Project portfolio selection in a colombian holding company

The adequate project selection allows companies to invest resources in specific initiatives that allow them to achieve their strategic objectives and to become more competitive. In contrast, non-adequate projects selection can burden the organizations with large investments that do not impact positively in the organization in general. This paper shows an application of Promethee I method, fifth version, as a multi-criteria method to support the strategic projects selection process, and a sensitivity analysis that were both carried out at the beginning of the planning period in a Colombian holding company. The application of Promethee I in a base scenario, and the development of two alternative scenarios allowed to identify that in the case study’s portfolio there are projects with a very high preference, regardless of the criteria weight. Similarly, it allowed to identify the least preferred projects. These results are an important input for projects selection decision-making to be carried out by the holding company board of directors. Moreover, it was identified that the case study’s holding company should focus efforts on the relative weights definition and on the measurement scale of each criterion, as this has a significant impact on the results obtained

Apoio Multicritério à Decisão para Priorização de Projetos de P&D: Um estudo de caso em empresa de óleo e gás

Este artigo se propõe a verificar a viabilidade de aplicação da análise multicritério como ferramenta de suporte à decisão em um portfólio de P&D com uma grande quantidade de projetos, múltiplas carteiras e um processo periódico de tomada de decisão. Realiza um estudo de caso na área de P&D de uma empresa de óleo e gás, utilizando a técnica de swing weighting para a ordenação e ponderação dos critérios e a teoria de utilidade multiatributo (MAUT) para ranquear os projetos. Os ranqueamentos obtidos por este processo foram apresentados aos responsáveis pelas carteiras de P&D, a fim de validar a aplicação e a utilidade do método. Os resultados do estudo de caso mostraram que o método é viável para o portfólio com as características descritas, tendo aprovação de todos os decisores entrevistados

Case: Peatland Selection

The importance of environmental decision making is growing. Private companies and public organizations are facing decisions involving multiple objectives. In particular, focusing solely on financial objectives is no longer enough but taking into account the environmental, social and political objectives is needed. The methods used to solve these environmental problems have been based on heuristic approaches. However, these methods lack the capability to provide optimal solutions as most of the environmental decisions are portfolio selection problems. Robust Portfolio Modeling (RPM) is a decision analysis method that combines mathematical optimization in portfolio selection to incomplete preference information. This incomplete information is common in environmental decision making which includes multiple stakeholders with conflicting views. However, RPM has not been applied before to real-life environmental cases. This thesis will first explore the characteristics of environmental decision making, secondly go through different methods used in environmental decision making and finally apply RPM methodology into peatland selection case. The results of RPM are then compared to the results of the heuristic YODA method previously used in the same peatland selection case. Results indicate that RPM and YODA select highly different type of peatlands. RPM takes better into account the cumulative effects related to portfolio selection than YODA. Therefore, it is argued that RPM might be suitable for environmental decision making

Modeling project preferences in multiattribute portfolio decision analysis

When choosing a portfolio of projects with a multi-attribute weighting model, it is necessary to elicit trade-off statements about how important these attributes are relative to each other. Such statements correspond to weight constraints, and thus impact on which project portfolios are potentially optimal or non-dominated in view of the resulting set of feasible attribute weights. In this paper, we extend earlier preference elicitation approaches by allowing the decision maker to make direct statements about the selection and rejection of individual projects. We convert such project preference statements to weight information by determining the weights for which (i) the selected project is included in all potentially optimal or non-dominated portfolios, or (ii) the rejected project is not included in any potentially optimal or non-dominated portfolio. We prove that the two complementary selection rules will exclude exactly the same set of weights. However, analyses that apply the dominance structure often lead to multiple, mutually exclusive feasible weight sets, and therefore the approach based on potential optimality is more relevant for practical decision analysis. We also propose ex ante value of information measures to guide the elicitation of project preference statements, and illustrate our results by analyzing a real case on the selection of infrastructure maintenance projects.Peer reviewe