Final Write Up 16

1

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.

2

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.

3

TABLE OF CONTENTS

4

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.

5

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.

6

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:

7

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.”

8

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.

9

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.

10

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

11

'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:

12

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.

13

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.

14

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

15

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.

16

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

17

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

18

exceeds expectations, disconfirmation is positive, and negative

when the opposite occurs (Johns & Roward, 1998:249).

19

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

20

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.

21

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:-

22

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.





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.

23



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


KMO and Bartlett's Test – Asset Waste


Bartlett's Test of

Sphericity


df 3

Sig. .000

Total Variance Explained – Asset Waste

Component


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


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.







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


KMO and Bartlett's Test – Process Waste


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


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.



which is acceptable. On running factor analysis of the said




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


KMO and Bartlett's Test – Information Waste

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .500Bartlett's Test of Sphericity


df 1

Sig. .000

Table 10

Table 11

Total Variance Explained – Information Waste

Component


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


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.



which is acceptable. On running factor analysis of the said




as shown below:-

Table 14

Component Matrix – Lean in HEIsa

Component

1EXECUTION .745

EXPOSURE .745


Table 13

KMO and Bartlett's Test – Lean in HEIs


Bartlett's Test of

Sphericity


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


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

Final Write Up 16

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