Mark A. Seely, PMP, PEng, is a professional engineer with extensive
experience helping managers to deal with issues associated with large-scale complex
projects in the private and public sectors. He received an MBA from the University
of Ottawa (Canada) and is actively involved with the Project Management Institute
(PMI®), holding various board positions, lecturing on project management, and providing
PMP® certification training. He is a Fellow at the Centre on Governance, University
of Ottawa. He can be reached at email@example.com
L. Quang P. Duong obtained his Ph.D. in statistics from the University of Western Ontario (London, Canada). His areas of research include the application of statistical methods to solve project management issues. He was with the Management Sciences group at Bell Canada where he applied statistical and operations research techniques to a wide range of business problems, in addition to lecturing at various universities. He is a Fellow at the Centre on Governance, University of Ottawa. He can be reached at firstname.lastname@example.org
Projects in today's business environment are reaching new levels of complexity as contracting authorities encounter aggressive technology developments and/or extensive business transformations. Prosperity is dependent on the effectiveness with which we analyze the nature of the challenge at hand, determine the likelihood of success, and respond with the appropriately tailored solutions.
The Dynamic Baseline Model (DBM) provides:
- A proven model for complexity discussion and analysis,
- A procurement orientation diagnostic template, and
- A framework for measuring on-going performance.
The goal of the Dynamic Baseline Model is to determine the probability of the project's success, and provide the framework for the analysis of the project management learning process. It suggests that our ability to create solutions is bounded by our current learning horizon, which may be too restrictive for our projects. The model explores the evolution of project management behaviors, establishes realistic levels of project complexity and expectations, and provides a pairing of the two.
Keywords: dynamic baseline model; project management learning process; project complexity; learning horizon
In this Part I, we describe:
In Part II we shall describe:
In Part III we will follow on with five "Paradoxes":