1,721,187 research outputs found
Decisions made on scant information: overview
Full text linkThis chapter brings an overview to an edited book that looks at how decisions can be made at the front-end of major projects, in circumstances where information is usually scant. The book examines how projects can be successfully aligned with the desired direction; how sufficient, appropriate and valid information can be gathered at the front-end; how information can be analysed; and finally how decisions can be made. Each chapter of the book is written by an expert in the field, and each chapter speaks for itself. However, some key themes run throughout the book. These include the need for alignment between organisational strategy and the project concept; dealing with complexity, in particular the systemicity and interrelatedness within project decisions; consideration of the ambiguity implicit in all major projects; taking into account psychological and political biases within estimation of benefits and costs; consideration of the social geography and politics within decision-making groups; and preparation for the turbulence within the project environment, including the maintenance of strategic alignment
Post-project reviews to gain effective lessons learned
No full textA key component of successful project management is the ability to glean key learning's from the experience throughout the lifecycle of the project, as well as at its conclusion. However, in practice, the lessons learned from a specific project are rarely incorporated into an organization's overall policies and procedures. Without a concerted effort to reflect on specific project learning's and a designated process to implement them across the organization, lessons are lost, mistakes are repeated and opportunities for operational efficiency are missed
Managing and modelling complex projects
No full textIt is widely acknowledged that traditional Project Management techniques are no longer sufficient, as projects become more complex and client's demand reduced timescales. Problems that arise include inadequate planning and risk analysis, ineffective project monitoring and control, and uninformed post-mortem analysis. Effective modelling techniques, which capture the complexities of such projects, are therefore necessary for adequate project management. This book looks at those issues, describes some modelling techniques, then discusses their merits and possible synthesi
Management science in practice
No full textTABLE OF CONTENTSPART I: MANAGEMENT SCIENCE.Chapter 1: What is Management Science?Chapter 2: Management Science interventions.PART 2: MODELLING TECHNIQUES.Chapter 3: Problem structuring techniques.Chapter 4: Multi-methodology.Chapter 5: Analysis techniques.PART 3: PRACTICAL SKILLS.Chapter 6: The proposal stage.Chapter 7: Data.Chapter 8: Appropriate modeling.Chapter 9: Creativity.Chapter 10: Ancilliary practical skills.PART 4: PRACTICE.Chapter 11: OR/MS groups.Chapter 12: Ethics.Chapter 13: Reflective practice.The final note: the future.References
Towards realism in network simulation
No full textThe use of networks handling uncertainty to provide a temporal risk analysis of projects is now widespread. However, such analyses frequently give rise to very wide probability distributions, and thus in practice are described as not credible. This is largely because the simulations do not reflect the actions that management would take to bring late-running projects under control. These are difficult to include in models, not because the actions themselves are complex, but rather because the effects of those actions are not well-understood. These effects are often much less effective than expected and some are counter-intuitive. However, much work has been done in modelling projects using system dynamics, and this work can give some useful insights into the effects of management actions in projects, both their behaviour and indications of their cumulative impact. This paper has attempted to describe these indications and then to apply such lessons to network simulations, to gain the benefit of the insights without losing the operational advantages of the networks. Some small illustrative models of the effects are given. It is hoped that the use of such modelling can help to bring additional realism to probabilistic network modellin
The Contribution of Mathematical Modelling to the Practice of Project Management
No full textThis paper looks at the contribution that mathematical modelling has made to project management over the past 50 years, and the contribution it is currently making and can make in the future. Project Management started with well-defined foundations posing precise, well-defined problems. In its growing phase, modellers played an essential role in taking the problems defined by the project-management world and offering solutions, from the original PERT, through resource allocation and levelling procedures, Monte Carlo simulation models, criticality analyses and so on. Since then, however, while the project management field itself has tried to establish its procedures, keeping to its philosophical stance, much of the mathematical-modelling world has continued along its trajectory, producing ever more complex solutions to ever more complex models, motivated by mathematical impressiveness rather than the need to solve real-world problems. This paper outlines much of this work, some of which does find its way into project-network software but much of which languishes in journals. However, over the last decade or so, Operational Researchers have begun to build models of projects that are systemic and dynamic and explain many of the behaviours of projects that conventional decomposition models do not; and at the same time, some of the Project Management world has started to realize the limitations of its philosophical stance and started looking to build new theory for modern, complex, dynamic projects. As these two trends come together, it is essential that modellers are at the forefront of building this new theory
A classified bibliography of research relating to project risk
No full textThis document contains a bibliography of recent research relating to project risk management, bringing together relevant research scattered across a range of publications. It considers how success or failure can be defined for a project (more than simple time/cost/technical target achievement). It looks at the historical evidence of projects, illustrating failure to achieve targets. What risk means to a project, and how a project team perceive, identify and quantify risk is considered — often the crucial credibility-point in practice. Techniques are discussed for the analysis of risk, to schedule (including analytical and more generally applicable simulation techniques), cost and technical achievement, both separate analyses and the first steps towards an integrated analysis. Success for project participation depends on who bears the risks, and the vital role of risk analysis in informing the contractual allocation of risk is explored. Finally, the management structures and procedures needed to manage risk are discussed
Identifying the hard lessons from projects – easily
No full textLearning lessons from projects is important, but the practice of project post-mortems does not occur frequently in practice. Recent work suggests that, one reason might be the difficulty in identifying the "hard", non-intuitive lessons from projects, such as those resulting from feedback and dynamic, systemic effects (which are difficult to discern intuitively and can greatly exacerbate initially small effects). However, while there are bodies of work to explain such effects, what are needed are simple, practical analysis methods that can be used routinely in post-project reviews to explicate how the project out-turn resulted and to identify the lessons which need to be learned. This paper reports a post-project review in NCR Financial Solutions Group Ltd., as an example of using just such simple techniques. It describes the procedures used, outlines the results found and discusses when and where such techniques might add value. Finally, it points the way ahead to more wide-ranging research in this field, to enable managers to identify the real lessons from the projects, including the hard lessons, but practically and easily. This paper will hopefully contribute to managers' ability to learn from projects
Modelling complex projects
No full textIt is widely acknowledged that traditional Project Management techniques are no longer sufficient, as projects become more complex and client's demand reduced timescales. Problems that arise include inadequate planning and risk analysis, ineffective project monitoring and control, and uninformed post-mortem analysis. Effective modelling techniques, which capture the complexities of such projects, are therefore necessary for adequate project management. This book looks at those issues, describes some modelling techniques, then discusses their merits and possible synthesis
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