949 resultados para project portfolio selection


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The selection of projects and programs of work is a key function of both public and private sector organisations. Ideally, projects and programs that are selected to be undertaken are consistent with strategic objectives for the organisation; will provide value for money and return on investment; will be adequately resourced and prioritised; will not compete with general operations for resources and not restrict the ability of operations to provide income to the organisation; will match the capacity and capability of the organisation to deliver; and will produce outputs that are willingly accepted by end users and customers. Unfortunately,this is not always the case. Possible inhibitors to optimal project portfolio selection include: processes that are inconsistent with the needs of the organisation; reluctance to use an approach that may not produce predetermined preferences; loss of control and perceived decision making power; reliance on quantitative methods rather than qualitative methods for justification; ineffective project and program sponsorship; unclear project governance, processes and linkage to business strategies; ignorance, taboos and perceived effectiveness; inadequate education and training about the processes and their importance.

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A modified Delphi approach has been applied in this study to investigate best practice and to determine the factors that contribute to optimal selection of projects. There are various standards and practices that some may recognise as representing best practice in this area. Many of these have similar characteristics and this study has found no single best practice. The study identified the factors that contribute to the optimal selection of projects as: culture, process, knowledge of the business, knowledge of the work, education, experience, governance, risk awareness, selection of players, preconceptions, and time pressures. All these factors were found to be significant; to be appropriate to public sector organisations, private sector organisations and government owned corporations; and to have a strong linkage to research on strategic decision making. These factors can be consolidated into two underlying factors of organisation culture and leadership.

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Con la creciente popularidad de las soluciones de IT como factor clave para aumentar la competitividad y la creación de valor para las empresas, la necesidad de invertir en proyectos de IT se incrementa considerablemente. La limitación de los recursos como un obstáculo para invertir ha obligado a las empresas a buscar metodologías para seleccionar y priorizar proyectos, asegurándose de que las decisiones que se toman son aquellas que van alineadas con las estrategias corporativas para asegurar la creación de valor y la maximización de los beneficios. Esta tesis proporciona los fundamentos para la implementación del Portafolio de dirección de Proyectos de IT (IT PPM) como una metodología eficaz para la gestión de proyectos basados en IT, y una herramienta para proporcionar criterios claros para los directores ejecutivos para la toma de decisiones. El documento proporciona la información acerca de cómo implementar el IT PPM en siete pasos, el análisis de los procesos y las funciones necesarias para su ejecución exitosa. Además, proporciona diferentes métodos y criterios para la selección y priorización de proyectos. Después de la parte teórica donde se describe el IT PPM, la tesis aporta un análisis del estudio de caso de una empresa farmacéutica. La empresa ya cuenta con un departamento de gestión de proyectos, pero se encontró la necesidad de implementar el IT PPM debido a su amplia cobertura de procesos End-to-End en Proyectos de IT, y la manera de asegurar la maximización de los beneficios. Con la investigación teórica y el análisis del estudio de caso, la tesis concluye con una definición práctica de un modelo aproximado IT PPM como una recomendación para su implementación en el Departamento de Gestión de Proyectos.

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The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

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The inquiries to return predictability are traditionally limited to conditional mean, while literature on portfolio selection is replete with moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework for both return prediction and portfolio selection. More specifically, a time-varying return distribution is modeled through quantile regressions and copulas, using quantile regressions to extract information in marginal distributions and copulas to capture dependence structure. A preference function which captures higher moments is proposed for portfolio selection. An empirical application highlights the additional information provided by the distributional approach which cannot be captured by the traditional moment-based methods.

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Identifying appropriate decision criteria and making optimal decisions in a structured way is a complex process. This paper presents an approach for doing this in the form of a hybrid Quality Function Deployment (QFD) and Cybernetic Analytic Network Process (CANP) model for project manager selection. This involves the use of QFD to translate the owner's project management expectations into selection criteria and the CANP to weight the expectations and selection criteria. The supermatrix approach then prioritises the candidates with respect to the overall decision-making goal. A case study is used to demonstrate the use of the model in selecting a renovation project manager. This involves the development of 18 selection criteria in response to the owner's three main expectations of time, cost and quality.

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This thesis examines three different, but related problems in the broad area of portfolio management for long-term institutional investors, and focuses mainly on the case of pension funds. The first idea (Chapter 3) is the application of a novel numerical technique – robust optimization – to a real-world pension scheme (the Universities Superannuation Scheme, USS) for first time. The corresponding empirical results are supported by many robustness checks and several benchmarks such as the Bayes-Stein and Black-Litterman models that are also applied for first time in a pension ALM framework, the Sharpe and Tint model and the actual USS asset allocations. The second idea presented in Chapter 4 is the investigation of whether the selection of the portfolio construction strategy matters in the SRI industry, an issue of great importance for long term investors. This study applies a variety of optimal and naïve portfolio diversification techniques to the same SRI-screened universe, and gives some answers to the question of which portfolio strategies tend to create superior SRI portfolios. Finally, the third idea (Chapter 5) compares the performance of a real-world pension scheme (USS) before and after the recent major changes in the pension rules under different dynamic asset allocation strategies and the fixed-mix portfolio approach and quantifies the redistributive effects between various stakeholders. Although this study deals with a specific pension scheme, the methodology can be applied by other major pension schemes in countries such as the UK and USA that have changed their rules.

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This paper aims to bring more information related to the critical question "how IT areas of insurance companies are defining and delivering their strategic initiatives Portfolios?" and make conclusions based on the collected data. To reach these interpretations, it is composed of a theoretical investigation on the theme, a strategy delineation for the research methodology and a conclusion presentation based on the findings. In this last part, this study concluded that explored organization does not applied a sufficient number of best practices answering the critical question as "the company is not mature on this subject".