The Progression Towards Project Management Competence

The purpose of this research was to investigate the soft competencies by project phase that IT project managers, hybrid and technical team members require for project success. The authors conducted qualitative interviews to collect data from a sample of 22 IT project managers and business leaders located in Calgary, Canada. They identified the key competencies for the three types of job roles. The research participants offered their opinions of what are the most important competencies from the following competence categories: Personal Attributes (e.g. eye for details), Communication (e.g. effective questioning), Leadership (e.g. create an effective project environment), Negotiations (e.g. consensus building), Professionalism (e.g. life long learning), Social Skills (e.g. charisma) and Project Management Competencies (e.g. manage expectations). The authors discuss the progression of competence through these job roles. They identified and discuss the interplay between a change in job role and the required competencies necessary for IT project success from a neuro-science perspective

Beyond IT interoperability assessment: Complexity analysis of the project context

IT people do best what they are trained to do: examine interoperability issues through a technical lens. It may be unfair to ask of them to systematically and comprehensively analyze non-IT concerns of an interoperability project such as business strategy, constraints and governance. Yet to fully understand the feasibility of an interoperability project, IT people need to examine non-IT factors that can make or break these complex, expensive and time consuming projects. This paper is about a model that emerged from a research project about understanding the nature of IT projects. The Complexity-Based Project Classification Framework can be used to assess the feasibility of a business interoperability project. A three-round international Delphi project with a sample of 23 acknowledged experts identified and prioritized the non-technical project attributes that need to be analyzed when assessing IT project feasibility. The Complexity-Based Project Classification Framework emerged. The Complexity-Based Project Classification Framework is composed of three parts: preconditions, contextual complexity attributes and project effort attributes. Once preconditions are in place (e.g. the organization needs to support using this model for assessing the feasibility of business interoperability) then the project team can assess the interoperability project by considering its project effort attributes (e.g. technology) and project contextual attributes (e.g. relative project size). It is suggested that practitioners who use this Framework will have an improved understanding of the IT interoperability project feasibility

The Delphi Method for Graduate Research

Introduction It continues to be an exciting time to be a researcher in the information systems discipline; there seems to be a plethora of interesting and pressing research topics suitable for research at the masters or PhD level. Researchers may want to look forward to see what will be the key information systems issues in a wireless world, the ethical dilemmas in social network analysis, and the lessons early adopters learn. Practitioners may be interested in what others think about the strengths and weaknesses of an existing information system, or the effectiveness of a newly implemented information system. The Delphi method can help to uncover data in these research directions. The Delphi method is an iterative process used to collect and distill the judgments of experts using a series of questionnaires interspersed with feedback. The questionnaires are designed to focus on problems, opportunities, solutions, or forecasts. Each subsequent questionnaire is developed based on the results of the previous questionnaire. The process stops when the research question is answered: for example, when consensus is reached, theoretical saturation is achieved, or when sufficient information has been exchanged. The Delphi method has its origins in the American business community, and has since been widely accepted throughout the world in many industry sectors including health care, defense, business, education, information technology, transportation and engineering. The Delphi method\u27s flexibility is evident in how it has been used. It is a method for structuring a group communication process to facilitate group problem solving and to structure models (Linstone & Turloff, 1975). The method can also be used as a judgment, decision-aiding or forecasting tool (Rowe & Wright, 1999), and can be applied to program planning and administration (Delbeq, Van de Ven, & Gustafson, 1975). The Delphi method can be used when there is incomplete knowledge about a problem or phenomena (Adler & Ziglio, 1996; Delbeq et al., 1975). The method can be applied to problems that do not lend themselves to precise analytical techniques but rather could benefit from the subjective judgments of individuals on a collective basis (Adler & Ziglio, 1996) and to focus their collective human intelligence on the problem at hand (Linstone & Turloff, 1975). Also, the Delphi is used to investigate what does not yet exist (Czinkota & Ronkainen, 1997; Halal, Kull, & Leffmann, 1997; Skulmoski & Hartman 2002). The Delphi method is a mature and a very adaptable research method used in many research arenas by researchers across the globe. To better understand its diversity in application, one needs to consider the origins of the Delphi method. The Classical Delphi The original Delphi method was developed by Norman Dalkey of the RAND Corporation in the 1950\u27s for a U.S. sponsored military project. Dalkey states that the goal of the project was to solicit expert opinion to the selection, from the point of view of a Soviet strategic planner, of an optimal U.S. industrial target system and to the estimation of the number of A-bombs required to reduce the munitions output by a prescribed amount, (Dalkey & Helmer, 1963, p. 458). Rowe and Wright (1999) characterize the classical Delphi method by four key features: 1. Anonymity of Delphi participants: allows the participants to freely express their opinions without undue social pressures to conform from others in the group. Decisions are evaluated on their merit, rather than who has proposed the idea. 2. Iteration: allows the participants to refine their views in light of the progress of the group\u27s work from round to round. 3. Controlled feedback: informs the participants of the other participant\u27s perspectives, and provides the opportunity for Delphi participants to clarify or change their views. 4. Statistical aggregation of group response: allows for a quantitative analysis and interpretation of data.