Project Management Assets and Project Management Performance: Preliminary Findings

Transcription

1 Project Management Assets and Project Management Performance: Preliminary Findings Kam Jugdev 1, Gita Mathur 2, Tak Fung 3 1 Athabasca University, Faculty of Business, Athabasca, AB, Canada 2 San José State University, College of Business, San José, CA USA 3 Information Technology, University of Calgary, Calgary, AB, Canada Abstract--The objective of this research is to examine the degree of competitive advantage from project management assets by exploring the link between the characteristics of project management assets as independent variables and project management performance outcomes as dependent variables. This paper analyses data from responses to an online survey by 198 North American Project Management Institute members. Factor analysis is used to identify the characteristics of project management assets and the project management performance outcome factors. Seven factors that comprised the characteristics of project management assets, three factors that comprised organizational support for project management assets, and two factors that comprised the project management performance outcomes were extracted from the data analysis. Preliminary findings are presented in the paper. We draw on the Resource Based View of the firm as a lens to examine and validate project management capabilities as a source of competitive advantage. This paper contributes an improved understanding of project management as a source of competitive advantage for scholars and practitioners interested in project management. I. INTRODUCTION Using the Resource Based View (RBV) of the firm, we take the perspective that firms are a collection of resources, that the project management process is a subset of resources of a firm, and that some of these project management resources are strategic and, therefore, a source of competitive advantage for the firm. Resources are considered strategic if they have the following competitive characteristics, they provide economic value (Valuable), they are unique (Rare), they are difficult to copy (Inimitable), and they have Organizational Support. The presence of these competitive characteristics, referred to as VRIO [1-3], lead to competitive advantage. A resource contributes to competitive parity by being valuable and having organizational support. If a resource is both valuable and rare, and has organizational support, it contributes to temporary competitive advantage. A resource needs to be valuable, rare, inimitable, and have organizational support to provide a sustained competitive advantage. The project management process has been getting an increasing amount of attention as a means to improve a firm s competitive position. The academic literature has focused primarily on operational aspects of project management, and the role of this process as a strategic capability, while it has been recognized, is still understudied. Our prior research has attempted to highlight the competitive advantage that can be gained from project management assets, empirically linking project management assets to the achievement of the characteristics, valuable, rare, inimitable, and organizationally supported [4-6]. In this paper, we report on preliminary findings using a revised survey instrument that draws on the VRIO framework to examine the factors that comprise these competitive characteristics of project management assets in order to link them to project management performance outcomes. We draw on a new set of data, collected using this survey instrument, and present the results of a factor analysis in this paper. The development of a path model based on data reported in this paper will be addressed in future research. Our objective is to make a contribution to the growing body of empirical research that provides an improved understanding of project management as a source of competitive advantage for scholars and practitioners interested in project management. The sections that follow include the literature review, the study methodology, a discussion of findings, conclusions, limitations, and the next steps in this research program. II. LITERATURE REVIEW The RBV examines competitive advantage in terms of a company s many resources or assets (e.g., financial, human, organizational, physical, social, technological). The firm s resources can be tangible (concrete; physical; codified or based on explicit knowledge) or intangible (tacit; unspoken but understood). Only a subset of a these resources, classified as strategic assets, contributes to its competitive advantage [7]. The RBV and the perspective that strategic assets contribute to a firm s competitive advantage are widely accepted in the literature. Strategic assets (e.g., intellectual property rights, reputation, brand, and culture) are resources that involve explicit and tacit knowledge [8-11] that is embedded in a company s unique skills, knowledge, resources, and ways of working [12, 13]. As a recent review indicates, the RBV continues to hold merit [14]. The VRIO framework has emerged from this perspective as a useful way of characterizing strategic assets [1, 3]. The RBV and Barney s VRIO framework have been widely used in empirical studies on strategic assets [2, 15-27]. Project management is a set of processes that encompasses the tools, techniques, and knowledge-based practices applied to projects, to achieve organizational goals and deliver products or services [28-30]. Project management practices involve tangible and intangible assets. 1887

2 Tangible resources involve codified or explicit knowledge while intangible resources are based on tacit knowledge. Codified and tacit knowledge have also been labeled as know-what and know-how [11]. To date, considerable project management literature has focused on the tangible resources and codified knowledge shared through research on project management offices, methodologies, databases, documents, and tools and techniques [31-38]. Following the RBV logic, the lesserstudied intangible project management resources are more likely to be rare and inimitable, and therefore more likely to be sources of competitive advantage. Intangible project management resources include tacit knowledge, the application and sharing of tacit knowledge, and processes and relationships for facilitating this sharing. While explicit knowledge is more formal, codified, and transmitted systematically [39], tacit knowledge is shared informally through social exchanges [40] and some examples in project management include brainstorming, mentoring, learning through shadowing, and storytelling [41, 42]. Project teams often share knowledge through informal exchange of ideas and practice in communities of practice (groups where members regularly engage in sharing and learning, based on their common interests) [43]. A few studies have applied the RBV and the VRIO framework to discuss how project management might contribute to a company s competitive advantage [28] [4-6]. Our literature review indicates that the stream of research on project management using the RBV lens is, however, evolving [44-47]. With firms increasingly focusing on project management as a source of competitive advantage to help leverage their resources [48, 49], we believe that an improved understanding of project management as a source of competitive advantage motivates further investigation. III. CONCEPTUAL MODEL We propose a high-level conceptual model (Figure 1) based on the literature to link the characteristics of project management assets, as independent variables, to project management performance outcomes, the dependent variables. Project management resources are classified as valuable (V), rare (R), and inimitable (I). It is expected that the level of project management performance will vary from competitive parity, to temporary competitive advantage, to sustained competitive advantage depending on whether the assets are valuable, rare, or inimitable. Since organizational support is required for all three classes of assets to lead to competitive advantage, we consider organizational support (O) as a moderating variable for these valuable, rare, and inimitable project management assets to lead to competitive advantage from the project management process. This paper reports on the findings from a factor analysis of data collected using a survey tool to explore the factors that constitute the independent, moderating, and dependent variables in this conceptual model. The linkages between the variables are beyond the scope of this paper. The development of a path model to link the variables in the conceptual model will be addressed in future research. Characteristics of Project Management Asset Valuable Rare Degree of Competitive Advantage from the Project Management Process Inimitable Organizational Support Figure 1: Conceptual model linking characteristics of project management assets to project management performance outcomes 1888

3 IV. METHODOLOGY This study draws on and builds upon a previous empirical study from which we have reported and published our earlier findings on the factors that we found to constitute project management strategic assets and project management process outcomes [4-6]. This earlier study resulted in development of factors that constitute project management strategic assets and project management process outcomes and structural equations models that show their relationship. Our earlier work was limited by the survey tool and the data collected. We refined our survey tool, pre-tested it, and conducted this study with the intent of elaborating the prior model, and in addition, looking for relationships between characteristics of project management assets and project management performance outcomes. We developed our survey design using the guidelines recommended by experts [50-53]. We used multiple items for each construct of interest. These items were adopted from the empirical literature and our earlier studies on this topic, and further developed through a focus group process with seven experienced project managers. Their feedback enabled us to include examples in our question wording as well as ensure that our items were more clearly worded. The final survey consisted of 17 structured questions and an eighteenth open-ended question soliciting feedback on additional comments on the survey topic. The survey was based on a 7-point ordinal Likert Scale, appropriate for perception-oriented questions, with the anchors being Strongly Agree and Strongly Disagree. We minimized retrospective bias by asking participants to respond in the context of projects within the past year. The survey questions were designed to focus on the constructs of interest in our theoretical model as outlined below. Question 1 addressed valuable project management resources with 12 items Question 2 addressed rare project management resources with 12 items Question 3 addressed inimitable project management resources with 12 items Question 4 addressed the overall maturity of the project management process with 1 item Question 5 addressed the organizational alignment of project management practices with the company s mission, services, and products and the construct organizational support with 3 items Question 6 addressed project communication and the construct organizational support with 3 items Question 7 addressed organizational integration and the construct organizational support with 5 items Question 8 addressed impact of project management resources on project management performance with 5 items Question 9 addressed impact of project management resources on firm-level performance with 6 items Questions addressed demographics Question 18 was open-ended. Note: For the purposes of this paper, we do not report on Questions 4 or 18. We purchased a randomly generated mailing list for 4,000 members from the Project Management Institute. The list represented a subset of the institute s members from North America 3,200 members from the United States and 800 members from Canada. Out of the 4,000 letters mailed, 315 letters (7.9%) were returned as undeliverable. A total of 240 individuals indicated an interest in completing the survey. We acknowledge that our survey involved non-response bias because we were only able to follow up with those who indicated interest in completing the survey. We sent these interested participants the survey link and two follow up reminders, each approximately a week apart. This approach enabled us to secure 212 responses, which is a response rate of 5.75%, a fair rate for internet based surveys since different survey approaches involve different variables and response rates [53, 54]. After data cleaning, we found we had a sample size of 198 respondents, which is considered fair for exploratory factor analyses [54]. We hosted our survey at Zoomerang as online surveys are faster and more cost-effective than mail-out surveys and can help reduce non-response errors [55]. While data was reported by individual participants, the unit of analysis was the project management process. The 198 study participants represented a group of experienced project management professionals. A large majority of the participants (80%) had their Project Management Professional designation. Nearly 60% of the participants worked as project managers and nearly 30% worked in senior level capacities. Over half (55%) had advanced degrees. About four-fifths of the participants were from four economic sectors - Information Technology, Financials, Government, Health Care, and Industrial. Close to three-quarters of the study participants came from companies with annual sales revenues greater than $50 million. About half of the respondents worked at companies with over 5,000 employees. Roughly half the participants represented companies that were 0-50 years old and the rest were from companies that were older and more established. The gender ratio was 74.7% male to 25.3% female We used SPSS v. 15 to conduct descriptive statistics, factor analysis and extract factors representing project management resource characteristics (independent variables) and the degree of competitive advantage achieved from the project management process (dependent variable). We used the Principal Components Extraction method with Varimax (variance maximizing) rotation. This extraction method is widely used, understood, and conforms to the factor analytic model in which common variance is analyzed with the unique 1889

4 and error variances removed [54]. We used 0.40 as a cut-off to identify items with the highest loadings for inclusion with a factor [56]. None of our loadings were lower than 0.5. Eigenvalues over one were used to extract reliable factors. Cronbach s alpha measures how well a set of items measures a single unidimensional latent construct. A reliability coefficient of 0.70 or higher is acceptable in the social sciences [57]. We used this test to assess the internal consistency of the items within each construct. We extracted seven factors for the independent variables (valuable, rare, and inimitable characteristics of project management resources). We extracted three factors for the moderating variable, organizational support. We extracted two factors for the dependent variable, project management performance. The results of the factor analysis are discussed in the section that follows. V. DISCUSSION OF FINDINGS The seven factors that comprised the characteristics of project management assets (the independent variables), three factors that comprised organizational support for project management assets (the moderating variable), and two factors that comprised the project management performance outcomes (the dependent variables) that were extracted from the data analysis are numbered from 1 through 12 and are labeled to reflect the items that define them. The items in each of these twelve factors are presented in the discussion that follows and the variance explained by these factors and Cronbach s Alpha are provided for each factor. The rotated component matrices from the factor analysis are available upon request. Factors 1, 2, and 3 represent valuable characteristics of project management resources and were extracted from data collected from Question 1. The total variance explained by these was 64.7 percent. 1. Valuable Project Management Resources (Structured Knowledge) consisted of 7 items with factor loadings from and a Cronbach s Alpha of The variance explained was 31.2 percent. The items included project management offices, project job shadowing, project management methodologies, databases, project management templates, printed project management material, and mentoring. 2. Valuable Project Management Resources (Unstructured Knowledge) consisted of 3 items with factor loadings from and a Cronbach s Alpha of The variance explained was 18.9 percent. The items included project social capital, tacit project management knowledge, and project management communities of practice. 3. Valuable IT Resources consisted of 2 items with factor loadings from and a Cronbach s Alpha of The variance explained was 14.6 percent. The items included computer hardware and software. Factor 4 and 5 represent rare characteristics of project management resources and were extracted from data collected from Question 2. The total variance explained by these was 64.0 percent. 4. Rare Knowledge Sharing Project Management Resources (Processes) consisted of 6 items with factor loadings from and a Cronbach s Alpha of The variance explained was 32.6 percent. The items that we considered most strongly in the factor labeling included project job shadowing, project mentoring, project management communities of practice, and project management offices. The item project databases loaded heavily on Factor 4 (0.715) and we expect that project databases capture and share process knowledge. The item printed project management material loaded the least heavily on the Factor 4 (0.615) and these materials are also expected to document and share process knowledge. 5. Rare Knowledge Sharing Project Management Resources (Tools) consisted of 6 items with factor loadings from and a Cronbach s Alpha of The variance explained was 31.4 percent. The items that had the highest loadings included project related software, computer hardware, methodologies, and templates. The last two items, tacit project management knowledge and project social capital had the lowest loadings and loaded very closely on both Factor 4 and Factor 5 and were, therefore, not considered in the labeling. Factor 6 and 7 represent inimitable characteristics of project management resources and were extracted from data collected from Question 3. The total variance explained by these was 65.4 percent. 6. Inimitable Codified Project Management Resources (Knowledge Practices) consisted of 7 items with factor loadings from and a Cronbach s Alpha of The variance explained was 35.1 percent. The items included difficult to imitate project management related software, computer hardware, databases, methodologies, printed material, templates, and project management offices. 7. Inimitable Uncodified Project Management Resources (Knowledge Practices) consisted of 5 items with factor loadings from and a Cronbach s Alpha of The variance explained was 30.3 percent. The items included difficult to imitate project social capital, tacit project management knowledge, project management communities of practice, mentoring, and job shadowing. The factor analysis yielded three factors that represent the moderating variable, organizational support for project management assets. Factor 8, 9, and 10 were extracted from data collected from Questions 5, 6, and 7 respectively. Single factors were extracted from the data for each of these questions. 8. Project Management Alignment consisted of 3 items with factor loadings from and a Cronbach s Alpha 1890

5 of The variance explained was 84.0 percent. The items included the importance of the quality of project management practices to the company s mission, services, and products. 9. Project Management Communication consisted of 3 items with factor loadings from and a Cronbach s Alpha of The variance explained was 82.6 percent. The items included ability to communicate upward in the project hierarchy, upward in the company hierarchy, and openly on the project. 10. Project Management Integration consisted of 5 items with factor loadings from and a Cronbach s Alpha of The variance explained was 71.9 percent. The items included a company environment that promotes sharing of knowledge/information, a company environment that encourages learning, people trusting each other, people working well together, and upper management support in critical project phases. The factor analysis yielded two factors that represent the dependent variables, project management performance outcomes. Factor 11 and 12 were extracted from the data collected from Question 8 and Question 9 respectively. Single factors were extracted from the data for each of these questions. 11. Project Management Performance consisted of 5 items with factor loadings from and a Cronbach s Alpha of The variance explained was 78.9 percent. The items included achievement of project scope requirements, project schedules, customer expectations, quality of deliverables, and project costs through project management processes. 12. Firm-level Performance consisted of 6 items with factor loadings from and a Cronbach s Alpha of The variance explained was 69.8 percent. The items included achievement of sales targets, customer loyalty, profitability levels, market share, continuous innovation, and customer satisfaction through project management resources and capability. All of the factors consisted of three or more items except the third factor for Q1, which had 2 items). We retained this two item factor because the items were on computer hardware and software, both of which strongly pertain to IT management. Work on path analysis and building of structural equation models that show the relationship between the factors is in progress and will be reported in upcoming papers. VI. CONCLUSION In this study, we conducted an online survey with 198 North American Project Management Institute members. We used factor analysis to identify the characteristics of project management assets and the project management performance outcome factors. Seven factors that comprised the characteristics of project management assets, three factors that comprised organizational support for project management assets, and two factors that comprised the project management performance outcomes were extracted from the data analysis. The factors extracted are aligned with the Resource Based View of the firm that only a select set of its resources are sources of competitive advantage. These resources add economic value, are rare, and are difficult to imitate. The three factors extracted as characterizing valuable project management assets involved structured knowledge, unstructured knowledge, and IT resources. The two factors extracted as characterizing rare project management assets involved knowledge sharing resources, both processes and tools. The two factors extracted as characterizing inimitable project management assets involved codified and uncodified knowledge practices. The three factors extracted for characterizing organizational support (moderating variable) involved project alignment, communication, and integration, all of which contribute to embedding project management practices into the fabric of a company s culture. Two factors were extracted for the dependent variable. The factor comprising project management performance pertains to the traditional measures of time, cost, and scope (quality). The factor comprising firm-level performance pertains to the traditional measures of firm competitive advantage, such as sales targets, customer loyalty and satisfaction, profitability, market share, and innovation. While we acknowledge that limitations of this study include sample size, response rate, and self-report bias, we believe that we have a valid and reliable instrument with which to develop a path model. In our ongoing research we are examining the relationship between the factors that were extracted to define the characteristics of project management assets and project management outcomes. This research is an important step towards an improved understanding of the characteristics of project management assets that lead to a firm s competitive advantage. This understanding has significant value for scholars and practitioners interested of project management. 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