Impact of Critical Success Factors of a Project

The objective of the present study is to measure the impact of project success factors on actual project success in the telecom firms, based in Rawalpindi/Islamabad. A construct adopted from the study of Andersen et al (2006) has been used to investigate the said impact. The results that are based on questionnaires filled by 150 respondent shows a strong correlation between managerial ability to deliver and clear project constraints. The regression analysis shows that clear project constraints have a strong impact on all the success criteria of projects. This suggests that well planned and informed timelines and financial constraints of the project to the project team enable the Management to deliver the project within time and budgetary prerequisites. Similarly the participation of project team in decision-making results in capturing the experiences and lessons learned from the project. The conclusion confirms the findings of pervious researches on similar topic with a focus on telecom industry.

Key Words: Project Management, Key Performance Indicators, Critical Success Factors, Project Success, Performance measures of Project

Introduction

Project success is one of the ambiguous concepts in project management. As each person or group of people who are involved in a project have different needs and expectations from the same project, it is very common that they take project success in their own way, as per their own understanding.

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Research on project measurement deliverables and focus on the main project management practices (time, cost and quality) shows that it is not possible to have a ubiquitous project success criterion that is suitable for all projects. Focus of project management activities differ from one project to another on the basis of a number of attributes like projects uniqueness, business, volume, complexity, customer preferences and the interest of stakeholders. So it is not enough to assume that time, cost and quality are the only success factors of a project but they must be explored and quantified with an overall establishment of a number of multifaceted and unified project evaluation criteria (Ojiako et al., 2008).

The difference between criteria and factors is unclear to many people. The Cambridge Advanced Learner’s Dictionary describes a criterion as “a standard by which you judge, decide about or deal with something” while a factor is explained as “a fact or situation which influences the result of something”. In this study I have tried to set up a relationship between the success factors of project and the actual project success variables through literature and an empirical analysis adopted from the research of Andersen et al (2006). Focus would be on the Telecom Sector of Pakistan. This is because all the telecom firms are working on the basis of projects. Moreover, not much research is being found on this particular sector of the economy, so it is important to find the relationship of critical success factors with the actual success of the project to make such projects more successful.

Objective of the Study

The purpose of this research is to study the relationship between the project success factors and actual project success in the telecom sector of Pakistan. It reports on an analysis of those factors that are within the direct control of project managers and that can make a possible difference to the outcome of project activities. The study also tends to find out the level of impact of project success factors on project success criteria.

Literature Review

Project success criteria

The traditional success criteria of project success is achieving the desired outcomes in terms of time, cost and quality (technical) or specifications that comes from the “iron/golden” triangle (Minarro-Viseras et al, 2005; Bryde and Robinson, 2007). Other factors like customer satisfaction (Hides et al, 2000), Information management and decision-making (Cozijnsen et al, 2000), stakeholders interest (Strang, 2005), organization and user satisfaction (Dimitrios, 2009) can also be taken into account as the project success criteria.

Lim and Mohamed (1999) classified project success criteria into two broad categories i.e. the micro and macro viewpoints of project success. Two criteria, project completion and satisfaction, were considered as enough in determining afore-mentioned viewpoints. Factors contributing project completion were economy, management, supervision, weather, etc. On the other hand, factors participating project satisfaction included convenience, location, prestige, parking, cost, etc.

Tukel and Rom (2001) considered overall project quality and customer satisfaction as the primary success measures of a Project by Project Managers. Whereas, a research conducted by Lam et al (2007) in Hong Kong on Design & Build (D&B) projects revealed that the success criteria of D&B projects can be represented in terms of time, cost, quality and functionality.

Westerveld (2003) linked project success criteria and critical success factors of project by devising a Project Excellence Model. Model was developed by connecting six project success criteria including leadership & Team, Policy and Strategy, Stakeholder management, Resources and Contracting with six organizational areas having critical factors as Project Results (time, cost, and quality), Client, Project Personnel, Contracting Partners Users and Stakeholders. While applying a case study of ERP system on subject model it was found that efficient use of resources contributes in having the project completed within time and financial constraints.

Chan & Chan (2004), in their research on key performance indicators (KPIs) for measuring construction projects success, derived some KPIs for subjective measure of a project. They found that subjective measures like quality, functionality, end user’s specifications, client’s satisfaction, design team’s satisfaction and customer team’s satisfaction are significant indicators of the performance of construction projects.

Other research on project measurement criteria (failure or success) indicates that it is impossible to generate a universal checklist of criteria suitable for all projects. Success (or failure) criteria will differ from project to project depending on a number of variables including size, uniqueness, industry, complexity and the stakeholders involved (Ojiako et al., 2008). However a great deal of research has been conducted to find out the success criteria of projects.

There is a long-held assumption that the performance of both the line and project managers could have improve d if they have a better understanding of what comprises of project success. In order to avoid failures at the end, there is a critical need to find the different aspects of what success means before the project gets start. It is also critical to remember that success criteria are the standards by which a project will be evaluated (Dimitrios, 2009).

Jung et al. (2008) found positive and significant path coefficients between the TQM elements and the project management performance thus indicating a strong influence of the TQM practice on project management performance. The study further revealed that competitive strategy (differential and cost leadership strategy) does not have a direct impact on the project success and suggests that competitive strategy must work in collaboration with a management philosophy to have a significant impact on project management performance.

Toor and Ogunlana (2010) in their research on mega public sector construction projects in Thailand rejects the traditional iron/golden triangle criteria to measure project success. Other performance indicators like efficient and effective use of resources, employee’s safety, stakeholder’s satisfaction, reduced conflicts and disagreements are the significant elements affecting project success.

Critical Success Factors:

Klimczak & Wedman (1997) in their research on “Instructional Design (ID) Project Success Factors” shows that the success of an ID project is viewed by various stakeholders to be a function of four broad areas consisting of training strategies, tangible resources, implementation support, and curriculum development. Similarly team work (Segalla, 1998) is an essential factor for project success.

Cicmil (1997) argued that TQM propositions can support practical implementation of the Project Management (PM). These propositions include; listening to the customers and understanding their requirements and expectations of the project outcome, planning realistically for time, budget, material and human resources while contemplating the re-planning of these to ensure the match with changing customer needs, ensuring project leadership skills necessary to build up effective project teams and having a sound communication system in place, that spans the project network.

Coronado and Antony (2002) highlighted management involvement and commitment, cultural change, organizational infrastructure, communication, business strategy, training, customer satisfaction, human resources, suppliers, PM skills, tools and techniques, and project prioritization and choice as the critical success factors for the successful implementation of six sigma projects in organizations.

According to Nguyen et al (2004) competent project manager, adequate funding until project completion, multidisciplinary/competent project team, commitment to project, and availability of resources are the Critical Success Factors (CSFs) of project success in large construction projects in Vietnam. In addition, they grouped most of the project CSFs into four components i.e. comfort, competence, commitment, and communication.

Personality of the project managers is also linked with the success of the project. Project Managers that have their personality profiles in line with the ideal Project Management profile for a particular project type are more successful in having an impact on the customers, benefits to the organization and overall success of the project (Pines et al, 2008). Moreover, the success of the project is clearer in firms that have permanent and exclusive project managers that apply project planning techniques, and firms that consider quality standards and completion schedules to be important milestones (Murphy and Ledwith, 2007).

Project manager himself holds a high responsibility for the overall success of project. Special attention should be given to the project manager’s personal qualities, interpersonal and other skills involved in managing the projects and to his understanding of the strategic direction of the organization (Minarro-Viseras et al, 2005). Similarly, Rauniar et al (2008) found that the Product Manager can also have a positive impact on the project performance in cross-functional teams.

Andersen et al (2006) used Principal Component Analysis (PCA) on 60 questions related to the actual project work performance that were gathered from four culturally different regions (UK, Norway, France, and China) and found that rich project communications, stakeholders endorsement of project plans, well structured and formal project approach, strong project commitment, early stakeholder influence, well understood and accepted project purpose, clear project constraints, project execution flexibility and influence over ongoing project processes are the key CSF for project success.

Other factors like overall organizational management, top management support, communication and interaction and knowledge management can also be considered as the critical success factors of effective project management (Ruuska and Vartiainen, 2000:, Remus, 2007).

Critical success factors are the key areas where things must go right if any project is to be successful. These are the essentials that shape the result of projects. Research by Dimitrios (2009) highlighted different areas including the role of project manager, project team, the project itself, the organization and the external environment as the key success factors of project management.

Conceptual Framework

The conceptual framework of this research has been adopted from the research of Andersen et al (2006). In their research they used the PEVS-questionnaire (Project Evaluation Scheme), initially developed by Andersen & Jessen (2000) for testing progress and quality of individual projects using 70 statements accounting for the hard (technically focused) and soft (behavioural) issues of project management. It covers the following aspects of project work:

Scope: Work that needs to be accomplished

Planning: Detail planning, work breakdown structure.

Organization: Formal/Informal organization.

Execution: Items, events, results.

Control: Project execution tracking, Financial and quality controls.

Using the PEVS questionnaire Andersen et al (2006) identified two set of factors that summarized the original seventy statements of PEVS-questionnaire into a manageable few categories of success factors and success criteria with the help of Principal Component Analysis (PCA) with Varimax rotation. Success factors were categorized into nine categories (X) and success criteria into three (Y). These variables include,

Under X category;

Rich Project Communications

Stakeholder endorsement of project plans

Well Structured and Formal Project Approach

Strong Project Commitment

Early Stakeholder Influence

Well Understood and Accepted Project Purpose

Clear Project Constraints

Project Execution Flexibility

Influence over ongoing project processes

Under Y category;

Project Impact

Captured Experience

Managerial Ability to Deliver

A stepwise regression of the X (the success factors) on Y (the success criteria) was performed to found the type and extent of the impact of project success factors on project success criteria.

That was an exploratory study and authors suggested that the same study can be extended for confirmatory studies cross culturally, to a different set of sample including project participants from a diverse number of countries and cultures, between the nationwide cultures, project types, size and duration. Therefore, we are using the same methodology with same success factors and criteria in the context of Pakistani culture, particularly for the telecom firms to know how these success factors account for, to the success of the projects.

Research Hypothesis

Based on the literature review and the most significant findings of Anderson et al (2006), we have formulated the following hypotheses,

H1 Rich Project communication has an impact on the overall project impact.

H2 Well understood and accepted project purpose has an impact the overall project impact.

H3 Project execution flexibility has an impact on the project impact.

H4 Clear project constraints have an impact the captured experience of the project.

H5 Influence over ongoing project activities have an impact on captured experience of the project.

H6 Rich project communication has an impact on managerial ability to deliver the project.

H7 Stakeholder endorsement of project plans has an impact on managerial ability to deliver the project.

H8 Clear project constraints have an impact on managerial ability to deliver the project.

Study Design and Methodology

Andersen et al (2006) used a combination of purposive and heterogeneous sampling techniques as that study was more exploratory and respondents from four different countries including China, France, Norway and UK. Respondents from these countries were considered to be reviewed for the likely universal approaches to project management.

Population

In the current study, our focus is only on the Telecom industry of Pakistan; a service industry consisting of five major operators namely Mobilink, Telenor, Ufone, Zong, Warid and a few sub contractors. Therefore, only purposive sampling is used. Reason for selecting telecom sector is that all of the Telecom firms are working in project based environments and are reaching their milestones on the basis of different projects.

Measurement Instrument

Coronado (2002) based their research, on the similar topic, on surveys and case studies/focus group analysis of companies. However, in the present research, a questionnaire, adopted from Andersen et al (2006) is considered as a valid measuring instrument to analyze the data for success factors and success criteria.

Data Collection

All of the questionnaires have been self-administered to ensure hundred percent responses. It is ensured that all the respondents are working with different projects as Project Managers, Assistant Project Managers, Project Coordinators, Executives, Project Directors and employees working in supporting functions. Prior to fill in the questionnaire, the respondents were asked to recall an explicit project they were associated with, it may be completed or in progress, to support their answers particularly based on that project. In the main section of the questionnaire, all the details were collected about project success factors and project success criteria. Responses are measured using a six-point Likert scale.

Sample

Considering the previous sample size of 265 cases for X class and 365 for Y class, for cross-cultural study, and conformity to the sample size formula given by Tabachnick and Fidell (2001, p. 117) for multiple regression analysis i.e. N≥50 +8M (where m is the number of predictor variables), a sample size of 150 is considered in the present study. We make sure a 100 percent response rate in the current study because of self-administrated questionnaires.

Reliability

Data is analyzed through SPSS Version 16. As all the questionnaires were self-administered it was established prior to floating the questionnaire that all the respondents should be associated to the project management related activities and should be aware of the concept of Project Success. The reliability of the questionnaire has been checked using Cronbach alpha test (Results are reported in Table I). Annexure A shows the complete list of questions asked. Table: I show the Cronbach alpha result for project success factors and criteria. It was found that all the variables met the cut off value (0.65) which is acceptable for retaining the variable. (Leech, N.L., Barrett, C.K and Morgan, G.A, 2005).

Table: I

Reliability Statistics

Sr. No

Variable Name

Cronbach α

1.  

Rich Project Communication

0.76

2.  

Stakeholder endorsement of project plans

0.65

3.  

Well Structured and Formal Project Approach

0.7

4.  

Strong Project Commitment

0.69

5.  

Early Stakeholder Influence

0.78

6.  

Well Understood and Accepted Project Purpose

0.7

7.  

Clear Project Constraints

0.74

8.  

Project Execution Flexibility

0.86

9.  

Influence over ongoing project processes

0.68

10.  

Project Impact

0.67

11.  

Captured Experience

0.78

12.  

Managerial Ability to Deliver

0.87

Data Analysis

5.1. Descriptive Analysis

Of the respondents, 24 per cent were working as Project Mangers, 62 per cent Project Team Member, 14 per cent End User; 84 per cent male, 16 percent female; 73 per cent of the projects were Production or construction oriented, 12 per cent Research and Development oriented, 15 per cent Decision support oriented; 32 per cent working on large projects, 58 per cent medium, 10 percent small.

5.2. Correlation

Having the aim of finding out those success factors that are highly correlated with the criterion variables, Pearson correlation was computed between the success factors (X) and the success criteria (Y). Table II shows the complete list of correlations between the Predictor and Dependent Variables using Pearson Correlations.

Table: II

Correlations

Project Impact

Captured Experience

Managerial Ability to Deliver

Rich Project Communication

.422**

0.088

.433**

Stakeholder endorsement of project plans

.411**

.536**

.490**

Well Structured and Formal Project Approach

.444**

.431**

.372**

Strong Project Commitment

.477**

.350**

.432**

Early Stakeholder Influence

.459**

.346**

.210**

Well Understood and Accepted Project Purpose

.404**

0.036

0.058

Clear Project Constraints

.481**

.423**

.618**

Project Execution Flexibility

.445**

.352**

.262**

Influence over ongoing project processes

.201*

.295**

.040

Correlation is significant at the 0.01 level (2tailed).

Correlation is significant at the 0.05 level (2-tailed).

Here, it’s evident that each of the predictor is significantly correlated with at least one of the dependent variables. Whereas most of the predictor variables are significantly correlated with all the criterion variables. Unlike the study of Andersen et al (2006) that resulted in complex set of interactions among the predictors and the criterion variables, here we have a clear picture that exactly which predictor has an impact on each of the success criterion.

Strongest correlation exists between the criterion variable “Managerial Ability to Deliver” and predictor “Clear Project Constraints”. This can be interpreted as if clear project constraints are defined in your project then the ability of the Management to deliver the project on time and within budget would certainly be increased. Similarly, “Managerial Ability to Deliver” strongly correlates with “Stakeholder endorsement of project plans”, “Rich Project Communication”, “Rich Project Communication”, “Strong Project Commitment”, and weakly correlated with “Project Execution Flexibility” and “Early Stakeholder Influence”.

“Captured Experience” correlates strongly with “Stakeholder endorsement of project plans”, “Clear Project Constraints”, “Well Structured and Formal Project Approach”, and to a lesser level with “Influence over ongoing project processes”. “Project Impact” strongly correlated with all the predictors except with “Influence over ongoing project processes”.

5.3. Regression and Hypothesis

Before applying the regression analysis, the data was checked for normality to make sure that it was acceptable for the use of this method. The distribution of the variables was examined with the help of visual tools like Histogram and P-P Plots. On the other hand, numerical tests of Skewness and Kurtosis were applied. Both the sample Skewness and Kurtosis coefficient were in the range of three standard errors of zero that confirms that the data is normally distributed, having multivariate characteristics and is subject for regression analysis.

Stepwise linear regression analysis is then performed for each of the outcome variable. To begin with, the regression analysis was undertaken for “Project Impact”. The model with the highest R square and that best fits the relationship is selected and presented in Table III. This model explains about 46 per cent variability of “Project Impact”.

Table: III

Stepwise Linear Regression Model (Project Impact)

Model Summary (Project Impact)

R

R Square

Adjusted R Square

Std. Error of the Estimate

R Square Change

0.694

0.481

0.463

0.489

0.017

Predictors: Clear Project Constraints, Project Execution Flexibility, Rich Project Communication, Well Understood and Accepted Project Purpose, Well Structured and Formal Project Approach.

Secondly, regression analysis for “Captured Experience” was performed. Model was selected on the same criteria as mentioned above. This model accounts for about 43 percent variability of “Captured Experience” (Table IV).

Table: IV

Stepwise Linear Regression Model (Captured Experience)

Model Summary (Captured Experience)

R

R Square

Adjusted R Square

Std. Error of the Estimate

R Square Change

0.669

0.448

0.429

0.723

0.031

Predictors: Stakeholder endorsement of project plans, Influence over ongoing project processes, Clear Project Constraints, Well Understood and Accepted Project Purpose, Well Structured and Formal Project Approach

Finally, “Managerial Ability to Deliver” was regressed and the selected model explains 50 per cent of the variance (Table V).

Table: V

Stepwise Linear Regression Model (Managerial Ability to Deliver)

Model Summary (Managerial Ability to Deliver)

R

R Square

Adjusted R Square

Std. Error of the Estimate

R Square Change

0.729

0.532

0.509

0.766

0.028

Predictors:Clear Project Constraints, Stakeholder endorsement of project plans, Well Understood and Accepted Project Purpose, Rich Project Communication, Well Structured and Formal Project Approach, Early Stakeholder Influence, Influence over ongoing project processes.

The results of hypothesis testing are reported in Table VI.

Table VI

Hypotheses Testing

Project Impact

Captured Experience

Managerial Ability to Deliver

Standardized β coefficients

Significance

Standardized βcoefficients

Significance

Standardized βcoefficients

Significance

1

Rich Project Communication

0.074

0

0.282

0

2

Stakeholder endorsement of project plans

0.297

0.001

0.117

0.141

3

Well Structured and Formal Project Approach

0.16

0.03

0.225

0.005

0.224

0.003

4

Strong Project Commitment

5

Early Stakeholder Influence

-0.256

0

6

Well Understood and Accepted Project Purpose

0.175

0.01

-0.291

0

-0.252

0

7

Clear Project Constraints

0.185

0.015

0.265

0.001

0.532

0

8

Project Execution Flexibility

0.303

0

9

Influence over ongoing project processes

0.306

0

0.206

0.004

H1 Rich Project communication has an impact on the overall project impact.

The regression analysis supports the hypothesis that rich project communication has a significant impact on the overall project impact. This impact is measured in terms of the impact on project participants and whether the product that the project intended to deliver has been achieved or not.

H2 Well understood and accepted project purpose has an impact the overall project impact.

Result shows that our second hypothesis is also accepted. So we can say that if we have a well comprehended project plan and the project goals are well understood, it would certainly have an impact on the overall project impact.

H3 Project execution flexibility has an impact on the project impact

The Beta coefficient explains that Project Impact is by and large affected by the factor, “Project Execution Flexibility” that accounts for flexibility in the execution of project goals and the availability of the project superiors to the key executors when necessary. In this way, the participation of the higher management and change in the terms and conditions of project goals, if required, seems to be the key factor while explaining the Project Success in project settings. This finding is also significant; hence our third hypothesis is also accepted.

H4 Clear project constraints have an impact the captured experience of the project.

The Beta loading of clear project constraints shows its importance in explaining the captured experience. The results proves that this relationship if also significant. Therefore our forth hypothesis is also accepted.

H5 Influence over ongoing project activities have an impact on captured experience of the project.

Influence over ongoing project processes accounts for the most significant amount in explaining the Captured Experience. This shows that the participation of project participants in the decision-making and responsibility allocation has a strong significant impact in retaining the experiences gained from the project.

H6 Rich project communication has an impact on managerial ability to deliver the project.

This relationship is also significant. This shows that if the project participants have an open and well-organized way of informing each other about the project plans or the project progress as necessary then it would have a significant impact on the managerial ability to deliver that project within time and financial obligations.

H7 Stakeholder endorsement of project plans has an impact on managerial ability to deliver the project.

Stakeholder endorsement of project plans has no significant impact on managerial ability to deliver. This shows that the project success is not necessarily dependent on stakeholder endorsement of project plans. Hence hypothesis is rejected

H8 Clear project constraints have an impact on managerial ability to deliver the project.

The regression analysis shows that the factor, “Clear Project Constraints”, has the highest impact on Managerial ability to deliver and both the variables have a significant relationship. This gives us evidence that the well described and informed timelines and financial limits of the project to the project team enables the Management to deliver the project within time and budgetary provisions. Hence our last hypothesis is also accepted.

Summary of all the hypotheses as per their acceptance/rejection status is mentioned below,

Table VII

Hypothesis

p value

Accepted/Rejected

H1

0

Accepted

H2

0.01

Accepted

H3

0

Accepted

H4

0.001

Accepted

H5

0

Accepted

H6

0

Accepted

H7<