Portfolio decision analysis for robust project selection and resource allocation

Organizations must take decisions on how to allocate resources to 'go/no-go' projects to maximize the value of their project portfolio. Often these decisions are complicated by several value criteria, multiple resource types and exogenous uncertainties that influence the projects' values. Especially when the number of projects is large, the efficiency of the resource allocation and the quality of the decision making process are likely to benefit from systematic use of portfolio decision analysis. This Dissertation develops and applies novel methods to manage uncertainty in decision analytic models for project portfolio selection. These methods capture incomplete information through sets of feasible model parameter values and use dominance relations to compare portfolios. Based on the computation of all non-dominated portfolios, these methods identify i) robust portfolios that perform well across the range of feasible parameter values and ii) projects that should surely be selected or rejected in the light of the incomplete information. These methods have several implications for project portfolio decision support. Explicit consideration of incomplete information contributes to the reliability of analysis, which is likely to increase the use of portfolio decision analysis in new contexts. Furthermore, cost and time savings in data elicitation may be achieved, because these methods can give robust decision recommendations based on incomplete data and identify projects for which additional information is beneficial. Finally, these methods support consensus building within organizations as different views about projects' quality or exogenous uncertainties can be considered simultaneously to identify projects on which further negotiations should be focused

A Portfolio Decision Analysis Study for Improving Consequence of Facility Failure Indices

The United States Air Force partially integrated the Mission Dependency Index (MDI) into its portfolio project selection model by assigning an MDI value to a facility type or real property category code (CATCODE) in lieu of assigning a unique MDI value to each facility through a structured interview process. This took an initial step to improve the Air Forces asset management practices; however, it failed to accurately capture the consequence of facility failure in some cases. Although a process to adjudicate the MDI value of individual facilities was created, it is still unknown how much the surveyed MDI value deviates from the CATCODE assigned MDI value and how this influences the Air Forces annual project portfolio selection model. The purpose of this research effort is to measure the deviation in MDI values produced from surveys and the adjudication process with the CATCODE assigned MDI values. It also uses a deterministic approach to portfolio decision analysis to determine the influence these surveyed and adjudicated MDI values have on the Air Forces project portfolio selection model. This research effort serves to provide insight to the Air Force Installation Mission Support Center and the Air Force Civil Engineer Center of the value and utility of surveyed and adjudicated MDI information when compared to their CATCODE assigned counterparts

Evaluating large, high-technology project portfolios using a novel interval-valued Pythagorean fuzzy set framework: An automated crane project case study

© 2019 Elsevier Ltd The contemporary organization relies increasingly on developing large, high technology projects in order to gain local and global competitive advantage. Uncertainty and the complexity of project evaluation requires improved and tailored decision making support systems. A new framework for high technology project portfolio evaluation is introduced. Novel development of an interval-valued Pythagorean fuzzy set (IVPFS) approach is shown to accommodate degrees of membership, non-membership and hesitancy in the evaluation process. Developed methods of linear assignment, IVPFS ranking, IVPFS knowledge index, and IVPFS comparison provide a new framework for group evaluation based on a weighting for each decision expert. The framework is developed as a last aggregation which avoids information loss and introduces a new aggregation process. A novel multi-objective model is then introduced to address project portfolio selection while optimizing the value of the portfolio in terms of resilience (the risk of disruption and delays) and skill utilization (assignment of human resources). The applicability of this framework is demonstrated through a case study in high technology portfolio evaluation. The case study shows that the presented framework can be applied as the core to a high technology evaluation decision support system

A multiple criteria methodology for prioritizing and selecting portfolios of urban projects

This paper presents an integrated methodology supporting decisions in urban planning. In particular, it deals with the prioritization and the selection of a portfolio of projects related to buildings of some values for the cultural heritage in cities. More precisely, our methodology has been validated to the historical center of Naples, Italy. Each project is assessed on the basis of a set of both quantitative and qualitative criteria with the purpose to determine their level of priority for further selection. This step was performed through the application of the Electre Tri-nC method which is a multiple criteria outranking based method for ordinal classification (or sorting) problems and allows to assign a priority level to each project as an analytical "recommendation" tool. To identify the efficient portfolios and to support the selection of the most adequate set of projects to activate, a set of resources (namely budgetary constraints) as well as some logical constraints related to urban policy requirements have to be taken into consideration together with the priority of projects in a portfolio analysis model. The process has been conducted by means of the interaction between analysts, municipality representative and experts. The proposed methodology is generic enough to be applied to other territorial or urban planning problems. We strongly believe that, given the increasing interest of historical cities to restore their cultural heritage, the integrated multiple criteria decision aiding analytical tool proposed in this paper has significant potential to be used in the future

Influence of Portfolio Management in Decision-Making

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.Peer Reviewe

Inhibitors to optimal project portfolio selection

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

A Project Portfolio Management model adapted to non-profit organizations

As they strive towards greater professionalism in carrying out their activities, non-profit organizations (NPOs) have begun paying attention to project management. The non-profit sector (NPS) has also begun to adopt strategic planning techniques, thus making the acceptance of project portfolio management (PPM) methodology a natural consequence. This article aims to propose a project portfolio management model adapted to the context of NPOs

Use of Network Analysis Technique for Prioritizing Project Portfolio: A Case Study

Network analysis is widely used in the context of exploring social phenomena that involve disciplines such as economics, marketing and psychology. This work proposes the use of network analysis from an optics perspective as a strategic analytical intelligence tool, where it discusses its use as a support tool when prioritizing project portfolios. The research was defined through a case study carried out in a Brazilian bank, in which a specific scenario of the need to prioritize demands within the existing portfolio was considered, covering the period from 2018 to the first quarter of 2019. To study these scenarios, 2-mode networks were analyzed to visualize the context and measures of centrality degree, proximity and intermediation were also used to provide analytical intelligence in identifying the best options for negotiation and prioritization. It was concluded, through the information provided by the use of network analysis, that complex scenarios and difficulties for prioritization can be predictively diagnosed, as well as the centrality measures allow the identification of the best options for prioritization and selection and the view of the impacted areas to be involved in the negotiation. The use of network analysis technique as a support tool for decision making in the prioritization of projects portfolio is very promising and becomes potential as a new efficient option to be considered, evaluating its ability to provide analytical intelligence and insights predictive of the prioritization scenarios

A variable neighborhood search simheuristic for project portfolio selection under uncertainty

With limited nancial resources, decision-makers in rms and governments face the task of selecting the best portfolio of projects to invest in. As the pool of project proposals increases and more realistic constraints are considered, the problem becomes NP-hard. Thus, metaheuristics have been employed for solving large instances of the project portfolio selection problem (PPSP). However, most of the existing works do not account for uncertainty. This paper contributes to close this gap by analyzing a stochastic version of the PPSP: the goal is to maximize the expected net present value of the inversion, while considering random cash ows and discount rates in future periods, as well as a rich set of constraints including the maximum risk allowed. To solve this stochastic PPSP, a simulation-optimization algorithm is introduced. Our approach integrates a variable neighborhood search metaheuristic with Monte Carlo simulation. A series of computational experiments contribute to validate our approach and illustrate how the solutions vary as the level of uncertainty increases

Selecting projects in a portfolio using risk and ranking

There are three dimensions in project management: time, cost and performance. Risk is a characteristic related to the previous dimensions and their relationships. A risk equation is proposed based on the nature of the uncertainty associated to each dimension as well as the relationship between the uncertainties. A ranking equation that is able to prioritise projects is proposed and discussed. The problem solved here is which projects to select in a given portfolio of projects. The model is implemented in a group decision support system (GDSS) which can guide decisionmakers in their decision process. However, the system is not intended as a substitution of the decisionmaker task, but merely as an aid. The methodology used is analysis of the equations proposed and trial and error based on examples. This paper’s main contribution is the risk equation and the ranking equation