Statement of the problem. The main source of errors in a priori deterministic planning of the production system is stochastic effects on the dynamics of work performance. The field of practical application of numerous classical and innovative methods of accounting for the influence of stochastic factors is limited by dependence on subjective expert assessments and the need to collect and analyze large amounts of data. The purpose of this study is to form algorithms free from these shortcomings for the quantitative description of the effect of stochastic impacts on the duration of technical and technological processes of construction production. Results. An algorithm is formulated for calculating the dynamics and the total duration of technical and technological processes, the deterministic part of which is based on objective characteristics of non-stored resources. The description of the impact of impacts on the use profile and resource productivity takes into account the qualitative difference between discrete and continuous stochastic mechanisms for increasing the duration of processes. The conditions that must be satisfied by the probability density of reducing the performance of the resource are formulated. The form is obtained and the practical meaning of the parameters of the distribution function is determined. The formulated algorithms are implemented in the MAPLE Vmathematical package. A computer simulation of the dynamics of the implementation of the process of construction production in a wide range of parameters of stochastic effects is carried out. Conclusions. The dependences of the a priori planning horizon on the characteristics of stochastic impacts, identified based on the analysis of modeling results, indicate that even with a low probability of stochastic distortion of the resource utilization profile, the planning horizon of the dynamics of construction production decreases rapidly with the growth of stochastic impacts on their productivity. As a result, the optimal approach is based on the integration of methods of a priori planning, dynamic monitoring of project implementation results and adjustment of the scenario of implementation dynamics.