP software being used by the companies is listed.
60% of the companies implemented SAP, Oracle, and J.D. Edwards. These packages
have more experience in this software arena and implementing these packages is more
effective then the others because of the standardizations they have in the implementation
phases. But as can be observed from the table, 28% of the companies use other software
packages most of which are self-programmed software by the companies themselves. The
reason that the companies choose this way is it is cheaper when compared to big software
vendor packages. But of course it is not always the most effective to choose the cheaper
one because these packages have a lot of gaps that have to be filled.
Another important issue in ERP implementations is the implementation time.
Generally companies exceed the implementation time that they initially planned because
ERP system implementation can cause many problems which cannot be seen in the very
beginning. Thus, the involvement of an experienced consulting firm and project team is
very important. Because for every increment of time which exceeds the plaimed time, an
additional cost will occur. In the following tables the implementation time that was
planned at the start and the actual implementation times are given.
Table 4.6 What was the implementation time that was planned before starting?(in
months)
Frequency Valid Percent
Cimiulative Percent
1-6
32
32.32
32.32
7-12
44
44.44
76.77
13-18
13
13.13
89.90
19-24
8
8.08
97.98
31-36
1
1.01
98.99
43 or more
1
1.01
100
99
100
Total
In the table 4.8, it can be seen that nearly half of the implementations exceed their
target values. 48.5% of the companies could not achieve the target that they determined at
the very beginning. This percentage is really high for such a big, important and expensive
37
project. Project management is one of the core techniques that should be used in these
implementations. With the experience of a good project team, the percentage of the
implementations that are within the time can be increased.
Table 4.7 How long did the implementation take? (in months)
Frequency Valid Percent
Cumulative Percent
1-6
21
21.21
21.21
7-12
25
25.25
46.46
13-18
22
22.22
68.69
19-24
9
9.09
77.78
25-30
9
9.09
86.87
31-36
6
6.06
92.93
43 or more
7
7.07
100
Total
99
100
Table 4.8 Percentages of the companies that exceed the planned implementation time
Frequency Valid Percent Cumulative Percent
Implementations within the time
51
51.52
51.52
Implementations exceed the time
48
48.48
100
Total
99
100
Frequency distribution of questions 11 and 12 is given in the tables below. As
seen in the first table, most companies transferred nearly 50% of their old data to the new
system. This procedure causes a lot of problems in terms of identifying the correct data
which is a priority in transferring to the new system.
Table 4.9 Percentage of the old data which is transferred to the new system
Frequency Valid Percent
Cumulative Percent
None
5
5.05
5.05
< 10%
8
8.08
13.13
11-40%
27
27.27
40.40
41-70%
35
35.35
75.76
71-100%
24
24.24
100
Total
99
100
38
Table 4.10 Percentage of the work processes which are redefined During BPR (Business
Process Reengineering).
Frequency Valid Percent
Cumulative Percent
None
5
5.05
5.05
< 10%
13
13.13
18.18
11-40%
54
54.55
72.73
41-70%
19
19.19
91.92
71-100%
8
8.08
100
Total
99
100
As with the transferring the old system, redefining the work processes is a critical
step in the ERP implementation. Mistakes in this step can cause the most problems after
ERP implementation. These mistakes have an impact on the period which is called
"going live". This is the period in which most of problems occur and require a lot of work
to get the system to work.
In terms of organizational structure types, respondents had 4 choices, one of
which is labeled "other" for the organizational structure type if it is different from the
three types involved in the survey. However, none of the companies select the "other"
option and write anything different fi-om these three structure types; Functional, Matrix
and Pure Project. The percentage of the companies' select Functional structure is 57.6%,
for the Matrix structure this percentage equals to 27.3% and 15.2% of the companies has
the Pure Project structure type.
4.4 Rehability Test of the Survey
Reliability analysis allows study of the properties of measurement scales and the
items that make them up. The Reliabihty Analysis procedure calculates a number of
commonly used measures of scale reliability and also provides information about the
relationships between individual items in the scale. Intraclass correlation coefficients can
be used to compute interrater reliability estimates. Testing reliability performance of the
surveys can be done by this kind of measurement in SPSS software package. While there
is a lot of information to be gleaned fi-om looking at correlations, a single summary
39
statistic is most desirable to determine the reliability of the survey. There are several
ways to do this, the most common of which is Cronbach's alpha. Cronbach's alpha is a
measure of reliability. More specifically, alpha is a lower bound for the true reliability of
the survey. Mathematically, reliability is defined as the proportion of the variability in the
responses to the survey that is the result of differences in the respondents. That is,
answers to a reliable survey will differ because respondents have different opinions, not
because the survey is confiising or has multiple interpretations. The computation of
Cronbach's alpha is based on the number of items on the survey and the ratio of the
average inter-item covariance to the average item variance (SPSS manual).
Table 4.11 Reliability Statistics
Cronbach's
Alpha
.754
Cronbach's
Alpha Based
on
Standardized
Items
.724
N of Items
29
In table 4.11, Cronbach's alpha value is given. 75.40% is the reliability degree of
the survey used in this research. This is an acceptable value for the reliability of a survey.
4.5 Statistical Analysis
As mentioned in the previous chapter, the data collected in the survey is
categorical data. This kind of data has a limited number of distinct values or categories
(for example, gender or marital status). It is also referred to as qualitative data.
Categorical variables can string (alphanumeric) data or numeric variables that use
numeric codes to represent categories (for example, 0 = Unmarried and 1 = Married).
There are two basic types of categorical data: nominal and ordinal data which are both
included in the survey.
Before hypothesis testing, a normality test was applied to the data in order to find
the most accurate analysis tool to test the hypothesis. For this purpose, a non-parametric
test, the One-Sample Kolmogorov-Smimov Test, was used. This test procedure compared
the observed cumulative distribution fiinction for a variable with a specified theoretical
40
distribution, which may be normal, uniform, poisson, or exponential. The KolmogorovSmimov Z is computed fi-om the largest difference (in absolute value) between the
observed and theoretical cumulative distribution functions. This goodness-of-fit test tests
whether the observations could reasonably have come fi-om the specified distribution.
Many parametric tests require normally distributed variables. The one-sample
Kolmogorov-Smimov test can be used to test that a variable is normally distributed. In
the following table, all data gathered fi-om the survey can be observed due to their
question numbers.
Table 4.12 Normality Test
One-Sample Kolmogorov-Smimov Test
Q2
N
Normal Parametersa.b
Mean
Most Extreme
Differences
Std. Deviation
Absolute
Positive
Negative
Kolmogorov-Smimov
Z
Asymp. Sig. (2-tailed)
99
1.71
.450
.454
.269
-.454
4.562
.000
Q3
Q4
99
Q5
99
1.35
.484
.409
.409
5.16
2.148
.206
.123
99
3.75
1.411
.146
.146
-.271
-.206
-.133
4.111
2.075
.000
.000
1.466
.027
Q6
99
2.54
1.260
.269
.237
-.269
2.701
.000
Q7
Q8
99
1.56
.740
.356
.356
-.219
99
4.04
2.787
.199
.170
-.199
3.573
.000
2.000
.001
One-Sample Kolmogorov-Smimov Test
QIO
Qll
3.16
2.012
.218
.218
99
2.11
1.278
.302
.302
99
3.66
1.087
.222
.134
-.139
-.189
Q9
N
Normal Parametersa.b
Most Extreme
Differences
Kolmogorov-Smimov
z
Asymp. Sig. (2-tailed)
99
Mean
Std. Deviation
Absolute
Positive
Negative
2.196
.000
3.040
.000
41
Q12
99
3.14
.913
.279
.279
-.222
-.266
2.232
2.802
.000
.000
Q13
Q14
99
2.83
1.037
.202
.202
99
4.02
.767
.266
.239
-.155
-.266
2.027
.001
2.677
.000
Q15a
99
4.40
.666
.299
.244
-.299
3.004
.000
Q15b
N
Q15c
Q15d
99
99
99
Q15e
Q15f
Q15g
Q16a
Normal Parametersa.b
Mean
4.17
4.24
3.98
99
4.10
Most Extreme
Differences
Std. Deviation
Absolute
Positive
Negative
.628
.311
.311
.830
.254
.192
.794
.248
.218
.823
.239
.196
.805
.271
.175
.799
.248
.218
.899
.234
.234
-.263
-.254
-.248
-.239
-.271
-.248
-.196
Kolmogorov-Smimov
Z
Asymp. Sig. (2-tailed)
3.124
.000
2.553
.000
2.488
2.407
.000
.000
99
4.24
99
4.10
99
3.83
2.719
.000
2.490
.000
2.354
.000
One-Sample Kolmogorov-Smimov Test
Q16b
99
Q16c
99
Q16d
99
Q16e
99
Q16f
99
Q16g
99
Q17
99
3.92
3.72
3.77
3.56
3.72
3.82
4.00
.785
.913
.795
.792
.902
.853
.831
Absolute
.283
.235
.242
.259
.266
.232
.268
Positive
.242
.171
.204
.211
.200
.193
.218
Negative
-.283
-.235
-.242
-.259
-.266
-.232
-.268
2.840
2.360
2.428
2.604
2.672
2.336
2.689
.000
.000
.000
.000
.000
.000
.000
N
Normal Parametersa.b
Most Extreme
Differences
Mean
Std. Deviation
Kolmogorov-Smimov
Z
Asymp. Si^. (2-tailed)
a. Test distribution is Normal.
b. Calculated from data.
From Table 4.12, the results of the normality test can be derived. All of the
asymptotic significance levels are below 0.05 and this value is an alpha value for the
Kolmogrov Smimov test. So, the null hypothesis is rejected. Thus, these variables do not
belong to a normal distributed sample. Especially, it is really important to find out if the
ordinal data is normal or not. hi this case, the ordinal data gathered from the survey is not
normal so, as a result, non-parametric tests are going to be applied to search for a possible
relationship.
In order to choose the most appropriate statistical test for this research, it is very
important to know the type of data that is going to be analyzed. In the previous chapter, it
was mentioned that the data from the survey is categorical data with nominal and ordinal
scales.
42
From the statements in the two paragraphs above, Crosstabs statistics is chosen to
analyze the relationship between variables. Crosstabs work best with category
variables as they can be used to understand relationships between the categories. The
crosstabulation table is a basic technique used to examine the relationship between two
categorical (nominal or ordinal) variables. This procedure offers tests of independence
and measures of association and agreement for nominal and ordinal data and, as a result,
the crosstabs procedure gives various non-parametric test results (Pearson Chi-Square,
Likelihood Ratio, Phi, Cramer's V, Contingency Coefficient, Lambda, Goodman &
Kruskal Tau, Uncertainty Coefficient, and Kappa) which can be used in describing the
relationship between the variables (SPSS manuals). To make sure if the results are correct
or not the Kruskal-Wallis H test is going to be used. The nonparametric tests for multiple
independent samples are useful for determining whether or not the values of a particular
variable differ between two or more groups. This is especially tme when the assumptions
of ANOVA are not met. In this case these assumptions are not met because the data is not
normal. Although one-way analysis of variance (ANOVA) is the method of choice when
testing for differences between multiple groups, it assumes that the mean is a valid
estimate of center and that the distribution of the test variable is reasonably normal and
similar in all groups. But, when the test variable is ordinal, the mean is not a valid
estimate because the distances between the values are arbifrary.
When the assumptions behind the standard ANOVA are invalid or suspect, the
nonparametric procedures designed to test for the significance of the difference between
multiple groups should be considered. They are called nonparametric because they make
no assumptions about the parameters (such as the mean and variance) of a distribution,
nor do they assume that any particular distribution is being used (SPSS manuals).
Like the F test in standard ANOVA, the Kruskal-Wallis H does not tell how
groups differ, only that they are different in some way. The Mann-Whitiiey test should be
applied for pairwise comparison.
For the second part of the hypothesis, under specific circumstances, (not normal
and discrete data) in order to find the differences between significance levels a non-
43
parametiic test, the Mann-Whitney U, is going to be used. This test is a nonparametric
test for two independent samples and useful for determining whether or not the values of
a particular variable differ between two groups. The Mann-Whitney U test is one of the
best known non-parametric statistical significance tests. It is sometimes called the MannWhitney-Wilcoxon test. By comparison of two independent variables the second part of
the hypothesis can be tested for each organizational structure type.
4.6 Hypothesis Testing
In this section, hypothesis which are described in the previous chapter are tested
as to whether they can be accepted or rejected.
Hypothesis 1; In comparing the organizational structure types, Functional
structure, Matiix structure, and Pure Project structure are not equal in terms of achieving
ERP success factors.
Hypothesis la
Null Hypothesis: The significance level of Functional Structure
Structure (|ap), and Matrix Sti-uctiare
()LIM)
(JIF),
Pure Project
are equal in terms of achieving ERP
Success factor; Flexibility (f)(Sl).
H Q : l^Mf^" ^Ff
H i : HMf 5^^Ff
H Q : M-Mf = ^pf
H i : ^Mf 5^Iipf
H o : ^pf = l^pf
H i : )ipf T^jxpf
Table 4.13 Crosstabulation results for the success factor SI
Flexibility of the software in responding to the
changes in the company's processes or how
adaptable is the ERP software in
accommodating business process changes?
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
1
Which organizational
structure exists in your
company?
1 Total
1
57
0
5
22
27
0
2
7
6
15
4
36
30
29
99
0
0
0
Pure
0
0
4
44
5
18
Functional
|y/iatrix
Project
4
3
2
Total
34
Chi-Square Tests
Value
Of
Asymp. Sig.
(2-sided)
Pearson Chi-Square
66.494(a)
6
.000
Likelihood Ratio
79.783
6
.000
Linear-by-Linear
Association
34.296
1
.000
N of Valid Cases
99
a 5 cells (41.7%) have an expected count less than 5. The minimum expected count is .61.
Symmetric Measures
Approx.
Sig.
Value
Nominal by
Nominal
Phi
.820
.000
Cramer's V
.580
.000
Contingency Coefficient
.634
.000
N of Valid Cases
99
a Not assuming the null hypothesis.
b Using the asymptotic standard error assuming the null hypothesis.
The crosstabulation table shows the frequency of each response at each
organizational structure type. If each structure type provides a similar level of success,
the pattern of responses should be similar across stinctures. At each independent variable,
the majority of responses occur in different places. The matrix organizational structure
type appears to have more success in terms of flexibility. From the crosstabulation alone,
it is impossible to tell whether these differences are real or due to chance variation. So,
the chi-square table has to be checked. This test measures the discrepancy between the
observed cell counts and what would be expected if the rows and columns are unrelated.
For the asymptotic significance level, a definition can be given as follows; there
are some sitiiations in which the distribution of a test statistic is not well defined. Often,
however, as the number of observations used to compute the statistic increases, its
distribution begins to approximate a known distribution. This well-defined distribution is
then used to calculate the significance value of the test statistic.
45
The two sided asymptotic of the chi-square statistic is
0.000<0.05(Q!),
so it is safe
to say that the differences are not due to chance variation. There is a relationship between
the organizational structure type and success factor S1, which implies that each structure
type does not achieve the same level of success in terms of flexibility. From the
symmetric measures of Cramer's V (because one of the variables is nominal), 0.580, it
can be determined that this relationship is a strong relationship.
To make sure that this test gives correct results, the Kruskal-Wallis H test is going
to be applied.
Table 4.14 The Kruskal-Walhs H test results for the success factor SI.
Flexibility of the
software in responding
to the changes in the
company's processes
or how adaptable is the
ERP software in
accommodating
business process
changes? Evaluate
these uses of ERP in
terms of the degree of
obtaining them after
implementation.
Organizational structure
Functional
Mean Rank
N
57
32.61
27
79.54
15
62.90
Matrix
Pure Project
Total
99
Test Statistics?'''
Chi-Square
df
Asymp. Sig.
Flexibility of the software in responding to the
changes in the company's processes or how
adaptable is the ERP software in
accommodating business process changes?
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
58.358
2
000
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists
in your company?
The Kruskal-Wallis test uses ranks of the original values and not the xalues
themselves. That procedure is appropriate in this case, because the scale used by the
success factor is ordinal. The Kruskal-Wallis statistics measure how much the group
46
ranks differ from the average rank of all groups (SPSS manual). The asymptotic
significance estimates the probability of obtaining a chi-square statistic greater or equal to
the one displayed, if there are no differences between the group ranks. A chi -square of
58.358 with degree 2 of freedom should occur 0 times per 1000. The table indicates that
achieving the success in terms of flexibility differs by type of organizational structure.
As a resuU, the Kruskal-Wallis and Crosstabulation tests gave the same answer
that the Null Hypothesis is rejected. These three organizational structure types have
different effects on success in terms of achieving flexibility. Because the Ho is rejected, it
is appropriate to look at the second part of the hypothesis which searches for the
significance level in pairwise comparison.
For this purpose, the Mann-Whitney U test is going to be performed between
organizational structure types in two pairs.
From the table below, it can be determined that the minimum sum of ranks belong
to the Functional structure type. Test statistic shows that because the asymp. sig. (2tailed) is 0.000 and smaller than 0.05, the null hypothesis HQ is rejected. As a resuh, it is
safe to say that the companies which use the Matrix Structure can be more successful in
Flexibility of the software after an ERP implementation compared to the Functional
Structure.
Table 4.15 The Mann Whitney U test between Functional Structure and Matrix Structure
in terms of the success factor flexibihty (SI).
Flexibility of the
software in responding
to the changes in the
company's processes
or how adaptable is the
ERP software in
accommodating
business process
changes? Evaluate
these uses of ERP in
terms of the degree of
obtaining them after
implementation.
Organizational structure
Functional
Mean Rank
Sum of Ranks
57
30.07
1714.00
27
68.74
1856.00
N
Matrix
Total
84
47
Test statistics '
Flexibiiity of the software in
responding to the changes in the
cxjmpany's processes or how
adaptable is the ERP software in
accommodating business process
changes? Evaluate these uses of
ERP in terms of the degree of
obtaining them after implementation.
Mann-Whitney U
61.000
Wilcoxon W
1714.000
Z
-7.182
Asynnp. Sig. (2-taiied)
.000
a- Grouping Variable: Which organizational structure
exists in your company?
In table 4.16, the Matrix Structure and Pure Project Structure are being compared.
As in the previous test, the null hypothesis is rejected. So, it can be determined that
Matiix Structure has an advantage in achieving the success of Flexibility of the software
after an ERP implementation.
Table 4.16 Mann Whitiiey U test between Matrix Structure and Pure Project Structure in
terms of the success factor flexibihty (SI).
Flexibility of the
software in responding
to the changes in the
company's processes
or how adaptable is the
ERP software in
accommodating
business process
changes? Evaluate
these uses of ERP in
terms of the degree of
obtaining them after
implementation.
Organizational structure
Ivlatrix
N
Mean Rank
27
24.80
669.50
15
15.57
233.50
Pure Project
Total
42
Test Statistics^
Mann-Whitney U
Sum of Ranks
Flexibility of the software in responding to
the changes in the company's processes or
how adaptable is the ERP software in
accommodating business process
changes? Evaluate these uses of ERP in
terms of the degree of obtaining them after
implementation.
113.500
233.500
Wilcoxon W
-2.832
Z
.005
Asymp. Sig. (2-tailed)
a- Grouping Variable: Which organizational structure exists in
your company?
48
This procedure is performed between the Functional structure and the Pure
Project structure. From the test results given in table 4.17, Ho is rejected and the
alternative hypothesis can be accepted which implies that companies using the Pure
Project structure have an advantage in achieving more success in flexibility of the
software after the implementation.
Table 4.17 Mann Whitney U test between Functional Structure and Pure Project Structure
in terms of the success factor flexibility (SI).
Flexibility of the
software in responding
to the changes in the
company's processes
or how adaptable is the
ERP software in
accommodating
business process
changes? Evaluate
these uses of ERP in
terms of the degree of
obtaining them after
implementation.
Organizational structure
Functional
Mean Rank
Sum of Ranks
57
31.54
1798.00
15
55.33
830.00
N
Pure Project
Total
72
Test Statistics?
Mann-Whitney U
Flexibility of the software in responding to
the changes in the company's processes
or how adaptable is the ERP software in
accommodating business process
changes? Evaluate these uses of ERP in
terms of the degree of obtaining them
after implementation.
145.000
1798.000
Wilcoxon W
-4.294
Z
.000
Asymp. Sig. (2-tailed)
a. Grouping Variable: Which organizational structure exists in
your company?
For hypothesis la, for the first part. Ho is rejected. As a result, it is safe to say that
there is a relationship between organizational stioicture types and the first success factor,
Flexibihty of the software. For the second part of the hypothesis. Ho is rejected and as it
was expected, the relationship comes out as follows: the Matiix Structure has more
49
advantage than the Pure Project structure, and the Pure Project structure has more
advantage than the Functional Structure in terms of achieving success in flexibility of the
software after the ERP implementation.
H i: ^Mf> |ipt\ H i: ^Mf>IiFf, H i: |Xpf> ^ipf
Hypothesis
lb
Null Hypothesis: The significance level of Functional Structiare (^p), Pure Project
Structure (^p), and Matrix Stiucture {\iu) are equal in terms of achieving ERP
Success factor; Having the proper tools (pt)(S2).
Ho: ^Mpt= l^Fpt
Hi: )iMpt T^S^V^X
Ho: M-Mpt = |Ltppt
H i : |j.Mpt J^Iippt
H o: lippt - liFpt
H i: ^ppt ?^M.Fpt
For any where HQ is rejected;
H"O: ^xpt <^iYpt
for X: M, F, P and Y: M, F, P
H 1: fO-xpt > ^iYpt
Table 4.18 Crosstabulation results for the success factor S2
Having the proper tools for the company does the
ERP software functionality satisfy the company's
business processing requirements? Evaluate these
uses of ERP in terms of the degree of obtaining them
after implementation.
2
1
Which
organizational
structure exists in
your company?
Functional
'^^^"^
Pure Project
Total
4
3
Total
5
1
2
15
30
9
57
0
0
4
13
10
27
0
0
3
9
3
15
1
2
22
52
22
99
50
Chi-Square Tests
Pearson Chi-Square
Value
7.360^
Asymp. Sig.
(2-sided)
.598
df
Likelihood Ratio
8.196
.415
Linear-by-Linear
Association
3.008
.083
N of Valid Cases
99
a- 8 cells (53.3%) have expected count less than 5. The
minimum expected count is .15.
Symmetric Measures
Nominal by
Nominal
Phi
Cramer's V
Contingency Coefficient
N of Valid Cases
Value
.273
.173
.263
99
Approx. Sig.
.598
.598
.598
a- Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
The two sided asymptotic of the chi-square statistic is 0.598 which is larger than
QF=0.05, so it failed to reject the null hypothesis and it can be determined that there is no
relationship between organizational structure types and success factor SI, which implies
that each structure type has the same level of success in terms of having the proper tools.
But, the symmetric measures of Cramer's V is only 0.173. This is also a small value to
say there is a relationship between two variables. So,
Ho: ^Mpt= MFpt
H'O: M-Mpt = I^Ppt
H"O: ^Ppt = M-Fpt cannot be rejected.
Because there is not any rejection in the null hypothesis, it is not necessary to look
at the pairwise relationship between the organizational structure types. Also, in table
4.19, the Kruskal-WalUs statistical analysis gave 0.054 as a test significance value, thus,
the null hypothesis is rejected again while a=0.05.
51
Table 4.19 The Kruskal-Wallis statistical analysis for success factor S2
Having the proper tools
for the company does the
ERP software functionality
satisfy the company's
business processing
requirements? Evaluate
these uses of ERP in
terms of the degree of
obtaining them after
implementation.
Organizational structure
Functional
N
.
^ "^
Mean Rank
57
45.00
27
59.72
15
51.50
Pure Project
' °^^'
99
Test Statistics^''
Chi-Square
df
Asymp. Sig.
Having the proper tools for the company does the
ERP software functionality satisfy the company's
business processing requirements? Evaluate
these uses of ERP in terms of the degree of
obtaining them after implementation.
5.835
2
.054
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists
in your company?
Hypothesis Ic
Null Hypothesis: The significance level of Functional Structure (M-F). Pure Project
Structiire (^P), and Matrix Structiire (^M) are equal in terms of achieving ERP
Success factor; Integration (i)(S3).
Ho: ^Mi= I^Fi
H i : ^tMi 5^M-Fi
H Q : |iMi = I^Pi
Hi:
HQ:
|ipi = IiFi
JIMI J^I^PI
H i: |Xpi T^UFI
For any where Ho is rejected;
H"O:
[ixi ^i^Yi
for X: M, F, P and Y: M, F, P
H"'I: ^xi>^Yi
52
Table 4.20 Crosstabulation resu ts for the success:factor S3
What degree of business process integration has
been achieved (i.e.common accesabiiity of data,
report and performance measure)? Evaluate these
uses of ERP in terms of the degree of obtaining
them after implementation.
1
Which
organizational
structure exists in
your company?
2
3
4
Total
5
Functional
0
10
25
22
0
57
Matrix
0
0
0
6
21
27
Pure Project
0
0
3
12
0
15
0
10
28
40
21
99
Total
Chi-Square Tests
6
Asymp. Sig.
(2-sided)
.000
Likelihood Ratio
92.676
6
.000
Linear-by-Linear
Association
20.672
1
.000
Pearson Chi-Square
Value
84.334^
N of Valid Cases
df
99
a- 4 cells (33.3%) have expected count less than 5. The
minimum expected count is 1.52.
Symmetric Measures
Nominal by
Nominal
Phi
Cramer's V
Value
.923
Contingency Coefficient
Approx. Sig.
.000
.653
.000
.678
.000
99
N of Valid Cases
a- Not assuming the null hypothesis,
b. Using the asymptotic standard error assuming the null
hypothesis.
From table 4.20, crosstabulation test shows a person chi-square asymptotic
significance value, 0.000. This is smaller than the a value, 0.05. So, the null hypothesis is
rejected. And the alternative hypothesis implies that there is a relationship between the
organizational structure types and the success factor S3, business process integration. A
Kruskal-Wallis statistical analysis is given in the following table. From table 4.21, the
53
that asym. sig. value is 0.000 and it proves that the crosstabulation gives the correct
answer.
Table 4.21 The Kruskal-Wallis statistical test for success factor S3.
What degree of business
process integration has
been achieved (i.e.
common accesebility of
data, report and
performance measure)?
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Mean Rank
57
34.29
27
82.22
15
51.70
Matrix
Pure Project
Total
99
Test Statistics?-''
Chi-Square
df
What degree of business process integration has
been achieved (i.e.common accesebility of data,
report and performance measure)? Evaluate
these uses of ERP in terms of the degree of
obtaining them after implementation.
56.703
2
.000
Asymp. Sig.
a- Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists
in your company?
For the second part of the hypothesis, the nonparametric test, Mann-Whitney U
statistical analysis is going to be performed for pairwise comparison.
The first test is applied to the Functional sti-ucture and Matrix structure types and
the results are given in the table 4.22.
In the table below, the Wilcoxon W value belongs to the Functional
organization structure and the asymptotic significance level is 0.000. So, the null
hypothesis is rejected and as a result it can be determined that the Matrix structure is
more effective in achieving the success in terms of integration after the ERP
implementation.
54
Table 4.22. The Mann-Whitney U test, the Functional Structure vs Matrix Structure.
What degree of business
process integration has
been achieved (i.e.
common accesebility of
data, report and
performance measure)?
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Mean Rank
Sum of Ranks
57
30.16
1719.00
27
68.56
1851.00
Total
84
Test Statistics?
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
What degree of business process
integration has been achieved (i.e.common
accesebility of data, report and performance
measure)? Evaluate these uses of ERP in
terms of the degree of obtaining them after
implementation.
66.000
1719.000
-7.027
.000
a. Grouping Variable: Which organizational structure exists in
your company?
For the other pair, the Matiix structure and Pure Project organization structiire
are going to be tested according to the hypothesis mentioned before. Table 4.23 shows
the details of the results of this comparison.
Table 4.23. Mann-Whitney U test between Matrix and Pure Project organization for
success factor, S3.
What degree of business
process integration has
been achieved (i.e.
common accesebility of
data, report and
performance measure)?
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Mean Rank
Sum of Ranks
27
27.67
747.00
15
10.40
156.00
Organizational structure
Matrix
Pure Project
Total
42
55
Test Statistics?
What degree of business process integration
has been achieved (i.e.common accesebility of
data, report and performance measure)?
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
Mann-Whitney U
36.000
Wilcoxon W
156.000
Z
-4.898
Asymp. Sig. (2-tailed)
.000
a- Grouping Variable: Which organizational structure exists in your
company?
From the test statistics, because the asymptotic significance level is equal to 0.000
and smaller than a=0.05. Ho is rejected. So, in terms of achieving the success in
integration, companies which have the Matrix structure have more advantage than
companies that use the Pure Project structures.
In the Table 4.24 the last pair, the Functional structure and Pure Project structure
for this success factor can be observed.
Table 4.24. Mann-Whitney U test between Functional and Pure Project organization for
success factor, S3.
What degree of business
process integration has
been achieved (i.e.
common accesebility of
data, report and
performance measure)?
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Mean Rank
Sum of Ranks
57
33.13
1888.50
15
49.30
739.50
Pure Project
Total
72
56
Test statistics'
Mann-Whitney U
Wilcoxon W
Z
Asymp, Sig. (2-tailed)
What degree of business process integration
has been achieved (i.e.common accesebility of
data, report and performance measure)?
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
235.500
1888.500
-2.916
,004
a- Grouping Variable: Which organizational structure exists in your
company?
From the table 4.24, the asymptotic significance level is 0.004 and it is smaller
than 0=0.05. The Ho hypothesis is rejected. It can be determined that the minimum sum
of ranks belong to Functional structure type. It is safe to say that the Pure Project
structure is more successful than the Functional structure in terms of achieving business
process integration. An analysis for the relationship of organizational structure types and
the success factor, business process integration, shows that the Matrix structure has more
effective than the Pure Project structure and the Project structure is more effective than
the Functional structure. These results will be discussed with a comparison of the
expectations mentioned in the previous chapter.
Hypothesis Id
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Stinicture (|ip), and Matrix Structure (I^M) are equal in terms of achieving ERP
Success factor; Standardization (s)(S4).
Ho: HMS = l^Fs
Hi:
Ho: ^Ms = I^Ps
Hi: ^Ms J^^PS
Ho: ^ps = |^Fs
H i : UPS 7^\i.?s
^MS J^^FS
For any where Ho is rejected;
H"O: ^XS ^IiYs
for X: M, F, P and Y: M, F, P
H ' I : HXS>^YS
57
Table 4.25. Crosstabulation test for the success factor, S4.
Standardization of the processes; what
degree of business process
standardization did you achieve?
Evaluate these uses of ERP in terms of
the degree of obtaining them after
implementation.
1
Which
organizational
structure exists
in your
company?
2
3
4
Total
5
^
,.
,
functional
0
4
21
30
2
57
Matrix
0
0
0
11
16
27
Pure Project
0
0
11
4
0
15
0
4
32
45
18
99
Total
Ctii-Square Tests
Pearson Chi-Square
Value
56.316^
6
Asymp. Sig.
(2-sided)
.000
df
Likelihood Ratio
61.284
6
.000
Linear-by-Linear
Association
1.315
1
.251
N of Valid Cases
99
a- 6 cells (50.0%) have expected count less than 5. The
minimum expected count is .61.
The chi-square test significance is 0.000 and this is less than a value of 0.05.
Thus, the null hypothesis is rejected and the alternative hypothesis is accepted which says
there is a relationship between organizational structure and standardization.
Table 4.26 Symmetric measures and Cramer's V for success factor S4.
Symmetric IVIeasures
Nominal by
Nominal
Phi
Cramer's V
Value
.754
.533
.602
99
Contingency Coefficient
N of Valid Cases
a- Not assuming the null hypothesis,
b. Using the asymptotic standard error assuming the null
hypothesis.
58
Approx. Sig.
.000
.000
.000
Table 4.26 indicates Cramer's V as 0.533 from which it can be determined that
the relationship mentioned above is strong enough between the variables.
Table 4.27. The Kruskal Wallis test for the success factor S4
Standardization of the
processes; what degree
of business process
standardization did you
achieve? Evaluate these
uses of ERP in terms of
the degree of obtaining
them after
implementation.
Organizational structure
Functional
Mean Rank
Matrix
Pure Project
Total
57
41.96
27
77.67
15
30.77
99
Test Statistics?''
Standardization of the processes; what degree of
business process standardization did you achieve?
Evaluate these uses of ERP in terms of the degree
of obtaining them after implementation.
Chi-Square
41.840
df
2
Asymp. Sig.
.000
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists in
your company?
The Kruskal Wallis asymptotic significance level, 0.000, tells that the null
hypothesis has to be rejected.
When the Functional structure is compared to the Matrix structure in terms of
achieving the success in standardization, the following table is created as a result. Asym.
Sig. is equal to 0.016 which is smaller than a value. So, the null hypothesis is rejected
and according to the alternative hypothesis the significance level of the Functional
structure is larger than the significance level of the Matrix structure.
Table 4.28 The Mann-Whitney U test between the Functional structure and Matrix
Structure for standardization.
Standardization
Organizational structure
Functional
Matrix
Total
N
57
27
84
59
Mean Rank
47.59
35.04
Sum of Ranks
2760.00
981.00
Test Statistics?
Standardization
575.000
981.000
-2.411
.016
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
a. Grouping Variable: Organizational Structure Type
For the second pair or the structure types, the Matrix structure and the Pure
Project organization structure are taken for the statistical test.
4.29 The Mann-Whitney U test between Matrix and Pure Project structure for
standardization
Standardization
N
Organizational structure
Matrix
Pure Project
Total
27
15
42
Mean Rank
25.18
16.07
Sum of Ranks
705.00
241.00
Test Statistics ^
Mann-Whitney U
Wilexjxon W
Z
Asymp. Sig. (2-tailed)
Standarcjization
121.000
241.000
-2.504
.012
a. Grouping Variable: Orgazanizational Structure Type
In this case, the asymptotic significance is 0.012 < a=0.05. As a result. Ho is
rejected. It can be determined that the Matrix structure is better than the Pure Project
structure in achieving a success in standardization.
When the same test is performed on the last pair of the structures types between
the Functional structure and the Pure Project Structure the results can be written as
follows.
4.30 The Mann-Whitney U test between the Functional and Pure Project structure for
standardization
Standardization
Orgazanizational Structure
Functional
Pure Project
Total
58
15
73
60
Mean Rank
42.19
16.93
Sum of Ranks
2447.00
254.00
Test Statistics?
Standardization
Mann-Whitney U
134.000
Wilcoxon W
254.000
Z
-4.474
Asymp. Sig. (2-tailed)
.000
a- Grouping Variable: Organizational Structure Type
Asymptotic significance level is 0.000 and smaller than a=0,05. The null
hypothesis is rejected; as a result the Functional structure is better than the Pure Project
structure.
Hypothesis le
Null Hypothesis: The significance level of Functional Stiucture (jip), Pure Project
Stiucture (^p), and Matrix Stiucture (JAM) are equal in terms of achieving ERP
Success factor; Ease of use of the ERP modules (eu).
H o : fXMeu= I^Feu
H i : |lMeu J^MFeu
H Q : |iMeu - IlPeu
H ^ |a.Meu 5^|^Peu
H o: I^Peu = M-Feu
H i: jXpeu ?^fXFeu
For any where Ho is rejected;
H"O: Hxeu ^liYeu
for X: M, F, P and Y: M, F, P
H 1: Jixeu > f^Yeu
Table 4.31. Crosstabulation between organizational structure and the success factor, S5.
Rate the 'ease of use' of the ERP system modules
Evaluate these uses of ERP in terms of the degree of
obtaining them after implementation.
1
Which
organizational
structure exists in
your company?
Total
2
4
3
Total
5
Functional
1
4
20
27
5
57
Matrix
0
2
11
10
4
27
Pure Project
0
0
7
7
1
15
1
6
38
44
10
99
61
Chi-Square Tests
Value
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Asymp. Sig.
(2-sided)
.891
.775
df
3.610^
4.834
.090
.765
99
a- 8 cells (53.3%) have expected count less than 5. The
minimum expected count is .15.
This table shows that the null hypothesis cannot be rejected with a pearson chisquare value of 0.765. It is much higher than QFO.05. SO, it can be determined from the
results that there is no relationship between the variables, organizational structure, and
the success factor S5, ease of use of the ERP modules.
Symmetric IVIeasures
Nominal by
Nominal
Phi
Cramer's V
Contingency Coefficient
N of Valid Cases
Value
.191
.135
.188
99
Approx. Sig.
.891
.891
.891
a- Not assuming the null hypothesis.
b- Using the asymptotic standard error assuming the null
hypothesis.
Table 4.32 The Kruskal-Walhs test for the success factor S5.
Rate the 'ease of use' of
the ERP system modules
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
.
^^^"^
Pure Project
N
57
Mean Rank
49.89
27
50.13
15
50.17
99
^°*^'
62
Test Statistics?''
Chi-Square
df
Asymp. Sig.
Rate the 'ease of use' of the ERP system
modules Evaluate these uses of ERP in terms of
the degree of obtaining them after
implementation.
.002
2
.999
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists
in your company?
The mean ranks are almost the same for three of the organizational structure types
as can be observed in table 4.32. So, it can be determined as a result that there is no
differences between the three types of organizational structures in achieving the success
factor S5. And the asymptotic significance level gives the value of 0.999 which is very
high to fail to reject the null hypothesis. As a result.
Ho: M-Meu= M-Feu
H o : fXMeu - MPeu
H o: p.Peu = MFeu
thcSC
equations can be written.
Hypothesis If
Null Hypothesis: The significance level of Functional Structure ()XF), Pure Project
Structure (^p), and Matrix Structure (JIM) are equal in terms of achieving ERP
Success factor; Reporting (r)(S6).
Ho: H-Mr= MFr
H i : ^Mr ^^M-Fr
H o : MMr= MPr
H i : |4,Mr 5^MPr
H " O : |Xpr = MFr
H i : JXpr ?i|iFr
For any where Ho is rejected;
H"O: Mxr ^IiYr
foi X: M, F, P and Y: M, F, P
H ' I : [tXr>MYr
63
Table 4.33 Crosstabulation table for the success factor S6.
Rate the effectiveness and the completeness
of reporting functionality within the system
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
1
2
0
Pure Project
0
2
Total
18
22
9
57
6
14
7
27
3
10
2
15
CO
Matrix
5
O
2
4
O
Functional
3
CO
Which
organizational
structure exists in
your company?
Total
27
46
18
99
Chi-Square Tests
Pearson Chi-Square
Value
10.3353
8
Asymp. Sig.
(2-sided)
.242
df
Likelihood Ratio
13.108
8
.108
Linear-by-Linear
Association
4.805
1
.028
N of Valid Cases
99
a- 9 cells (60.0%) have expected count less than 5. The
minimum expected count is .30.
Symmetric Measures
Nominal by
Nominal
Phi
Cramer's V
Value
.323
Contingency Coefficient
Approx. Sig.
.242
.128
.242
.307
.242
99
N of Valid Cases
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
In this situation the null hypothesis cannot be rejected because of the pearson chisquare value of 0.242 > a=0.05. Cramer's V value is only 0.126 which indicates that the
relationship is really weak. To make sure that this test is correct, a Kruskal Wallis test is
performed on the data. As it can be observed in table 4.34 the null hypothesis cannot be
rejected with the asymptotic value of 0.053 which is also larger than 0.05=a.
64
Table 4.34 The Kruskal Wallis test for success factor, S6.
Rate the effectiveness
and the completeness of
reporting functionality
within the system
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Mean Rank
57
44.45
27
58.69
15
55.47
Matrix
Pure Project
Total
99
Test Statistics?''
Rate the effectiveness and the completeness of
reporting functionality within the system Evaluate
these uses of ERP in terms of the degree of
obtaining them after implementation.
Chi-Square
df
Asymp. Sig.
5.889
2
.053
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists in
your company?
As a result, null hypothesis which implies that three organizational structure types
are equal in terms of achieving the success for success factor S6 cannot be rejected. The
results can be written as follows;
HQ:
M-Mr^ M-Fr
H o : ^MT = M'Pr
H o: I^Pr = M^Fr
Hypothesis Ig
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Structure (|ip), and Matrix Structure (IIM) are equal in terms of achieving ERP
Success factor; Satisfying the customer demands (scd)(S7).
H o : |iMscd= M^Fscd
H i : I^Mscd 5^M-Fscd
H Q : I^Mscd = lapsed
H i : jlMscd 5^IiPscd
H o: M-Pscd = MFscd
H i: |J.pscd J^^Fscd
For any where Ho is rejected;
H"O: Mxscd ^MYscd
for X: M, F, P and Y: M, F, P
H 1: ^Xscd > MVscd
65
Table 4.35 Crosstabulation for the success factor S7.
Rate the ability to satisfy customer demand
Evaluate these uses of ERP in terms of the degree
of obtaining them after implementation.
1
Which
organizational
structure exists
in your
company?
2
3
4
Total
5
Functional
1
3
22
23
8
57
Matrix
0
0
4
10
13
27
Pure Project
0
0
4
9
2
15
1
3
30
42
23
99
Total
Chi-Square Tests
8
Asymp. Sig.
(2-sided)
.024
Likelihood Ratio
18.194
8
.020
Linear-by-Linear
Association
5.116
1
.024
Pearson Chi-Square
Value
17.701^
N of Valid Cases
df
99
a- 8 cells (53.3%) have expected count less than 5. The
minimum expected count is .15.
Symmetric IVIeasures
Nominal by
Nominal
Phi
Cramer's V
Value
.423
Contingency Coefficient
Approx. Sig.
.024
.299
.024
.389
.024
99
N of Valid Cases
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
The Pearson chi-square has a value of 0.024 which is smaller than the a value
which is set to 0.05. So, the null hypothesis is rejected according to this chi-square test.
The table below shows that the asymptotic significance for the Kruskal Wallis test
is 0.001, which is smaller than the a value.
66
Table 4.36. Kruskall Wallis test for the success factor S7.
Rate the ability to satisfy
customer demand
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Mean Rank
57
42.45
^^tm
Pure Project
27
65.81
15
50.23
^°'al
99
Test Statistics?''
Chi-Square
df
Asymp. Sig.
Rate the ability to satisfy customer demand
Evaluate these uses of ERP in terms of the
degree of obtaining them after implementation.
13.729
2
.001
a- Kruskal Wallis Test
b. Grouping Variable: Which organizational structure exists
in your company?
So, the null hypothesis is rejected. There is a relationship between organizational
structure types and success factor S7. The three organizational structure types have a
different effect on this success factor.
From the statistical test performed for the Functional and Matrix structures, the
asymptotic significance level comes out to the level of 0.000,seen in table 4.37. This is
smaller than the a value so the null hypothesis is rejected. The alternative hypothesis
implies that the Matrix structure has more advantage than the Functional structure in
terms of achieving the success for success factor S7.
Table 4.37 The Mann-Whitney U test between Functional structure and the Matrix
structure for success factor S7.
Rate the ability to satisfy
customer demand
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
Matrix
N
Mean Rank
Sum of Ranks
57
36.28
2068.00
27
55.63
1502.00
Total
84
67
Test Statistics^
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
Rate the ability to satisfy customer demand
Evaluate these uses of ERP in terms of the
degree of obtaining them after
implementation.
415.000
2068.000
-3.591
.000
a. Grouping Variable: Which organizational structure exists in
your company?
In comparing the Matrix structure and the Pure Project structure, an asymptotic
significance level of 0.040 is achieved. So the null hypothesis is rejected. As a result, the
Matrix Structure is more effective than the Pure Project structure in achieving success for
success factor S7.
Table 4.38 The Mann-Whitney U test between the Matrix structure and Pure Project
structure for success factor S7.
Rate the ability to satisfy
customer demand
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Matrix
Pure Project
Total
Mean Rank
Sum of Ranks
27
24.19
653.00
15
16.67
250.00
N
42
Test Statistics "
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
Rate the ability to satisfy customer
demand Evaluate these uses of ERP in
terms of the degree of obtaining them
after implementation.
130.000
250.000
-2.058
.040
a- Grouping Variable: Which organizational structure exists in
your company?
And in the last comparison for success factor S7, we fail to reject the null
hypothesis. From table 4.39, the significance level is 0.257 and this is larger than the a
value 0.05. Thus, it is safe to say that the Functional structure does not have as much
advantage as the Pure Project structure in achieving success for success factor S7. The
68
companies that use the Pure Project structure type are more effective than the companies
which have the Functional structure in customer satisfaction.
Table 4.39 The Mann-Whitney U test betiveen Functional structure and Pure Project
structure for success factor, S7.
Rate the ability to satisfy
customer demand
Evaluate these uses of
ERP in terms of the
degree of obtaining them
after implementation.
Organizational structure
Functional
N
Pure Project
Total
Mean Rank
Sum of Ranks
57
35.17
2004.50
15
41.57
623.50
72
Test Statistics?
Mann-Whitney U
Rate the ability to satisfy customer
demand Evaluate these uses of
ERP in terms of the degree of
obtaining them after implementation.
351.500
Wilcoxon W
2004.500
Z
-1.135
Asymp. Sig. (2-tailed)
.257
a. Grouping Variable: Which organizational structure
exists in your company?
As a result, for the customer satisfaction success, the structure types can be put in
a sequence as follows;
M-Mscd >M-Pscd >|LtFscd
Hypothesis Ih
Null Hypothesis: The significance level of Functional Structure (^F), Pure Project
Structure (jip), and Matrix Structure (|IM) are equal in terms of achieving ERP
Success factor; Implementation time (it).
H o : ^ M i t ^ ^Fit
H i : ^Mit 5^IiFit
H o : ^Mit = I^Pit
H 1 : jXMit r^l^Pit
H o: M-pit = IiFit
H i: jipit ?^|iFit
For any where Ho is rejected;
H"O: jixit <^Y,t
for X: M, F, P and Y: M, F, P
69
H i: ^txit > IlYit
hi order to test this hypothesis, two questions fi-om the survey are used. Questions
9 and 10 about planned implementation time before implementation and the
implementation time after going live to find out if the company implemented the system
on time or not.
If the planned implementation time (question 9) is equal or smaller than the actual
implementation the time is coded as "0", otherwise it is coded as "1". So, a nominal scale
is created for tiie success factor, of time.
Table 4.40 Crosstabulation for success factor SB, time.
Time
On time
Which organizational
structure exists in your
company?
Total
Functional
Matrix
Pure Project
Over time
Total
32
25
57
12
15
27
7
8
15
51
48
99
Chi-Square Tests
2
Asymp. Sig.
(2-sided)
.557
Likelihood Ratio
1.172
2
.557
Linear-by-Linear
Association
.828
1
.363
Pearson Chi-Square
Value
1.170^
N of Valid Cases
df
99
a- 0 cells (.0%) have expected count less than 5. The
minimum expected count is 7.27.
Symmetric Measures
Nominal by
Nominal
Phi
Cramer's V
Value
.109
Contingency Coefficient
N of Valid Cases
.109
.557
.108
.557
99
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
70
Approx. Sig.
.557
The table above indicates that the pearson chi-square value for the crosstabulation
test for success factor S8 is 0.557. Because of 0.557>0.05, we failed to reject the null
hypothesis. Also, Cramer's V is small enough to say that there is no relationship between
organizational structure types and implementation time. The Kruskal Wallis test also
supports that result with a the significance level of 0.560 which is greater than the a
value.
As a result, the relationship between the effectiveness of the organizational
structures on the success factor, time can be written as follows;
^ M i t = M^FiP V-?\\.
Table 4.41 Kruskal Wallis test for the success factor S8
Time
Organizational structure
Functional
Matrix
Pure Project
Total
N
Mean Rank
47.71
53.50
52.40
57
27
15
99
Test Statistics?"
Chi-Square
df
Asymp. Sig.
Time
1.158
2
.560
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational
structure exists in your company?
Hypothesis 2: Functional Structiire, Pure Project Structure and Matrix Structure are not
equal in terms of achieving total success of ERP implementation
Null Hypothesis: HQ: The significance level of Functional Stiucture, Pure Project
Structure, and Matrix Stiiictiire are equal in terms of total success (ts) of the ERP
implementation.
H o : M^Mts = M'Fts
H i : fiMts 5»^M-Fts
H o : f^Mts — M-Pts
H i : ^Mts 5^M-pts
H o: ^ P t s = I^Fts
H 1: ^pts ?^Fts
For any where Ho is rejected;
71
H o: ^xts :^IiYts
for X: M, F, P and Y: M, F, P
H 1: i^xts > M^Yts
Table 4.42 Crosstabulation for the total success of ERP implementation.
Rate the success of your ERP Implementation Total
success of the ERP implementation.
1
Which
organizational
structure exists in
your company?
2
3
Total
5
4
Functional
1
3
13
34
6
57
Matrix
0
0
0
5
22
27
Pure Project
0
0
6
9
0
15
1
3
19
48
28
99
Total
Chi-Square Tests
Pearson Chi-Square
Value
56.392^
8
Asymp. Sig.
(2-sided)
.000
df
Likelihood Ratio
60.715
8
.000
Linear-by-Linear
Association
2.660
1
.103
N of Valid Cases
99
a. 8 cells (53.3%) have expected count less than 5. The
minimum expected count is .15.
Symmetric Measures
Nominal by
Nominal
Phi
Cramer's V
Contingency Coefficient
N of Valid Cases
Value
.755
.534
.602
99
Approx. Sig.
.000
.000
.000
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
From the data above, it can be determined that the null hypothesis is rejected with
the significance level of 0.000 which is smaller than the o=0.05. There is a strong
relationship between organizational structure and total success because the Cramer's V is
0.534. Kruskal Walhs supports this result by rejecting the null hypothesis.
72
So, because the null hypothesis is rejected it is safe to say that there is a
relationship between the organizational structure types and the total success of ERP
implementation. Three types of organizational structures have different effects on the
total success of the implementation.
Table 4.43 The Kruskal Walhs test for the total success of the ERP implementation
Rate the success of your
ERP Implementation.
Total success of the
ERP implementation.
Organizational structure
Functional
Matrix
Pure Project
N
57
Mean Rank
40.70
27
78.46
15
34.10
99
Test Statistics?"
Chi-Square
Rate the success of your ERP
Implementation. Total success of the
ERP implementation.
43.302
2
df
.000
Asymp. Sig.
a. Kruskal Wallis Test
b. Grouping Variable: Which organizational
structure exists in your company?
Table 4.44 The Mann-Whitiiey U test between the Functional and Matiix structures for
the total success of the ERP implementation.
Rate the success of your
ERP Implementation.
Total success of the
ERP implementation.
57
Mean Rank
32.18
Sum of Ranks
1834.00
Matrix
27
64.30
1736.00
Total
84
Organizational structure
Functional
N
Test Statistics?
Mann-Whitney U
Rate the success of your ERP
Implementation. Total success of the ERP
implementation.
181.000
1834.000
Wilcoxon W
-6.081
Z
Asymp. Sig. (2-tailed)
.000
a. Grouping Variable: Which organizational structure exists in
your company?
73
From the test statistics which are shown in table 4.44, the null hypothesis is
rejected because the asymptotic significance equals 0.000 and is smaller than the cf=0.05.
As a result, this test shows that the Matrix structure is more effective than the Functional
structure in terms of achieving the total success of the ERP implementation.
Table 4.45 The Mann-Whitney U test between the Matrix structure and Pure Project
structures for the total success of the ERP implementation.
Rate the success of your
ERP Implementation.
Total success of the
ERP implementation.
Organizational structure
Matrix
•
p • *
N
Total
27
Mean Rank
28.17
Sum of Ranks
760.50
15
9.50
142.50
42
Test Statistics?
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
Rate the success of your ERP
Implementation. Total success of the
ERP implementation.
22.500
142.500
-5.228
.000
a. Grouping Variable: Which organizational structure
exists in your company?
The asymptotic significance is 0.000 and this is smaller than the 0.05(Q: value).
So, the null hypothesis is rejected and the alternative hypothesis implies the Matrix
structure is better than the Pure Project structure in achievmg the total success of the ERP
implementation.
For the last pair of organizational structures, the Mann-Whitney U test is
performed and the resuhs are given in the following table. The asymptotic significance
level is 0.355 and this is larger than the a. value (0.05). Thus, the null hypothesis cannot
be rejected and therefore the Pure Project structiu-e does not have much more effect as the
Functional sti-ucture has. In other words, the Functional structure has larger significance
level in achieving the total success in the ERP implementation.
74
Table 4.46 The Mann-Whitney U test between the Functional structure and Pure Project
structure for the total success of the ERP implementation
Organizational structure
Functional
p,,e Project
Rate the success of your
ERP Implementation.
Total success of the
ERP implementation.
57
Mean Rank
37.53
Sum of Ranks
2139.00
15
32.60
489.00
N
Total
72
Test Statistics?
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
Rate the success of your ERP
Implementation. Total success of the
ERP implementation.
369.000
489.000
-.926
.355
a. Grouping Variable: Which organizational structure
exists in your company?
The results can be written as follows for the total success of the ERP
implementation;
I^Mts ^ I^Fts > ^iPts
4.7 hiterpretation of the Results
The statistical analysis used in this study is appropriate for the data received fi-om
survey in order to search for a relationship between variables which are in nominal and
ordinal scales. Because the reliability test of the survey gives a Cronbach's Alpha value
of 0.754, which is high enough, it is safe to say that the survey is trustworthy.
After the hypothesis testing the following table has been created to show the
differences between organizational structiires in terms of achieving the defined success
factors if there is any relationship. As can be determined from the table, there is no
relationship for the success factors, involved in the survey.
hi table 4.47, the expected (in parenthesis) and the actiial values for the achieved
success levels are given.
75
Table 4.47 Actual relationships between significance levels of organizational structures
in terms of achieving the success factors. (H:High, M:Medium, L:Low)
Functional
Matrix
Project Structure
Success Factor
L(L)
H(H)
M(M)
Flexibility
No Relationship
Having the proper tools
L(L)
H(H)
M(M)
Integration
H(H)
M(L)
L(M)
Standardization
L(M)
No Relationship
Ease of use of the ERP modules
No Relationship
Reporting
H(L)
Satisfy customer demands
M(H)
Implementation time
No Relationship
M(M)
H(H)
Total Success of the implementation
L(L)
(*): Expected values before the analyzing the variables.
For the four success factors; having the proper tools, ease of use of the ERP
modules, reporting, and implementation time, there is not any relationship observed with
the organizational sti-ucture types. It is expected that organizational structure does not
have an impact on these success factors because in most cases, these success factors are
related to the ERP software with exception of implementation time. In fact, these results
can be referred to as a proof or reliability of the survey because these relations are
rejected. Although organizational structure types do not effect these success factors, they
are really important and worth to examination. ERP implementation is a very complex
procedure and there are many factors that can be related to its success. Thus, every aspect
which is related to the ERP implementation should be stiidied separately, as has been
done in this research. As mentioned before, the main goal of this research is to identify
the possible relationships between the organizational structure types and the success
factors for the ERP implementation that are described in the literatiue. Implementation
time is connected to a different set of variables which include quahty of the consulting,
money, effectiveness of the project group, and complexity of the procedures in the
76
company which have to be defined to the system. So, it should be expected that the
relationship between organizational stiucture and implementation time is low.
For the flexibility success factor, actual levels of the relationships are the same as
the expected values. The availability of quick responses to changes and the project needs
makes the Matrix stiucture more powerful than the other tivo organizational structures.
Impossible technical interchange and lack of strong fiinctional groups in the Pure Project
organizations, flexibility is kind of a problem especially for the technical part of the
projects. Functional structures have a complex coordination system and require additional
time in approval decisions which makes the projects go more slowly compared to the
other two organizational stiiactures. Thus, flexibility is an issue for the companies that
have this kind of structure.
Business process integration is achieved at high levels in matrix structures. Other
structure types, the Pure Project structure and Functional structure, have lower levels of
success.
Standardization, as was expected, is best achieved with the Functional structure.
Easily defined and understandable policies and procedures make standardization more
easily achieved. In classical hierarchical structures, one of the most important features is
the availabihty of standardization. High formalization with strict rules and procedures
guaranteeing uniformity makes the implementation of the ERP systems easy and
effective in terms of the business process standardization. Most of the time, ERP system
implementation requires business process reengineering, data transformations, and
redefining the old data. If the Functional structure has the best standardization level
compared to the other structures, then in achieving success with the standardization
factor, the Functional structure has more advantage. It can be derived when the flexibility
is increases, the standardization decreases. Statistical analysis shows that the Matrix
structure is the worst one between these three structure types. This may be because of the
flexibility that the Matrix structiire obtains.
77
Ease of use of the ERP modules and reporting ability are not dependent on the
organizational structure type. As mentioned before, this is an expected behavior of the
ERP implementation because these success factors are most often related to the software.
Because both the Matrix structure and the Pure Project structure develop outside
company customer relations, these structures are expected to be more successful than the
Functional structure. From the statistical results, it can be seen that the actual levels of
achieving this success factor are nearly the same as the expected ones. Satisfying
customer demand is a really important feature for companies in such a competitive world
where customers look for high standards.
Total success of the ERP implementation is the main issue in this study. Besides
other success factors, achieving higher total success is more important in terras of the
success of the whole project. Of course, there are many independent factors that can
effect to total success of the ERP project. Organizational structure is just one of the
independent variables described in detail in the previous chapters. Defining the total
success of the ERP implementation is a subjective issue and the experience and the
knowledge of the individual who takes the survey has an impact on identifying this issue.
Thus, the responses have been eliminated fi-om individuals who appeared to lack proper
knowledge and experience. From the results, the Matrix structure has the most advantage
of achieving more success. It can be also derived fi-om the results that the Functional
structure is better than the Pure Project stioicture in achieving total success in ERP
implementations. The reasons behind these results should be as follows;
• Flexibility is a serious issue in ERP implementations.
• Communication ability of the company is one of the most important featiires in such a
big software implementation because the implementation takes place all over the
company. Every department and individual is effected by this installation.
. Technological interchange and sti-ong project teams have a relationship with the total
success.
. Development of policies and the procedures independently for each project can help the
ERP implementation.
78
Equally distributed knowledge existence is a feature that can make the implementation
more successful.
79
CHAPTER V
CONCLUSION
The evolution of Enterprise Resource Planning (ERP) systems has been a
highlight in information systems (IS) literature since early 1990's. The growth of ERP
systems has been enormous; however, the time and cost to implement ERP systems and
other critical success factors have undermined its true capabilities.
Companies are radically changing their information technology strategies by
purchasing prepackaged software instead of developing IT systems in-house. When
systems developed in-house do not work properly, most of the time, the reason is the
complexity of the procedures and difficulties in identifying these processes in the system.
ERP software automates core corporate activities, such as manufacturing, human
resource, finance, and supply chain management, by incorporating best practices to
facilitate rapid decision making, cost reductions, and greater managerial control. The
growing interest in ERP packages may be explained by the promises these systems offer.
These factors malce ERP software integration complex, because consensus is required
from an entire enterprise to reengineer a core business process and take advantage of the
software.
This research is performed to analyze the relationship between the organizational
structure types and the ERP implementation success. The survey study includes a large
variety of companies from different sizes, countries, and different sectors. Organizational
processes and structures are often stated as a major success factor for the success of an
ERP implementation. Thus, three main organizational structure types are involved in this
study; the Functional Structure, Matrix Structure, and Pure Project Stiucture.
The review of the data analysis which is described in the previous chapter shows
that there is a significant relationship between organizational structure types and the ERP
implementation success. When the organizational structure types are analyzed in more
details between the organizational structure types, the level of the effectiveness for each
type can be derived. In the previous section, a matrix is created to show the significance
80
levels of each organizational structure types. In general, it can be seen that companies
that have the Matrix structure are able to achieve more success in the implementation
than the other types of the structures. Knowing the differences in the significance levels
of the each structure separately is one of the most important resuhs of this study. With
this information, companies can recognize the advantages or the disadvantages of their
organizational
structures
before
the
implementation.
Getting
ready
for
the
implementation is a very important step in ERP implementations. Being aware of the
disadvantages and getting rid of them can help companies get on the way to a successful
implementation.
For example, having strong project teams is an important issue for the ERP
implementation. This conclusion can be derived from this research and by this
information a company, which using the functional structure, can create teams for this
implementation thereby giving them an important advantage. As found in the literature,
there is a lack of sfrong project teams in functional structures and without this knowledge
of the relationship between teams and implementation success, the company would not
take any precautions.
Pure project structures have a lack of technological interchange, hi this kind of
structure, it is impossible to change the technology between the projects. Yet, ERP
implementation is a very big and complex project that can affect all procedures,
employees, and the technology within the company. This project requires every resource
that the company has. When it is known that technological interchange has a strong
impact on the implementation success, which is one of the resuhs of this sttidy,
companies can take action before the implementation to make technology available for all
aspects of this project. Again, awareness of potential problems can affect the
implementation success to help the company in this project.
This study can also help by showing the significance level between the variables
which are mentioned above and fiirther analysis can be done for more detailed research.
ERP implementation is not only a software implementation but also a business
integration which has to be undertaken as a critical issue. These implementations have
81
many critical success factors and in order to achieve success, all of the critical success
factors have to be studied in detail. From this research, organizational structure can be
listed between the critical success factors and can give an advantage to companies if it is
studied carefully with all its aspects.
After finding the resuh that implies organizational structure as a critical success
factor, ERP implementation success can be studied more in detail. After performing a
linear regression analysis, just to see the relationship in percentages, it is observed that
3% of the total success of the implementation can be described by the organizational
structure. This percentage equals 15% when a non-linear regression analysis is
performed. So, for a project which has many critical success factors, these values are high
enough to say that organizational structure is a very important success factor for ERP
implementations.
Future Research
For fiitvtre research, it is recommended to study organizational structures in detail,
for example, for the affects in different countries. Describing the total success of the ERP
implementation in terms of the most effective critical factors can be studied. If this
success is formulated in terms of the critical factors by using regression analysis, it would
be very helpfiil to companies in achieving successful implementations.
In conclusion, it might be better to know the organizational structure of the
company in detail in terms of the features that it has. Then, before the ERP
implementation starts or during the decision period before the installation of the system,
the disadvantages can be eliminated in order to get the level of success desired.
82
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85
APPENDICES
86
A: CODE BOOK FOR THE SURVEY DATA
87
Variable Name
Codes
(Q2) Sector that the company works
for
l=Public
2=Private
(Q3) Product type of the company
1= Goods
2= Service
(Q4) Endorsement of the company
in year 2003 (sales)
l=Non-profit Company
2=Lessthen$10mi]
3=$10-$25mil
4=$25-$49
5=$50-$74mil
6=$75-$99mil
7=$100-$500mil
8=More then $500mil
l=less then 50
2=51-150
3=151-500
4=501-1500
5=1501-5000
6=More then 5001
(Q5) Number of the Employees
l=Centralized decisions made at
the corporate level.
2=Decentralized at the corporate
level, centralized decisions made
at the divisional level.
3=Decentralized at the corporate
and divisional level, decisions
made at lower operating levels.
4=Some decisions made at a
central corporate or divisional
level, other decisions made at
other levels.
(Q6) Decision making system in
your company
1= Functional Structure
2= Matrix Structure
3= Pure Project Structure
4= Other
(Q7)Which organizational structure
exists in your company?
88
(Q8) Which ERP software does the
company use
(Q9) How long did the
implementation take? (in months)
(QIO) What was the implementation
time that was planned before
starting?
1=SAP
2= Oracle
3= J.D. Edwards
4= Baan
5=QAD
6= Link
7= Adonix
8= Other
1=1-6
2=7-12
3=13-18
4= 19-24
5= 25-30
6=31-36
7= 37-42
8= More then 43
1=1-6
2= 7-12
3=13-18
4= 19-24
5= 25-30
6=31-36
7= 37-42
8= More then 43
l=None
2= less then %10
3=%ll-40
4=%41-70
5= %71-100
(Ql 1) At what percent the Data in
the old system transferred to the
new system
1= None
2= less then %10
3=%ll-40
4=%41-70
5= %71-100
(Q12) During BPR (business
process reengineering), what
percent of the work processes were
redefined?
(Q13) What percent of the ERP
Software was redesigned to be
adapted to the company?
l=None
2= less then %10
3=%ll-40
4= %41-70
5=%71-100
(Q14) What percent of your
expectations from the ERP software
were satisfied after implementation?
l=None
2= less then % 10
3=%ll-40
89
4=%41-70
5= %71-100
(Q15) Evaluate these uses of ERP in
terms of degree of obtaining them
after implementation
(Q15a) Flexibility of the software in
responding to the
changes in the company's processes
(Q15b) Having the proper tools for
the company. Does the
ERP software functionality satisfy
the company's
business processing requirements?
(Q15c) Business process integration
(i.e. common
accesebility of data, report and
performance
measure)
(Q15d) Standardization of the
processes; what degree of
business process standardization did
you achieve?
(Q15e) The "ease of use" of the
ERP system modules
(Q15f) The effectiveness and the
completeness of reporting
fiinctionality within the system
(Q15g) The ability to satisfy
customer demand
90
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1=1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
1= 1 (none)
2= 2 (very little)
3= 3 (little)
4= 4 (partially)
5= 5 (totally)
(Q16) Rate your ERP
implementation Success from 1 to
5
1= 1 (very low)
2= 2 (low)
3= 3 (medium)
4= 4 (high)
5= 5 (very high)
91
B: SURVEY
92
Welcome:
You are invited to participate in a research project to determine if a relationship exists between
organizational structure and ERP (Enterprise Resource Planning) Systems Implementation Success. In
this survey, approximately 150 people will be asked to complete a survey that asks questions about ERP
implementation success and their respective organizational structure.lt will take approximately 5-10
minutes to complete the questionnaire.
Your participation in this study is completely voluntary. There are no foreseeable hsks associated with this
project. However, if you feel uncomfortable answering any questions, you can withdraw from the survey at
any point. It is very important for us to learn your opinions.
This survey is anonymous that it does not contain any personal information about people or companies.If
you have questions at any time about the survey or the procedures, you may contact Murat Colak by email
at the email address specified below, colak_murat@yahoo.com
or the research supervisor Dr. Elliot Montes at elliot.montes@ttu.edu and tel:(806) 742-3543
Thank you very much for your time and support
1
Your position in the company
2 Sector that the company works for
3
4
Product type of the company
Endorsement of the company in year
2003 (sales)
n Public
• Private
n Goods
• Setvice
D Less than $10mil
D $50-$74mil
n $10-$25mil
G $75-$99mJl
G $25-$49mil
G $100-$500mil
G More than $500mil
1 1 Non-profit Company
5 Number of the Employees
6
7
Decision making system in the
company
Which organizational structure
exists in your company?
G less than 50
Q 501-1500
G 51-150
G 1501-5000
G 151-500
G More than 5001
G Centralized decisions made at the corporate level.
G Decentralized at the corporate level, centralized decisions made at the
divisional level.
G Decentralized at the corporate and divisional level, decisions made at
lower operating levels.
G Some decisions made at a central corporate or divisional level, other
decisions made at other levels.
r—1 Functional Structure (classical hierarchical structured
orgazanizationhaving several levels arrenged in a tree-likestructure)
G Matrix Structure (Functional organization for increasing the efficiency
interdepartmental business)
G Pure Project Structure(project manager maintains complete line
authority over the entire project and associated resources)
n Other
93
Which ERP software does the
company use?
How long did the implementation
take? (in months)
10
What was the implementation time
that was planned before starting?
At what percent was the Data in the
11 old system transferred to the new
system
During BPR (Business Process
12 Reengineering), what percent of the
work processes were redefined?
What percent of the ERP Software
13 was redesigned to be adopted to the
company?
What percent of your expectations
14 from the ERP software were
satisfied after implementation?
GSAP
G Oracle App.
G l D . Edwards
Gunk
GBaan
GQAD
I I Adonix
G Other
Dl-6
07-12
G 13-18
G 19-24
G 25-30
G 31-36
G 37-42
I I More then 43
1-6
7-12
G 13-18
G 19-24
G 25-30
G 31-36
G 37-42
G More then 43
GNone
G less than %10
G%ll-40
G%41-70
G%71-100
GNone
G less than %10
G%ll-40
G%41-70
G%71-100
GNone
G less than %10
G%ll-40
G%41-70
G%71-100
GNone
G less than %10
G%1M0
a%41-70
G%71-100
94
Importance of the uses
Evaluate these uses of ERP in terms of the
importance and the degree of obtaining them after
implementation (5;totally,4;partially,3:little,2:very
ittle,1:none)
14
Flexibility of the software in responding to the
changes in the company's processes or how
adaptable is the ERP software in accommodating
business process changes?
15
Having the proper tools for the company does the
ERP software functionality satisfy the company's
business processing requirements?
16
What degree of business process integration has
been achieved (i.e.common accesebility of data,
report and performance measure)?
17
Standardization of the processes; what degree of
business process standardization did you achieve?
18
Rate the "ease of use" of the ERP system modules
19
Rate the effectiveness and the completeness of
reporting functionality within the system
20
Rate the ability to sutisfy customer demand
21
Rate your ERP implementation Success from 1 to
5 (5:very high,4:high,3:medium,2:low,1:very low)
95
M
Degree of obtaining
C: RAW DATA
96
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