Thesis (3)

A STUDY ON PETER PRINCIPLE EFFECT IN

SOFTWARE DEVELOPMENT FIRMS OF SRI LANKA

Melanie Samaratunga

(9046)

Master of Business Administration in

Management of Technology

Department of Management of Technology

University of Moratuwa

Sri Lanka

November 2011

A STUDY ON PETER PRINCIPLE EFFECT IN

SOFTWARE DEVELOPMENT FIRMS OF SRI LANKA

Melanie Samaratunga

(9046)

Dissertation submitted in partial fulfillment of the requirements for the degree of

Master of Business Administration in Management of Technology

Department of Management of Technology

University of Moratuwa

Sri Lanka

November 2011

DECLARATION

I declare that this is my own work and this dissertation does not incorporate without

acknowledgement any material previously submitted for a Degree or Diploma in any

other University or institute of higher learning and to the best of my knowledge and

belief it does not contain any material previously published or written by another

person except where the acknowledgement is made in the text.

Also, I hereby grant to University of Moratuwa the non-exclusive right to reproduce

and distribute my dissertation, in whole or in part in print, electronic or other

medium. I retain the right to use this content in whole or part in future works (such as

articles or books).

……………………………. …………………………….

M. Samaratunga Date:

The above candidate has carried out research for the Masters dissertation under my

supervision.

……………………………. …………………………….

Prof. Vathsala Wickramasinghe Date

i

ABSTRACT

The Peter Principle — that individuals in an organization rise to their level of

incompetence —represents potential problems for all employees. Wondering if the

Peter Principle is prevalent in the software development firms of Sri Lanka, the

author revisited Dr. Laurence Peter’s study of 1969, The Peter Principle—Why

Things Always Go Wrong, which achieved best-seller status and soon became a part

of the lexicon of the business world.

A survey based study was carried out using respondents from selected software

development firms to identify if the effect exists. This study shows that the Peter

Principle, the universal phenomenon in which employees, around the world, are said

to rise to their level of incompetence, is ingrained in the software development firms

of Sri Lanka as well.

The behaviors embodied in the Peter Principle still have disrupting effects that occur

only too frequently in organizations. As a result, the Peter Principle cannot be

ignored. Its effects, however, can be remedied by improving the quality of

performance and rewards management practices, recruitment and selection practices

and by providing extensive training before employees reach their ultimate level of

incompetence.

ii

ACKNOWLEDGMENT

I would like to express my deepest appreciation to my supervisor, Prof. Vathsala

Wickramasinghe for her valuable support, ideas, and criticism during the springtime.

Her knowledge of the related literature, strong managerial perspective, and

willingness to exchange and shape ideas were crucial in the overall development of

this study. Your contributions had been of great value to the final result.

Additionally, I would like to convey my deep sense of appreciation for the

continuous help received from the team members of my organization, Virtusa

Corporation.

I would like to thank my family members for the contribution towards the success of

the research. They have sacrificed in many ways by allowing me to spend more time

on the study.

Further, the contribution of each and every respondent of the survey who extended

their support in the data collection process is very much appreciated.

Last but not least I thank all those whose names were, though not mentioned for their

help and encouragement in completing this research study.

iii

TABLE OF CONTENTS

DECLARATION.....................................................................................................................................i

ABSTRACT............................................................................................................................................ii

ACKNOWLEDGMENT......................................................................................................................iii

LIST OF TABLES................................................................................................................................vi

LIST OF FIGURES.............................................................................................................................vii

LIST OF ABBREVIATIONS............................................................................................................viii

CHAPTER 1 - INTRODUCTION........................................................................................................1

1.1 INTRODUCTION...............................................................................................................................11.2 RESEARCH PROBLEM......................................................................................................................31.3 RESEARCH OBJECTIVES..................................................................................................................81.4 SIGNIFICANCE OF THE STUDY........................................................................................................81.5 SCOPE OF THE RESEARCH STUDY..................................................................................................91.6 CHAPTER OUTLINE.......................................................................................................................10

CHAPTER 2 – LITERATURE REVIEW.........................................................................................11

2.1 INTRODUCTION.............................................................................................................................112.2 THE PETER PRINCIPLE..................................................................................................................11

2.2.1 Percussive Sublimation........................................................................................................132.2.2 Lateral Arabesque................................................................................................................132.2.3 Hierarchical Exfoliation.......................................................................................................132.2.4 Peter’s Inversion..................................................................................................................142.2.5 Paternal In Step....................................................................................................................152.2.6 Promotion by Pull and Push................................................................................................152.2.7 Final Placement Syndrome..................................................................................................152.2.8 Peter's Corollary..................................................................................................................17

2.3 PETER PRINCIPLE IN SOFTWARE DEVELOPMENT FIRMS..............................................................182.4 RESEARCHES CARRIED ON PETER PRINCIPLE EFFECT.................................................................192.5 SUMMARY....................................................................................................................................23

CHAPTER 3 - METHODOLOGY.....................................................................................................25

3.1 INTRODUCTION.............................................................................................................................253.2 CONCEPTUAL FRAMEWORK OF THE STUDY.................................................................................253.3 RESEARCH HYPOTHESES..............................................................................................................273.4 RESEARCH MODEL WITH HYPOTHESES........................................................................................273.5 OPERATIONALIZATION OF VARIABLES.........................................................................................29

3.5.1 The size of the company........................................................................................................293.5.2 The structure of the company...............................................................................................293.5.3 Quality of performance and rewards management practices..............................................303.5.4 Quality of Selection and recruitment practices....................................................................303.5.5 Human resource development practices..............................................................................30

3.6 UNIT OF ANALYSIS.......................................................................................................................353.6.1 Target Population.................................................................................................................35

iv

3.6.2 Data collection instrument...................................................................................................363.6.3 The method of data collection and analysis.........................................................................37

3.7. SUMMARY...................................................................................................................................37

CHAPTER 4 – DATA ANALYSIS AND DISCUSSION..................................................................38

4.1 INTRODUCTION............................................................................................................................384.2 CHARACTERISTICS OF THE SAMPLE...........................................................................................38

4.2.1 Characteristics of the organizations...............................................................................384.2.2 Characteristics of the respondents..................................................................................39

4.3 GOODNESS-OF-FIT MEASURES....................................................................................................434.3.1 Reliability and validity analysis - the existence of Peter Principle effect........................444.3.2 Reliability and validity analysis - the contributing factors for the existence of Peter Principle effect..............................................................................................................................47

4.4 DESCRIPTIVE STATISTICS.............................................................................................................504.5 CORRELATION ANALYSIS.............................................................................................................544.6 MULTIPLE REGRESSION ANALYSIS..............................................................................................584.7 SUMMARY....................................................................................................................................64

CHAPTER 5 – CONCLUSIONS AND RECCOMENDATIONS...................................................65

5.1 INTRODUCTION.............................................................................................................................655.2 CONCLUSIONS..............................................................................................................................655.3 RECOMMENDATIONS AND MANAGERIAL IMPLICATIONS.............................................................665.4 LIMITATIONS OF THE STUDY........................................................................................................715.5 DIRECTIONS FOR FUTURE RESEARCH..........................................................................................715.6 SUMMARY....................................................................................................................................73

REFERENCES.....................................................................................................................................74

Appendix A – Questionnaire..................................................................................................................78

Appendix B – SPSS Data Analysis Output............................................................................................83

v

LIST OF TABLES

Table 1.1: Summary of various researches carried out on software project failures ................................................. 3 Table 1.2: Summary of Standish chaos reports .......................................................................................................... 6 Table 3.1: Hypothesis statements ............................................................................................................................. 27 Table 3.2 : Operationalization of the identified variables ........................................................................................ 32 Table 3.3: Companies selected for the sample ......................................................................................................... 36 Table 4.1: Summary table for number of employees in organizations ..................................................................... 40 Table 4.2: Summary table for number of employees in different organization structures ....................................... 40 Table 4.3: Summary table for the age distribution of the respondents ..................................................................... 41 Table 4.4: Summary table for the gender distribution of the respondents ............................................................... 41 Table 4.5: Summary table for the marital status of the respondents ........................................................................ 41 Table 4.6: Summary table for the education level of the respondents ..................................................................... 42 Table 4.7: Summary table for the designation level of the respondents .................................................................. 43 Table 4.8: Summary table for the years of experience in IT of the respondents ...................................................... 43 Table 4.9: Summary table for the years of experience in the current company of the respondents ......................... 44 Table 4.10: Summary table for the years of experience in the current post of the respondents ............................... 44 Table 4.11: Reliability analysis for the factors that determine the existence of Peter Principle effect .................... 45 Table 4.12: Principle component analysis for the factors that determine the existence of Peter Principle effect . . . 46 Table 4.13: Rotated component matrix for the factors that determine the existence of Peter Principle effect ........ 46 Table 4.14: Reliability analysis results for quality of performance and rewards management practices related variables .................................................................................................................................................................... 48 Table 4.15: Principle component analysis results for quality of performance and rewards management practices related variables ........................................................................................................................................................ 48 Table 4.16: Factor loadings for quality of performance and rewards management practices related variables ...... 49 Table 4.17: Reliability analysis results for quality of recruitment management practices related variables ........... 49 Table 4.18: Principle component analysis results for quality of recruitment management practices related variables .................................................................................................................................................................... 50 Table 4.19: Factor loadings for quality of recruitment management practices related variables ............................. 50 Table 4.20: Reliability analysis results for quality of human resource development practices related variables....50Table 4.21: Principle component analysis results for quality of human resource development practices related variables .................................................................................................................................................................... 51 Table 4.22: Factor loadings for quality of human resource development practices related variables ..................... 51 Table 4.23: Descriptive statistics for the factors that explain the existence of Peter Principle effect ...................... 52 Table 4.24: Descriptive statistics for the factors that explain the quality of performance and rewards management practices .................................................................................................................................................................... 53 Table 4.25: Descriptive statistics for the factors that explain the quality of selection and recruitment practices . . . 54 Table 4.26: Descriptive statistics for the factors that explain the quality of human resource development practices .................................................................................................................................................................................. 54 Table 4.27: Correlation analysis results ................................................................................................................... 56 Table 4.28: Model summary for the existence of Peter Principle related behavior patterns and the contributing factors ....................................................................................................................................................................... 59 Table 4.29: ANOVA table for existence of Peter Principle related behavior patterns and the contributing factors60 Table 4.30: Coefficients for existence of Peter Principle related behavior patterns and the contributing factors ... 60 Table 4.31: Model Summary for the existence of incompetent employees in the higher levels of the hierarchy and the contributing factors ............................................................................................................................................. 61 Table 4.32: ANOVA table for the existence of incompetent employees in the higher levels of the hierarchy and the contributing factors ............................................................................................................................................. 62 Table 4.33: Coefficients for the existence of incompetent employees in the higher levels of the hierarchy and the contributing factors ................................................................................................................................................... 62 Table 4.34: Group Statistics for structure of the company ....................................................................................... 63

vi

LIST OF FIGURES

Figure 3.1: Conceptual Model .................................................................................................................................. 26 Figure 3.2: Conceptual Model with Hypotheses ...................................................................................................... 28 Figure 4.1: Revised Conceptual Model....................................................................................................................47

vii

LIST OF ABBREVIATIONS

IT – Information Technology

ICT – Information Communication Technology

IFS – Industrial and Financial Systems

BPO – Business Process Outsourcing

RPO – Recruitment Process Outsourcing

SPSS – Statistical Package for the Social Sciences

viii

CHAPTER 1 - INTRODUCTION

1.1 Introduction

Sri Lanka is emerging as a global IT-BPO destination of choice in a number of key

focus domain areas. It is ranked among the Top 50 Global Outsourcing destinations

by A.T. Kearney according to Sri Lanka Business Portal - Trade Information (2011).

In addition, Sri Lanka has emerged as the most preferred ICT/BPO hub in the Asian

region and is the destination renowned for Best-Of-Breed in Global Market.

Sri Lanka acts as an off-shore development center for several Fortune 500 companies

from the USA, Ireland, UK, Australia, etc and joint venture development center

companies from Sweden, Norway, USA, Japan etc. Some business entities that have

set-up their operations in the island include: HSBC, Industrial & Financial Systems

(IFS), Amba Research, RR Donnelley, Quattro, Virtusa, eCollege, Eurocenter,

Aepona, Millennium Information Technology and Innodata Isogen etc. At present

there are over 300 IT and BPO companies that operate in Sri Lanka, mostly small

and medium companies and a few large global players.

According to Sri Lanka Business Portal - Trade Information (2011), Sri Lanka offers

a rapidly growing, highly adaptable, innovative and loyal workforce. Currently, over

50,000 are employed in the IT and BPO industry in Colombo and the workforce is

growing at over 20% year-on-year. The workforce is stable with very low attrition

rates ranging from 10-15%.

The Software services sector focuses on telecommunication, banking, financial

services and insurance and software testing. Earnings from exports of IT-BPO sector

have shown a steady upward trend during the past decade, and annual exports of the

ICT sector for the last three years recorded as US $ 213 million in 2007, US $ 256

million in 2008 and US $ 271 million in 2009. The industry has set a target of $ 2bn

in export revenue from IT-BPO sector by 2012.

1

Sri Lankan IT industry shows good potential, but in the long term for any industry to

succeed it is highly necessary that a competent workforce is available. For this talent

should be managed effectively.

Talent management is very important for a number of reasons. It is about people and,

without people an organization would not exist. Employers should understand where

the strengths and weaknesses of their employees lie, in order to ensure they are

correctly deployed across the business. Identifying where the promising talent lies,

allows a company to plan ahead and nurture staff, so their personal development is

serving organizational development benefitting both parties.

One of the challenges of talent management in business is, knowing whether a

seemingly talented individual will thrive if promoted to a new task or area. Once

assigned and moved into a talent pool, these individuals must also be managed

properly, in terms of their own expectations and those of the employer.

Peter and Hull (1969), in their book, The Peter Principle state that, “in a hierarchy,

every employee tends to rise to his level of incompetence”, which means that in a

hierarchy, members are promoted so long as they work competently. Eventually they

are promoted to a position at which they are no longer competent i.e. their level of

incompetence and there they remain, being unable to earn further promotions.

To further elaborate on the Peter Principle theory, it is a concept that in

organizations, new employees typically start in the lower ranks, but when they prove

to be competent in their current designation, they get promoted to a higher rank,

generally management. This process of climbing up the hierarchical ladder can go on

indefinitely, until the employee reaches a position where he or she is no longer

competent. At that moment, the process typically stops, since the established rules of

bureaucracies make it very difficult to demote someone to a lower rank, even if that

person would be a much better fit and happier in a lower rank. The net result of this

principle is that, most of the higher levels of a bureaucracy will be filled by

incompetent people, who got there because they were quite good at doing different

and usually, but not always, easier work than the work they are expected to perform

at present. For example if you're a proficient and effective software developer, you're

2

most likely demonstrating high competence in your job right now. As a result of your

performance, your valuable contribution results in a promotion to a management

position. In this new position, you now do few of the original tasks which gained you

acclaim. In fact, little of your current job remains enjoyable, therefore your heart is

no longer in your work, and it shows. Given this, promotions stop, and there you

stay, until you retire or your company goes under due to mismanagement.

According to this principle, work is accomplished by those employees who have not

reached their level of incompetence. Thus we can see why organizations still

function even as Peter Principled employees accept promotions. Dr. Peter (1969)

provides an insightful analysis of why so many positions in so many organizations

seem to be populated by employees who seem incompetent. This concept is likely to

be ignored by most senior managers, since to admit one's organization is suffering

from this bureaucratic dilemma is admission that, people have been improperly

promoted. This, in turn, suggests that senior management might have attained their

own level of incompetence, and the problem is easily ignored, in case it become

suggested that senior management be more closely examined for their incompetence.

Once a company forms a culture of incompetence, only the incompetent staff will

remain, and the competent ones will eventually get frustrated and leave. As a result

the organization’s growth will hinder as they have incompetent employees at many

levels.

1.2 Research Problem

According to the article Facts and Figures – Why Technology Projects Fail (2011), a

number of studies have been completed that look into the success and failure rates of

software projects. These studies indicate that serious problems exist across the

industry as a whole. Table 1.1 summarizes some recent reports.

Table 1.1: Summary of various researches carried out on software project failures

Source Type of Survey Date Result

Geneca Interview based study

of software projects

2010-

2011

Interviews with 600 people closely

involved in software development projects

finds that even at the start of a project

3

many people expect their projects to fail

“Fuzzy business objectives, out-

of-sync stakeholders, and

excessive rework” mean that 75%

of project participants lack

confidence that their projects will

succeed.

A truly stunning 78% of

respondents reported that the

“Business is usually or always out

of sync with project

requirements”

KPMG (New

Zealand)

Survey of 100

businesses across a

broad cross-section of

industries

Dec 2010 KPMG survey of Project Management

practices in New Zealand finds some truly

startling results:

Survey shows an incredible 70%

of organizations have suffered at

least one project failure in the

prior 12 months

50% of respondents also indicated

that their project failed to

consistently achieve what they set

out to achieve

IBM Survey of 1,500

change management

executives

Oct 2008 IBM survey in the success / failure rates of

“change” projects finds:

Only 40% of projects met

schedule, budget and quality

goals

Best organizations are 10 times

more successful than worst

organizations

Biggest barriers to success listed

as people factors: Changing

mindsets and attitudes - 58%.

Corporate culture - 49%. Lack of

senior management support -

32%.

4

Underestimation of complexity

listed as a factor in 35% of

projects

United States

Government

Accountability

Office

Review of federally

funded technology

projects

31 Jul

2008

Study finds 413 of 840 (49%) federally

funded IT projects are either poorly

planned, poorly performing or both.

Information

Systems Audit

and Control

Association

(ISACA)

400 respondents May

2008

Key findings

43% of organizations have

suffered a recent project failure

At a typical enterprise 20% of

technology investments are not

fully realized

Guardian

Newspaper (UK

)

Investigation into

government waste in

the UK since year

2000

5 Jan

2008

Study of government projects

reveals $4billion in wasted efforts

as a result of failed projects

“Only 30% of our projects and

programs are successful” -Joe

Harley, programme and systems

delivery officer at the Department

for Work and Pensions

Dr Dobbs

Journal

586 respondents to

email survey (Dr

Dobbs subscriber list)

Aug

2007

70% of respondents had been

involved in a project they knew

would fail right from the start

Success rates for Agile projects

72%, success rate for traditional

approaches 63%

KPMG - Global

IT Project

Management

Survey

Survey of 600

organizations

globally

2005 In just a 12 month period 49% of

organizations had suffered a

recent project failure

In the same period only 2% of

organizations reported that all of

their projects achieved the desired

benefits

86% of organizations reported a

shortfall of at least 25% of

targeted benefits across their

5

portfolio of projects

Many organizations fail to

measure benefits so they are

unaware of their true status in

terms of benefits realization

The following research findings were listed in the article, Software Project Failure

Costs Billions (2008).

Standish Chaos Reports: Standish reports define success as projects on budget, of

cost, and with expected functionality. Standish findings by year, are shown in table

1.2.

Table 1.2: Summary of Standish chaos reports1994 1996 1998 2000 2002 2004 2009

Succeeded 16% 27% 26% 28% 34% 29% 32%

Failed 31% 40% 28% 23% 15% 18% 24%

Challenged 53% 33% 46% 49% 51% 53% 44%

Mercer Consulting: When the true costs are added up, as many as 80% of

technology projects actually cost more than they return. It is not done intentionally

but the costs are always underestimated and the benefits are always overestimated.

Oxford University: Regarding IT project success reported the following figures.

Successful: 16%

Challenged: 74%

Abandoned: 10%

British Computer Society: In 2004, the UK public sector spent an estimated 12.4

bn. on software and the overall amount spent on IT was about 22.6 Billion British

Pounds. From those projects the success rate was 16%.

6

National Institute of Standards and Technology (NIST): According to NIST

Software defects cost nearly $60 billion, annually

80% of development costs involve identifying and correcting defects

Tata Consultancy: In 2007 Tata consultancy reported that

62% of organizations experienced IT projects that failed to meet their

schedules

49% suffered from budget overruns

47% had higher-than-expected maintenance costs

41% failed to deliver the expected business value and ROI

33% file to perform against expectations

From Bob Lawhorn presentation on software failure (March 2010):

Poorly defined applications (miscommunication between business and IT)

contribute to a 66% project failure rate, costing U.S. businesses at least $30

billion every year (Forrester Research)

60% – 80% of project failures can be attributed directly to poor requirements

gathering, analysis, and management (Meta Group)

50% are rolled back out of production (Gartner)

40% of problems are found by end users (Gartner)

25% – 40% of all spending on projects is wasted as a result of re-work

(Carnegie Mellon)

Up to 80% of budgets are consumed fixing self-inflicted problems (Dynamic

Markets Limited 2007 Study)

Considering all of the research findings above, it is clear that the software project

failure rates are high, globally. Most of the problems have occurred due to poor

quality products, lack of proper leadership, unrealistic estimations etc. Hence it is

reasonable to assume that these problems might have occurred due to incompetency

of the employees i.e. poor quality code could have been a result of software

developed by unskilled software developers, inability to meet deadlines would have

been a result of estimates created by incompetent project leads etc. As mentioned

7

earlier incompetence in an organization’s hierarchy denotes the existence of Peter

Principle effect.

The risks of over promoting and under developing employees lead to many problems

in an organization. One such problem is that, it could lead to the perception that a

culture of incompetence is being fostered, resulting in your competent staff

becoming frustrated and leaving the organization. Problems as such eventually lead

to the downfall of the company. Hence the Peter Principle effect needs to be avoided

in organizations for them to grow and succeed. This research was designed to

identify if Sri Lankan software development firms are victims of this effect and to

develop strategies to avoid it.

1.3 Research Objectives

The research objectives are as follows.

Objective 1:

To identify if the Peter Principle effect exists in Software development firms of Sri Lanka

Objective 2:

To identify and analyze the impact of the determining factors that associate with the existence of Peter Principle effect

Objective 3:

To propose recommendations to help software firms in Sri Lanka to avoid the Peter Principle effect

1.4 Significance of the Study

A decisive success factor for software producers is the quality of their software.

Software systems must meet steadily rising demands regarding stability,

performance, usability and maintainability. Economic indicators such as

development time and costs need to be considered as well. All these together define

high quality software which will define the success of the software development

organization.

8

The human resources are the most important assets of any organization. The success

or failure of an organization is largely dependent on the caliber of the people

working therein. Without positive and creative contributions from people,

organizations cannot progress and prosper. In order to achieve the goals of an

organization, it should have a highly competent workforce and the right people

should be employed in the right jobs. The absence of the above and the presence of

incompetent employees in the wrong jobs denote the existence of Peter Principle

effect. As mentioned earlier, once a company forms a culture of incompetence, only

the incompetent staff will remain, and the competent ones will get frustrated and

leave the company making the company’s growth hinder as they have incompetent

employees at many levels. Hence it is important to avoid this malady to ensure that

the software industry in Sri Lanka grows to its maximum potential.

This study intended to identify, if the Peter Principle effect exists in software

development organizations of Sri Lanka and to provide remedies to avoid it. This

will help software development organizations to properly manage talent and identify

where the promising talent lies, allowing them to plan ahead and nurture staff, so

their personal development is serving organizational development benefiting both

parties.

1.5 Scope of the Research Study

The main focus area of the study was to identify if the Peter Principle effect exists in

software development organizations of Sri Lanka and to recommend a set of

solutions to avoid the effect.

The scope of the research will be limited to software development organizations

within Sri Lanka. The selected software organizations use either tall or flat

organizational structures. The sample of respondents will be selected at random from

the selected organizations. The software development firms selected will be small,

medium or large scale.

The research methodology will be focusing on collecting information from the

employees through online questionnaires. The questionnaires will be targeted

9

towards Software Engineers, Business Systems Analysts, Quality Assurance

Engineers, Team Leads, Project Managers and Architects who are in the middle level

management or the lower levels of the hierarchy so that the sample selected will have

fewer employees who have reached their highest level of incompetence.

1.6 Chapter Outline

The outline of the report is as follows.

Chapter 2, discusses the previous researches carried out on Peter Principle effect by various researchers.

Chapter 3, discusses the design of the study, developing the conceptual model based on the literature that was reviewed in chapter 2, development of hypotheses for the purpose of checking the validity of the relationships of among constructs, data collection methods and operationalization of measurements.

Chapter 4, discusses the data analysis and hypotheses testing carried out. It includes primary and secondary data analysis, reliability and validity testing of the data set, descriptive data analysis, correlation analysis and regression analysis.

Chapter 5, concludes the entire study and discusses the findings of the study and recommends suggestions, guidelines and strategies to avoid the Peter Principle in Sri Lankan IT Firms. The chapter will also highlight limitations of the study and future research opportunities.

10

CHAPTER 2 – LITERATURE REVIEW

2.1 Introduction

This chapter contains a comprehensive analysis on the researches carried out

previously. It is important to understand the viewpoints of the earlier studies to get a

thorough understanding on the research area and ensure that the research covers all

the required areas in the formation of a comprehensive view of the total scenario.

Thus, the literature review would create the foundation of the total study based on the

previous literature and the discussions which have taken place on the topic.

2.2 The Peter Principle

“In a hierarchy every employee tends to rise to his level of incompetence”

(Peter and Hull 1969, p.25)

The above quote was taken from Dr.Laurence J.Peter and Raymond Hull’s

bestselling book: “The Peter Principle – Why things always go wrong?” This sets the

outline for this research.

The Peter Principle theory was introduced by Dr. Laurence J. Peter in the year 1969.

He was a sociologist, who taught at the University of British Columbia before

becoming a professor of education at the University of Southern California (Taylor,

1969). He was an expert in the area of hierarchical incompetence and wrote a couple

of books about this controversial topic. His first book, “The Peter Principle - Why

things always go wrong?” introduced the Peter Principle to the world. He claimed

that in a hierarchy, every employee tends to rise to his level of incompetence (Peter,

1969, p. 25). Additionally, his view was that one will advance to his highest level of

competence and consequently get promoted to a position where he will be

incompetent. The book contains many real-world examples and thought-provoking

explanations of human behavior, including the fact that “Every organization

11

contained a number of persons who could not do their jobs, and that occupational

incompetence is everywhere” (Peter, 1969, p. 20).

It is deciphered in a multifactor framework and is based on a study in which, data in

the form of hundreds of case histories were collected through observing overt

behavior and avoiding introspection or inferences. Peter and Hull(1969) concluded

that an employee’s process of climbing up the hierarchical ladder in an organization

can go on indefinitely until the employee reaches a position where he or she is no

longer competent and is, thus, regarded as incompetent. It states that in time, every

post tends to be occupied by an employee who is incompetent to carry out their

duties and adds that, work is accomplished by those employees who have not yet

reached their level of incompetence.

Why a research is still needed about the Peter Principle, which was developed over

40 years ago? Schapp and Ogulink(2009), in their recent research paper, shows that

the Peter Principle, is still prevalent today and little regarding its presence has

changed since 1969. 73% of the participants in their study had said that they have

seen a Peter Principle situation happen within the last five years.

The ability of an employee is determined not by outsiders, but by his or her superior

in the hierarchy. At that point if the employee has reached his level of incompetence,

the upward process usually stops since the recognized rules of organizations make it

very difficult to demote someone, even if that person would fit in much better in a

lower job. The end result is that most of the higher levels of an organization will be

filled by inept people. For e.g. managers, who got there because they had previously

shown competence in doing a task, different than the new one they are expected to

do.

Essentially, Peter said that as employees move upward through the chain of

command, they do worse, as managers, than they did before having been promoted.

And this phenomenon is not limited in scope. According to Peter and Hull(1972, p.

24) “Sooner or later, this could happen to every employee in every hierarchy

business, industry, trade-unions, politics, government, armed forces, religion, and

education”.

12

Peter and Hull (1969) points out several symptoms to identify the existence of Peter

Principle effect in organizations. These come in the form of behavioral patterns of

incompetent employees or techniques used by organizations to deal with employees,

who have reached their level of incompetence. Some of the important symptoms are

as follows:

2.2.1 Percussive Sublimation

According to Peter and Hull (1969, p.37) this is a pseudo-promotion technique where

an incompetent employee is promoted to a higher position which brings on no new

responsibility, but unclogs the rest of the hierarchy. This is commonly known as

kicking a man upstairs. The objective of Percussive Sublimation usually is to deceive

the outside world. It camouflages the flaws in the employer’s promotion policy,

supports staff morale, and maintains the hierarchy in lieu of firing the incompetent

person which might result in him getting another job with a competitor where,

despite his incompetence, his knowledge could be dangerous.

2.2.2 Lateral Arabesque

Lateral Arabesque is another pseudo-promotion. Without being raised in rank,

sometimes without even a pay raise, the incompetent employee is given a new and

longer title and is moved to an office in a remote part of the building, states Peter and

Hull (1969, p.39). This is similar to Percussive Sublimation where the main objective

is to unclog the hierarchy by removing the incompetent employee, so that the

workflow can run smoothly.

2.2.3 Hierarchical Exfoliation

Peter and Hull (1969, p.45) states that, in most hierarchies, super-competence is

more objectionable than incompetence. Ordinary competence is no cause for

dismissal: it is simply a bar for promotion. On the other hand super-competence

often leads to dismissal as it disrupts the hierarchy. The super-competents, who seem

13

to know everything and do everything well at all levels in anticipation of always

moving up, are more likely to be fired because they disrupt the hierarchy. In Peter's

view, these people attract too much attention to themselves, worrying others in the

organization so much, that they disrupt the super-competent's climb to the top. Hence

super-competent employees often get stuck in their ranks or get dismissed to

preserve the hierarchy.

This phenomenon is often related with negative selection. Negative selection is a

political process that occurs especially in rigid hierarchies, most notably

dictatorships. The person on the top of the hierarchy, wishing to remain in power

forever, chooses his associates with the prime criterion of incompetence – they must

not be competent enough to remove him from power. The associates do the same

with those below them in the hierarchy, and the hierarchy is progressively filled with

more and more incompetent people.

If the dictator sees that he is threatened nonetheless, he will remove those that

threaten him from their positions and emptied positions in the hierarchy are normally

filled with people from those who were less competent than their previous masters.

So, over the course of time, the hierarchy becomes less and less effective. As this

happens relatively often, once the dictator dies, or is removed by some external

influence, what remains is a grossly ineffective hierarchy.

2.2.4 Peter’s Inversion

Peter’s Inversion also known as the professional automaton, is when there are

employees who have little or no capacity for independent judgment but always obey

and never decide. These are the kind of employees who show obsessive concern with

filling out forms correctly permitting no deviations from established routine. To a

person who follows the professional automaton, it is clear that means are more

important than ends; the paperwork is more important than the purpose for which it

was originally designed. He no longer sees himself as existing to serve the public; he

sees the public as the raw material that serves to maintain him, the forms, the rituals,

14

and the hierarchy. Unfortunately for the public, the automaton appears to be

competent from the hierarchy’s point of view. As a result he remains eligible for

promotion until by some mischance he is elevated into a position where he absolutely

has to make a decision. It is at that point that he reaches his level of incompetence,

wrote Peter and Hull (1969, p.41). These people are often managed by incompetent

managers who care about sycophancy, courtesy towards bosses, etc. more than one's

internal efficiency.

2.2.5 Paternal In Step

Paternal In Step is when a family member is promoted several steps above his or her

level of incompetence. According to Peter and Hull (1969, 49-50), this could take

place in two ways: an existing employee may be dismissed or removed by lateral

arabesque or percussive sublimation, to make a place for the in stepper, or a new

position with an impressive title is created for the in-stepper . These techniques may

cause considerable ill-feeling towards the new appointee.

2.2.6 Promotion by Pull and Push

Peter and Hull (1969) suggests two main means by which a person can affect

promotion rate, Pull and Push. Pull is an employee's relationship - by blood,

marriage or acquaintance with a person above the employee in the hierarchy. Push on

the other hand is sometimes manifested by an abnormal interest in study, vocational

training and self-improvement. In small hierarchies, Push may have a marginal effect

in accelerating promotion; in larger hierarchies the effect is minimal. Pull, is

therefore likely to be more effective than push. Peter & Hull (1969, p.63) states

“Never stand when you can sit; never walk when you can ride, never Push when you

can Pull”.

2.2.7 Final Placement Syndrome

According to Peter and Hull (1969, p.108) when an employee reaches his level of

incompetence, he can no longer do any useful work. This was termed as Final

Placement Syndrome by Dr.Peter(1969). He further discusses some symptoms to

identify employees who have reached this state. It is found out that such employees

15

are overly stressed, mentally disturbed and frequently sick (Peter and Hull, 1969,

109-115).

Peter and Hull (1969, 116-127) lists some areas of behavior which identify those

who have reached their highest level of incompetence.

Abnormal Tabulology: This is an important area of hierarchiology. A competent

employee normally keeps on his desk just the books, papers, and apparatus that he

needs for his work. After final placement, an employee is likely to adopt some

unusual and highly significant arrangement of his desk.

Papyromania: This manifestation of final placement causes the employee to clutter

his desk with piles of never used papers and books. Consciously or unconsciously, he

thus tries to look busy and mask his incompetence by giving the impression that he

has too much to do than any human could accomplish.

Fileophilia: Here we see a mania for the precise arrangement and classification of

papers, usually combined with a morbid fear of losing any document. By keeping

himself busy rearranging and re-examining bygone business, the fileophiliac

prevents other people-or himself-from realizing that he is accomplishing little or

nothing of current importance.

Self-pity: One excellent indication of final placement is the telling of chronic hard-

luck stories. It is always the fault of someone outside and beyond the pitier’s control

that makes them incompetent. This self-pity is usually combined with a strong

tendency to reminisce about "the good old days," when the complainant was working

at a lower rank, a level of competence.

Cachinatory Inertia: The habit of telling jokes instead of getting on with business.

Side-Issue Specialization: a commonplace substitute for competence characterized

by the motto: "Look after the molehills and the mountains will look after

themselves."

16

Substitution: Once an employee has reached his level of incompetence, he must

engage in one or more substitutions to keep sane and happy. Otherwise he would

have to face the Sordid Truth, that he is unfit and incompetent to do the job.

Buck passing: Passing the buck is another symptom. It is the act of attributing

another person or group with responsibility for one's own actions

2.2.8 Peter's Corollary

Peter's Corollary states that "in time, every post tends to be occupied by an employee

who is incompetent to carry out their duties" and adds that "work is accomplished by

those employees who have not yet reached their level of incompetence"(Peter and

Hull 1969,p.27). "Managing upward" is the concept of a subordinate finding ways to

subtly manage superiors in order to limit the damage that they end up doing.

Peter (1985, p. 28) wrote in “Why Things Go Wrong or the Peter Principle

Revisited”, that: “I named it The Peter Principle, because it described a

generalization or a tendency and not something inevitable”. The typical

organizational systems encourage individuals to climb to their levels of

incompetence. If you are able to do your job efficiently and with ease, you will be

told that you need to take up more challenges and you will be moved up.

Nevertheless the problem is that when you find something you can’t do very well,

that is where you stay, inept in the job, frustrating your co-workers, and harming the

effectiveness of the organization.

However Peter (1972, p. 35) states that he first wrote about the Peter Principle, he

assumed it applied to all or at least most professions, but he could not be certain.

Although it was impossible for him to study every organization that existed in the

world, the ones he investigated conformed to the principle. Hence further research is

needed to identify if the Peter Principle is prevalent in the IT industry. As IT is a

fairly new industry, minimal research has been done to identify if the Peter Principle

exists in its context.

17

2.3 Peter Principle in Software Development Firms

A software company is made up of employees who either follow the management

track or the technical track. Hence the Peter Principle could affect a software

company mainly in two different ways. The first scenario is when a technical person

gets promoted to a managerial position. For e.g. programmers make up the majority

of the entry level roles in software companies. These people have highly developed

technical skills. A successful programmer will usually, after an appropriate time, be

offered a promotion. That's what tends to happen in a hierarchy, and the prospect of a

career path is what attracts many people to entry-level jobs in these organizations.

Once he becomes a Senior Engineer, he'll be dealing with more challenging projects.

But he'll still be using the same skills, just at a more advanced level. Then, the time

comes for him to be promoted again, and this time he will be made a manager, who

is in charge of a team of programmers. This is where things can start to go wrong.

While his knowledge of the company, its products and its clients mean that he's well

placed to be managing a department, he may not have any of the soft skills needed to

handle people, or liaise with other teams and senior management. His technical

expertise is no longer useful to him. As a result, his performance in this new role

may be poor. If he can't improve his soft skills, he'll never be promoted again. But

because people are rarely demoted in a hierarchy, he'll remain at that level – his level

of "incompetence" – doing a bad job. Not only will this make him unhappy, but the

organization will suffer too. Taken to its extreme, many of the roles in the upper part

of a hierarchical organization may be occupied by people who are not particularly

good at their jobs.

Cline, Lomow and Girou(1998,p.301) states that when exit interviews are reviewed

for technical workers, two troubling facts are noted:

1. Technical workers with the highest appraisal scores tend to leave in the largest

numbers.

2. The most common reason cited for leaving a company is “I don’t like working for

bad management.”

18

The second scenario is when incompetency occurs in technical positions. For e.g.

there may be employees with average technical skills. Once these employees are

promoted to a higher level, say from software engineer to senior software engineer,

they may lack the necessary competence to cope with the new responsibilities

assigned to them. For e.g. a software engineer may not be required to do software

designs, but once he becomes a senior software engineer, his new responsibilities

may require him to do software designing as well. At this point, if the employee is

not good at the task, he may end up designing software that are of very low quality.

This may lead to the Software Peter Principle. According to Cline, Lomow and

Girou(1998,p.47) ,the Software Peter Principle is in operation when unwise

developers improve and generalize the software until they themselves can no longer

understand it, then the project slowly dies. The Software Peter Principle can ruin

projects. The insidious thing about it is that it's a silent killer. By the time the

symptoms are visible, the problem will have spread throughout every line of code in

the project. This principle has been derived from the Peter Principle.

There may be various other instances where incompetence of employees can occur.

But in this research we will focus more on the above mentioned two areas of

incompetence.

2.4 Researches Carried on Peter Principle Effect

A number of researches has been carried out to identify the causes of Peter Principle

Effect and to find a solution to the problem. They are listed down below

chronologically, to highlight development of the thinking of various writers about

this controversial topic from 1969 to date.

Where and by whom, the, know-how of an employee is determined? According to

Peter (1969), employee competence is determined not by outsiders, but by the

employee’s superior in the hierarchy. If the superior is still at a level of competence,

that person may evaluate subordinates in terms of the performance of useful work i.e.

the evaluation of actual output. On the other hand, if the superior has reached a level

of incompetence, that person will probably rate subordinates, in terms of institutional

19

values i.e. the superior will see competence as the actions that support the rules,

rituals, and forms of the organization as they are, as opposed to how they should be.

Peter (1969) concluded from his studies that what appear to be exceptions are not

exceptions at all, because even though employees want to be productive, the Peter

Principle still applies to all employees in, all hierarchies.

Minter (1972) mentioned, as part of the “Peter Principle in Training”, that

individuals who have been in charge of planning and developing training programs

have historically had little or no formal training to prepare them for such a position.

Thus, they usually lack training in educational principles, psychology of learning,

communication and instruction, and in methods of testing and evaluation. As a result,

individuals who have to assume responsibility for planning and training, often learn

by trial-and-error at the expense of both the trainees and the organization.

The author of “CPAs Meet the Peter Principle” (1988) stated and seemed to support

Peter (1969) in that: Everything Dr. Peter predicted in The Peter Principle is coming

home to roost in the field where stability is such a virtue, that nobody ever thought it

would happen. Employees, who are continually promoted because the next slot is

vacant, not necessarily because they are qualified, will eventually be promoted to

their levels of incompetence.

Koontz and Weihrich (1990, p.236) pointed out that errors in the selection process

can lead to actualization of Peter Principle.

Odiorne (1991) pointed out, even though not mentioning anything about the Peter

Principle per se, that people have more talent and intelligence than we often assume.

This researcher also said that employees should be taught the skills and tasks in order

to be knowledgeable, because ongoing training can prevent competence from eroding

and becoming obsolete.

Gately (1996), found that employees can avoid the Peter Principle as long as

employees are judged on technical merit and accomplishment, and that promotions

go to the technically proficient and verbally expressive employees, while the less

technically proficient and verbally expressive wait their turn.

20

Anderson, Dubinsky, and Mehta (1999) wrote that, sales performance is determined

by how well the sales manager can motivate, lead, and control sales-force operations.

But, whether viewed from the perspective of salespeople, customers, sales managers

themselves, or top management, there is concern that sales organizations are not

performing as desired. Their findings support the contention that, sales managers

may well be marketing’s, best example of the Peter Principle: They too have arrived

at their level of organizational incompetence.

Faria (2000) mentioned concern about the role of promotions to manager and its

impacts on the firm behavior, assuming an internal labor market structure. Faria

further stated that a shortcoming of this process is that, people can be placed in

important jobs for which they are ill-qualified. That is, the Peter Principle can be an

outcome of this process, where people are promoted out of jobs for which they are

overqualified until they reach ones, where the job demands are suited to maximum of

individual ability levels. Namely, they are on the edge of their competence, so they

cannot achieve anything more than what they had already achieved.

Fairburn and Malcolmson (2000) have put forward as a basis of argument, that if a

firm provides incentives by promoting those who have performed well in a given job,

it may simply transfer them to another job to which they are not well suited—that is

a mild version of the Peter Principle.

Lazear (2004, p.159), in his theoretical model, which was a review of Peter’s work,

concluded the following from direct Peter Principle research: Workers who are

promoted, receive this treatment because they are observed to have exceeded some

standard. Part of the observation is based on lasting ability, but part is based on

transitory components that may reflect measurement difficulties, short-term luck, or

skills that are job specific. As a result, there is regression to the mean, creating a

Peter Principle effect.Workers who are promoted do not appear to be as able, as they

were before the promotion.

Lazear (2004, p. 159) further deduced the following: Firms take this phenomenon

into account in setting up their promotion rule. Under general conditions, when fewer

than 50% of the workers are better suited to the high level job, the firm adjusts the

21

promotions standard upward to compensate for the regression to the mean. The

amount of the adjustment depends on the tightness of the error distribution. When the

pre-promotion error has high dispersion, promotion standards are inflated by more

than they are when the error dispersion is low.

And finally, Lazear (2004) deduced that all workers who remain at a given level will

be incompetent in that they are neither as good as the average worker coming into the

job nor are they as good as they were in their previous job relative to their

comparison set. Lazear (2004, p. 148) also stated that: “The regression-to-the-mean

phenomenon implies that movie sequels are lower quality than the original films on

which they are based and that excellent restaurant meals are followed by ones that

are closer to mediocre”

King (2004), in the same year, speculated that persons in bureaucratic institutions are

promoted until they reach the level of their incompetence and remain there until they

quit, retire, or rarely, are fired. Furthermore, King stated that this phenomenon does

not occur only in governmental institutions. In many publicly held companies in

corporate America, the exercise of less oversight than is exerted in governmental

agencies lends itself to layers of bureaucracy and incompetence. To a lesser degree,

small businesses are also plagued by this.

Fetzer (2006) mentioned that as people climb up the organizational ladder, they reach

a level within the organization in which, they cannot perform competently, which

leads to a dead-wood supervisor/manager/executive whose position and its duties are

too much for this person to handle well.

In 2007, Chapman affirmed that: For every job in the world, there is someone who

cannot do it.

Newman (2008) cited an affable but invasive regional manager (i.e., M. Scott) as the

type of person who rises just above his abilities and then plateaus at a level of

incompetence. A. Donovan, professor of business ethics at Dartmouth’s Tuck

Business School, posited that: Ninety percent of the population deals with the M.

Scott’s in their daily lives (Newman, 2008, p. 6).

22

According to Schapp & Ogulink(2009, p.2), in their research, Peter Principle, the

phenomenon in which employees around the world, are said to rise to their level of

incompetence, is still prevalent today and that little regarding its use has changed

since 1969. Seventy-three percent of the participants in their study said that, they

have seen a Peter Principle situation happen within the last five years.

Pluchino, Rapisarda and Garofalo(2009) stated that, The Peter Principle would

realistically act in any organization where the mechanism of promotion, rewards the

best members and, where the mechanism at their new level in the hierarchical

structure, does not depend on the competence they had at the previous level, usually

because the tasks of the levels are very different to each other. They show, by means

of agent based simulations, that if the latter two features actually hold in a given

model of an organization with a hierarchical structure, then not only is the Peter

principle unavoidable, but also it yields in turn a significant reduction of the global

efficiency of the organization. Within a game theory-like approach, they explored

different promotion strategies and found, that in order to avoid such an effect the best

ways for improving the efficiency of a given organization are, either to promote each

time an agent at random or to promote randomly the best and the worst members in

terms of competence.

Thus it appears, at least according to the literature review performed in this study that

the Peter Principle is still thriving. It is evident that not much has truly changed in the

many years since Dr. Peter’s study in 1969.

2.5 Summary

This chapter introduces the Peter Principle and goes on to explain its various

characteristics which helps us to identify whether the effect exists in an organization.

It then discusses the possibility of the existence of this effect in software

development organizations. A software company is made up of employees who

either follow the management track or the technical track. The Peter Principle can be

present in two different scenarios. The first scenario is when a technical person gets

promoted to a managerial position and the second scenario is when incompetency

occurs in the technical positions itself. Both of the above should be avoided in a

23

software company for it to succeed. The chapter concludes with a discussion on

studies carried out by previous researchers on the Peter Principle effect.

24

CHAPTER 3 - METHODOLOGY

3.1 Introduction

This chapter discusses the methodology adopted for the study in detail to address the

research problem identified in Chapter 1. The research study carried out was

empirical in nature. An empirical study needs to be supported by theories so that

hypotheses can be generated and a basis can be given for interpreting and

summarizing the research results. Based on the review of the literature in Chapter 2,

this chapter describes the development of the conceptual model and the hypotheses

that guide the rest of the study and presents the methodology used in the study,

specifically in relation to the research design and the data collection process.

3.2 Conceptual Framework of the Study

After formulating the theoretical framework, the researcher has to develop the

conceptual framework of the study. A conceptual framework is described as a set of

broad ideas and principles taken from relevant fields of enquiry and used to structure

a subsequent presentation (Reichel & Ramey, 1987). It has potential usefulness as a

tool to scaffold research and, therefore, to assist a researcher to make meaning of

subsequent findings. Such a framework should be intended as a starting point for

reflection about the research and its context. A theoretical framework or the theory

on which the study is based was identified in Chapter 2. The conceptual framework

introduced in this section will be the operationalization of the identified theory. The

following Figure 3.1 indicates the key concepts associated with the study and their

relationships with each other.

25

Figure 3.1: Conceptual Model

According to the information gathered during the literature review, the above

relationships were derived from various researches carried out in the past.

The theory of Peter Principle and the criteria to identify its existence was introduced

by Peter and Hull (1969). The existence of a relationship between performance and

rewards management practices and Peter Principle was empirically studied by Gately

(1996); Faria (2000); Fairburn and Malcolmson (2000); Lazear (2004); King (2004);

Fetzer (2006); Chapman (2007) and Pluchino,Rapisarda and Garofalo(2009). The

existence of a relationship between selection and recruitment practices, was

described in the works of Koontz and Weihrich (1990). The relationship between

human resource development and Peter Principle was empirically studied by Minter

(1972) and Odiorne (1991). The relationship between the company structure and

Peter Principle was empirically studied by Peter and Hull (1969).

Quality of Performance and Rewards Management Practices

Quality of Selection and Recruitment Practices

Quality of Human Resource Development Practices

Company Structure

Company Size

Existence of

Peter Prinicple related

Behavior Patterns

26

3.3 Research Hypotheses

The hypothesis would indicate the predetermined relationship between the key

variables of the study and this would be based on the literature review ideas and the

understanding of the researcher on the considered subject area (Malhotra, 2007).

Thus, formulating the hypothesis would ensure that the study remains focused, and

on track as the researcher would have to seek to prove whether the hypothesis is

correct or incorrect. Formulating the hypothesis indicates that the researcher has a

preconceived idea and he would gather data and analyze them with the view of either

proving or disproving the hypothesis established. The following Table 3.1 indicates

the hypotheses which the study is seeking to prove.

Table 3.1: Hypothesis statements

Hypothesis

Description

H1 There is a significant relationship between the size of the company and the existence of the Peter Principle effect, where larger firms suffer more from this effect.

H2 There is a significant relationship between the structure of the company and the existence of the Peter Principle effect, where firms with tall structures suffer more from this effect.

H3 The quality of performance and rewards management practices in a company significantly, negatively influence the existence of Peter Principle effect

H4 The quality of recruitment practices in a company significantly, negatively influence the existence of Peter Principle effect

H5 The quality of human resource development practices in a company significantly, negatively influence the existence of Peter Principle effect

3.4 Research Model with Hypotheses

Following is the research model (Figure 3.2) with the introduction of the above

mentioned hypotheses. The graphical representation of the proposed framework

depicts the pattern and structure of relationships among the set of measured

variables. The purpose of the study was to measure relationships among these

variables. This research intended to investigate the existence of the Peter Principle

27

effect in Software Development firms of Sri Lanka, and the relationships between the

existence of the Peter Principle effect and company size, company structure, quality

of performance and rewards management practices, selection and recruitment

practices and human resource development practices.

Figure 3.2: Conceptual Model with Hypotheses

In the investigation, the existence of the Peter Principle effect was taken as the

dependent variable and, company size, company structure, quality of performance

and rewards management practices, quality of selection and recruitment practices and

quality of human resource development practices were taken as independent

variables. This research used a regression study to establish the existence of

relationships between the measured variables. As mentioned earlier the researcher’s

intention was to identify whether any relationships exists between these measured

H5

H4

H3

H2

H1

Existence of

Peter Prinicple related

Behavior Patterns




Company Structure

Company Size

28

variables. Regression study provides a measure of degree between two or more

variables. Therefore, the study was designed as a regression study.

3.5 Operationalization of Variables

This section intends to discuss the operationalization of the constructs identified in

the research model proposed for this study under section 3.4. These constructs must

be operational so as to enable the researcher to measure them. To do so, the abstract

notions of the constructs must be reduced into observable behavior or characteristics

(Sekaran, 2008). Operational definitions provide meaning to the constructs and a

tangible way to measure them.

In addition, constructs in the study uses multi items measures and a five point Likert

type scale. The constructs were adapted from the literature review carried out. The

following sections describe the definitions and item measures of the constructs.

3.5.1 The size of the company

As mentioned in Chapter 1, software development firms of Sri Lanka can be

categorized into three groups by size; small, medium and large. In general the size of

a business has been defined based on the number of employees. This differs from

country to country. More than 500, is generally considered to be a large business.

According to Campbell, (2007) some software organizations, such as Microsoft,

consider a small business as being up to 50 employees. Others consider anything

under 100 employees as a small business, and some consider anything under 500 a

small business. With respect to Sri Lankan software development companies, the

author defined less than 100 employees as small, between 100-300 employees as

medium and more than 300 employees as large size. The intention of the author was

to identify if there is a significant relationship between the size of a company and the

existence of the Peter Principle effect.

3.5.2 The structure of the company

29

Software development firms in Sri Lanka can be categorized as having tall or flat

hierarchies in a broad sense. According to Peter and Hull (1969), the Peter Principle

effect is more prevalent in tall hierarchies. The intention of the author was to identify

if there is a significant relationship between the structure of a company and the


3.5.3 Quality of performance and rewards management practices

Performance and rewards management practices are methods by which the job

performance of an employee is evaluated. It is the process of obtaining, analyzing,

and recording information about the relative worth of an employee to the

organization. It will analyze an employee's recent successes and failures, personal

strengths and weaknesses, and suitability for promotion or further training. The

intention of the author was to identify if there is a significant relationship between

the quality of performance and rewards management practices of a company and the


3.5.4 Quality of Selection and recruitment practices

Selection and recruitment of employees is an important aspect for any company. It

cannot be faulted as the success of any firm depends on the quality of human

resources or talents in that firm. Therefore it is very important for any company to be

very sure of hiring the right staff without compromising anything from the onset. The

intention of the author was to identify if there is a significant relationship between

the quality of selection and recruitment practices of a company and the existence of

the Peter Principle effect.

3.5.5 Human resource development practices

Human Resource Development is the integrated use of training, organization, and

career development efforts to improve individual, group and organizational

effectiveness. It develops the key competencies that enable individuals in

organizations to perform current and future jobs through planned learning activities.

The intention of the author was to identify if there is a significant relationship

30

between the human resource development practices of a company and the existence

of the Peter Principle effect.

The following table 3.2 depicts the operationalization of the identified variables.

31

Table 3.2 : Operationalization of the identified variables

Objectives Variables Indicators Sub Indicators Source-from Level of Measurement

Question Number

To identify if the Peter Principle effect exists in Software development firms of Sri Lanka

Peter Principle related behavior patterns

Percussive Sublimation

Incompetent employees promoted to reduce the harm done by them

(Peter& Hull,1996) Likert 9

Lateral Arabesque Isolating incompetent employees to reduce the harm done by them


Hierarchical Exfoliation

Competent employees are fired to preserve the hierarchy


Peter’s Inversion Existing process consistency is more valued than efficient service


Paternal In Step Employees are placed high up in the hierarchy based on personal relationships


Pull & Promotion Followers of Incompetent superiors get promoted easily


32

Frustration of incompetent employees

Frustration due to incompetence


Buck-Passing Shifting of responsibility or blame to anothers


Substitution of work

Substitute work to competent employees


Final Placement Syndrome

Employees who have achieved their highest level of incompetence

(Peter& Hull,1996) Likert 7,8,18

Work is accomplished by those employees who have not yet reached their level of incompetence

The number of competent employees in the hierarchy and their level of productivity

(Peter& Hull,1996) Likert 21,23

Rate of Incompetence at higher levels

The presence of incompetent employees

The number of incompetent employees in the hierarchy and their level of productivity

(Peter& Hull,1996) Likert 20,22

Dissatisfaction of competent employees

Frustration of competent employees

The turnover rate of competent employees

Author Developed Likert 10

Push & Promotion Competent employees have to push hard for promotions

(Peter& Hull,1996) Likert 15,24,25,26

33

To identify and analyze the impact of the determining factors that associate with the existence of Peter Principle effect

Size of the Organization

Size of the organization has an impact or not on the existence of Peter Principle

- Author Developed Likert 5

Company Structure Structure of the organization has an impact or not on the existence of Peter Principle


Performance & Rewards Management Practices

Having proper performance evaluation methods in place

- (Drucker,1993) Likert 27

Satisfaction of the employees on the performance evaluation method used


Clearly defined job responsibilities

- Author Developed Likert 29,30,31

Rewards based on performance ratings


Selection & Recruitment Practices

Proper job descriptions for job vacancies

- (Yate,1997) Likert 33

Well Structured Interviews that tests all aspects to select the best candidate

- (Yate,1997) Likert 34,36

34

Competent Interviewers


HR Development & Talent Management Practices

Good Training and Development Programs

- (Berger & Berger ,2003)

Likert 37,38,39

Employee Satisfaction towards training programs

- (Berger & Berger ,2003)

Likert 41

Competent Trainers


Demographics Age - - Author Developed Nominal 42Gender - - Author Developed Nominal 43Marital Status - - Author Developed Categorical 44Educational Qualifications

- - Author Developed Categorical 45

Designation - - Author Developed Categorical 2Experience in IT Industry

- - Author Developed Nominal 1

Experience in current company


Experience in current position


35

3.6 Unit of Analysis

As the study intended to investigate the effect of Peter Principle in the Software

Development firms of Sri Lanka, the study would cover a stratified selected sample

from the large, medium and small software development firms in the country.

3.6.1 Target Population

According to Sri Lanka Business Portal - Trade Information (2011), over 50,000 are

employed in the IT and BPO industry in Colombo. Therefore a stratified sampling

technique was used to select the sample. Sampling is the process of selecting a

sufficient number of elements from a population to represent the properties or

characteristics of that population (Sekaran, 2008, 226-227). A sample consisting of

381 employees was calculated as the ideal sample size for the above population. In

determining the sample size, Sekaran (2008, p.294) provided a table that generalized

scientific guideline for sample size decisions. According to the table, for a population

size of 50,000, the appropriate sample size is 381. This was calculated using a

confidence level of 95% and confidence interval of 5.

The sample was selected from the companies listed below in Table 3.3.

Table 3.3: Companies selected for the sample

Company Size (Large : Over 300 Medium:100-300Small : Less than 100)

Year of Establishment

Virtusa Large 1995IFS Large 1997MIT Large 1996Reservations Gateway

Medium 2001

Mubasher Medium 2000Aepona Medium 1999Creative Solutions Medium 1999Eurocenter Medium 2000Ecollege Medium 2004Aeturnum Medium 2001WSO2 Small 2005B Sharp Lanka Small 2003Interblocks Small 2000

36

Sabre Technologies Small 2001EDM Systems Small 1995

The selected sample mostly included employees who are in the lower levels of the

hierarchy and in the middle level management positions such as technical leads,

quality assurance leads, project managers, architects etc. Such employees were

selected as there is a high possibility that they have not reached their level of

incompetence, thus enabling the researcher to obtain more accurate responses.

3.6.2 Data collection instrument

A research survey will be only as good as the questions it asks. Questionnaire design,

therefore, is one of the most critical stages in the research process. According to

Sekaran (2008), a good questionnaire design should focus upon three areas; the

wording of the questions, the principle of measurements, the general appearance of

the questionnaire. Taking the above into consideration a structured questionnaire was

designed in order to collect the required data for the investigation.

The questionnaire was designed only in English language as it was fair to assume

that all employees in software development firms will have the general

understanding of English language.

The questionnaire was made up of two key areas: the core area and the demographics

area. Under demographics, all demographic related information was collected. This

information included the age, gender, duration of work and other personal

information related to the respondent. Even though this information would not have a

direct relevance to the research study, it was used to understand the demographic

profile of the respondents and was used as cross analysis points where further

analysis of the research data was required.

The core area consisted of the questions, which had direct relevance to the key

information areas the study attempted to cover. That is to identify the existence of

Peter Principle effect, and the contribution of the factors listed in section 3.5, to its

existence. All core area questions would take the form of Likert scale based

questions where the respondents could indicate the levels of agreement using a five

37

point Likert scale. According to Sekaran(2008), the advantage of using the Likert

scale is that the respondents would have the freedom to express their views using a

range of alternatives and the response would be focused and easy to directly use for

analysis purposes.

3.6.3 The method of data collection and analysis

The questionnaire was distributed as a web based questionnaire. The researcher was

able to collect a total of 396 valid responses from the survey carried out. The

questionnaire used can be found under Appendix-A.

The responses from the questionnaire were used to study whether the Peter Principle

effect exists in Sri Lankan software development firms and to identify the

contribution of the factors identified in the literature review to its existence.

Proposing recommendations to avoid the Peter Principle, which was the final

objective of this study, was based on the entire output of first and second objectives.

The raw data set that was obtained from the sampled questionnaires was fed in to the

Statistical Package for Social Sciences (SPSS version 15) software and various

statistical analysis methods like, correlation analysis and regression analysis were

carried out.

3.7. Summary

This chapter discusses the methodology adopted for the study. It gives a

comprehensive explanation on the conceptual model that was created and the

hypotheses that the researcher intends to test. It then discusses the operationalization

of the variables identified and the target population selected. It concludes with an

explanation on the data collection and analysis method selected to carry out the

study.

38

CHAPTER 4 – DATA ANALYSIS AND DISCUSSION

4.1 Introduction

This chapter presents the data and a discussion of the findings. The findings

presented under this section are derived from the data gathered from the research

questionnaire. The study was exclusively limited to employees of the software

development firms mentioned in chapter 3. First section of the chapter will highlight

the general information and demographics of the studied sample. In the second

section of the study reliability and the validity analysis of the identified constructs

are discussed. In the next sections of this chapter, descriptive statistics, correlation

analysis will be presented followed by the regression analysis among the constructs

identified.

4.2 Characteristics of the Sample

This section analyzes the general characteristics of the sample in consideration. It is

presented in two sections as characteristics of the organizations and the respondents.

4.2.1 Characteristics of the organizations

The characteristics of the organizations in the sample are given below. In question 5

(Refer Appendix A) the respondents were requested to state the size of their

respective organizations. The summary of the responses to the said question is as

follows. From the total of 396 respondents, 32.8% were from companies had less

than 100 employees, 31.6% were from companies that had employees between 100

and 300 and the remaining 35.6% were from companies that had over 300

employees. The Table 4.1 summarizes the data obtained.

39

Table 4.1: Summary table for number of employees in organizations

Frequency Percent Valid PercentCumulative

PercentLess than 100 130 32.8 32.8 32.8

Between 100 and 300 125 31.6 31.6 64.4

Greater than 300 141 35.6 35.6 100.0

Total 396 100.0 100.0

In question 6 (Refer Appendix A) the respondents were asked about the structure of

their company. The summary of the responses to the said question is as follows.

From the total of 396 respondents, 50.3% mentioned that their company’s hierarchy

is flat and the remaining 49.7% said it was tall. The table 4.2 summarizes the data

obtained.

Table 4.2: Summary table for number of employees in different organization structures


PercentFlat 199 50.3 50.3 50.3

Tall 197 49.7 49.7 100.0

Total 396 100.0 100.0

4.2.2 Characteristics of the respondents

This section presents the key demographic features of the respondents who

participated in the survey.

Age

From the responses given to question 42 (Refer Appendix A), the age distribution of

the respondents is as follows. From the 396 respondents 10.6% were in the age group

below 25, 87.1% were in the age group between 26 and 35. Therefore the majority of

the respondents were in their 20s and 30s. 2% were in the group between 36 and 45

40

and the remaining 0.3% were in the above 45 group. The table 4.3 summarizes the

data obtained.

Table 4.3: Summary table for the age distribution of the respondents


PercentBelow 25 42 10.6 10.6 10.6

Between 25 and 35 345 87.1 31.6 97.7

Between 36 and 45 8 2.0 2.0 99.7

Above 45 1 0.3 0.3 100.0Total 396 100.0 100.0

Gender

Question 43 (Refer Appendix A), inquired about the gender of the respondents. From

the 396 respondents 55.8% were male and 44.2% were female. The table 4.4

summarizes the data obtained.

Table 4.4: Summary table for the gender distribution of the respondents


PercentMale 221 55.8 55.8 55.8

Female 175 44.2 44.2 100.0

Total 396 100.0 100.0

Marital Status

From the responses to the question 43 (Refer Appendix A),, the marital statuses of

the respondents are as follows. From the 396 respondents, 77.8% were single and

22.2% were married. The table 4.5 summarizes the data obtained.

Table 4.5: Summary table for the marital status of the respondents


PercentSingle 308 77.8 77.8 77.8

Married 88 22.2 22.2 100.0

Total 396 100.0 100.0

41

Education Level

Question 44(Refer Appendix A), inquired about the education level of the

respondents. From the 396 respondents, 0.5% had advanced level or below

qualifications. These could probably be trainees who have not yet completed their

degrees. 87.6% had bachelor’s degrees or equivalent. The remaining 11.9% had

postgraduate qualifications. The table 4.6 summarizes the data obtained.

Table 4.6: Summary table for the education level of the respondents


PercentAdvanced Level or below 2 .5 .5 .5

Bachelor's Degree or equivalent 347 87.6 87.6 88.1

Postgraduate Qualifications47 11.9 11.9 100.0

Total 396 100.0 100.0

Current Designation

Question 2 inquired about the current designation of the employees. From the

responses given, 12.4% were in the Trainee Level (e.g. associate software engineers,

associate QA engineers etc), 42.9% were in the intermediate level (e.g. software

engineers, QA engineers, business analysts etc) 31.6% were in the senior level (e.g.

senior software engineers, senior business analysts etc), 8.1% were in the lead level

(e.g. tech leads, QA consultants etc) and the remaining 5.1% (e.g. project managers,

architects etc) were in the managerial level. The designations were split into the

above four broad categories as the main intention of the author was to find the level

of the employee’s position in the hierarchy. The Table 4.7 summarizes the data

obtained.

42

Table 4.7: Summary table for the designation level of the respondents


PercentTrainees/Associate Level 49 12.4 12.4 12.4

Intermediate Level 170 42.9 42.9 55.3

Senior Level 125 31.6 31.6 86.9

Lead Level 32 8.1 8.1 94.9

Managerial Level 20 5.1 5.1 100.0

Total 396 100.0 100.0

Years of experience in IT

The total years of experience of the respondent was inquired by question 1. The

responses are as follows. 11.9% had below 2 years of experience in total, 65.9%

were in the 2-5 years range, 19.7% were in the 5-10 years range and the remaining

2.5% were in the over 10 years range. The table 4.8 summarizes the data obtained.

Table 4.8: Summary table for the years of experience in IT of the respondents


PercentBelow 2 years 47 11.9 11.9 11.9

Between 2-5 years 261 65.9 65.9 77.8

Between 5 -10 years 78 19.7 19.7 97.5

Above 10 years 10 2.5 2.5 100.0Total 396 100.0 100.0

Years of experience in the current company

Question 3 inquired about the years of experience in the current company. The

responses are as follows. 19.7% had below 2 years of experience, 69.9% were in the

2-5 years range, 9.1% were in the 5-10 years range and the remaining 1.3% were in

the over 10 years range. The table 4.9 summarizes the data obtained.

43

Table 4.9: Summary table for the years of experience in the current company of the respondents



Between 2-5 years 277 69.9 69.9 89.6

Between 5 -10 years 36 9.1 9.1 98.7

Above 10 years 5 1.3 1.3 100.0

Total 396 100.0 100.0

Years of experience in the current post

Question 4 inquired about the years of experience in the current post. The responses

are as follows. 61.6% had below 2 years of experience, 36.8% were in the 2-5 years

range, 1.3% were in the 5-10 years range and the remaining 0.3% were in the over 10

years range. The table 4.10 summarizes the data obtained.

Table 4.10: Summary table for the years of experience in the current post of the respondents



Between 2-5 years 146 36.8 36.8 98.4

Between 5 -10 years 5 1.3 1.3 99.7

Above 10 years 1 0.3 0.3 100.0

Total 396 100.0 100.0

4.3 Goodness-of-Fit Measures

Reliability analysis was carried out for all variables in the conceptual framework to

test reliability and the consistency of data. The Cronbach’s alpha indicates how well

the items in a set are positively correlated to one another. The closer the reliability

reaches 1.0, the better the reliability and validity. Generally, reliabilities less than 0.6

are considered poor. Those in the range of 0.7 are acceptable and those over 0.8 good

(Sekaran 2008, p311).

44

Principle component analysis was used to identify the underlying components that

explain the pattern of correlations within a set of observed variables. It is used in data

reduction to identify a small number of factors that explain most of the variance

observed in a much larger number of variables.

The results of the tests carried out and the decisions taken will be discussed in the

following sections.

4.3.1 Reliability and validity analysis - the existence of Peter Principle effect

The results of the reliability analysis carried out on the factors that indicate the

existence of Peter Principle effect are as follows. Refer Appendix A for the

descriptions of the questions.

Table 4.11: Reliability analysis for the factors that determine the existence of Peter Principle effect

Concept/Variable Questions Retained Questions Rejected

Cronbach’s Alpha Value

Peter Principle Behaviors

Q7,Q8,Q9, Q10,Q11,Q12,Q13,Q14, Q15,Q16,Q17,Q18,Q19,Q20,Q22

Q21,Q23,Q24,Q25,Q26

0.96

Q21,Q23,Q24,Q25 and Q26 were very weakly correlated with the rest of the

variables. Hence they were removed .The Cronbach alpha value increased to 0.96

after the removal. (Refer appendix B)

Principle component analysis was carried out to identify the underlying components

(Refer appendix B). The results obtained from the analysis is shown in table 4.12:

45

Table 4.12: Principle component analysis for the factors that determine the existence of Peter Principle effect

Component Initial EigenvaluesExtraction Sums of Squared

LoadingsRotation Sums of Squared

Loadings

Total% of

VarianceCumulative

% Total% of

VarianceCumulative

% Total% of

VarianceCumulative

%1 9.432 62.883 62.883 9.432 62.883 62.883 6.550 43.668 43.6682 1.321 8.805 71.687 1.321 8.805 71.687 4.203 28.019 71.687

3 0.759 5.063 76.750

4 0.589 3.929 80.679

5 0.485 3.235 83.914

6 0.480 3.198 87.113

7 0.390 2.601 89.714

8 0.315 2.100 91.815

9 0.274 1.825 93.640

10 0.247 1.647 95.288

11 0.210 1.399 96.686

12 0.183 1.221 97.907

13 0.136 0.909 98.816

14 0.122 0.816 99.632

15 0.055 0.368 100.000

The analysis showed that there were two components with high factor loadings.

Those two components together explained 71.7% of the variance. The factor loadings

on each of the components are as follows.

Table 4.13: Rotated component matrix for the factors that determine the existence of Peter Principle effect

Component

1 2Q7 0.704 0.471Q8 0.885Q9 0.689 0.436Q10 0.581 0.445Q11 0.781 Q12 0.745 Q13 0.855 Q14 0.630Q15 0.546 0.430Q16 0.831 Q17 0.835 Q18 0.839 Q19 0.731 Q20 0.900Q22 0.880

Thus the variables were split into two groups based on the factor loadings above.

46

Existence of Peter Principle related behavior patterns

Q7,Q9,Q10,Q11,Q12,Q13,Q15,Q16,Q17,Q18 and Q19 loaded heavily on component one. They mainly explained the existence of Peter Principle related behavior patterns.

Existence of incompetent employees in the higher levels of the company hierarchyQ8, Q14, Q20, Q22 loaded highly on component two. These variables explained the existence of incompetent employees in the higher levels of software development firms.

Considering the component breakdown above there was a need to adjust the

initial conceptual framework accordingly. The revised conceptual framework is

shown in Figure 4.1:

Figure 4.1 Revised conceptual model

Existence of Peter Principle related behavior patterns

Existence of incompetent Employees in the higher levels of the company hierarchy




Company Structure

Company Size

H5

H4

H3

H2

H1

47

4.3.2 Reliability and validity analysis - the contributing factors for the existence of Peter Principle effect

The results of the reliability analysis carried out on the contributing factors for the

existence of Peter Principle effect are as follows.

a) Quality of performance and rewards management practices

Table 4.14: Reliability analysis results for quality of performance and rewards management practices related variables

Concept/Variable Questions Retained Questions Rejected Cronbach’s Alpha Value

Evaluation and Rewards Management Practices

Q27, Q28, Q29 , Q30, Q31, Q32

- 0.91

All the variables in concern were highly correlated to each other. Therefore none of

them were rejected. The Cronbach alpha value obtained for the set of variables that

explained the quality of performance and rewards management practices in

companies was 0.91, which is a very high value and it shows that the variables

considered are highly reliable. (Refer appendix B for more details on the analysis)

The principle component analysis gave the following results.

Table 4.15: Principle component analysis results for quality of performance and rewards management practices related variables

Component

Initial Eigen values Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %1 4.209 70.144 70.144 4.209 70.144 70.1442 0.680 11.331 81.4753 0.365 6.090 87.5654 0.301 5.024 92.5895 0.273 4.557 97.1476 0.171 2.853 100.000

48

The analysis showed that there was one component with high factor loadings. It

explained 70.1% of the variance. The factor loadings are as follows:

Table 4.16: Factor loadings for quality of performance and rewards management practices related variables

Component

1Q27 0.832Q28 0.829Q29 0.847Q30 0.871Q31 0.819Q32 0.825

All the factors loaded well on the component. Hence none of the factors were rejected.

b) Quality of recruitment management practices

Table 4.17: Reliability analysis results for quality of recruitment management practices related variables

Concept/Variable Questions Retained Questions Rejected Cronbach’s Alpha Value


Q33, Q34, Q35 , Q36 - 0.88



explained the quality of recruitment practices in companies was 0.88, which is a very

high value and it shows that the variables considered are highly reliable.

49

The principle component analysis gave the following results.

Table 4.18: Principle component analysis results for quality of recruitment management practices related variables

Component


Total % of Variance Cumulative % Total % of Variance Cumulative %1 2.943 73.574 73.574 2.943 73.574 73.5742 .458 11.439 85.0143 .363 9.085 94.0984 .236 5.902 100.000


explained 73.6% of the variance. The factor loadings are as follows.

Table 4.19: Factor loadings for quality of recruitment management practices related variables

Component

1Q33 0.820Q34 0.852Q35 0.889Q36 0.868


c) Quality of human resource development practicesTable 4.20: Reliability analysis results for quality of human resource development practices related variables

Concept/Variable Questions Retained Questions Rejected

Cronbach’s Alpha Value


Q37, Q38, Q39 , Q40, Q41 - 0.92



explained the quality of human resource development practices in companies was

50

0.92, which is a very high value and it shows that the variables considered are highly

reliable.

Principle component analysis results for the above sets of variables are as follows.

Table 4.21: Principle component analysis results for quality of human resource development practices related variables

Component


Total % of Variance Cumulative % Total % of Variance Cumulative %1 3.839 76.789 76.789 3.839 76.789 76.7892 .468 9.363 86.1523 .313 6.256 92.4074 .241 4.829 97.2375 .138 2.763 100.000


explained 76.8% of the variance. The factor loadings are as follows.

Table 4.22: Factor loadings for quality of human resource development practices related variables

Component 1Q37 0.887Q38 0.852Q39 0.837Q40 0.885Q41 0.918


4.4 Descriptive Statistics

Measure of central tendency and dispersions provide a way to have a feel for the

collected data set. Descriptive statistics such as maximum, minimum, means,

standard deviations and variance were obtained for the independent variables that

described the Peter Principle effect and the factors that contributed to its existence.

51

The values mean and standard deviation values obtained are shown in the below

tables. (Refer Appendix B for additional information). It should be noted that all

variables were measured on five point Likert scale ranging from 1-Very Less to 5-

Very High and the total numbers of subjects in the selected sample was 396.

The descriptive statistics obtained for the factors that explain the existence of the

Peter Principle effect are as follows.

Table 4.23: Descriptive statistics for the factors that explain the existence of Peter Principle effect

Question Mean Std. DeviationExistence of previously competent employees who have become incompetent after obtaining promotions (Final placement syndrome) 3.17 1.406

Existence of incompetent employees who could not obtain further promotions (Final placement syndrome) 3.13 0.983

Existence of employees who are promoted to minimize the harm done by them in the current position(Percussive sublimation) 2.76 1.221

The rate of competent employees leaving the organization3.55 1.269

Discouraging innovative ideas and processes to preserve the organization’s existing practices(Peter’s inversion) 3.15 1.396

Highly competent employees being fired to preserve the company’s hierarchy (Hierarchical Exfoliation) 2.61 1.269

Promotions given based on personal relationships(Paternal In Step)3.16 1.496

Followers of superiors getting promoted regardless of their competency level (Pull and Promotion) 3.16 1.350

Competent employees have to push hard to get promoted (Push and Promotion)3.09 1.038

Existence of employees who shift the blame on to others for their actions(Buck Passing) 3.30 1.244

Existence of incompetent superiors who substitute work to the subordinates under them 3.38 1.284

Existence of employees who ignore their duties and focus more on activities that are not direct responsibilities of their position(Final placement syndrome) 3.17 1.311

Existence of employees who are overly stressed, mentally disturbed and frequently sick even though they do not do a lot of productive work. (Final placement syndrome)

2.96 1.052

The number of incompetent employees in the higher levels of organizations3.07 1.000

The productivity of the employees in the higher levels of the organization hierarchies 3.09 0.957

52

The mean values obtained above are in the range of 2.61 – 3.55. This implies that the

Peter Principle moderately exists in the software development firms of Sri Lanka.

Hierarchal exfoliation and percussive sublimation has a lesser value compared to the

other factors but it doesn’t imply that those behaviors are nonexistent. The lesser

value maybe due to the fact that, it is not ethical to carry out the above activities or

maybe because the employees who come under those categories resign prior to the

occurrence of the above.

The descriptive statistics obtained for the factors that explain the perspective of the

employees of the quality of the performance and rewards management practices in

their respective organizations are as follows.

Table 4.24: Descriptive statistics for the factors that explain the quality of performance and rewards management practices

Question Mean Std. DeviationThe organization has a standard way of evaluating employee performance

3.02 1.058

Employee satisfaction with the current performance evaluation methods in the organization 2.75 0.950

The organization maintains proper job descriptions for all positions2.88 1.051

The organization clearly communicates job responsibilities to the employees3.06 1.062

The work performed by the employees match their job descriptions3.03 1.027

The organization provides rewards/promotions solely based on performance ratings2.97 1.030


quality of performance evaluation and rewards management practices in

organizations are in a moderate level and improvement is needed for the

organizations to reach their maximum potential.


employees of the quality of recruitment and selection practices in their respective

organizations are as follows.

53

Table 4.25: Descriptive statistics for the factors that explain the quality of selection and recruitment practices

Mea

nStd.

DeviationThe organization provides comprehensive job descriptions when advertising jobs

3.07 0.966

Selection interviews are well structured to identify the best candidates3.02 1.035

Members of the selection panel are competent and properly trained3.01 1.010

The organization gives due attention to skills like teamwork, leadership, attitude etc when selecting a new employee 3.10 1.018


quality of selection and recruitment practices in organizations are in a moderate level

and improvement is needed for the organizations to reach their maximum potential.


employees of the quality of human resource development practices in their respective

organizations are as follows.

Table 4.26: Descriptive statistics for the factors that explain the quality of human resource development practices

Question Mean Std. DeviationThe organization provides job related trainings for all employees on technical matters 3.01 1.119

The organization provides training on soft skills2.86 1.090

The organization has a well defined HR development /talent management process to achieve organizational goals 2.72 1.054

The trainers in the organization are highly competent2.96 1.058

The employees are satisfied with the training they receive2.89 1.016


quality of human resource development practices in organizations is in a moderate

level and improvement is needed for the organizations to reach their maximum

potential.

54

4.5 Correlation Analysis

Correlation analysis was performed on the two dependent and five independent

variables identified during the conceptual model.

The two dependent variables are

The existence of Peter Principle related behavior patterns (AvPPB)

The existence of incompetent employees in the higher levels of the company hierarchy (AvIEHL)

The five independent variables are:

The size of the company(Q5)

The structure of the company(Q6)

The quality of performance and rewards management practices in a

company(AvPRM)

The quality of recruitment practices in a company(AvRP)

The quality of human resource development practices in a company(AvHRD)

The correlation analysis results for the above are shown in the below table

followed by the interpretation of the results.

55

Table 4.27: Correlation analysis results

AvPRM AvRP AvHRD AvPPB AvIEHL Q5 Q6AvPRM

1 0.811** 0.794** -0.721** -0.495** 0.059 -0.436**

AvRP

0.811** 1 0.739** -0.691** -0.508** 0.066 -0.453**

AvHRD

0.794** 0.739** 1 -0.587** -0.381** 0.147** -0.332**

AvPPB

-0.721** -0.691** -0.587** 1 0.719** -0.019 0.564**

AvIEHL

-0.495** -0.508** -0.381** 0.719** 1 -0.048 0.416**

Q5

0.059 0.066 0.147** -0.019 -0.048 1 0.077

Q6

-0.436** -0.453** -0.332** 0.564** 0.416** 0.077 1

According to the results shown in table 4.26, the following were identified:

The significant value of the correlation between the size of a company(Q5)

and the existence of Peter Principle related behavior patterns(AvPPB) is

0.711, which is greater than 0.05. Hence we can conclude that there is no

significant correlation between the two factors in consideration.

The significant value of the correlation between the size of a company(Q5)

and the existence of incompetent employees in the higher levels of the

company hierarchy(AvIEHL) is 0.344, which is greater than 0.05. Hence we

can conclude that there is no significant correlation between the two factors

in consideration.

56

The significant value of the correlation between the structure of a

company(Q6) and the existence of Peter Principle related behavior

patterns(AvPPB) is 0.001, which is less than 0.05. Further the Pearson

correlation coefficient for above-mentioned relationship is 0.564. Hence we

can conclude that there is a strong significant positive correlation between the

two factors in consideration.

The significant value of the correlation between the structure of a

company(Q6) and the existence of incompetent employees in the higher

levels of the company hierarchy(AvIEHL) is 0.001, which is less than 0.05.

Further the Pearson correlation coefficient for above-mentioned relationship

is 0.416. Hence we can conclude that there is a significant positive correlation

between the two factors in consideration.

The significant value of the correlation between the quality of performance

and rewards management practices (AvPRM) of a company and the existence

of Peter Principle related behavior patterns (AvPPB) is 0.001, which is less

than 0.05. Further the Pearson correlation coefficient for above-mentioned

relationship is -0.721. Hence we can conclude that there is a strong

significant negative correlation between the two factors in consideration.

The significant value of the correlation between the quality of performance

and rewards management practices of a company (AvPRM) and the existence

of incompetent employees in the higher levels of the company hierarchy

(AvIEHL) is 0.001, which is less than 0.05. Further the Pearson correlation

coefficient for above mentioned relationship is -0.495. Hence we can

conclude that there is a significant negative correlation between the two

factors in consideration.

The significant value of the correlation between the quality of recruitment

practices (AvRP) of a company and the existence of Peter Principle related

behavior patterns (AvPPB) is 0.001, which is less than 0.05. Further the

57

Pearson correlation coefficient for above-mentioned relationship is -0.691.

Hence we can conclude that there is a strong significant negative correlation

between the two factors in consideration.

The significant value of the correlation between the quality of recruitment

practices of a company (AvRP) and the existence of incompetent employees

in the higher levels of the company hierarchy (AvIEHL) is 0.001, which is

less than 0.05. Further the Pearson correlation coefficient for above-

mentioned relationship is -0.508. Hence we can conclude that there is a

strong significant negative correlation between the two factors in

consideration.

The significant value of the correlation between the human resource

development practices of a company (AvHRD) and the existence of Peter

Principle related behavior patterns (AvPPB) is 0.001, which is less than 0.05.

Further the Pearson correlation coefficient for above mentioned relationship

is -0.587. Hence we can conclude that there is a strong significant negative

correlation between the two factors in consideration.

The significant value of the correlation between the human resource

development practices of a company (AvHRD) and the existence of

incompetent employees in the higher levels of the company hierarchy

(AvIEHL) is 0.001, which is less than 0.05. Further the Pearson correlation

coefficient for above-mentioned relationship is -0.381. Hence we can

conclude that there is a significant negative relationship between the two

factors in consideration.

58

4.6 Multiple Regression Analysis

Correlation coefficient r indicates the strength of the relationship between two

variables, but it does not give an idea of how much of the variance in the dependent

variable will be explained, when several independent variables simultaneously

influence it. Multiple regression analysis is used to analyze such situations (Sekaran

2008, p405).

Multiple regression analysis was used in this study to analyze the relationships when

all independent variables simultaneously influence the dependent variable. It is

conducted to examine how well those independent variables predict the dependent

variable when taken as a model. As two components were identified as the

determining factors of Peter Principle during section 4.3.1, multiple regression

analysis was performed for each dependent variable.

Multiple regression analysis results for the dependent variable “existence of Peter

Principle related behavior patterns” and the independent variables “size of the

company” , “structure of the company”, “quality of performance and rewards

management practices in a company” , “quality of recruitment practices in a

company” and quality of “human resource development practices in a company” ,

are given below.

Table 4.28: Model summary for the existence of Peter Principle related behavior patterns and the contributing factors

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate1 0.784(a) 0.614 0.609 0.65614

a Predictors: (Constant), Q6, Q5, AvHRD, AvRP, AvPRM

Q5 - The size of the companyQ6 - The structure of the companyAvHRD - The quality of performance and rewards management practices in a companyAvRP - The quality of recruitment practices in a companyAvPRM - The quality of human resource development practices in a company

59

Table 4.29: ANOVA table for existence of Peter Principle related behavior patterns and the contributing factors

Model Sum of Squares df Mean Square F Sig.

1 Regression 267.197 5 53.439 124.127 .000(a)

Residual 167.904 390 .431

Total 435.101 395

a Predictors: (Constant), Q6, Q5, AvHRD, AvRP, AvPRMb Dependent Variable: AvPPB

Q5 - The size of the companyQ6 - The structure of the companyAvHRD - The quality of performance and rewards management practices in a companyAvRP - The quality of recruitment practices in a companyAvPRM - The quality of human resource development practices in a companyAvPPB - The existence of Peter Principle related behavior patterns

Table 4.30: Coefficients for existence of Peter Principle related behavior patterns and the contributing factors

Model

Unstandardized Coefficients

Standardized Coefficients t Sig.

B Std. Error Beta B Std. Error1 (Constant) 5.163 .172 29.973 .000

AvPRM -.508 .076 -.417 -6.651 .000

AvRP -.284 .069 -.234 -4.101 .000

AvHRD .011 .061 .010 .181 .856

Q5 -.002 .041 -.001 -.041 .967

Q6 .586 .075 .280 7.781 .000

a Dependent Variable: AvPPB

AvPPB - The existence of Peter Principle related behavior patterns

The model summary table 4.27 above provides the R and R2 values for the

relationships between the said dependent and independent variables. R or the

correlation coefficient indicates the strength of the relationship. In this case the R-

value indicates multiple R, which is the correlation of all the independent variables

against dependent variable, which is 0.784. This is quite a high value and it confirms

there is a strong relationship between the variables. The value of the R2 gives the

amount of variance explained by these models. In this case the R2 value is 0.614

which means the independent variables together (the model) explain 61.4% of the

variance in the existence of Peter Principle related behavior patterns. Hence we can

60

conclude that the independent variables considered largely define why the Peter

Principle effect exists.

The Coefficients table 4.29 shows Beta values for all the independent variables when

they are regressed jointly against dependent variables. The independent variables,

“quality of performance and rewards management practices”, “quality of selection

and recruitment practices” have negative Beta values. Therefore it shows a negative

relationship towards the dependent variables. The results imply that an increase in

the above two independent variables will inherently decrease the dependent variable.

Even though the independent variable quality of human resource development

practices had a significant correlation when correlated individually with the

dependent variable, it proves to be insignificant when jointly regressed with the other

independent variables. The size of the company proves to be insignificant. Hence

there is no relationship between the size of a company and the existence of Peter

Principle effect related behaviors patterns. The structure of a company has a

significant relationship and the Peter Principle effect related behavior patterns seems

to be high in companies that have tall structures.

Multiple regression analysis results for the dependent variable “existence of

incompetent employees in the higher levels of the company hierarchy” and the

independent variables “size of the company”, “structure of the company”, “quality of

performance and rewards management practices in a company”, “quality of

recruitment practices in a company” and “quality of human resource development

practices in a company”, are given below.

Table 4.31: Model Summary for the existence of incompetent employees in the higher levels of the hierarchy and the contributing factors

R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .566(a) .320 .311 .78509

a Predictors: (Constant), Q6, Q5, AvHRD, AvRP, AvPRM

Q5 - The size of the companyQ6 - The structure of the companyAvHRD - The quality of performance and rewards management practices in a companyAvRP - The quality of recruitment practices in a companyAvPRM - The quality of human resource development practices in a company

61

Table 4.32: ANOVA table for the existence of incompetent employees in the higher levels of the hierarchy and the contributing factors

Model Sum of Squares df Mean Square F Sig.

1 Regression 113.120 5 22.624 36.705 .000(a)

Residual 240.385 390 .616

Total 353.506 395

a Predictors: (Constant), Q6, Q5, AvHRD, AvRP, AvPRMb Dependent Variable: AvIEHL

Q5 - The size of the companyQ6 - The structure of the companyAvHRD - The quality of performance and rewards management practices in a companyAvRP - The quality of recruitment practices in a companyAvPRM - The quality of human resource development practices in a companyAvIEHL - The existence of incompetent employees in the higher levels of the company hierarchy

Table 4.33: Coefficients for the existence of incompetent employees in the higher

levels of the hierarchy and the contributing factors

Model

Unstandardized Coefficients

Standardized Coefficients t Sig.

B Std. Error Beta B Std. Error1 (Constant) 4.464 .206 21.657 .000

AvPRM -.283 .091 -.258 -3.098 .002

AvRP -.304 .083 -.278 -3.669 .000

AvHRD .109 .073 .108 1.488 .138

Q5 -.053 .049 -.046 -1.088 .277

Q6 .409 .090 .217 4.543 .000

a Dependent Variable: AvIEHL

AvIEHL - The existence of incompetent employees in the higher levels of the company hierarchy

In this case the R-value, is 0.566. This is quite a high value and it confirms there is a

strong relationship between the variables. The R2 value is 0.320 which means the

independent variables together explains only 32% of the variance as to why there are

incompetent employees in higher levels of the hierarchy. This could be due to the

reason that there may be more reasons why incompetent employees exist in the

higher levels of the hierarchy than the ones considered here.

The Coefficients tables show Beta values for all the independent variables when they

are regressed jointly against dependent variables. The independent variables, “quality

62

of performance and rewards management practices”, “quality of selection and

recruitment practices” have negative Beta values in this case too. Therefore it shows

a negative relationship towards the dependent variable. The results imply that an

increase in the above two independent variables, will inherently decrease the

dependent variable. Even though the independent variable “quality of human

resource development practices” had a significant correlation when correlated

individually with the dependent variable, it proves to be insignificant when jointly

regressed with the other independent variables. The size of the company proves to be

insignificant. Hence there is no relationship between the size of a company and the

existence of incompetent employees in the higher levels of the company hierarchy.

The structure of a company has a significant relationship and incompetent employees

in the higher levels of the company hierarchy seem to be high in companies that have

tall structures.

The software development companies considered for the study were divided into two

main groups considering the structure of the company as “Tall” or “Flat” in a broad

sense. As the data collected for this aspect is categorical in nature, the Independent

sample’s T-Test was used to test the relationship between the structure of a company

and the existence of the Peter Principle effect. The results obtained from the test are

as follows.

Table 4.34: Group Statistics for structure of the company

Q6 N Mean Std. DeviationStd. Error

MeanAvPPB Flat 199 2.5313 .72411 .05133

Tall 197 3.7134 .99216 .07069AvIEHL Flat 199 2.7224 .81448 .05774

Tall 197 3.5076 .90665 .06460



According to the results obtained, it can be seen that the mean values obtained for

existence of the Peter Principle related behavior patterns and incompetent employees

63

in higher levels of the hierarchy is comparatively less for companies with flat

hierarchies.

Table 4.35: Independent Sample Test for structure of the companyIndependent Samples Test

30.858 .000 -13.553 394 .000 -1.18214 .08722 -1.35362 -1.01065

-13.532 358.522 .000 -1.18214 .08736 -1.35394 -1.01033

6.416 .012 -9.068 394 .000 -.78525 .08659 -.95549 -.61501

-9.064 388.691 .000 -.78525 .08664 -.95559 -.61491

Equal variancesassumed

Equal variancesnot assumed

Equal variancesassumed

Equal variancesnot assumed

AvPPB

AvIEHL

F Sig.

Levene's Test forEquality of Variances

t df Sig. (2-tailed)Mean

DifferenceStd. ErrorDifference Lower Upper

95% ConfidenceInterval of the

Difference

t-test for Equality of Means



According to table above the significant value of the relationships are less than 0.05.

Therefore the relationships are significant. Hence we can conclude that there is a

significant relationship between the structure of the company and the existence of the

Peter Principle effect. The tall organization structures seem to be affected more

according to the results obtained above.

Hence we can conclude the hypothesis statements generated in Chapter 3 as follows.

There is no significant relationship between size of a company and the

existence of Peter Principle effect. Therefore the alternative hypothesis was

rejected with a 95% confidence level.

There is a significant relationship between the structure of a company and the

existence of Peter Principle effect. Organizations with tall structures suffered

more from the Peter Principle effect. Therefore the alternative hypothesis was

accepted with a 95% confidence level.

64

There is a significant negative relationship between the quality of

performance and rewards management practices in a company and the

existence of Peter Principle effect. Therefore the alternative hypothesis was

accepted with a 95% confidence level.

There is a significant negative relationship between the quality of selection

and recruitment practices in a company and the existence of Peter Principle

effect. Therefore the alternative hypothesis was accepted with a 95%

confidence level.

There is no significant relationship between human resource development

practices in a company and the existence of Peter Principle effect. Therefore

the alternative hypothesis was rejected with a 95% confidence level.

4.7 Summary

This chapter presented the data gathered through the empirical study conducted using

employees working in software development organizations in Sri Lanka. Data

collection methods, which were employed for this study, were discussed in detail,

supported by the figures of the collected data. The chapter started with a description

of the general information and demographics of the respondents. It then went on to

check the validity of the data through reliability and validity analysis. Descriptive

statistics were provided for the constructs identified. Inferential analysis techniques

such as correlation analysis and multiple regression analysis were used to analyze the

data set and test the hypotheses. The chapter concluded with the hypothesis test

results.

65

CHAPTER 5 – CONCLUSIONS AND RECCOMENDATIONS

5.1 Introduction

The following sections of the final chapter would discuss conclusions derived from

the data analysis while interpreting data analysis results in detail and the next section

will provide the recommendations. Then, it would analyze the limitations of this

study and highlight the guidelines for the future research.

5.2 Conclusions

The purpose of this research was to identify if the Peter Principle effect exists in

software development firms of Sri Lanka and to analyze the determining factors that

associate with the existence of Peter Principle effect. After identifying the research

problem, three research objectives were formed with five hypotheses. A stratified

random sample size of 396 was derived from the population which consisted of

employees from software development firms of Sri Lanka. A conceptual framework

was designed after in depth literature review. The required data was collected with

the use of an online questionnaire and the data analysis was carried out in an orderly

manner as illustrated in chapter 4.

The first objective of the study was to identify if the Peter Principle effect exists in

the software development companies of Sri Lanka. With the knowledge gained from

the in-depth literature review carried out, the researcher was able to identify the

characteristics that indicate that the Peter Principle effect exists in a company. The

descriptive statistics obtained for the areas that tested whether these characteristics

were present in the software development organizations of Sri Lanka confirmed that

the effect was present in a moderate level. Hence, objective one; was successfully

achieved by proving that the Peter Principle effect is prevalent in the software

development companies of Sri Lanka.

The second objective of the study was to identify and analyze the determining factors

that associated with the existence of the Peter Principle effect. These factors were

66

identified in the literature review and they were studied thoroughly using the survey

data to identify their contribution to the existence of the Peter Principle effect. Five

hypotheses were formed to identify if there was a relationship between the size,

structure, quality of performance and rewards management practices, quality of

selection and recruitment practices and quality of human resource development

practices in an organization and the existence of Peter Principle effect. According to

the results obtained under the data analysis chapter, there are strong significant

relationships between the structure, quality of performance and rewards management

practices, selection and recruitment practices and the existence of Peter Principle

effect. The size of a company did not have a significant relationship with the

existence of the Peter Principle effect. This implies that the Peter Principle effect can

exist in any company regardless of its size. Also the quality of human resource

development practices of a company did not have a significant relationship with the

existence of the Peter Principle effect. This could be due the fact that once an

employee reaches his ultimate level of incompetency, it is hard to improve his

productivity by providing training as he is not suitable for the job. Hence whatever

training that is provided should be provided before an employee reaches his level of

incompetency.The third objective was to propose recommendations to help software

development companies in Sri Lanka to avoid the Peter Principle effect. This has

been achieved by the recommendations provided in the section 5.3 of the

dissertation.At the end of the study the researcher was able to achieve all the

objectives stated in chapter one. Hence we can conclude that the study was

successful.Recommendations and Managerial Implications

Based on the views provided by the industry professionals, findings gathered from

the study and the literature found on the study, this section would propose

recommendations that software development firms can adopt to avoid the Peter

Principle effect.

Opting for flatter hierarchies

As mentioned by Peter and Hull (1969), the Peter Principle is most prevalent in

organizations that have tall hierarchical structures. This was confirmed further by the

67

results obtained from the analysis as the Peter Principle effect was less prevalent in

flatter organizations. Therefore opting for flatter hierarchical structures seems to help

software companies avoid the Peter Principle effect to some extent.

Higher pay without promotions

Employees often accept a promotion, not for the power and prestige, but the

increased pay attached to it. If software companies are willing to offer large pay

increases for excellent work within the same position, the Peter Principle would be

avoided, and the employee could make more money while staying in the position he

enjoys and in which he's competent. It is pretty much easy to carry this concept in

flatter hierarchies.

Clear division of managerial and technical career paths

Software development organizations should offer enough opportunities in

management as well as technical tracks. The skills needed to succeed and measures

of success for each track are very different and sometimes unclear. To succeed in

management track, one needs to be good at dealing with ambiguities, taking

decisions based on partial data, and be able to deal to managing regular management

challenges; measure of success most of the time could be very indirect. It could

mostly be through the success of the team members or the success of a project

assigned etc and hence can be very subjective and debatable. To succeed in the

technical track, one needs to have deep technical and domain expertise, should be

good at solving complex technical problems, and be able to provide technical and

thought leadership; measure of success is very direct and objective and mostly based

on visible results of the individual. Software development firms should identify their

employees’ competencies, guide and groom them to reach their maximum potential

in the right track so that their personal development is serving organizational

development benefiting both parties.

Demotion and Dismissal

68

Although not ethical, perhaps a good way to address the Peter Principle in an

organization would be to institute a policy of demoting employees to their most

appropriate level of work competence. If an employee isn't working out in a higher

position, allowing him to go back to whatever position he excelled in would avoid

the effects of the principle. This would, however, require the supervisor who made

the poor promotion decision to admit he made a mistake, an act not often found in

the higher levels of a hierarchy. Werhane, Radin and Bowie (2003, p.69) stated that,

in dismissing or demoting employees, the employer is not denying rights to persons;

rather, the employer is simply excluding that person's labor from the organization.

This is quite a justifiable reason to demote or dismiss an employee who is not

performing well. From the employer’s side, demotion or dismissal will be reducing

the harm done by that employee to the organization and from the employee’s side he

will get freed from a job that he is neither enjoys nor good at.

Recruiting employees on contract basis

Another solution to the Peter Principle effect is to recruit employees on contract

basis. If the employee doesn’t perform well, the employer has the right to not extend

his contract period and the employee will have to leave the organization once his

contract is over. This will avoid the problems that can arise from demotion and

dismissal as such actions are seen as unethical in the eyes of the employees and it

could harm the good name of the company.

Playing the job role prior to the promotion

Allowing the employee to play the next designation role prior to giving the

promotion will also help avoid the Peter Principle effect. This way the employer will

be able to evaluate whether the employee can do a good job if he was provided the

designation. The promotion can be given based on the performance of the employee

in the given role. If he performs well he will be eligible for the next promotion, if not

he will have to remain in his current position till he performs well enough to carry

out the responsibilities of a designation at the next level.

Improve selection and recruitment practices

69

It is important to always provide proper job descriptions when advertising to avoid

attracting employees who are not suitable for the job. Also companies should ensure

that they have a competent, properly trained selection panel to interview and select

the best candidates. Incompetent interviewers might end up selecting employees who

are far worse than them resulting in an increase in the Peter Principle effect. Also the

organization should have a standardize procedure of recruiting employees.

According to Carpers (2009, p.50), what seem to give the best results are multiple

interviews combined with a startup evaluation period of perhaps six months.

Successful performance during the evaluation period is a requirement for joining the

organization on a full-time regular basis.

Improve performance and rewards management practices

Proper performance and rewards management mechanisms should be put into

practice. Standardized mechanisms like Management by Objectives (MBO),

Balanced Score Cards can be used for proper performance evaluation depending on

the objectives defined by the organization.

According to Gately (1996) employers can avoid the Peter Principle as long as

employees are judged on technical merit and accomplishment, and promotions are

given to the technically proficient and verbally expressive employees, while the less

technically proficient and verbally expressive wait their turn.

Provide proper trainings and improve human resource development practices

According to the analysis done, it was identified that the quality of human resource

development practices in an organization was insignificant when taken as a model

with the other constructs. This could be because when an employee reaches his

maximum level of incompetence, no amount of training can fix his state.

Nevertheless providing proper training while the person is competent might reduce

the chance of him becoming an incompetent employee. Also it will help him identify

his strengths and weaknesses and help him identify what he is most talented in doing.

70

Odiorne (1991) stated, that employees should be taught the skills and tasks in order

to be knowledgeable because ongoing training can prevent competence from eroding

and becoming obsolete.

Outsource performance appraisals

According to “How to get human resources careers” article, Performance appraisals

may be carried out by the company’s human resources department, or it may also be

outsourced. Outsourcing and getting the appraisals done by an independent third

party will help an organization get unbiased and reliable performance evaluations on

their employees.

Recruitment process outsourcing

Recruitment Process Outsourcing (RPO) is an outsourcing arrangement whereby an

external provider takes over part or all of the recruitment functionalities of an

organization. The RPO provider assumes responsibility over the hiring process, from

job profiling through on boarding, as well as the resources, methodologies and

reporting used. With effective implementation RPO can reduce a company’s time to

hire and associated costs, increase the quality of candidate pool and ensure regulatory

compliance. According to Nelson and Gerard (2005), RPO offers companies a

proven way to attract the best talent and, ultimately, ensure the highest possible level

of customer satisfaction.

71

5.3 Limitations of the Study

Every research conducted has limitations of its own nature because of resource

limitations, time considerations and many more. This study also has certain

limitations of its own. Firstly, the research was limited to employees from the

selected organizations. Software organizations can be either product based or project

based. This was not considered when selecting the sample. There is a chance that the

existence of the Peter Principle effect could differ according to the nature of work

carried out. This was not properly captured in the collected sample as it did not have

equal number of respondents from project based and product based software

companies. This was a limitation.

The population of IT professionals in Sri Lanka is high. A proper census could not be

done and only a rough estimate was available regarding the number of IT

professionals. When a convenience based sample is selected to collect responses,

there is a chance that there may be biased results than expected. If a random sample

was selected, the results would have been more accurate.

Data gathering limitations should also be considered. As mentioned in chapter 3 data

was gathered using an online survey. The correctness of gathered data and whether

the respondents provided their actual impressions or manipulative responses was a

major concern.

As mentioned above, there were many limitations in this study and author did his

best to make this study successful with those limitations.

5.4 Directions for Future Research

This study was primarily concerned with identifying whether the Peter Principle

effect existed in software development firms of Sri Lanka. This was successfully

achieved and it was identified that the effect exists. If the limitations identified in the

previous section can be overcome, the study can be further extended and the results

will be more accurate.

72

While studying the factors that determine the existence of the Peter Principle effect

only five factors (the size of the company , the structure of the company, the quality

of performance and rewards management practices, the quality of recruitment and

selection practices and the quality of human resource development practices) were

taken into consideration. Further research should be carried out to identify what other

factors have an influence on the existence of this effect. Further the researcher only

checked whether the there were significant relationships between the factors and the

Peter Principle effect in a broad manner. Each of these factors should be broken

down into smaller and more specific sections and analyzed. For e.g. we could carry

out a thorough search on which kind of performance evaluation mechanisms best

reduce the existence of the Peter Principle effect.

Research could be carried out to identify various human resource development

practices that can help prevent competence from eroding and becoming obsolete.

This way we would be able to identify ways to reduce the Peter Principle effect.

The psychological factors associated with Peter Principle effect can be studied. That

is research should be carried out to identify why employees are eager to accept

promotions even when they know they would be happier doing something else in a

lower level in the hierarchy.

Various organization structures like tall, flat, hybrid etc can be studied to identify the

best organization structure that suits software development firms to minimize the

Peter Principle effect from occurring.

Studies can be carried out on selection and recruitment practices and the skills of an

employee that should be tested to select the best talent so that in the long run, the

company will have less Peter Principled employees.

Problems faced by the HR department when dealing with incompetent employees

should be analyzed to identify proper remedies to minimize the harm done to the

organization by employees who have reached their level of incompetence.

73

Software development firms will have employees working in many areas. It could be

software engineering, quality assurance, business analysis, project management etc.

In each of these areas there could be different reasons as to why the Peter Principle

effect occurs. Studies should be carried out to identify these reasons and to provide

solutions to prevent them.

5.5 Summary

This chapter discussed the interpretation of results obtained from the data analysis

and provided the recommendations based on the findings throughout this study.

Further, it concluded the entire study by exploring pathways for future studies while

explaining the limitations of the completed study.

74

REFERENCES

Anderson, R. E., Dubinsky, A. J., & Mehta, R. (1999, January-February). Sales

managers: Marketing’s best example of the Peter Principle. Business Horizons,

42(1), 19-26.

Anonymous. (1988, July). CPAs meet the Peter Principle. Management Review,

77(7), 9-10.

BUDMAN.Can we turn back the tide of incompetence? The Conference Board

http://www.theage.com.au/ed_docs/incompetence.pdf [accessed April 28, 2011]

Berger,Lance A. and Berger,Dorothy R.(2003),The Talent Management Handbook:

Creating Organizational Excellence by Identifying, Developing, and Promoting Your

Best People.New York:McGraw-Hill

Better Estimation & Planning Can Help : Project Planning & Estimation. [ONLINE] Available at: http://www.galorath.com/wp/software-project-failure-costs-billions-better-estimation-planning-can-help.php. [Accessed 13 November 2011].

Campbell, A.2007. Call it a Small Business, No a Mid-Sized Business, No a Large

Corporation.Small Business Trends. http://www.sellingtosmallbusinesses.com/call-it-a-

small-business-no-a-mid-sized-business-no-a-large-corporation [accessed October 1,2011]

http://www.sellingtosmallbusinesses.com/call-it-a-small-business-no-a-mid-sized-business-

no-a-large-corporation/

Capers,Jones, 2009. Software Engineering Best Practices: Lessons from Successful

Projects in the Top Companies. 1st Edition. New York: McGraw-Hill Osborne

Media.

Chapman, S. (2007, April 26). Why nothing fails like success: The Peter Principle in

the executive branch. Reason

online.http://www.reason.com/news/show/119867.html.

75

http://www.sellingtosmallbusinesses.com/call-it-a-small-business-no-a-mid-sized-business-no-a-large-corporation/

http://www.sellingtosmallbusinesses.com/call-it-a-small-business-no-a-mid-sized-business-no-a-large-corporation/

http://www.theage.com.au/ed_docs/incompetence.pdf

Cline, M.P., Lomow, G. and Girou,M. 1998.C++ FAQs.2nd ed.Boston:Addison-Wesley

CLARK.How the Peter Principle works.How Stuff Works

http://money.howstuffworks.com/peter-principle.htm [accessed May 01, 2011]

Drucker,Peter,.F. (1993), The Practice of Management.New Jersey: Collins

Facts and Figures – Why Technology Projects Fail. 2011. Facts and Figures – Why Technology Projects Fail. Calleam Consulting Ltd.http://calleam.com/WTPF/?page_id=1445. [accessed 13 November 2011].

Faria, J. R. (2000, January). An economic analysis of the Peter and Dilbert

Principles. Working Paper No. 101, School of Finance and Economics, University of

Technology, Sydney, Australia. [On-line.] Available: ISSN: 1036-7373, 1–18.

Fairburn, J. A., & Malcolmson, J. M. (2000). Performance, promotion, and the Peter

Principle. The Review of Economic Studies, 68(1), 45-66.

Fetzer, J. (2006, October 3). The curse of having a bad supervisor. Analytical &

Bioanalytical Chemistry, 386, 1577-1578.

Gately, R. F. (1996, May/June). Selecting managers—How to avoid the Peter

Principle. Journal of Management in Engineering, 12(3), 3-5.

How to get human resources careers. How to do things . http://www.howtodothings.com/business/human-resources-careers. [accessed 21 November 2011].

Koontz, H. and Weihrich, H. 1990. Essentials of Management.New York, Mcgraw-Hill.

King, A. (2004, June 14-20). Ask yourself: Incompetent or in the wrong job?

Mississippi Business Journal, 26(24), 5-6.

Lazear, E. P. (2004, February). The Peter Principle: A theory of decline. Journal of

Political Economy, 112(1), 141-163.

Malhotra N.K., Marketing Research: An Applied Orientation, Prentice Hall of India, 2007.

76

http://money.howstuffworks.com/peter-principle.htm

Minter, R. L. (1972, July). Mismanagement of training programs. Training and

Development Journal, 26(7), 2-5.

Nelson,Tim and Gerard, Brett.(2005)Recruitment process outsourcing:Transforming end to end talent acquisition.The Korn/Ferry Institute. http://www.kornferryinstitute.com/files/pdf1/Futurestep_RPO_Whitepaper_FINAL_1205.pd

f.[accessed 21 November 2011].

Newman, R. (2008, March 24). Combating the Peter Principle. U.S. News & World

Report, 144(9), 6.

North, G. (2004, July 17). Computers vs. the Peter Principle. [On-line]. Available:

LewRockwell.com, 1-7.

Odiorne, G. S. (1991, May). Competence versus passion. Training & Development

Journal, 45(5), 61-64.

Peter, L. F. 1985. Why things go wrong or the Peter Principle revisited. New York,

NY: William Morrow & Company, Inc.

Peter, L. F. 1972. The Peter prescription – How to make things go right. New York,

NY: Bantam Books.

Peter, L. F.,and Hull, R. 1969. The Peter principle – Why things always go wrong.

New York, NY: William Morrow & Company, Inc.

Peter,Laurence.J. and Hull,Raymond (1996), The Peter principle: Why things always

go wrong.New York: Buccaneer Books

Pluchino,A., Rapisarda, A. and Garofalo,C.2009. The Peter Principle Revisited: A Computational Study.Cornell University Libarary. http://arxiv.org/abs/0907.0455[Accessed October 1,2011]

Reichel, M., & Ramey, M. A. (Eds.). (1987). Conceptual frameworks for bibliographic education: Theory to Practice. Littleton Colorado: Libraries Unlimited Inc.

SchaaP,James I. and Ogulnick Sy.2009.The Peter Principle: Is This Forty-Year-Old Universal Phenomenon in Decline or Growing?Journal of Global Business

77

http://arxiv.org/abs/0907.0455

Managers,vol.5, http://www.jgbm.org/page/1%20James%20Ike%20Schaap%20.pdf [Accessed October 1,2011]

Sekaran U. (2008), Research Methods for Business-A Skill Building Approach, 4th

ed., Wiley, Delhi.

SLDEB . Information Communication Technologies (ICT) - Industry Overview.

http://www.srilankabusiness.com/trade_info/srilankaproduct/ict.htm [accessed April 28, 2011]

Software Project Failure Costs Billions.. Better Estimation & Planning Can Help : Project Planning & Estimation. 2011. Software Project Failure Costs Billions..

Sri Lanka Business Portal - Trade Information. 2011. Sri Lanka Business Portal - Trade Information. http://www.srilankabusiness.com/trade_info/srilankaproduct/ict.htm. [accessed 13 November 2011]

Taylor, E. K. 1969, The Peter Principle. Personnel Psychology, 22(4), 535-537.

Werhane, P.H, Radin,T.J., and Bowie.N.E (2003), Employment and employee

rights.New York :Wiley

Yate,Martin (1997), 4th edition , Hiring the Best: A Manager's Guide to Effective

Interviewing.New York :Adams Media Corporation

78

http://www.srilankabusiness.com/trade_info/srilankaproduct/ict.htm

http://www.jgbm.org/page/1%20James%20Ike%20Schaap%20.pdf

Appendix A – Questionnaire

Research Questionnaire

A study on worker competence in Software Development Firms of Sri Lanka

Dear Participant,

I am a postgraduate student of University of Moratuwa, currently doing a research

study which is a requisite to complete the Master of Business Administration in

Management of Technology programme.

This questionnaire is designed to study on worker competence in software

development firms of Sri Lanka.

Your responses will be kept strictly confidential and all information provided here

will only be used for this research study.

Thank you very much for spending your valuable time and I greatly appreciate your

help in furthering this research endeavor.

Thanks and Regards,

M.Samaratunga

79

1. Experience in IT industry Years

2. Which of the following category best describes your current job?

Trainees / Associate Level ( E.g. Associate Software Engineers , Associate QA Engineers , Associate Business Analysts etc)

Intermediate Level (E.g. Software Engineers, Business Analysts, QA Engineers etc)

Senior Level (E.g. Senior Software Engineers, Senior QA Engineers, Senior BAs etc)

Lead Level (E.g. Technical Team Leads, Business Consultants etc)

Managerial Level (E.g. Architects, Project Managers etc)

If Other, Please specify: ………………………………………..

3. Experience in the current organization Years

4. How many years have you been employed in your current position? Years

5. How many employees are there in the company that you work at present?

Less than 100 Between 100 and 300

Greater than 300

6. How would you define the structure of your organization in a broad sense?

Flat Hierarchical (Tall)

#From your perspective, in your organization the

occurrence of the following scenarios are:

Ver

y L

ess

Les

s

Mod

erat

e

Hig

h

Ver

y H

igh

7 There are previously competent employees who have become incompetent after getting promoted

80

8 There are employees who are not successful in obtaining further promotions due to incompetence in their current position

9 Some incompetent employees are promoted to a "higher" position to minimize the harm done by them

10 The rate of competent employees leaving the company is

11 Innovative ideas and processes are discouraged as preserving the organization’s existing way of doing work is highly valued than providing efficient service to the customer

12 Highly competent employees are fired to preserve the organization’s hierarchy

13 Some employees are placed very high in the organization’s hierarchy based on personal relationships

14 Incompetent employees get promoted in the hierarchy if they are followers of the superiors

15 Competent people have to push hard to get promoted

16 There are employees who shift the blame on to others for their own actions

17 There are superiors who take credit by getting work assigned to them, done by competent employees under them

18 There are superiors who ignore their duties and focus more on activities that are not direct responsibilities of their position

19 There are employees who are overly stressed , mentally disturbed and frequently sick even though they do not do a lot of productive work

20 The number of incompetent employees in the higher levels of your organization’s hierarchy is

21 The number of competent employees in the lower levels of your organization’s hierarchy is

22 The productivity of the employees in the higher levels of your organization’s hierarchy is

81

23 The productivity of the employees in the lower levels of your organization’s hierarchy is

# With regards to your organization

Str

ongl

y D

isag

ree

Dis

agre

e

Nei

ther

agr

ee n

or

disa

gree

Agr

ee

Str

ongl

y ag

ree

24 I am satisfied with my current job with regards to the responsibilities assigned to me

25 I believe I am eligible for further promotions

26 I am happy to take over more responsibilities

27 My organization has a standard method of evaluating employee performance

28 The employees in my organization are happy with the current performance evaluation method

29 My organization maintains proper job descriptions for all job positions

30 My current job responsibilities have been clearly communicated to me

31 The work that I perform matches with my job description

32 In my organization rewards/promotions are solely based on performance ratings

33 My organization provides comprehensive job descriptions when advertising job vacancies

34 In my organization selection interviews are well structured to identify the best candidates

35 The members of the selection panels in my organization are competent and properly are trained

82

36 My organization gives due attention to skills such as teamwork, leadership, attitude etc when recruiting new employees

37 My organization provides job related training for all employees on technical matters

38 My organization provides training on soft skills (E.g. teamwork, leadership skills etc )

39 My organization has a well defined HR development /talent management process to achieve organizational goals

40 The trainers in my organization are highly competent

41 The employees in my organization are happy with the training they receive

Kindly answer the following questions. The information is required solely for statistical purposes.

42. Age: Years

43. Gender: Male Female

44. Marital Status

Single

Married

45. What is the highest academic qualification you have obtained?

Advanced Level or below

Diploma (E.g. ACS)

Bachelor’s Degree or equivalent professional qualifications (E.g. BCS)

Postgraduate Qualifications

Thank you for filling the questionnaire

83

Appendix B – SPSS Data Analysis Output

This section contains the reliability and validity analysis outputs and the descriptive

statistics outputs obtained via the SPSS software .Please refer Appendix A for the

question descriptions.

Reliability and Validity Analysis

a) Factors that denote the existence of Peter Principle effect

Scale: Reliability Analysis Round 1

Case Processing Summary

N %Cases Valid 396 100.0

Excluded(a) 0 .0Total 396 100.0

a Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's Alpha N of Items

.929 20

Item Statistics

Mean Std. Deviation NQ7 3.17 1.406 396Q8 3.13 .983 396Q9 2.76 1.221 396Q10 3.55 1.269 396Q11 3.15 1.396 396Q12 2.61 1.269 396Q13 3.16 1.496 396Q14 3.16 1.350 396Q15 3.09 1.038 396Q16 3.30 1.244 396Q17 3.38 1.284 396Q18 3.17 1.311 396Q19 2.96 1.052 396Q20 3.07 1.000 396Q21 3.58 .763 396Q22 3.09 .957 396Q23 3.55 .750 396

84

Q24 2.46 .903 396Q25 2.27 .467 396Q26 2.23 .465 396

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

DeletedQ7 57.68 180.839 .815 .921Q8 57.72 192.109 .755 .923Q9 58.09 186.019 .785 .922Q10 57.30 188.296 .682 .924Q11 57.70 181.969 .789 .921Q12 58.24 185.746 .760 .922Q13 57.69 178.370 .827 .920Q14 57.69 189.790 .592 .926Q15 57.76 193.956 .644 .925Q16 57.55 184.243 .824 .921Q17 57.47 183.667 .814 .921Q18 57.68 182.817 .821 .921Q19 57.89 191.596 .719 .923Q20 57.78 192.609 .722 .924Q21 57.27 207.169 .268 .931Q22 57.76 194.085 .699 .924Q23 57.30 208.602 .207 .932Q24 58.39 217.622 -.180 .938Q25 58.58 215.535 -.154 .934Q26 58.62 215.577 -.158 .934

Scale Statistics

Mean Variance Std. Deviation N of Items

60.85 213.641 14.616 20

Scale: Reliability Analysis Round 2



Excluded(a) 0 .0

Total 396 100.0



85


.956 15

Item Statistics

Mean Std. Deviation NQ7 3.17 1.406 396Q8 3.13 .983 396Q9 2.76 1.221 396Q10 3.55 1.269 396Q11 3.15 1.396 396Q12 2.61 1.269 396Q13 3.16 1.496 396Q14 3.16 1.350 396Q15 3.09 1.038 396Q16 3.30 1.244 396Q17 3.38 1.284 396Q18 3.17 1.311 396Q19 2.96 1.052 396Q20 3.07 1.000 396Q22 3.09 .957 396






DeletedQ7 43.60 177.765 .818 .951Q8 43.64 188.641 .771 .953Q9 44.01 183.106 .782 .952Q10 43.21 184.912 .693 .954Q11 43.61 178.851 .793 .952Q12 44.15 182.620 .764 .953Q13 43.61 175.707 .819 .952Q14 43.60 186.610 .596 .957Q15 43.67 190.692 .651 .955Q16 43.46 181.075 .830 .951Q17 43.38 180.424 .822 .951Q18 43.59 179.635 .827 .951Q19 43.81 188.405 .724 .954Q20 43.69 189.125 .738 .953Q22 43.68 190.548 .717 .954

Scale Statistics


86

46.77 210.418 14.506 15

Principle Component Analysis

Communalities

Initial ExtractionQ7 1.000 .718Q8 1.000 .910Q9 1.000 .665Q10 1.000 .536Q11 1.000 .717Q12 1.000 .664Q13 1.000 .800Q14 1.000 .510Q15 1.000 .483Q16 1.000 .788Q17 1.000 .783Q18 1.000 .794Q19 1.000 .617Q20 1.000 .904Q22 1.000 .865

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial EigenvaluesExtraction Sums of Squared

LoadingsRotation Sums of Squared

Loadings

Total

% of Varianc

eCumulativ

e % Total

% of Varianc

eCumulativ

e % Total

% of Varianc

eCumulativ

e %1

9.432 62.883 62.8839.43

262.883 62.883

6.550

43.668 43.668

21.321 8.805 71.687

1.321

8.805 71.6874.20

328.019 71.687

3 .759 5.063 76.7504 .589 3.929 80.6795 .485 3.235 83.9146 .480 3.198 87.1137 .390 2.601 89.7148 .315 2.100 91.8159 .274 1.825 93.64010 .247 1.647 95.28811 .210 1.399 96.68612 .183 1.221 97.90713 .136 .909 98.81614 .122 .816 99.63215 .055 .368 100.000


87

Component Matrix(a)

Component

1 2Q7 .846Q8 .814 .498Q9 .813Q10 .732Q11 .822Q12 .795Q13 .843Q14 .645Q15 .695Q16 .853Q17 .845Q18 .852Q19 .759Q20 .781 .542Q22 .765 .528

Extraction Method: Principal Component Analysis.a 2 components extracted.

Rotated Component Matrix(a)

Component

1 2Q7 .704 .471Q8 .885Q9 .689 .436Q10 .581 .445Q11 .781Q12 .745Q13 .855Q14 .630Q15 .546 .430Q16 .831Q17 .835Q18 .839Q19 .731Q20 .900Q22 .880

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.

a Rotation converged in 3 iterations.

88

Component Transformation Matrix

Component 1 21 .803 .5962 -.596 .803

Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.

b) Factors that explain the quality of performance and rewards management practices in an organization



Excluded(a)

0 .0

Total 396 100.0




.915 6

Item Statistics

Mean Std. Deviation NQ27 3.02 1.058 396Q28 2.75 .950 396Q29 2.88 1.051 396Q30 3.06 1.062 396Q31 3.03 1.027 396Q32 2.97 1.030 396






DeletedQ27 14.70 18.779 .751 .901Q28 14.96 19.571 .750 .901Q29 14.83 18.659 .772 .897Q30 14.65 18.318 .806 .892Q31 14.68 19.115 .736 .902Q32 14.74 19.039 .743 .901

Scale Statistics

89


17.71 26.778 5.175 6


Communalities

Initial ExtractionQ27 1.000 .692Q28 1.000 .688Q29 1.000 .718Q30 1.000 .759Q31 1.000 .670Q32 1.000 .681



Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %1 4.209 70.144 70.144 4.209 70.144 70.1442 .680 11.331 81.4753 .365 6.090 87.5654 .301 5.024 92.5895 .273 4.557 97.1476 .171 2.853 100.000


Component Matrix(a)

Component

1Q27 .832Q28 .829Q29 .847Q30 .871Q31 .819Q32 .825


90

Rotated Component Matrix(a)a Only one component was extracted. The solution cannot be rotated.

c) Factors that explain the quality of selection and recruitment practices in an organization

Case Processing SummaryN %

Cases Valid 396 100.0

Excluded(a)

0 .0

Total 396 100.0




.880 4

Item Statistics

Mean Std. Deviation NQ33 3.07 .966 396Q34 3.02 1.035 396Q35 3.01 1.010 396Q36 3.10 1.018 396






DeletedQ33 9.13 7.393 .688 .866Q34 9.18 6.890 .732 .849Q35 9.18 6.777 .788 .827Q36 9.10 6.877 .754 .841

Scale Statistics


12.19 11.939 3.455 4

91

Principle Component Analysis Communalities

Initial ExtractionQ33 1.000 .673Q34 1.000 .727Q35 1.000 .790Q36 1.000 .754



Component


Total % of Variance Cumulative % Total % of Variance Cumulative %1 2.943 73.574 73.574 2.943 73.574 73.5742 .458 11.439 85.0143 .363 9.085 94.0984 .236 5.902 100.000


Component Matrix(a)

Component

1Q33 .820Q34 .852Q35 .889Q36 .868



a only one component was extracted. The solution cannot be rotated.

92

d) Factors that explain the quality of human resource development practices in an organization



Excluded(a)

0 .0

Total 396 100.0




.924 5

Item Statistics

Mean Std. Deviation NQ37 3.01 1.119 396Q38 2.86 1.090 396Q39 2.72 1.054 396Q40 2.96 1.058 396Q41 2.89 1.016 396






DeletedQ37 11.44 13.806 .815 .903Q38 11.58 14.299 .771 .912Q39 11.72 14.673 .750 .916Q40 11.49 14.245 .811 .904Q41 11.55 14.208 .862 .895

Scale Statistics


14.44 21.842 4.674 5

93


Communalities

Initial ExtractionQ37 1.000 .787Q38 1.000 .725Q39 1.000 .700Q40 1.000 .784Q41 1.000 .844



Component


Total % of Variance Cumulative % Total % of Variance Cumulative %1 3.839 76.789 76.789 3.839 76.789 76.7892 .468 9.363 86.1523 .313 6.256 92.4074 .241 4.829 97.2375 .138 2.763 100.000


Component Matrix(a)

Component

1Q37 .887Q38 .852Q39 .837Q40 .885Q41 .918



a Only one component was extracted. The solution cannot be rotated.

94

Descriptive Statistics

Descriptive statistics for the factors that explain the existence of Peter Principle Effect

N Minimum Maximum Mean Std. Deviation VarianceQ7 396 1 5 3.17 1.406 1.977Q8 396 1 5 3.13 .983 .966Q9 396 1 5 2.76 1.221 1.490Q10 396 1 5 3.55 1.269 1.610Q11 396 1 5 3.15 1.396 1.948Q12 396 1 5 2.61 1.269 1.610Q13 396 1 5 3.16 1.496 2.239Q14 396 1 5 3.16 1.350 1.824Q15 396 1 5 3.09 1.038 1.077Q16 396 1 5 3.30 1.244 1.548Q17 396 1 5 3.38 1.284 1.649Q18 396 1 5 3.17 1.311 1.719Q19 396 1 5 2.96 1.052 1.107Q20 396 1 5 3.07 1.000 1.000Q22 396 1 5 3.09 .957 .916

Valid N (listwise) 396

Descriptive statistics for the factors that explained the quality of performance and rewards management practices

N Minimum Maximum Mean Std. Deviation VarianceQ27 396 1 5 3.02 1.058 1.119Q28 396 1 5 2.75 .950 .902Q29 396 1 5 2.88 1.051 1.105Q30 396 1 5 3.06 1.062 1.128Q31 396 1 5 3.03 1.027 1.055Q32 396 1 5 2.97 1.030 1.060


Descriptive statistics for the factors that explained the quality of selection and recruitment practices

N Minimum Maximum Mean Std. Deviation VarianceQ33 396 1 5 3.07 .966 .932Q34 396 1 5 3.02 1.035 1.071Q35 396 1 5 3.01 1.010 1.020Q36 396 1 5 3.10 1.018 1.036


95

Descriptive statistics for the factors that explained the quality of human resource development practices

N Minimum Maximum Mean Std. Deviation VarianceQ37 396 1 5 3.01 1.119 1.253Q38 396 1 5 2.86 1.090 1.188Q39 396 1 5 2.72 1.054 1.111Q40 396 1 5 2.96 1.058 1.120Q41 396 1 5 2.89 1.016 1.032


CorrelationsCorrelations

1 .811** .794** -.721** -.495** .059 -.436**

.000 .000 .000 .000 .240 .000

396 396 396 396 396 396 396

.811** 1 .739** -.691** -.508** .066 -.453**

.000 .000 .000 .000 .188 .000

396 396 396 396 396 396 396

.794** .739** 1 -.587** -.381** .147** -.332**

.000 .000 .000 .000 .003 .000

396 396 396 396 396 396 396

-.721** -.691** -.587** 1 .719** -.019 .564**

.000 .000 .000 .000 .711 .000

396 396 396 396 396 396 396

-.495** -.508** -.381** .719** 1 -.048 .416**

.000 .000 .000 .000 .344 .000

396 396 396 396 396 396 396

.059 .066 .147** -.019 -.048 1 .077

.240 .188 .003 .711 .344 .128

396 396 396 396 396 396 396

-.436** -.453** -.332** .564** .416** .077 1

.000 .000 .000 .000 .000 .128

396 396 396 396 396 396 396

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

AvPRM

AvRP

AvHRD

AvPPB

AvIEHL

Q5

Q6

AvPRM AvRP AvHRD AvPPB AvIEHL Q5 Q6

Correlation is significant at the 0.01 level (2-tailed).**.

96

Thesis (3)

Documents

verbally expressive

standish chaos

promising

final placement

william morrow

software development

pearson correlation

rewards management