The forecasting of the consequences of nonlinear environmental impacts in large-scale IT projects

managing large-scale, fixed-budget IT projects is increasingly challenging in today's unpredictable environment. This paper presents a forecasting-based framework to enhance project resilience by anticipating and adapting to nonlinear environmental impacts. By integrating predictive models, the approach allows project managers to mitigate risks associated with unexpected external fluctuations, ensuring alignment with budget constraints. Experimental results show improved project outcomes, including a 43% reduction in forecast error (MAPE), better budget adherence, and more accurate timeline predictions. The model achieved an R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> value of 0.87, demonstrating its effectiveness in forecasting complex project dynamics. These findings highlight the framework's value in dynamic project management.