The analysis of the planning activities of industrial construction projects can help to evaluate some of the causes that have an impact on the variation of execution times and can also contribute to identifying those activities and components that are most likely to experience or cause delays. Data analysis is facilitated by the use of techniques based on statistical programs, allowing delays to be unequivocally linked to the different elements that make up these projects. In a theoretical study, a simulation is carried out with data that are hypothetical but consistent with real projects, which are transformed and standardized before being uploaded to the statistical software. Using the statistical software’s graphical interface, the data set is analyzed from a descriptive point of view, unraveling the relationships between variables and factors by means of contingency tables and scatter plots. Using other techniques such as the comparison of variables and correlation studies, as well as linear regression and variance analysis, the characteristics are evaluated and the differences in project delays are investigated in order to determine, after the fact, which components have the highest rates of delay in execution times.
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