A Multi-level Approach to Project Management under Uncertainty (original) (raw)

Project management under uncertainty: Solution methods revisited

2016

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, an increase in its cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule especially when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource alloc...

Project management under uncertainty: a study on solution methods

2015

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and sched...

On the project risk baseline: Integrating aleatory uncertainty into project scheduling

Computers & Industrial Engineering, 2021

Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for project managers. The literature on this topic focuses mainly on methods to obtain schedules that meet resource restrictions and, more recently, financial limitations. The methods provide different viable schedules for the same project, and the solutions with the shortest duration are considered the best-known schedule for that project. However, no tools currently select which schedule best performs in project risk terms. To bridge this gap, this paper aims to propose a method for selecting the project schedule with the highest probability of meeting the deadline of several alternative schedules with the same duration. To do so, we propose integrating aleatory uncertainty into project scheduling by quantifying the risk of several execution alternatives for the same project. The proposed method, tested with a well-known repository for schedule benchmarking, can be applied to any project type to help managers to select the project schedules from several alternatives with the same duration, but the lowest risk.

Allocating time and resources in project management under uncertainty

36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the, 2003

We define and develop a solution approach for planning, scheduling and managing project efforts where there is significant uncertainty in the duration, resource requirements and outcomes of individual tasks. Our approach yields a nonlinear optimization model for allocation of resources and available time to tasks. This formulation represents a significantly different view of project planning from the one implied by traditional project scheduling, and focuses attention on important resource allocation decisions faced by project managers. The model can be used to maximize any of several possible performance measures for the project as a whole. We include a small computational example that focuses on maximizing the probability of successful completion of a project whose tasks have uncertain outcomes. The resource allocation problem formulated here has importance and direct application to the management of a wide variety of project-structured efforts where there is significant uncertainty.

Managing project risks and uncertainties

Forest Ecosystems, 2015

This article considers threats to a project slipping on budget, schedule and fit-for-purpose. Threat is used here as the collective for risks (quantifiable bad things that can happen) and uncertainties (poorly or not quantifiable bad possible events). Based on experience with projects in developing countries this review considers that (a) project slippage is due to uncertainties rather than risks, (b) while eventuation of some bad things is beyond control, managed execution and oversight are still the primary means to keeping within budget, on time and fit-for-purpose, (c) improving project delivery is less about bigger and more complex and more about coordinated focus, effectiveness and developing thought-out heuristics, and (d) projects take longer and cost more partly because threat identification is inaccurate, the scope of identified threats is too narrow, and the threat assessment product is not integrated into overall project decision-making and execution. Almost by definition, what is poorly known is likely to cause problems. Yet it is not just the unquantifiability and intangibility of uncertainties causing project slippage, but that they are insufficiently taken into account in project planning and execution that cause budget and time overruns. Improving project performance requires purpose-driven and managed deployment of scarce seasoned professionals. This can be aided with independent oversight by deeply experienced panelists who contribute technical insights and can potentially show that diligence is seen to be done.

Project management under uncertainty

Construction Management and Economics, 1989

Morris' (1986) analysis of the factors affecting project success and failure is considered in relation to the psychology of judgement under uncertainty. A model is proposed whereby project managers may identify the specific circumstances in which human decision-making is prone to systematic error, and hence may apply a number of de-biasing techniques.

A new approach for project control under uncertainty. Going back to the basics

In this paper we propose a new methodology for project control under uncertainty. In particular, we integrate Earned Value Methodology (EVM) with project risk analysis. The methodology helps project managers to know whether the project deviations from planned values are within the "expected" deviations derived from activity planned variability. Although the methodology is new and innovative, we only go back to the fundamentals of project simulation to generate the "universe" of possible projects, according to the assumed variability of project activities. Then we organize and gather the information in order to make the data coherent with EVM. We explain the steps to implement the methodology and we show three case studies. The methodology makes explicit that the schedule and budget resulting from traditional methods like PERT are statistically very optimistic.

A classification and review of approaches and methods for modeling uncertainty in projects

International Journal of Production Economics, 2020

In this paper, we created a classification for major sources of uncertainty in projects and categorized the studies in project scheduling literature with respect to the uncertainty source(s) they address. In addition, we investigated the approaches and methods to manage uncertainty, and studied the literature regarding these methods. Project management predominantly models the randomness in duration of activities; however, studies modeling the uncertainty due to other sources are scarce. We focused on these sources of uncertainty and highlighted the promising areas of research. The results presented in this paper will help researchers to identify the research gaps in modeling project uncertainty.

Project Uncertainty Management

The aim of this paper is to discuss the phenomenon of uncertainty in projects and attempt to integrate it as part of project management. Despite the fact that project management discipline has gained a lot of attention in the past decade from both academia and practitioners, there is still considerable potential for development in this field. Recent trends in project management stress the need to re-address the issue of uncertainty. Though one can come across the notion of uncertainty in traditional project risk management literature rather often, there is no common understanding between the scholars as to what this term means. Based on the review of the existing research, I present my own definition of uncertainty as a crucial element in managing projects. The management of uncertainty is seen as a necessary condition for effective project management. Sources of uncertainty are wide ranging and have a fundamental effect on projects and project management. These sources are not confined to potential events, and include lack of information, ambiguity, characteristics of project parties, trade offs between trust and control mechanisms, and varying agendas in different stages of the project life cycle. There is a high level of uncertainty with both positive and negative effects in any project. The traditional approach to project management still puts a lot of emphasis on assuring conformance to time, budget and scope constraints. Considerations, such as continuous improvement, customer-centric thinking, reflective learning are often left behind. This leads to the fact that project companies become less flexible, unable to accumulate knowledge and experience necessary for coping with uncertainty. Moreover, in project risk management literature, there is no common understanding as to what uncertainty is. DEFINITIONs: Project: A project is a unique, transient endeavour, undertaken to achieve planned objectives, which could be defined in terms of outputs, outcomes or benefits. A project is usually deemed to be a success if it achieves the objectives according to their acceptance criteria, within an agreed timescale and budget. A project is a temporary endeavour designed to produce a unique product, service or result with a defined beginning and end (usually time-constrained, and often constrained by funding or deliverables) undertaken to meet unique goals and objectives, typically to bring about beneficial change or added value. [Wikipedia] A project is a series of complex, connected activities with a common purpose; our most common context is a project to develop or refine a program, but principles of project management apply to most projects. Often program and project are used interchangeably, but nominally, a program is a larger concept than a project. (A project is a sequence of unique, complex, and connected activities having one goal or purpose and that must be completed by a specific time, within budget, and according to specification). [UC davis, 2013] Management in businesses and organizations is the function that coordinates the efforts of people to accomplish goals and objectives using available resources efficiently and effectively. Management includes planning, organizing, staffing, leading or directing, and controlling an organization to accomplish the goal. [Wikipedia] Management is often included as a factor of production along with‚ machines, materials, and money. According to the management guru Peter Drucker [1909-2005], the basic task of management includes both marketing and innovation. Practice of modern management originates from the 16th century study of low-efficiency and failures of certain enterprises, conducted by the English statesman Sir Thomas More [1478-1535]. Management consists of the interlocking functions of creating corporate policy and organizing, planning, controlling, and directing an organization's resources in order to achieve the objectives of that policy. Project management: This is the application of processes, methods, knowledge, skills and experience to achieve the project objectives. Project management; is the process and activity of planning, organizing, motivating, and controlling resources, procedures and protocols to achieve specific goals in scientific or daily problems. Management is frequently used as an enabler for meeting an uncertain and turbulent environment. Consequently, the overall effectiveness of the project management process is essential for long-term profitability. The aim and final effects of project management are to predict the outcome, i.e. cost, time and quality. Uncertainty: We define uncertainty as a context for risks as events having a negative impact on the project's outcomes, or opportunities, as events that have beneficial impact on project performance. This definition stresses dual nature of uncertainty in potentially having both positive and negative influence on the project's outcomes. Uncertainty can arise from sources both internal and external to the project. [LeRoy & Singell, 1987] Uncertainty: in contrast, is an event or a situation, which was not expected to happen, regardless of whether it could have been possible to consider it in advance. In other words, uncertainty is when the established facts are questioned and thereby the basis for calculating risks (known negative events) or opportunities (known positive events) is questioned. [Own Definition] Uncertainty: This is a term used in subtly different ways in a number of fields; it applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable and/or stochastic environments, as well as due to ignorance and/or indolence. However, uncertainty is inherent in the objectives of the project itself, as we use assumptions and expectations in defining and realizing the outcome of the project. A project's ability to identify and react to uncertainty will influence the outcome of the project. [Wikipedia]