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IS Project Management: Size, Complexity, Practices and the Project Management Office

Nancy L. Martin Southern Illinois University

at Carbondale nlmartin@siu.edu

John M. Pearson Southern Illinois University

at Carbondale jpearson@cba.siu.edu

Kimberly A. Furumo Southern Illinois University

at Carbondale kfurumo@siu.edu

Abstract

The current research is an exploratory investigation into current IS project management practices related to projects of varying size and complexity across diverse industries Survey data on a broad range of project management issues was collected from 129 IS project managers. The relationships between project size and complexity with 13 project management practices and 3 project performance measures were analyzed. In addition, the influence of a PMO on the use of standardized project management practices and project performance was empirically tested. Our findings suggest that IS project size influences budget and project quality, while project complexity influences the use of specific project management practices. The PMO is empirically linked to project budget.

1. Introduction

Information systems (IS) projects are commonplace for organizations in today’s technologically evolving and globalized business environment.

Organizations are faced with IS projects of varying size and technical complexity and ensuring the success of these projects is of paramount concern for both firm leaders and IS project managers.

Studies suggest that a significant percentage of IS projects encounter problems, many requiring additional time, financial and human resources. The Standish Group International, Inc., a research advisory firm, surveyed executives in 1998 and found that American companies spent an estimated $22 billion in IS project overruns and

$75 billion on software projects that were eventually cancelled [1]. In an effort to better coordinate and control IS projects, many organizations utilize formal project management practices. Project management in IS is defined as the application of formal and informal knowledge, skills, tools and techniques to develop a system that provides a desired level of functionality on time and within budget.

Previous research has established a positive relationship between formal project management

practices and project performance . Research also suggests that most IS project problems are related to management, organizational and cultural issues, not technical problems . These findings imply that project management is a critical component of IS project success.

Other IS project management research has considered the relationship between particular project characteristics, project management practices and project performance. Specific project management practices have been recommended based on project size and complexity and technological newness [4]. One study has demonstrated the mediating role of project team size with project performance . Other studies have shown a positive relationship between project size and complexity and certain project management practices and their combined effect on project performance [4, 5]. Still others have focused on the measure of project size or complexity itself [6]. It is clear that a considerable number of studies have explored the relationships among IS projects, project characteristics and project management practices. However, discerning exactly how practices vary with project complexity is still in need of empirical research [7].

Practitioners and industry analysts tout the importance of establishing a project management office (PMO) to implement and enforce standardized project management practices. It has been suggested that organizations with a PMO will experience half the cost and schedule overruns of organizations that do not have a PMO [8], although no known empirical research has confirmed this claim.

A review of the literature reveals the need for empirical research to consider specific project management practices related to varying project size and complexity and the influence of size and complexity on IS project performance. This research is an exploration of current IS project management issues across a wide variety of projects and industries. It considers project size and complexity, specific project management practices and their combined effect on several measures of IS project performance. To overcome the limitation that most prior research has considered only software projects, this study explored both hardware and software development projects. Additionally, the evolving role of

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a project management office was investigated with respect to project management practices and project performance.

The following section presents a review of the literature related to IS project performance, project characteristics, project management practices and the PMO. Following that are sections describing the research hypotheses, methodology and results. The paper closes with a discussion of the findings, limitations and suggestions for future research.

2. Literature Review

2.1 Project Performance

IS project performance has typically been established as a multidimensional construct [9].

Researchers have utilized many measures of project success which can be summarized into six categories:

system quality, information quality, system use, user satisfaction, individual impact of the IS and organizational impact of the IS [9]. Other IS researchers have suggested that project performance measurement should also include project team member satisfaction, stakeholder satisfaction with the project team and the added business value of the IS project .

2.2 Project Characteristics

Past research has shown that certain project characteristics directly impact project management performance. Specifically, project size, technological complexity and change, and the newness of the application influence the outcome of large software projects . IS project size has been found to have a significant negative relationship with project completion [5].

The definitions of IS project complexity and size have, at times, been hard to discern as project complexity is sometimes based on the size of the project. Project size may be based on the dollar value of the project, the number of people on the project team or the number of components comprising the final system. For example, a large IS project might consist of numerous interrelated parts that must function together and may be physically dispersed around the globe [7]. Others, however, distinguish between the technological complexity and size of the project [10, 11].

Project complexity can be impacted by the variety of solutions available to the project team. There is no longer one obvious solution, but choices of many.

Today’s environment may require rapid deployment of software solutions running on distributed platforms, web- based applications, user-friendly interfaces to legacy

systems, purchased application packages or a combination of these and other solutions [12]. The wide variety of technological options available increases the possibility that the organization lacks knowledge of and expertise with a chosen solution. Research has established that lack of experience with a technology and low project- specific knowledge in an organization are associated with a higher risk of project failure [4]. Other research has confirmed that lack of experience with a technology has a direct effect on project completion and an indirect effect on budget variances [5]. Moreover, when a technology is new to an organization, it is more likely that external vendors and/or consultants will participate in the project.

Researchers have suggested that because of new development technologies, integrated package suites and exploding technological innovations, information technology departments may interface with as many as 50 to 100 suppliers to meet organizational needs [12]. This addition of multiple constituents to a project team also increases IS project complexity.

IS complexity has been widely discussed in IS literature; however, very little research has attempted to classify IS projects based on complexity. Some researchers have created IS related frameworks for classifying development methodologies [13] or knowledge-based systems [14]. Industrial projects have been categorized according to level of technological uncertainty and system complexity, but IS projects were only a small subset of the framework .

2.3 Project Management Practices

Project management practices can be described as either formal or informal. Formal project management practices include setting goals, creating plans and providing documented rules, standards and procedures to the project team. Research has repeatedly established a relationship between the use of formal project management practices and project performance. Project planning has been consistently associated with favorable project outcomes in terms of schedule and budget [2].

The need for effective plans and procedures as well as the setting of clear goals and milestones were also found to be critical to project success [3]. A direct link between planning and budget performance [5] and other project outcomes in IS projects has also been established. Other research has noted that project goals impact project planning and the control process [15].

While prior research has focused on formal project management practices, some notable findings regarding informal project management practices must be mentioned. In particular, control can be exercised both formally and informally and research has found that various choices of control methods are related to project performance [16, 17, 18].

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Project managers must be skilled in both formal and informal project management practices and project manager performance has been positively linked to project success. Project management skills can be divided into hard skills (planning, monitoring, coordinating) and soft skills (leading, controlling, resolving conflict, team building) [7]. Specific practices of the successful project manager include planning and documenting the project charter, policies and tasks; team development; frequent and personal internal team communication; gaining senior management and key personnel support; focusing on conflict avoidance and monitoring changes in team performance [19].

The combination of hard and soft skills and formal and informal practices necessary for project management are combined into project management job functions. In a study partially funded by the National Science Foundation, researchers from industry and academia together established specific job functions as essential for good project management in the information technology field [20]. The importance of these specific project management job functions is stressed by both practitioners and in information technology project management textbooks [21].

IS researchers have suggested a contingent approach in applying project management practices based upon the type of IS project being implemented. It has been proposed that the established set of general purpose project management tools (e.g. planning, controlling, etc.) may contribute to project success in varying degrees based on particular project characteristics, such as the level of structure and the familiarity of the technology involved [4]. Additionally, practitioners have recommended adjusting project management practices based on the phase of the project [22]. Projects in the initiation phase may require different project management practices than projects in the planning or execution phases.

2.4 Project Management Office

Practitioners have long been touting the need for better project control through the establishment of a project management office [23, 24]. A project management office (PMO) is a formal, centralized layer of control between senior management and project management. Early project offices were usually devoted to one project. By contrast, today’s multiple-project or project portfolio environment requires a PMO to provide a combination of managerial, administrative, training, consulting and technical services for a broad range of projects throughout an organization [25].

The general purpose of a PMO is to ensure consistency of approach across projects. In support of this effort, the project office establishes project

management methods and procedures, defines and implements project structures, implements automated project management systems and tools, and institutes project management education and training [26].

Through the consistency of approach to projects, it is assumed that project performance will improve [26].

Other benefits of a PMO are reported to include formalized and consistent project selection, formalized and consistent project management, more efficient coordination of multiple projects, improvement in project performance in terms of cost, schedule, scope and people, and improvement in organizational profitability [27].

Although practitioner journals have repeatedly stressed the importance and benefits of a PMO, no known academic research has explored the relationship between the existence of a PMO and the use of specific project management practices or project performance.

In summary, a great deal of literature has addressed various IS project management practices.

However, there has been little research that allows for different types, sizes or complexities of projects even though academics have suggested that project characteristics should impact the type of project management practices employed [7, 28, 29].

Additionally, no known research has attempted to establish a link between a PMO and the effective use of project management practices or between the establishment of a PMO and project performance.

The current research will contribute to the project management literature by empirically studying the relationship between project size and complexity, project management practices, including the existence of a PMO, and project performance.

3. Research Hypotheses

Today’s technological and organizational environment requires a new examination of the project management practices employed in IS projects. As IS projects become more complex, established project management practices may or may not be as effective as they were when most projects were in-house or domestic in nature. The research questions in this study explore the relationships between project size and complexity, current project management practices, the establishment of a PMO and project performance. Based on the preceding review of literature, it is expected that specific factors are related to IS project success.

As project size and complexity increase, greater risk is introduced to the IS project. With projects of greater size and complexity, it has been shown that schedules and budgets are negatively influenced. We also believe that working with projects of greater size and complexity will impact the final quality of the project due to the greater dispersion of people, responsibilities and

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decision-making. Therefore, we believe the greater the IS project size and complexity, the less likely it is that the project will finish on schedule, within budget and with all the quality objectives met. This leads to the first set of hypotheses of the current study:

H1a: IS project size will influence project schedule adherence.

H1b: IS project size will influence project budget adherence.

H1c: IS project size will influence project quality.

H2a: IS project complexity will influence project schedule adherence.

H2b: IS project complexity will influence project budget adherence.

H2c: IS project complexity will influence project quality.

In combating project risk, many organizations utilize formal project management practices. Research has established that certain project management practices are associated with better project performance. A more recent trend is the establishment of a PMO to ensure consistent project management practices are followed.

Organizations institute PMOs to provide better communication and coordination activity for projects and to act as a clearinghouse for project information. We believe the presence of a PMO is likely to result in an organization utilizing established practices. These beliefs are stated in the hypothesis that follows:

H3: Organizations with a PMO are more likely to utilize established project management practices.

Moreover, it is assumed that PMOs add the value of greater communication and coordination to IS projects.

Supporters of PMOs argue that project costs and schedules will benefit from establishment of a PMO.

Therefore, the presence of a PMO should influence IS project performance directly as addressed by the following hypotheses.

H4a: The presence of a PMO will influence IS project schedule adherence.

H4b: The presence of a PMO will influence IS project budget adherence.

H4c: The presence of a PMO will influence IS project quality.

Additionally, we are interested in determining if project size and/or complexity determine which, if any, project management practices are utilized. Specific project management practices will likely be utilized based on varying levels of project size and complexity. Projects which are large or highly complex are expected to require different project management practices than projects which are smaller or less complex. For example, a small project with technology that is not considered new to the organization would not require the level of formal project management that a large project utilizing new technology

would require. Certain project management practices will be considered more effective when the project is large, costly or otherwise complex. Therefore, we suggest that project size and complexity are related to the use of certain project management practices. The related hypotheses follow.

H5a: IS project size will influence the use of particular project management practices.

H5b: IS project complexity will influence the use of particular project management practices.

4. Methodology

4.1 Measurement of Constructs

The purpose of this study was to explore IS project management in the current business environment by examining project size and complexity, project management practices, the impact of a PMO and project performance. The constructs of this research include IS project performance, project complexity, project size, project management practices and the existence or nonexistence of a PMO.

For this study, IS project performance is considered to be a multidimensional construct measured in terms of meeting budgets, schedules and quality objectives . Schedule is a categorical variable and was classified as either met or not met. Budget was also a categorical variable and considered met or not met. IS project quality was measured by the percentage of quality objectives (both technical and functional) that were met.

IS project size and complexity have been operationalized via many different constructs in the past and at times the terms have been used interchangeably.

As such, we chose to develop a distinct scale for each construct, separating IS project size from complexity.

Drawing on relevant literature, IS project complexity was considered in terms of newness of the technology to the organization and whether or not the required technical expertise was available within the organization. Project size consisted of components also drawn from IS project management literature and included project cost, project length in months, the number of systems the project connected with, the number of people on the project team and the number of outside vendors or suppliers involved in the project.

To verify the distinction between the two constructs, a confirmatory factor analysis was used to check the convergent and discriminant validity of the IS project size and complexity constructs. An exploratory factor analysis with Varimax rotation was employed and the results are summarized in Table 1 below. The seven items demonstrated a clear factor structure. Two factors with eigenvalues greater than one emerged from the

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analysis and these two factors collectively explained 60.11 percent of the variance.

Table 1. Factor analysis results of IS project size and complexity constructs

Item

IS Project Size

IS Project Complexity

Project cost .892 .186

Number of vendors .821 .236 Number of team

members

.745 .148

Number of systems connected

.578 .174

Project Length .491 -.092 New technology -.275 .808 Expertise

availability

-.404 .751

Eigenvalue 2.840 1.368

% of variance 40.57 19.54 The internal consistency of the IS project size construct was assessed using Cronbach’s alpha. The five measures constituting project size yielded a reliability of .78. An alpha of at least .5 is recommended for exploratory studies such as the current study [30].

Therefore, the construct for IS project size is considered reliable.

The measurement items for project complexity were both dichotomous; thus standard measures of reliability, such as Cronbach’s alpha, could not be used.

Rather, the degree to which items associated with a given scale exhibited complete conformity or non-conformity was assessed [31]. Complete conformity occurs when coded responses are identical for all items associated with a scale. Non-conformity occurs in two-item scales when the coded response for one item is different from the coded response on the other item. A two item scale is considered acceptable if the level of complete conformity is substantially higher than the level of nonconformity.

The IS project complexity displayed a complete conformity level of 74.8% and a non-conformity level of 24.6% indicating an acceptable scale.

Thirteen project management practices were considered based on a review of IS project management literature. Since one objective of this study was to discern how specific project management practices vary with project size and complexity, the 13 project management practices were considered individually. The practices were rated on a five point scale from highly ineffective to highly effective or not used. The project management practices are listed and labeled for future use in Table 2.

Table 2. Labeled project management practices in the current study

Label Project Management Practice

DS Define scope

IDST ID Stakeholder decision-makers and escalation procedures

WBS Develop detailed task list or work breakdown structures

TIME Estimate time requirements

FLOW Develop project management flow charts IDRS Identify required resources and budget CONT Identify and evaluate risks to prepare

contingency plan

INTDP Identify interdependencies MILE Identify and track critical milestones PHAS Participate in project phase review SECR Secure needed resources

CHNG Manage the change control process REPT Report project status

The final construct in this research was the PMO. The relationship of a PMO with project performance or with the use of certain project management practices has yet to be empirically studied;

therefore existing scales were not available for the PMO construct. For this study, the PMO construct was operationalized using one question which discerned whether or not the organization had an established PMO.

4.2 Sample Description

Data for this study was collected through a web- based survey of IS project managers. The survey contained questions designed to collect information regarding respondent demographics, project performance, project and project team characteristics, and project management practices related to the respondent’s most recently completed project. The survey was pre-tested on six IS project managers and project team members in three different organizations. The test group provided feedback regarding survey content and wording which was integrated into the final survey. The web-based survey was then tested for usability by several experienced project managers and Ph.D. students.

The targeted participants for this study were IS project managers who were identified from a mailing list supplied by the Project Management Institute (PMI).

Invitations to participate in the survey were mailed to the project managers and follow-up invitations were mailed two weeks later. The survey was available to the project managers for a period of six weeks.

Of the two thousand addresses obtained from PMI, 89 were undeliverable, reducing the potential sample size to 1911. From the sample of 1911, 129

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individuals completed the survey for a response rate of 6.7%. Most of the respondents held the project manager title (73%), were male (71%) and between the ages of 30 and 59 (92%). Respondents representing public, private, large and small organizations provided survey data as illustrated in Table 3.

Table 3. Types and sizes of organizations in the study sample

Private Public Total

Large (>500)

Small (”500)

Large (>500)

Small (”500) Communications

& Media

11.8% 5.3% 8.6% 0.0% 6.4%

Financial Services

11.8% 10.5% 22.9% 0.0% 11.3%

Government 5.9% 10.5% 14.3% 16.7% 11.9%

Manufacturing 11.8% 5.3% 8.6% 0.0% 6.4%

Technology 23.5% 42.1% 34.3% 66.6% 41.6%

Other 35.2% 26.3% 11.3% 16.7% 22.4%

Of the 129 reported projects, more than half were on schedule (51.9%) and more than half were within budget (53.5%). Nearly half (45.7%) of IS projects reportedly met all of the project’s quality objectives. A considerable number of projects met both schedule and budget targets and achieved all of the required quality objectives (22.7%).

The reported projects represented a wide variety of project types as well with the largest percentage being application development (45%). Most projects cost over one million dollars (52%), lasted eighteen months or less (75%), involved up to twenty vendors (77%), included up to thirty project team members (77%) and required less than fifteen connections to others systems (83%).

IS projects involving infrastructure such as data center upgrades and telecommunications networks were the most expensive types of projects (µ = $75M and

$68M respectively). Outsourced IS projects were reported to have the longest mean project length (28 months). Network type projects logically were required to connect with the largest mean number of other systems (387) and these projects also reported the largest mean size project teams (98) and the highest mean number of involved vendors (90).

It is clear from the descriptive statistics that the sample represented a broad range of IS project types across a variety of industries and from small and large, public and private organizations. The extensive representation of projects and organizations should reduce concerns of bias in the sample.

Non-response bias is a serious threat to the validity of empirical results in survey research; therefore we tested for this problem by comparing early versus late

respondents [32]. The results of the analysis indicate that there are no significant differences between early and late respondents along key sample characteristics, that is, demographics of the respondents and organizations, project dimensions and performance measures (alpha = 0.05).

5. Results

This research was intended to explore how IS project size, complexity, project management practices, a PMO and project performance are related. In order to study these constructs, ten distinct hypotheses were formulated. Following is a summary of the results of the data analysis.

5.1 Project Size and Complexity Related Hypotheses

Logistic regression was chosen as the appropriate statistical technique to analyze data relative to the hypotheses involving IS schedule, budget and quality measures (H1a-H1c, H2a-H2c) since all three measures utilized categorical dependent variables. Binary logistic regression was utilized for project schedule and budget;

ordered logistic regression was utilized for quality. For hypothesis testing, a forced entry is recommended [33]

and was thus used in this analysis.

This study was interested in determining whether IS project size and/or complexity influence measures of project performance. For this type of inquiry, the statistic of interest in a logistic regression is the Wald statistic.

This statistic has been recommended for cautious use when the regression coefficient (ȕ) is large because the Wald statistic may be underestimated [34]. However, in the current study, the regression coefficients were small and thus were not cause for concern.

The results of the binary logistic regression are presented in Table 8. Project size was found to be a significant predictor of budget attainment but not of schedule adherence. Project complexity was not a significant predictor of either of these performance measures.

Results from the ordered logistic regression which analyzed the relationship between IS project size and complexity and levels of project quality achieved are also reported in Table 4. IS project size was found to be a significant influence on quality. That is, as project size increased, project quality decreased. Surprisingly, project complexity did not have a significant effect on project quality.

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Table 4. Logistic regression for IS project size and complexity with project schedule, budget

and quality

ȕ Wald df Sig.

Project Schedule

Project Size -.603 3.1 1 .078

Project Complexity .083 .128 1 .720

Project Budget

Project Size -.974 5.56 1 .018*

Project Complexity .101 .149 1 .699

Project Quality

Project Size -.651 6.48 1 .011*

Project Complexity .234 1.11 1 .293

5.2 PMO Related Hypotheses

Hypothesis 3 suggested that organizations with a PMO would be more likely to utilize standard project management procedures. The 13 project management practices were categorized as either used or not used, creating a dichotomous dependent variable to be associated with the dichotomous independent variable for PMO. This hypothesis was tested using Fisher’s exact test. The Fisher’s exact test is used when a Chi Square test is warranted, but one or more of the cells has a value of five or less. As reflected in Table 5 below, no significant associations were uncovered in the analysis, suggesting that organizations without a PMO are just as likely to utilize standard project management practices as those with a PMO.

Table 5. Fischer’s exact tests for PMO and project management practices

df Fisher’s

Exact Test

Define Scope 1

ID Stakeholders 1 .732

WBS 1 .543

Estimate Time 1 .471

Flowcharts 1 .163

ID Resources 1 .529

Contingency Plan 1 .390 ID Interdependencies 1 .537

Milestones 1 .661

Phase Review 1 .436

Secure Resources 1 .732 Change Management 1 .378

Report Status 1 .491

†Note: All respondents reported using scope definition, thereby eliminating the comparison group.

The hypotheses related to the influence of a PMO on dimensions of project performance (H4a – H4c) were measured using Chi Square tests since the

independent variable ( PMO) and dependent variables (IS project schedule, budget and quality) were categorical.

The strength of the relationship between a PMO and meeting project schedule is non-significant, indicating that having a PMO does not necessarily influence whether or not projects are completed on schedule. A similar result was obtained for the relationship between PMO and project quality. However, the relationship between PMO and meeting project budget was significant at p=.033, signifying that a PMO does improve the project team’s ability to complete a project within budget. The relative statistics are presented in Table 6 below.

Table 6. Chi Square tests for PMO and project performance

Chi Square df Sig.

PMO -> Schedule 2.31 1 .129 PMO -> Budget 4.55 1 .033*

PMO -> Quality 6.35 4 .174 5.3 Project Management Practices Related Hypotheses

Hypotheses 5a and 5b suggested that IS project size and complexity would influence the use of certain project management practices. In these tests, each of the 13 project management practices are categorical dependent variables (either used or not used) and IS project size and complexity are continuous variables. For this analysis, binary logistic regression was chosen as the appropriate statistical technique. Only 11 of the project management practices produced meaningful results for this analysis because P1-DF (scope definition) and P13- RPT (reporting status) displayed no variance. All projects were reported as utilizing scope definition and all but one utilized project reporting as project management functions, causing these two practices to appear as constants in the statistical analysis.

IS project size was not found to be a significant predictor of the use of any particular project management practice. However, IS project complexity was found to be a significant predictor of the use of project phase reviews.

The results of the logistic regressions are summarized in Table 7.

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Table 7. Binary logistic regressions for IS project size and complexity with the use of project management practices

IS Project Size IS Project Complexity Project

Mgmt Practice

ȕ Wald df Sig. ȕ Wald df Sig.

IDST 22.062 1.869 1 .172 -.178 .048 1 .826 WBS -.139 .891 1 .345 -.466 .891 1 .345 TIME 1.385 .190 1 .663 2.154 .567 1 .451 FLOW .045 .039 1 .843 -.423 3.376 1 .066 IDRS .339 .018 1 .892 -

8.453

.011 1 .915 CONT -.126 .308 1 .579 .065 .046 1 .829 INTDP .158 .078 1 .780 .460 .593 1 .441 MILE 2.444 .546 1 .460 .205 .088 1 .767 PHAS .188 .108 1 .742 -.741 3.967 1 .046*

SECR 14.084 .902 1 .342 -9.08 .017 1 .897 CHNG 1.594 .600 1 .439 -.328 .418 1 .518

6. Discussion

Four important contributions were derived from this study. First, constructs for IS project size and technical complexity were developed which exhibited acceptable measurement properties. Past researchers have utilized a variety of definitions for project size and complexity, even blurring the two at times. This research produced two distinct constructs for size and complexity which may be useful in future IS project research.

Second, empirical evidence was found to support the direct relationship between IS project size and complexity and certain measures of project performance.

In the current study, project size was linked to budget adherence and project quality. That is, as project size increased the likelihood of adhering to the project budget and meeting project quality objectives decreased. As projects increase in size, the cost, project length, number of team members, vendors and required system connections are greater. Larger projects have more difficulty meeting project budgets due to the cost of the technology, increased staff allocated to the project, greater number of vendors hired and the longer duration of the project requiring devoted resources. As project size increases, project quality likely suffers because larger projects create greater demands for coordination and control. Additionally, larger projects are apt to have many more quality requirements than smaller projects.

Although not significant, the relationship between IS project size and schedule adherence was found to be inverse as well, indicating the same issues that harm project budget and quality likely influence project schedule as well, just not to the same degree. Prior studies have empirically linked project size and/or complexity to project completion, project success and project budget. This study contributes to established theory by affirming the project size-budget link. The

study also contributes to existing theory by empirically linking project size with project quality.

IS project complexity was not found to be a significant predictor of any of the three project performance measures. Our measure of project complexity considered the newness of the technology to the organization and the availability of the required technical skill within the organization. The non- significant findings are likely due to the fact that it is commonplace for organizations to hire consultants or vendors to supply the expertise found to be lacking for IS projects. Previous research has established relationships between project complexity and project success, project completion and project budget adherence. The current study calls into question some previous findings.

Certainly further exploration of this situation is warranted.

It is also possible that the lack of significant findings was due in part to the measure of complexity established. The measure was comprised of two bipolar questions and as such may have been too insensitive to detect significant relationships.

Third, this study launched an initial exploration of the PMO. The PMO was empirically linked only to IS project budget. This finding implies that a PMO has little influence on the quality or schedule adherence of IS projects, but it does influence the ability to complete a project within budget. Perhaps budget is a more tangible part of project management and can be measured and/or controlled more easily by the PMO than the less tangible factors of schedule and quality.

Contrary to the assertions of practitioners, empirical support was not established for influence of a PMO on the use of standard project management practices. One possible explanation for this lack of support is the fact that IS project managers supplied the sample data. Because these respondents are affiliated with the PMI, it is likely that they are educated in the use of standard project management practices. Thus, even though their respective organizations may not support a PMO, the project managers themselves institute standard practices. Another possible explanation is that because of the recent attention focused on project management in both business and academia, standard practices are followed by many organizations. Still, there is a need to empirically substantiate the many claims made regarding the importance of a PMO. For example, a PMO may be more appropriate for an organization that does not employ certified or professional project managers. This research should spur further inquiry in this area.

Finally, as researchers have demanded [7], this study made a first attempt to link IS project size and complexity with various project management practices.

Previous researchers have suggested a contingent choice of project management practices based upon the size and/or complexity of a project. We found the vast

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majority of organizations utilize a common set of project management practices regardless of project size or complexity, indicating that a contingent approach has not been adopted. As such, this study calls into question prior theoretical discussion regarding the contingent choice of project management practices.

In this initial inquiry, we tested only if project size and complexity were related to the use or non-use of standard project management practices and a PMO. The results indicate that only phase review was statistically linked to IS project complexity. This is a logical finding signifying that if technology is new to the organization or that reliance on expertise falls outside the organization, project managers are more often instituting phase review as a means of control. The lack of statistical support for other practices may be influenced by the sample respondents. Since the survey respondents are affiliated with the PMI, it is reasonable to believe that most, if not all, of them already appreciate the importance of standard practices. Hence, a similar study of non-PMI members is warranted.

This work is not without limitations. The use of a respondent population supplied by the PMI may introduce project management bias into the sample.

Although project management practices are widely accepted in business and in academia, a future study should consider a wider population of respondents not necessarily affiliated with the PMI. A second limitation is that of a single survey respondent. Respondents were asked to report on their most recently completed project.

However, since project managers chose which projects to report, there may indeed have been a tendency to report successful projects. The large number of projects reporting high quality raises a question as to whether the respondents were biased in the tendency to only report successful projects. Future research should include multiple respondents to insure a well-rounded perspective of the reported project. While the low response rate to the survey may be of concern, the respondent demographics demonstrated that a wide variety of projects, industries and organizations were represented.

Despite limitations, this study has implications for both IS research and practice. The groundwork has been laid for further refinement of IS research based on the project size and complexity constructs established.

Moreover, there is still a need to further define the relationship between IS project size and complexity and measures of performance and particular project management practices For example, what specific factors or processes mediate the relationship between IS project size and budget and quality? Are there precautions that can be taken to lessen the impact of larger projects on these performance measures? Also of interest is how do organizations satisfy the need for technical expertise when it is not available within the organization. This

study has revealed many questions which are still to be answered.

Researchers must also further explore the importance of a PMO. The intended benefits of a PMO must be empirically supported or the PMO is in danger of becoming a fad that organizations follow without recognizing any real advantage. Additionally, just as the emergence of a Chief Information Officer was the result of the influence of information technology in organizations, so is the emergence of a PMO. In addition to or rather than establishing a PMO, many organizations create a Project Management Officer. The role of a Project Management Officer and the role of the PMO need to be empirically studied.

Practitioners gain insight from this study as well.

It is clear that IS project size influences certain performance measures. Large projects require more rigid control to insure budgets and quality objectives are met.

Managers should carefully consider the establishment of a PMO. Organizations which already employ professional project managers may not glean the same benefit from a PMO as organizations without professionals on staff. Organizations which have embraced a PMO should consider establishing measures of effectiveness for the PMO. It is important to ascertain the exact contribution the PMO is making to the organization in order to calculate its worth.

7. Conclusion

IS projects continue to be an important responsibility for organizations. Rapid technology advancements and globalization of organizations necessitated a fresh look at project management issues in IS. This research was an exploration into current IS project management issues. It addressed a lapse in the IS literature regarding the relationship of IS project size and complexity with the use of particular project management practices and measures of project performance. The study was also a first attempt to empirically investigate the role of a PMO in IS projects. Although the results did not produce an alarming number of statistically significant findings, the fact that certain relationships were not established is of keen interest. This research has provided new insights into the project management issues and uncovered important relationships and non- relationships relative to the IS project environment.

8. References

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References

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