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Modeling Strategic Decisions Using Activity Diagrams to Consider the Contribution of Dynamic Planning in the Profitability of Projects Under Uncertainty

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2 Author(s)
García-Fernández, L.E. ; Dept. de Ing. de Sist. Telematicos, Univ. Politec. de Madrid, Madrid, Spain ; Garijo, M.

In this paper, a framework to consider the contribution of decision making and dynamic planning in the profitability of a project under uncertainty is proposed. Unified modeling language (UML) activity diagrams are constructed for different strategies of an ongoing engineering project whose final profitability is highly influenced by a set of uncertain variables, such as demand, costs and prices, or unexpected events. Some of these strategies can be, for instance, expanding, contracting, switching, abandoning, waiting, transferring, etc. A method to derive a simple mathematical model for carrying out a project from any UML activity diagram describing the strategy is also presented. This mathematical model can be easily implemented in a simulation environment, where the random nature of the different uncertain variables of the project, the relationships between them, and its final profitability can be considered. An example of the application of the proposed model is shown. This example also illustrates how to model the uncertainty in demand by means of a stochastic Bass process. We suggest that the proposed methodology be used by itself or as a complementary tool to the existing methods of capital budgeting by solving some of the deficiencies found in them. For instance: 1) net present value or return on investment is static in nature and cannot cope with uncertainty; 2) real options valuation may be an obscure technique and in many cases does not allow an operational strategy to be derived for guiding the project in real life; and 3) decision analysis occurs within the problem of the “flaw of averages,” by using expected values of different uncertain variables to calculate the profitability of a project instead of their complete probability distribution.

Published in:

Engineering Management, IEEE Transactions on  (Volume:57 ,  Issue: 3 )