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.     

Complexity,uncertainty and mental models: From a paradigm of regulation to a paradigm of emergence in project management

In project management research, it is acknowledged that two perspectives on project performance must be considered: project efficiency (delivering efficient outputs) and project success (delivering beneficial outcomes). The first perspective is embedded in a deterministic paradigm of project management, while the second appears more naturally connected to the emerging non-deterministic paradigm. Complexity and uncertainty are key constructs frequently associated with the non-deterministic paradigm. This conceptual paper suggests that these two concepts could very well explain and define particularities of both paradigms, and seeks to articulate both perspectives in a contingent model.First, the constructs of complexity and uncertainty are clarified. Second, the role of project managers' mental models in managerial decision-making is considered. In the third part of this article, we propose a theoretical model suggesting that project managers should consider contingent variables to differentiate managerial conditions of regulation from managerial conditions of emergence.