When a project is developed in a framework out of optimal conditions, the rate at which it progress, and/or the quantity of resources used for its completion, is somehow affected by each of the non-optimal conditions (nOC). In the case of a single nOC, the quantity of resources (units) needed to complete a given task will be larger than the quantity required to complete it in optimal conditions. That single nOC will be associated to a PF as follows: (1) Where: is the quantity of units required for the completion of the task when executed in optimal conditions. This value is obtained from a benchmark and supposed accurate. is the quantity of units required for the completion of the task when executed in non-optimal conditions. PF is the factor associated to the nOC that affects the productivity in the execution of the task, and causes a larger quantity of units required to complete it. In the case of multiple (m) non-optimal conditions affecting the execution of a task, the expression (1) changes as follow: , and we can define:

Where are the productivity factors associated to each of the non-optimal conditions, and the function is to be defined within the model to be developed and tested. is the global productivity factor, a function of the s. In an environment of nOCs within a time period t, there will occur k identifiable events associated with each nOC that will affect the execution of tasks. An observer will be capable of classifying and registering those events according to its source and affected tasks. Given a large enough set of tasks and time periods, it is of our interest to translate the number of events of a given kind into a corresponding .