The major challenge addressed in this research concerns the coordination of the multiple interdependent decisions that must be made during the project, either technical, financial, or contractual. Interdependence means that making one decision without considering the impacts for other decisions may imply some underperformance, or even dead ends, iterations, and rework.To overcome this challenge, a more adaptable multi-decision-making process has been proposed, consisting of three blocks: 1/ modeling the decision network and formulating the multi-decision problem; 2/ structuring the problem to propose relevant and plausible scenarios assembled from elementary decision alternatives; 3/ solving the problem by selecting and recommending scenarios.Building the multi-decision-making process is based on multiple possibilities for each block. The decision-maker selects from a set of possible choices to adapt the decision-making process to the precise context.For block #1, we have first articulated the need to build a global decision network that models the decisions under study and the interdependencies they may have with other decisions. We have then argued that graphs and matrices can be used to fulfill this need. Both methods allow to include all decisions and interdependencies of the decision network in one single model, each of them having its advantages and drawbacks, with a kind of complementarity.Then, to formulate the local multi-decision problem, two interactions-based clustering approaches are proposed: the top-down approach (considering decision interdependencies) and the bottom-up approach (with an additional due date-based grouping of decisions). Both help to delineate the focus of decision makers on a specific set of decisions, since considering the whole network of decisions at the same time can be challenging.In block #2, to structure the problem, two matrix-based and one graph-based methods have been proposed. These methods offer the possibility to generate possible scenarios considering compatibility and performance criteria, either sequentially (morphological analysis), simultaneously (QFD), or with a hybrid way (graph exploration). For the two matrix-based methods, an algorithm was proposed to facilitate the identification of plausible scenarios. As for the graph-based method, a lighter heuristic can be applied on live during a decision meeting.Finally, to solve the problem in block #3, several MCDA methods have been listed for evaluating and selecting a recommended scenario: absolute compensatory methods, relative pairwise comparison methods, and relative comparison to reference point methods.According to industrial actors, such a process could improve coordination mechanisms between the major decisions of their projects. Even though decisions were interdependent, they were not often considered as such, and our proposed process permits (according to them) to have a better vision of the decisions to be made together and of the consequences of the choices. A fictitious case study, inspired by real past projects, was used to illustrate the proposed multi-decision coordination process.We are convinced that our research will provide a solid basis for further studies on the coordination of multiple interdependent decisions in complex projects, although there are academic and industrial perspectives that need to be tackled.