An Adaptive Process Model to Support Product Development Project Management

Projects are temporary allocations of resources commissioned to achieve a desired result. Since each project is unique, the landscape between the current state ( the start of the project) and the desired state ( the successful end of the project) is often dynamic, uncertain, and ambiguous. Conventional project plans define a set of related activities ( a work breakdown structure and activity network) with the assumptions that this set is necessary and sufficient to reach the project's desired result. Popular models for project planning ( scheduling, budgeting, etc.) and control are also based on a set of project activities that are specified and scheduled a priori. However, these assumptions often do not hold, because, as an attempt to do something novel, the actual path to a project's desired result is often revealed only by the additional light provided once the work is underway. In this paper, we model a product development process as a complex adaptive system. Rather than prespecifying which activities will be done and when, we set up: 1) a superset of general classes of activities, each with modes that vary in terms of inputs, duration, cost, and expected benefits; and 2) simple rules for activity mode combination. Thus, instead of rigidly dictating a specific project schedule a priori, we provide a "primordial soup" of activities and simple rules through which the activities can self-organize. Instead of attempting to prescribe an optimal process, we simulate thousands of adaptive cases and let the highest-value process emerge. Analyzing these cases leads to insights regarding the most likely paths ( processes) across the project landscape, the patterns of iteration along the paths, and the paths' costs, durations, risks, and values. The model also provides a decision support capability for managers. For researchers, this way of viewing projects and the modeling framework provide a new basis for future studies of agile and adaptive processes.