Forecasting of business processes as a decision-making tool within the proactive approach to management

Aim . The work aimed to justify and develop an integrated approach to the use of business process forecasting as a key tool for decision-making in the “from future” logic, with a special emphasis on the integration of digital twin technology and the use of nonlinear sensitivity analysis methods. Objectives . The work seeks to identify the synergistic effect of the integration of forecasting and digital twin technology based on the presented mechanism for improving the quality and depth of forecasts; to justify the use of nonlinear sensitivity analysis to assess the sustainability of forecast models and the reliability of management decisions; to propose methodological recommendations for integrating forecasting, digital twins and nonlinear sensitivity analysis into a single management decision-making process; to assess the potential benefits, and to identify the key challenges and risks associated with the implementation of such an integrated approach into management practice. Methods . The study employed methods of theoretical analysis, system analysis and data analysis to solve the problem set. Results . The work formulates and discloses the concepts of proactive management and forecasting of business processes, and it substantiates an integrated approach to their application based primarily on the use of digital twins. The concept of decision-making from the future is disclosed as a strategic paradigm, while organizations do not simply predict the most probable future with it, but form actively the desired development scenario and create a strategy to achieve it. The necessity and importance of nonlinear sensitivity analysis within the approach described is substantiated. Conclusions . The study enabled to substantiate and detail an integrated approach to forecasting business processes as a central tool for decision-making in the “from future” logic. It reveals that in the context of increasing dynamism and uncertainty of the external environment, traditional reactive management methods are becoming insufficient, giving way to a proactive paradigm aimed at shaping the desired future. The key element of such a transition is the synergistic combination of advanced analytical methods.