Transcript
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ACKNOWLEDGEMENT
THE REPORT HAS BEEN HIGHLY BENEFICIAL IN MAKING US
UNDERSTAND THE TECHNIQUES ALONGWITH PROS AND CONS OF
LEAN IMPLEMENTATION. THE EFFORTS OF DR.
IRFAN ANJUM MANARVI AND
TA NASIR SHAFIQ ARE HIGHLY COMMENDABLE WHO HAS NOT ONLY
PROVIDED THE NECESSARY GUIDANCE BUT AN OPPORTUNITY OF
RECEIVING FIRST HAND KNOWLEDGE OF PRACTICAL NATURE. THE
EFFORT PUT IN BY ME IS A CONCERTED AND WHOLE HEARTED
ATTEMPT WHICH CAN BE TERMED AS A FIRST ENDEAVOR TO
ACHIEVE PROFICIENCY IN THE FIELD.
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ABSTRACT
Comm and Mathaisel stated that “Historically, the purpose of the higher
education sector has been to teach and to conduct research, and for centuries
this has held true. Higher education is also one of the most immutable of
institutions”. Competition in today’s higher education marketplace is fierce.
Community colleges, four-year colleges, universities, and even higher schools
that offer online distance learning courses are all vying for the same students
—and the revenue they represent. To find success, institutions of higher
education must demonstrate that they can offer what others cannot. Naturally,
providing a quality, affordable education is of the utmost importance to
students and their families. But schools can also improve their chances of
attracting students by improving the levels of service they offer in every
“customer facing interaction”—which often times necessitates improving
internal work processes. The parents and the society in general expect more
and more of the HEIs, and on the other side, the constant budget cuts make a
big pressure, exposing their need to reformulate the organizations and to
manage the resources to respond to the external demand. These changes
make HEIs strive to the implementation of the Lean Service concept and to
internalize a cultural change in order to stay competitive and attractive in
business.
The subject is relatively new and not much work has been done in this field. In
this paper three to four variables have been defined which are termed as
wastes in this sector. In order to carry out the literature review a questionnaire
was devised and input from both the teachers and students had been sought.
Basing on this literature review recommendations were given to implement
this technique in higher education sector in a meaningful manner.
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TABLE OF CONTENTS
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IMPLEMENTATION OF LEAN IN HIGHER EDUCATIONAL INSTITUTIONS (HEIs)
PART – 1 INTRODUCTION
2.1 Introduction . Quality in Higher Education is an established notion which
is described vividly in terms of desirable characteristics of the activities
undertaken, individuals involved, and infrastructure needed. For the higher
education scenario in the local context, quality is achievable if the factors
influencing quality are identified and then conscious manipulating of these will
allow quality to be induced in the education system1. The lean concept is an
attempt to consciously identify factors that are instrumental in the effective
functioning of academia and their success in achieving the main objectives of
the educational activity. Lean Management is not a new concept, but it is new
for the education industry. There is no question that differences exist between
the products of a manufacturing assembly line and those of an education
service. But a huge similarity exists in the delivery systems of these
organizations, delivery systems made up of thousands of complex processes.
As such, many aspects of Toyota’s process improvement methodologies and
other Lean tools can and do apply to improving the processes of delivering
education. Forward thinking educators recognize both the application and the
implications Lean has for improving their institution operations and program
outcomes. The consistency with which Lean has delivered such improvements
in every industry that has applied them demonstrates the universality of its
principles. However, unlike products or services that are produced or delivered
in assembly line fashion, students are not designed to be replicas of each
other. Nor do they flow through a production or service line one at a time. Only
experienced educators can fully comprehend the numerous variables that
affect an individual student’s learning and how those variables affect the end
product – an educated human being ready for work, higher education, and
competition in a global economy. 2Lean Process Improvement, even in its
limited introduction within education, has resulted in increased performance
with cost savings. We strongly believe that higher education can benefit from
the principles of lean thinking, but it is important to realise that the application
1 PARAMETERS OF QUALITY IN HIGHER EDUCATION: A THEORETICAL FRAMEWORK by Dr. Sajida Zaki.2 DOIING MORE WIITH LESS – GOING LEAN IIN EDUCATION by Betty Ziskovsky, MAT, Joe Ziskovsky, MBA, Lean Education Enterprises, Inc.
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of lean thinking in higher education often becomes more complicated
compared to the application in a private enterprise producing goods. First of all
education is a sort of service, with a multiple set of customers both inside and
outside the higher education and some of their goals are conflicting. Higher
education is faced with two rather different tasks, namely research and
teaching, which also might be in conflict. Furthermore, the definition of the
value concept is complicated, for reasons already given, but also because the
value cannot be measured just once, but is a measurement task over a life-
long period of time. 3 HEIs are agents responsible for knowledge creation and
dissemination, and are responsible for preparing their students to be active
members of society, experts and future leaders. The need of preparation and
the exigency of the degrees are even more crucial in a constantly changing
world where personal and collective competences and know-how are tested
daily. The parents and the society in general expect more and more of the
HEIs, and on the other side, the constant budget cuts make a big pressure,
exposing their need to reformulate the organizations and to manage the
resources to respond to the external demand.4 Lean is not the "one" system by
any means that will solve education's problems, but, the philosophy and tools
of lean systems approaches are useful in education. The private sector has
been able to devote substantial resources to lean organizational development
initiatives and can now share best practice. What is useful for organizations
from other sectors is now available for institutions to sort through and
contextualize. In short, it is a mistake for educators to dismiss lean without
understanding it. In fact, lean may be the basis for mutually beneficial HEIs
partnerships, rather than the one- way dictates from the business community
that education have suffered through in past. 5
3 TQM AND LEAN THINKING IN HIGHER EDUCATION by Jens J. Dahlgaard* Peder Østergaard.4 BEYOND CLASSROOM BOUNDARIES: HOW HIGHER EDUCATION INSTITUTIONS APPLY LEAN by Ingrid P. M. Barroso; Sandra M. F. Santos; Maria A. Carravilla5 Is Lean Appropriate for Schools? By Shannon Flumerfelt, Ph.D.
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PART IIPARAMETERS OF RESEARCH
2.1 Statement of the Research Problem . Against the above background
the research problem to be researched within the ambit of this dissertation
reads as follows:
“HEIs in Pakistan are not strategically focused on the quality of
service to students, impacting adversely the standard of
education".
Investigative Sub-Questions . The investigative questions to be
researched in support of the research hypothesis reads as follows:
Can lean management principles be incorporated to resolve
the problem of quality of service in HEIs?
To what extent is management of HEIs is responsible for
quality assurance?
What are the key drivers of continuous improvement in HEIs?
To what extent does quality management improve the
efficiency of HEIs?
Primary Research Objectives . The primary research objectives of
this dissertation, the following:
To identify key drivers underpinning terms of service
delivery.
To determine if management has a strategic focus on the
quality of service to students.
To demonstrate the impact that management has on the
quality of service delivery.
Research Assumptions . The following assumption applies to the
research:
HEIs comply with the Higher Education Commission (HEC)
guidelines.
Research Constraints . The following constraints apply to the
research:
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Lack of knowledge and understanding of Lean concept by the
sample may pose as a constraint to the research.
The research is limited to small online local students and on
campus which were approachable in the Area of
responsibility.
The Research Process . The research process provides insight into the
process of 'how' the research will be conducted from developing
the proposal to submitting the dissertation. Remenyi, Williams,
Money and Swartz (2002:64-65), explains that the research
process as consisting of eight specific phases, which will also be
applied to this research study. The phases include:
Reviewing the literature.
Formalising a research question.
Establishing the methodology.
Collecting evidence.
Analysing the evidence.
Developing conclusions.
Understanding the limitations of the research.
Producing management guidelines or recommendations.
2.2 SCOPE OF THE RESEARCH
The importance of higher education lies in several areas, including the
financial, social, emotional and intellectual realms. Haile Selassie
quotes:-
“Education develops the intellect; and the intellect distinguishes
man from other creatures. It is education that enables man to
harness nature and utilize her resources for the well-being and
improvement of his life. The key for the betterment and
completeness of modern living is education. But, ' Man cannot live
by bread alone '. Man, after all, is also composed of intellect and
soul. Therefore, education in general, and higher education in
particular, must aim to provide, beyond the physical, food for the
intellect and soul. That education which ignores man's intrinsic
nature, and neglects his intellect and reasoning power cannot be
considered true education.”
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White paper on “Future of UK Higher Education” vividly summarize
the importance of HE:-
“Higher education is a great national asset. Its contribution to the
natural and social wellbeing of the nation is of vital importance. Its
research pushes back the frontiers of human knowledge and is the
formation of human progress. Its teaching educates and skills the
nation for knowledge dominated age. It gives graduates both
personal and intellectual fulfillment. Working with business, it
powers the economy and graduates are crucial for public services.
And wide access to higher education makes for a more enlightened
and socially just society”.
Lean is based on the concept of reducing waste of resources. Seven
types of waste, or categories of inefficiency, were initially identified at
Toyota, with an eighth about employee creativity added (Liker, 2004).
Overproduction . Producing items not needed for immediate
use, which will lead to waste in storage, transportation, and
staffing
Waiting . Idle time between activities due to scheduling
errors, missing material or information; waiting for
information or material from ‘upstream’.
Transportation . Moving material more than needed, due to
poor layout or storing material between steps in the process.
Processing . Doing more during the process than necessary;
unnecessary steps or motions; providing higher quality than
is needed; over processing or incorrect processing.
Excess Inventory . Excess materials; work in progress (WIP);
completed work still on site.
Unnecessary Movement . Extra motion not necessary, such
as looking for or reaching for material or tools or walking to
get material.
Defects or Spoilage . Defective completed products; items
needing rework or repair
Unused Employee Creativity . Not making the most use of
employee skills, creativity, and knowledge.
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2.3 Variables. There are eight types of waste which are identified during
going through various research analyst efforts best amongst them is Jens Jorn
Dahlgaard (2000). There were some additional variables which were
highlighted by a reputed Lean Education Enterprise Incorporation in 2007.
However, to reduce the number of variables these have been transformed into
four major types of wastes, which are as under:-
People Waste . Refers to the category of waste that occurs when
universities fail to capitalize fully on the knowledge skills and
abilities of employers and workgroups.
Teachers and students in downstream activities are waiting
because upstream activities at the supportive staff level
have not been delivered in time and vice versa.
Graduate students, who do not have the ability to get a job
and do not have lifelong learning capabilities.
Significant population that relies on community rather than
contributes to it.
Burned out, disheartened staff.
Asset Waste . Refers to the cluster of waste that occurs when the
university does not use its resources (human facility and materials)
in the most effective manner.
Bad planning so that materials and facilities needed for
teaching, coaching and testing are not appropriate in terms
of time, cost and quality.
Bad planning and mistakes in teaching, coaching and testing
so that students, teachers and the supportive staff have to
move from one place to another or from time to another
without any purpose, or have to ‘repair’ damage and
mistakes they are not responsible for.
Under or over utilization of people’s skills and not solicitation
or listening to other ideas.
Failure to meet scope and sequence targets.
Various unresolved challenges, problems, or abandoned
opportunities.
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Process Waste . Refers to the cluster of wastes that occur due to
shortcomings in the design or implementation of university
processes.
Uncoordinated teaching, coaching and testing, with the
consequence that students do not pass exams.
Scheduling courses for which the students have not yet got
the appropriate qualifications to pass.
Students who fail to dream, set goals, learn, and experience
success.
Failure to meet scope and sequence target.
Professionals doing non-professional tasks.
Various unresolved challenges, problems, or abandoned
opportunities.
Going through training you have already had.
After searching and finding information, recalling you already
knew it.
Information Waste . Refers to the category of waste that occurs when
the information that is available is deficient for supporting
university the processes.
Design of courses and supportive activities, which do not
meet the needs of the customers inside and outside the
higher educational institution.
Courses that do not contribute to the customer value
concepts.
Non-mastery of assigned curriculum.
Significant population that relies on community rather than
contributes to it.
Requiring curriculum that is not needed, not offering what is
needed.
Creating a new report when the data exists in a different
department or format.
More information than the next process requires.
2.4 Data Collection Design and Methodology . Questionnaires will serve
as the data collection methodology, as it falls within the broader definition of
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'survey research' or 'descriptive survey'. Remenyi et al. (2002:290), defines
the concept of 'survey' as: "... the collection of a large quantity of evidence
usually numeric, or evidence that will be converted to numbers, normally by
means of a questionnaire". A questionnaire consists of a list of questions
compiled in order to elicit reliable responses from a chosen sample with the
aim to determine what the participants do, think or feel. There are two
approaches in structuring questions namely, positivistic (structured 'closed'
questions) and phenomenological (unstructured 'open-ended questions). The
sample frame will consist of students and teachers of different, whereas the
sample will be drawn randomly from students and teachers. Five questions for
each variable as per the sequence have been asked to evaluate and
recommend viable options for application of lean in higher education.
Data Validity and Reliability . According to Collis and Hussey
(2003:186), 'validity' is concerned with the extent to which the
research findings accurately represents what is happening. More
specific, whether the data is a true picture of what is being studied.
According to Cooper and Schindler (2006:318-320), three major
forms of validity can be identified, namely 'content validity',
'criterion-related validity' and 'construct validity'. Reliability (also
referred to as 'trustworthiness'), is concerned with the findings of
the research (Collis & Hussey, 2003: 186). The findings can be said
to be reliable if you or anyone else repeated the research and
obtained the same results. There are three common ways of
estimating the reliability of the responses to questions in
questionnaires or interviews, namely:
Test Re-test Method.
Split Halves Method.
Internal Consistency Method.
Ethics . In the context of research, according to Saunders, Lewis and
Thornhill, (2001: 130), "... ethics refers to the appropriateness of
your behaviour in relation to the rights of those who become the
subject of your work, or are affected by it". The following ethics will
be observed in the research study:
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Informed Consent . Participants should be given the choice
to participate or not to participate, and furthermore be
informed in advance about the nature of the study.
Right to Privacy . The nature and quality of participants'
performance must be kept strictly confidential.
Honesty with Professional Colleagues . Findings must be
reported in a complete and honest fashion, without
misrepresenting what has been done or intentionally
misleading others as to the nature of it. Data may not be
fabricated to support a particular conclusion.
Confidentiality/Anonymity . It is good research practice to
offer confidentiality or anonymity, as this will lead to
participants giving more open and honest responses.
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PART IIIRESEARCH ENVIORMENT
3.1 Introduction to Research Environment
The application of lean thinking principles in the HEI (Higher Education
Institutions) setting is beginning to gain the interest of educators
and administrators (Comm & Mathaisel 2003). Comm & Mathaisel
(2003) provide a paradigm of lean initiatives in the higher
education setting for long-term sustainability. Nightingale (2000,
as cited in Comm & Mathaisel, 2003) mentions some of the current
and future benefits of e-lean. However, very few have actually
conceptualized the design, market, delivery of learning programs
as a service quality for enhancing customer value. By conceptually
recognizing learning essentially as a customer or learner-centered
process, new theory and knowledge initially developed by the
automotive industry can be applied to meet the challenges of
learning in higher education and the corporate sector. Although
this innovative approach comes from a business paradigm of
meeting mass production challenges, lean thinking uniquely
reinforces the need for individualizing learning experiences for the
online learner. Regardless of the setting, whether in the corporate
or the higher education context, it is imperative to review some of
the terms of lean thinking processes into the employee education
context.6 Svensson and Wood (2007:17) citing Shurpe (1999),
states that from a marketing perspective the relationship between
customer-supplier or buyers-seller is inappropriate for the student-
university relationship. Due to the fact that the relationship is not
exclusively based on the purchase and use of a product. 7
Lean in Higher Education Institutions . Sandra M. F. Santos; Maria A.
Carravilla (2010) stated that “Historically, the purpose of the
higher education sector has been to teach and to conduct
research, and for centuries this has held true. Higher education is
6 An International Comparative Analysis of Sustainability Transformation Across Seven Universities by D. Ferrer-Balas, J. Adachi, S. Banas, C.I. Davidson, A. Hoshikoshi, A. Mishra, Y. Motodoa, M. Onga and M. Ostwald7 Quality assurance in higher education : a managerial perspective at a university of technology by Maleecka Harris.
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also one of the most immutable of institutions”. More recently the
context in which HEI’s are working is changing quite rapidly and,
according to Comm and Mathaisel (2003), the most important
factors for change are: higher public expectations over what
universities should be delivering; increasing parental concern
about the quality of education; greater emphasis on college
ratings; demographic changes in student population and higher
costs. To these five factors we add the reduction of public funding.
HEIs are agents responsible for knowledge creation and
dissemination, and are responsible for preparing their students to
be active members of society, experts and future leaders. The
need of preparation and the exigency of the degrees are even
more crucial in a constantly changing world where personal and
collective competences and know-how are tested daily. The
parents and the society in general expect more and more of the
HEIs, and on the other side, the constant budget cuts make a big
pressure, exposing their need to reformulate the organizations and
to manage the resources to respond to the external demand.
These changes make HEIs strive to the implementation of the Lean
Service concept and to internalize a cultural change in order to
stay competitive and attractive in business. 8
Best Practices of Lean Applied to HEIs . According to Comm and
Mathaisel (2003) the best practices of Lean, established by
Nightingale (1999), that are being applied by some HEIs include:
Optimizing the flow of products and services, either affecting
or within the process, from concept design through point of
use.
Providing processes and technologies for seamless transfer
of, and access to, pertinent data and information.
Optimizing the capability and utilization of people.
Implementing integrated product and process development
teams.
8 BEYOND CLASSROOM BOUNDARIES: HOW HIGHER EDUCATION INSTITUTIONS APPLY LEAN by Ingrid P. M. Barroso; Sandra M. F. Santos; Maria A. Carravilla
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Developing relationships built on mutual trust and
commitment.
Continuously focusing on the customer.
Promoting lean thinking at all levels.
Continuously processing improvements.
Maximizing stability in a changing environment.
For a successful implementation of the Lean concept on HEIs, there are
seven important best practice components that must be followed.
These are:
Environment for change.
Leadership.
Culture.
Employee empowerment.
Training.
Communication.
Measurement.
The Lean concept, once implemented correctly, results on the
elimination of waste, making processes more efficient and
providing better value to the customer of the HEIs. The processes
within HEIs Harrington (1991) states that “There is no Product or
Service without a process, the same way there is no process
without a Product or Service”. According to Davenport (1994) a
process is a structured and calculated sequence of activities,
designed to produce a specific output based on a defined input.
HEIs, because of their nature and complexity, have a vast amount
of processes that are created based on the mission, vision and on
the specific objectives of each institution. As mentioned in Cardoso
et al., (2005), the core processes of a HEI are:
Teaching process, related with the application of knowledge;
Research process, associated with creation of new
knowledge;
Sharing process, that is the dynamic process between the
other two processes.
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These core processes of a HEI can be organized, according to Madeira
(2007) as the following key areas:
Students along their academic trajectory.
Programmes.
Research.
Technology transfer.
Financial resources.
Human resources.
Physical resources.
“Lean Thinking” in Distance Education . In the move away from
mass media- and correspondence-based distance education
systems toward online distance education programmes, a more
relevant management approach referred to as “lean thinking”
offers guidance for distance education program managers. Owing
its origin to the innovative leadership of Taichi Ohno at Toyota
Motors in Japan, and popularized by Womack and Jones (2003),
lean thinking has enabled industries and public service
organizations in many countries to eliminate waste, i.e., “any
human activity which absorbs resources but creates no value”
(Womack and Jones, 2003, p. 15), lower costs and, at the same
time, to increase production. Lean thinking provides “a way to do
more and more with less and less – less human effort, less
equipment, less time, and less space – while coming closer and
closer to providing customers with exactly what they want”
(Womack and Jones, 2003, p. 15).
Higher Education Structures in Pakistan . The Higher Education
Commission (HEC), formerly the University Grant Commission, is
the primary regulator of higher education in Pakistan. It also
facilitates the development of higher educational system in
Pakistan. Its main purpose is to upgrade the Universities of
Pakistan to be centres of education, research and development.
The HEC is also playing a leading role towards building a
knowledge based economy in Pakistan by giving out hundreds of
doctoral scholarships for education abroad every year. Dr. Javaid
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Laghari is the newly appointed HEC Chairman. HEC main programs
are following:
Faculty development.
Curriculum revision.
Higher education infrastructure development.
Indigenous scholarships.
Foreign scholarships.
Patent filing support.
Conference travel grants.
Increase industry and university research collaboration.
Developing new technology parks.
3.2 Factors that Impact the Service Sector
Customer Expectations . According to Johns and Roward (1998:250),
the theory on expectancy disconfirmation assumes that the
expectations customers have regarding a service are qualitatively
adequately similar to their perceptions of performance.
Furthermore, this will enable the direct measurement of the
differences between the two variables (Johns & Roward, 1998:250).
John and Tyas (1997) cited by Johns and Roward (1998:250), found
that previous critical incidences and culture has a strong influence
on a customer's expectation and perception of service
performance. Johns and Roward (1998:250), are of the opinion that
"... expectations are the basis upon which customers select and
judge services". Furthermore, an understanding of the customer's
dimensionality, will provide insight into the following:
The satisfaction process.
The most appropriate way to measure service quality.
The design of services to best match customers' needs.
Customer Perceptions . According to Johns and Roward (1998:249)
citing Bolton and Dew (1991), and Oliver (1980), that research on
service quality originated from the expectancy disconfirmation
theory, which states that the customers' perception of service
quality is the difference between their expectations and the actual
service performed. Furthermore, when service performance
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exceeds expectations, disconfirmation is positive, and negative
when the opposite occurs (Johns & Roward, 1998:249).
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PART IV RESEARCH METHODOLOGY
4.1 Methodology . The development of this research work includes an
extensive literature review on the subjects presented in section above. The
methodology includes the development of an on-line survey to obtain data
from students/teachers of higher education institutions. Efforts were made to
design a questionnaire that would effectively address the areas of wastes
mentioned above. A 20 question form was made available on a designated
Internet address in the form of a web form. Prior to the development of the
questionnaire, three face-to-face interviews were conducted including one
Principle of HEI (Hajvaery University), student of public sector HEI (Services
Institute of Medical Sciences) and private sector HEI (UET Lahore). The results
of the face-to-face interviews were essential for the formulation of the survey
questions. After collecting the results of on line survey, the scope of research
was limited to public sector institutes. Reason being that the problems and
difficulties experienced by the teachers/students of both the sectors are
entirely different. The on line questionnaire and the summary of the survey, as
well as the comments/suggestions collected are presented in appendices A
and B respectively.
The Target Population . Collis and Hussey (2003:232), defines target
population as follows: "A population is any precisely defined set of
people or collection of items which is under consideration". A
random sample (Collis and Hussey, 2003:156) will be drawn from
the faculties listed above, ten respondents from each faculty. This
approach was taken to ensure that each faculty identified as the
survey population represented (ColIis & Hussey, 2003:232;
Easterby-Smith & Lowe, 1996:122125). In this research initially
both the public and private sectors institutes were focused,
however in the later stages it was limited to public sectors
educational institutes. Babbie (2005: 196-197), suggests that the
following are the two reasons for using random sampling:
It serves as a check on conscious or unconscious bias of the
researcher as it (random sampling) erases the danger of the
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researcher selecting cases on intuitive basis to support the
research expectations or hypothesis.
Random sampling offer access to the body of probability
theory, forming the basis of estimating characteristics of the
population as well as estimates of accuracy of the samples.
Measurement Scales
Lickert scale has been used in the survey relating to this
research. The Lickert scale allows respondents to respond to
each question or statement by choosing one of the five
agreement choices. The following as the advantages of the
Lickert scale:
Easy and quick to construct.
Each item meets an empirical test for discriminating
ability.
The Lickert scale is probably more reliable than the
Thurston differential scale.
The Lickert scale is also treated as an interval scale.
The Lickert scale was used in this survey as it can be used in
both 'respondent centred' and stimulus-centred' studies. One
questionnaire was developed for both students and the
teacher. The attention of the reader is drawn to the fact that
more than 50% of the questions were of generalized nature
to have a candid view of both teacher and students. Such
type of surveys is generally weak on validity, and strong on
reliability.
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PART VRESEARCH ANALYSIS
5.1 Data Analysis and Interpretation of Results . This chapter discusses
the statistical analysis of data gleaned from the surveys conducted as
described above. The aim of this study is to determine whether the concept of
lean thinking can be employed in public sector HEIs. The information obtained
from the questionnaires posed to students and teachers will be presented and
analysed below. The tool so floated was not an internationally accepted
version; therefore factor analysis of the designed tool was conducted as per
the defined variable. In order to undertake this activity SPSS software was
used. The details of this activity is appended in ensuing lines:-
People Waste (VAR-1)
Initially the survey on this variable was conducted by asking
5 questions which are as under:-
Do you think that lean thinking be applied in education
sector?
Teachers in education sector are employed as per their
qualification.
Teachers are over loaded in your institution therefore
their output is not completely utilized.
Strength in each class can be easily managed by the
teacher.
Results of the students should affect the salary and
promotion of teacher.
The Eigenvalue above 1 was accepted and the variance of
this variable is 49%. The KMO value came out to be 0.622
which is above 0.5. On running factor analysis of the said
variable, collinearality was present between the questions of
Var_1.To remove the same, the questions were reframed and
analyzed again through SPSS. The values were within limits
as shown below:-
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Asset Waste (VAR-2)
The questions asked to analyze this parameter are as under:-
Performance of students in open market/ competitive
exams/board exams is satisfactory.
Sufficient training facilities are available to the
students for gaining professional competence.
Administrative facilities held with the institute are
sufficient enough to facilitate the students.
Training equipment/gadgets held with the institute are
in line with the latest technology.
Equipment held by the institution is meaningful and
not an asset waste.
The Eigenvalue above 1 was accepted and the variance of
this variable is 65%. The KMO value came out to be 0.664
which is above 0.5. On running factor analysis of the said
variable, collinearality was present between the questions of
Table 3
Component Matrix – People Waste a
Component
1
APPLICATION OF LEAN IN EDUCATION SECTOR .626EMPLOYMENT OF TEACHER AS PER THERE QUALIFICATION .774EASILY MANAGED BY TEACHER .865AFFECT SALARY AND PROMOTION OF TEACHER .508
Extraction Method: Principal Component Analysis.a. 1 components extracted.
Table 1
KMO and Bartlett's Test – People Waste
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .622
Bartlett's Test of
Sphericity
Approx. Chi-Square 106.116
df 6
Sig. .000
Total Variance Explained – People Waste
Component
Initial EigenvaluesExtraction Sums of Squared
Loadings
Total% of
Variance Cumulative % Total% of
VarianceCumulativ
e %
1 1.997 49.917 49.917 1.997 49.917 49.9172 .934 23.341 73.2583 .687 17.171 90.4294 .383 9.571 100.000
Extraction Method: Principal Component Analysis.
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Var_2.To remove the same, the questions were reframed and
analyzed again through SPSS. The values were within limits
as shown below:-
Component Matrix – Asset Waste a
Component
1SUFFICIENT FACILITIES ARE AVAILABLE TO GAIN COMPETENCE .834SUFFICIENT FACILITIES ARE AVAILABLE .836INLINE WITH THE LATEST TECHNOLOGY .747
Extraction Method: Principal Component Analysis.a. 1 components extracted.
KMO and Bartlett's Test – Asset Waste
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .664
Bartlett's Test of
Sphericity
Approx. Chi-Square 98.094
df 3
Sig. .000
Total Variance Explained – Asset Waste
Component
Initial EigenvaluesExtraction Sums of Squared
Loadings
Total% of
VarianceCumulative
% Total% of
VarianceCumulative
%
1 1.952 65.069 65.069 1.952 65.069 65.0692 .620 20.651 85.7203 .428 14.280 100.000
Extraction Method: Principal Component Analysis.
Process Waste (VAR-3)
Table 4
Table 5
Table 6
24
The questions asked to analyze this parameter are as under:- Admission procedure of the institutes is quite
cumbersome.
Students interested in admission should be tested
through written test.
Interview of the students clearing entry test should be
compulsory.
Send up exams should be taken before sending the
admission of students for board / professional exams.
Students should be tested once in a year rather than 3
to 4 times.
The Eigenvalue above 1 was accepted and the variance of
this variable is 49%. The KMO value came out to be 0.578
which is above 0.5. On running factor analysis of the said
variable, collinearality was present between the questions of
Var_3.To remove the same, the questions were reframed and
analyzed again through SPSS. The values were within limits
as shown below:-
Component Matrix – Process Wastea
Component
1ADMISSION PROCEDURE IS CUMBERSOME .651SEND UP EXAM SHOULD BE TAKEN BEFORE SENDING THE ADMISSION .680STUDENTS BE TESTED ONCE IN A YEAR RATHER THAN 3 TO 4 TIMES .781
Extraction Method: Principal Component Analysis.a. 1 components extracted.
KMO and Bartlett's Test – Process Waste
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .578
Bartlett's Test of Sphericity Approx. Chi-Square 27.446
Table 7
25
df 3
Sig. .000
Total Variance Explained – Process Waste
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total% of
VarianceCumulative
% Total % of Variance Cumulative %
1 1.497 49.910 49.910 1.497 49.910 49.9102 .846 28.190 78.1003 .657 21.900 100.000
Extraction Method: Principal Component Analysis.
Information Waste (VAR-4) The questions asked to analyze this parameter are as under:-
Knowledge imparted to the students does not help R &
D activity.
Curriculum of majority of the institutes does not
commensurate with the modern syllabi around the
world.
Educational system is limiting the competence of
students.
People of advanced nations have progressive approach
due to their better educational system.
The Eigenvalue above 1 was accepted and the variance of
this variable is 69%. The KMO value came out to be 0.500
which is acceptable. On running factor analysis of the said
variable, collinearality was present between the questions of
Var_4.To remove the same, the questions were reframed and
analyzed again through SPSS. The values were within limits
as shown below:-
Table 8
Table 9
26
Component Matrix – Information Wastea
Component
1DOESNOT COMMENSURATE WITH MODERN SYLLABI .831
LIMITING THE COMPETENCE OF STUDENTS .831
Extraction Method: Principal Component Analysis.a. 1 components extracted.
KMO and Bartlett's Test – Information Waste
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .500Bartlett's Test of Sphericity
Approx. Chi-Square 23.516
df 1
Sig. .000
Table 10
Table 11
Total Variance Explained – Information Waste
Component
Initial EigenvaluesExtraction Sums of Squared
Loadings
Total% of
VarianceCumulative
% Total% of
VarianceCumulative
%
1 1.382 69.076 69.076 1.382 69.076 69.0762 .618 30.924 100.000
Extraction Method: Principal Component Analysis.
27
Lean in HEIs (VAR-5)
The questions asked to analyze this parameter are as under:-
Awareness of LEAN is not common in our society.
People have a little exposure about the application of
lean in their related organization.
It is difficult to implement lean in the organization due
to procedural limitations.
The Eigenvalue above 1 was accepted and the variance of
this variable is 55%. The KMO value came out to be 0.500
which is acceptable. On running factor analysis of the said
variable, collinearality was present between the questions of
Var_5.To remove the same, the questions were reframed and
analyzed again through SPSS. The values were within limits
as shown below:-
Table 14
Component Matrix – Lean in HEIsa
Component
1EXECUTION .745
EXPOSURE .745
Extraction Method: Principal Component Analysis.
Table 13
KMO and Bartlett's Test – Lean in HEIs
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .500
Bartlett's Test of
Sphericity
Approx. Chi-Square 23.516
Df 1
Sig. .000Total Variance Explained – Lean in HEIs
Componen
t
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulativ
e %
1 1.109 55.448 55.448 1.109 55.448 55.448
2 .891 44.552 100.000
Extraction Method: Principal Component Analysis.
28
5.2 Regression Analysis
The regression model was found to be of significance. Of the variables
considered, however, only a few gave robust results. These are shown
in Table 16.
Significant Value of Variables
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig.B Std. Error Beta
1 (Constant) 3.896 .678 5.748 .000
INFORMATION_WASTE -.033 .080 -.037 -.416 .678
PROCESS_WASTE .144 .078 .180 1.844 .067
ASSET_WASTE .176 .061 .275 2.905 .004
PEOPLE_WASTE -.036 .058 -.065 -.628 .531
a. Dependent Variable: LEAN_IN_HEI
Asset Waste Variable
As expected, there was a definite predominant role of Asset
Waste Variable in determining problems that are
experienced for implementation of lean in HEIs. The input
was received from the teachers and students of different
institutes in Lahore. In order to analyze this asset waste
variable against lean in HEIs, both were plotted on this
graph. This trend is illustrated in Figure 1 below, where
asset waste is measured quantitatively. For values of asset
waste, the moving average trend line for Lean in HEIs is
generally showing a proportional trend.
Table 15
Table 16
29
Statistical analysis reveals a positive direct relationship
between asset waste and implementation of lean. As the
awareness on the basic principles of asset waste is increased
the implementation of lean in HEIs will become much easier.
Information Waste Variable
As expected, there was a definite predominant role of
Information Waste Variable in determining problems that
are experienced for implementation of lean in HEIs. The input
was received from the teachers and students of different
institutes in Lahore. In order to analyze this information
waste variable against lean in HEIs, both were plotted on this
graph. This trend is illustrated in Figure 2 below, where
information waste is measured quantitatively. For values of
information waste, the moving average trend line for Lean in
HEIs is generally showing a proportional trend.
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 790
5
10
15
20
25
30
TREND LINE ANALYSIS - ASSET WASTE vs LEAN IN HEIsASSET WASTELEAN IN HEIsMoving average (LEAN IN HEIs)
Figure 1
30
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 790
2
4
6
8
10
12
14
16
18
20
TREND LINE ANALYSIS - INFORMATION WASTE vs LEAN IN HEIsINFORMATION WASTELEAN IN HEIsMoving average (LEAN IN HEIs)
Statistical analysis reveals a positive direct relationship
between information waste and implementation of lean. As
the awareness on the basic principles of asset waste is
increased the implementation of lean in HEIs will become
much easier.
Comparison of All Variables
In order to evaluate the effect of both significant and
insignificant variable on implementation of lean both were
plotted on time line graph. The results are as shown in figure
3.
Figure 2
31
0 2 4 6 8 10 120
2
4
6
8
10
12
TREND LINE ANALYSIS - VARIABLES vs LEAN IN HEIsASSET WASTE PROCESS WASTE
PEOPLE WASTE INFORMATION WASTE
LEAN IN HEIs Moving average (LEAN IN HEIs)
Statistical analysis reveals no significant relationship
between variables and implementation of lean. As the
awareness on the basic principles of wastes is increased the
implementation of lean in HEIs will become much easier.
Comparison of Asset Variable Factors vs Lean in HEIs Factors
In order to evaluate the effect of factors of asset waste
variable on lean in HEIs the trend line of both lean in HEIs
factors has been generated. This has been displayed in
figure 4.
Figure 3
32
33
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 790
1
2
3
4
5
6
TREND LINE ANALYSIS - ASSET WASTE FACTORS vs LEAN IN HEIs FACTORS
TRAINING ADMINSTRATIVE TRAINING_EQUIPMENTEXPOSURE_OF_PEOPLE Moving average (EXPOSURE_OF_PEOPLE) DIFFICULTY_IN_EXECUTIONMoving average (DIFFICULTY_IN_EXECUTION)
34
Statistical analysis reveals both factors of lean are
proportionally increasing and decreasing with the factors of
asset waste variables except at few places which are
showing there positive relationship with lean
implementation. As the awareness on the basic principles
of wastes is increased the implementation of lean in HEIs
will become much easier.
5.3 Cause and Effect Analysis . In order to make the study more
beneficial for public sector HEIs SIPOC analysis was conducted to find the
most sensitive variable. After the SIPOC analysis Key Process Input Variables
(KPIV) and Key Process Output Variables (KPOV) were evaluated and put in
Cause and Effect Matrix to determine the most sensitive variables. In this
case the asset variable came out to be the most significant. The details of
these are attached as Anx 1 and 2.
35
PART VI
RECOMMENDATIONS AND CONCLUSSION
6.1 Recommendations . Recommendations to mitigate to the research
problem and to provide an answer to the investigative questions, the
following:
Develop a more sophisticated management system tailored for HEIs
to cater for their entire administrative requirements i.e. buildings,
transportation, record keeping and allied facilities for proper
implementation of lean.
HEIs management need to have a strategic focus on meeting and
exceeding the availability of latest training equipment required to
keep the students abreast with new trends in technology. By using
latest gadgetry quality education will be imparted with minimum
human effort.
Management of HEIs needs to focus their energy on continuous
improvement for sustainability purposes, and in order to meet the
challenges of globalization and market competition.
Encourage student feedback by providing students with the
opportunity to give suggestions or feedback with regard to improving
service delivery. (By having suggestion boxes, feedback cards or
questionnaires at all faculties and servicing departments for
example: Information Technology, Library, Clinic, student debtors
departments etc.).
6.2 Conclusion . The challenges facing higher education was
identified as increasing customer demand for quality products and services,
globalisation and competition for market share. In order for organisations
(Higher Education Institutions) to keep abreast with these technological
advancements, management of these organisations need to have a strategic
focus on quality of service to students. By encouraging student feedback
management will be able to identify areas where improvement is needed
and subsequently focus their energy on improving customer service by
minimizing complaints.
36
REFERENCES
Beyond Classroom Boundaries: How Higher Education Institutions
Apply Lean by Ingrid P. M. Barroso; Sandra M. F. Santos; Maria A.
Carravilla FEUP - Faculdade de Engenharia da Universidade do
Porto.
A Review of Lean Principles As Applied to the Education
Environment BY Meera Alagaraja Educational Administration and
Human Resource Department Texas A&M University and Stephen
Thompson Engineering Technology and Industrial Distribution
Department Texas A&M University.
An international comparative analysis of sustainability
transformation across seven universities by D. Ferrer-Balas, J.
Adachi, S. Banas, C.I. Davidson, A. Hoshikoshi, A. Mishra, Y.
Motodoa, M. Onga and M. Ostwald (Information about the authors
can be found at the end of the article).
Doing More with Less – Going Lean in Education by Betty Ziskovsky,
MAT, Joe Ziskovsky, MBA, CLM Lean Education Enterprises, Inc,
2007.
Application of Lean Thinking in Higher Education by Yashwant Raj
Parsamal.
New Development: Creating a Lean University by Peter Hines and
Sarah Lethbridge
WOMACK J.P., JONES D.T, ROOS. D. (1990). The Machine that
changed the world, MacMillan, New York.
PARAMETERS OF QUALITY IN HIGHER EDUCATION: A THEORETICAL
FRAMEWORK by Dr. Sajida Zaki. Associate Professor, Dept of
Humanities, NED University of Engineering & Technology, Karachi –
Pakistan
WOMACK J.P, JONES D.T. (1996). Lean Thinking. Banish waste and
create wealth in your corporation. Touchstone Books. London.
Dahlgaard, J. and Østergaard, P. (2000), “TQM and lean thinking in
higher education”, in Shina, M. (Ed.),The Best on Quality, Vol. 11,
Quality Press/American Society for Quality, Milwaukee, WI, pp. 203-
26.
Comm. C.L., & Mathaisel, D.F.X (2003). Less is more: a framework
for a sustainable university. International Journal of Sustainability in
Higher Education. Vol 4 (4), pp.314-323.
37
LIST OF TABLESTable 1 Component Matrix – People Waste 23Table 2 KMO and Bartlett's Test – People Waste 23Table 3 Total Variance Explained – People Waste 23Table 4 Component Matrix – Asset Waste 24Table 5 KMO and Bartlett's Test – Asset Waste 24Table 6 Total Variance Explained – Asset Waste 25Table 7 Component Matrix – Process Waste
26Table 8 KMO and Bartlett's Test – Process Waste 26Table 9 Total Variance Explained – Process Waste 26Table 10 Component Matrix – Information Waste 27Table 11 KMO and Bartlett's Test – Information Waste 27Table 12 Total Variance Explained – Information Waste 27Table 13 Component Matrix – Lean in HEIs 28Table 14 KMO and Bartlett's Test – Lean in HEIs 28Table 15 Total Variance Explained – Lean in HEIs 29Table 16 Significant Value of Variables 29
38
LIST OF FIGURESFigure 1 Trend Line Analysis - Asset Waste vs Lean in HEIs 30Figure 2 Trend Line Analysis - Information Waste vs Lean in HEIs 31Figure 3 Trend Line Analysis - Variables vs Lean in HEIs 32Figure 4 Trend Line Analysis – Asset Waste Factors vs Lean 33
in HEIs factors
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