IT Project Selection and Organisational Agility – An Integrated Conceptual Framework
2023 | Americas Conference on Information Systems | Citations: 0
Authors: van Raay, Adrian; Duan, Sophia; Whiteside, Naomi
Abstract: Sustained competitive advantage is elusive to organisations, in a volatile cont ...
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Abstract: Sustained competitive advantage is elusive to organisations, in a volatile contemporary context. Organisational agility (OA), enabled by information technology, offers hope. However, organisations that pursue agility encounter incompatibility with IT project selection (ITPS) -as they select and fund projects, before implementation. Existing ITPS literature provides rich insights into methods, processes and people but is fragmented. Without integration, the incompatibility cannot be resolved. To address this problem, this study conducted a literature review of 159 articles to develop an integrated framework for understanding OA and ITPS. Findings show that methods, processes and people in ITPS can both enable and disable OA. Following conceptual-framework-analysis, ITPS is redefined as an enabler of agility. The resultant three-layered conceptual framework shows that firms can deploy ITPS methods, processes and people that enable sensing, deciding and responding, leading to OA. This study contributes by integrating literature to facilitate further research in this area.
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Semantic filters:
IS project selection
Topics:
decision making IT investment information technology capability competitive advantage IT project
Methods:
literature sample literature study synthesis
Value-driven IT Project Portfolio Management: Process Model, Evaluation Framework, and Decision Support
2022 | International Conference on Information Systems | Citations: 0
Authors: Karrenbauer, Christin; Breitner, Michael H.
Abstract: Companies must optimize their information technology (IT) project portfolio to ...
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Abstract: Companies must optimize their information technology (IT) project portfolio to achieve goals. However, IT projects often exceed resources and do not create their promised value, for example, because of missing structured processes and evaluation methods. Continuous IT portfolio management is thus of importance and a critical business activity to reach value-driven goals. Guided by Design Science Research with literature reviews and expert interviews, we develop, evaluate, and adjust an IT project portfolio management process model, a holistic IT project evaluation framework, and implement a decision support system prototype. Our results and findings synthesize and extend previous research and expert opinions and guide decision-makers to make more informed and objective IT project portfolio management decisions aligned with optimal value creation. Furthermore, we deduce new research opportunities for IT project portfolio management process models, decision tools, and evaluation frameworks. Introduction and MotivationInformation technology (IT) impacts a company's long-term performance and competitiveness and forms a critical success factor (Bezdrob et al. 2020). Thereby, IT projects are characterized by complexity, crossfunctionality, dynamics, non-routine, temporality, and uncertainty. These make IT project portfolio management (ITPPM) a challenging task (Chiang and Nunez 2013;Kester et al. 2011). Selecting the "right" IT projects is essential to create optimal value. Nevertheless, ITPPM is often unstructured and decisions are made ad hoc instead of long-term planning. Thus, many IT projects deviate from their defined objectives, are not completed, or completely fail (Varajão and Trigo 2016). According to the Project Management Institute (PMI 2017a), roughly $97 million US Dollars per $ 1 billion investments in IT projects are wasted. Similarly, Lee et al. (2021) refer that on average 66% of implemented IT projects are more expensive and 33% require longer as planned. Failed IT projects due to weak ITPPM processes lead to resource losses and exceedances (e.g., Hershey: $150 in lost sales, 19% drop in earnings), project abandonment (e.g., Dell: $200 million), or bankruptcies (e.g., FoxMeyer) (Fadlalla and Amani 2015; Hughes et al. 2017). Thus, companies need adequate and resilient methods for the critical business activity of ITPPM. Considering existing interdependencies and constraints, these methods ensure that selected IT projects fit the company's strategy and create value (Chiang and Nunez 2013;Kester et al. 2011). If departments and functions are aligned to strategy, IT projects are more likely to be completed successfully ITPPM: Process Model, Evaluation Framework, and DSS Forty-Third International Conference on Information Systems, Copenhagen 2022 2 (PMI 2017a). Additionally, uniform IT guidelines stabilize the performance of IT projects (Martin 2006). However, many decisions are motivated by subjectivity, personal experiences and perceptions. Often uniform ITPPM methods, evaluation and selection criteria, and their consistent usage are missing (Varajão and Trigo 2016). An ITPPM tool can further support decision-makers (DM) to ensure efficient, transparent, and consistent decisions more rapidly (Caniëls and Bakens 2012;Killen et al. 2020).Even though ITPPM is considered to be a structured process, besides best practices for PPM (e.g., PMI 2017b) only few ITPPM process models exist in literature which are rather perfunctory. Mostly, existing models encompass three (Ajjan et al. 2016) to five main phases (Archer and Ghasemzadeh 1999). Typically, they include activities such as the definition of baseline conditions (Alaeddini and Mir-Amini 2020), IT project identification (Montgomery 2007), evaluation (Chiang and Nunez 2013), selection (Ajjan et al. 2016), and monitoring with adaptions (Miller 2002). Other than that, existing models vary in their phases and activities. Moreover, the procedure is mostly sequential with no or few re-cycles between and within phases. To address this and better meet IT project characteristics, we propose an integrated ITPPM process model that allows an objective and value-driven ITPPM. To do this, we synthesize existing process models and expand them with expert interviews. It comprises activities from different models combined within an integrated one. Unlike many existing models, it also allows re-cycles between and within individual phases and allows to address peculiarities of IT projects. It enables, e.g., a flexible reaction to changes and uncertainties and a discussion between stakeholders. In addition, IT project evaluation, prioritization, and selection are critical activities (Varajão and Trigo 2016). Several methods have been researched on this topic ranging from rather simple financial project selections (Rosacker and Olson 2009), and balance scorecard approaches (Asosheh et al. 2010), to more advanced optimization models (Cho and Shaw 2013) and fuzzy programming (Heidary et al. 2020), among others (Mohagheghi et al. 2019). In rather simple methods, IT project decisions are often based only on the evaluations. In more advanced methods, several constraints are considered, however, the project evaluation is often already available and not described in more detail (Archer and Ghasemzadeh 1999). We combine both approaches and develop a holistic scoring framework that enables a quantification of subjective estimations and thus an objective evaluation of IT projects of different types and sizes. The scoring results then serve as an input for our decision support system (DSS) prototype. It allows to select from a large number of IT project proposals those that maximize the value proposition, considering interdependencies and limitations. In doing so, we mitigate disadvantages resulting from the sole use of scoring approaches (Mohagheghi et al. 2019) and decisions are not made on an individual project level but consider other factors such as resource constraints and dependencies. Our main contributions are our three artifacts, an integrated ITPPM process model, a holistic scoring framework, and our DSS prototype. These Level 1 and Level 2 artifacts (Gregor and Hevner 2013) support ITPPM and enhance and contribute to the knowledge base. We provide knowledge to increase transparency and objectivity to make more informed IT portfolio decisions and thus decrease IT project failure rates, minimize subject manipulations, increase value creation, and goal achievement. We follow a Design Science Research (DSR) process (Hevner et al. 2004) to address the following research questions (RQ):RQ 1: What activities constitute a value-driven ITPPM process? RQ 2: How can IT projects (and proposals) be uniformly evaluated to generate a value-driven IT portfolio? RQ 3: How can a DSS support IT project selection and scheduling?First, we describe the theoretical background of ITPPM. Then, we motivate our DSR-oriented research design. Afterwards, we present our results and findings of our literature reviews and expert interviews, including an ITPPM process model and a scoring framework. Then, we introduce our DSS prototype and provide an applicability check. Finally, we discuss our results and findings, their implications, deduce recommendations for theory and practice and a research agenda, present limitations, and conclusions.
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Semantic filters:
IS project selection
Topics:
IT project project management decision support system value creation knowledge base
Methods:
qualitative interview business process modeling design artifact literature study design science
Balancing the Strategic Value and the Operational Value in IT Portfolio Selection
2009 | Americas Conference on Information Systems | Citations: 0
Authors: Cho, Wooje; Shaw, Michael J
Abstract: This paper provides a methodological framework in which the problem of IT projec ...
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Abstract: This paper provides a methodological framework in which the problem of IT project portfolio selection is solved by balancing between operational and strategic IT investments. From interviews with CIOs, we found that the interest in IT projects in many firms tends to center on operational benefits, rather than strategic benefits. We examined the impact of strategic IT investments from an IT portfolio perspective. We applied an optimization model for the IT the portfolio selection and developed a computational method to explore the impact of strategic IT investments. We found that, based on a longterm evaluation, IT portfolio selection focusing on both the operational value and the strategic value resulted in greater performance than IT portfolio selection focusing on the operational value alone. In addition, we found that the risk level of the strategic value of IT did not significantly affect the outcome of the IT portfolio in a strategic IT investment.
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Semantic filters:
IS project selection
Topics:
IT project IT investment project management IT manager decision making
Methods:
qualitative interview simulation statistical hypothesis test chi squared test field study
Rejection and Selection Decisions in the IT Portfolio Composition Process:An Enterprise Risk Management Based Perspective
2007 | Americas Conference on Information Systems | Citations: 7
Authors: Karhade, Prasanna; Shaw, Michael
Abstract: This paper presents a model of the IT portfolio composition process for IT inves ...
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Abstract: This paper presents a model of the IT portfolio composition process for IT investments based on data collected from a Fortune-25 enterprise. We argue that IT project rejection and IT project selection decisions are two distinct components of the IT Portfolio composition process and are governed by different factors. The risk factors we use in our study to explain the IT portfolio composition phenomenon are derived from the Enterprise Risk Management — Integrated Framework published by the COSO of the Treadway Commission (COSO 2004). We find that maturity of the project idea, type of the idea and the process–readiness risk factors explain IT project rejection decisions where as technological characteristics (for e.g. technological complexity), timing considerations (for e.g. go live date for the project is less than a year away) and financial characteristics ( total investment for a project is less than hundred thousand dollars) explain IT project selection decisions.
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Semantic filters:
IS project selection
Topics:
IT project project management IS project selection IT investment logistics management
Methods:
logistic regression descriptive statistic field study
MAKE OR BUY OR BAG IT: THE SREF FRAMEWORK FOR ANALYZING IT OUTSOURCING DECISIONS
2002 | Americas Conference on Information Systems | Citations: 0
Authors: Birkin, Stanley; Gill, T Grandon; Steigner, George
Abstract: The “make or buy” decision for information technology applications, systems and ...
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Abstract: The “make or buy” decision for information technology applications, systems and infrastructure has been the subject of extensive analysis in the IT literature over the past decade. While outsourcing has garnered enthusiastic support from many quarters, a number of cautionary notes have also been sounded, and despite auspicious starts, many outsourcing arrangements have been less successful than had been expected. In this paper, we propose a framework intended to help managers weigh the benefits of outsourcing the development of an IT project against the negative consequences. The framework, referred to as the SREF (Strategy-RiskEconomics-Future benefits) framework, is derived by marrying portfolio theory of selecting IT projects with recent research findings relating to outsourcing versus in-house development decisions.
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Semantic filters:
IS project selection
Topics:
outsourcing systems development IT project IS project selection project management
Methods:
survey field study theory development
Theories:
portfolio theory
Project selection criteria by strategic orientation
Abstract: One information planning decision involves project selection from among a portfo ...
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Abstract: One information planning decision involves project selection from among a portfolio of options. This involves multiple steps, including selection and weighting of alternatives. Choice and weighting on criteria become crucial in the selection of the projects to pursue. A survey conducted by the authors found that organizations with an expectation of future IS importance rely heavily on organizational goals, management support and environmental factors. Organizations with low strategic expectations of IS rely more heavily on management support, political considerations, and risk. The results allow managers to position selection criteria according to their strategic use of information technology.
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Semantic filters:
IS project selection
Topics:
IT workforce IT manager top management support IS project selection project management
Methods:
survey multivariate analysis of variance ANOVA parametric test survey design
The Organizational Context of Process Reengineering Project Initiatives
1997 | Americas Conference on Information Systems | Citations: 1
Authors: Teng, James T C
Abstract: In this study, three potentially facilitating sources of influence on BPR initia ...
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Abstract: In this study, three potentially facilitating sources of influence on BPR initiatives -- innovative capacity of the organization, IS maturity and Strategy-IS interface -- were examined. It was found that while factors related to IT factors such as experience in mainframe and client/server computing may facilitate the decision to reengineer, they are not critical to project success. On the other hand, factors having significant relationships beyond the initial decision include variables pertaining to innovative capacity of the organization and Strategy-IS interface.
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Semantic filters:
IS project selection
Topics:
IS maturity change management innovation management project management IS project selection