According to a 2001 OECD report, as few as 28 percent of IT projects undertaken
in the US were successful in terms of budget, functionality and timeliness. And a
similar number of IT projects were cancelled. The OECD recognized that problems with
IT projects represented a significant economic, political, efficiency and effectiveness
risk to government, and that IT implementations that do not achieve their objectives
put at risk many government initiatives. More recent reports have substantiated this
Moreover, projects that run over schedule, over budget, under-perform or are abandoned
before completion are not exclusive to the public sector. There are probably just
as many poorly performing business projects in the private sector. They are simply
not as publicized. Many suggest that the real problem lies with project management
in general, and that project management tools and techniques have not been effectively
applied. This in turn has led to a call for further research into developing new techniques,
and in educating and certifying more project managers in the associated skills.
Increasing our capability to deliver projects is perhaps the most convenient response
to the situation. The more fundamental issue is whether or not classical project management
concepts still apply and to what extent they fit the new realities of greater complexity.
This has given rise to much debate and a lot of controversy.
To focus the debate, we must first explore a simpler question. Can projects be
classified by some parameter such as their propensity to fail? And if so, the degree
to which this propensity would be dependent on:
- The capability of the project team, or
- The project commodity type (information technology; systems engineering, buildings,
- Some other more appropriate indicator.
The Dynamic Baseline Model (DBM) provides
a framework for addressing these types of questions. Using a set of graphical depictions,
constructs, and terminologies, the DBM explores the evolution of project management
behaviors. It establishes realistic levels of project complexity and expectations,
and provides a linkage, or matching, between the behavior and the project complexity
The model provides a context for discussion. It helps us to ask the right questions,
to address the courses of action necessary for improving our performance, and to identify
learning requirements appropriate for today's projects.
1. Seely, Mark,
& Duong, Quang. (1999). The Dynamic Baseline Model, published on the Internet,
(accessed June 1999)