COMPETITIVE STRATEGY ASSESSMENT MODELS BASED ON THE USE OF PREDICTIONAL ANALYTICS

Abstract

The paper notes that today an important role in the assessment of competitive strategies is played by the use of predictive analytics, which allows predicting future trends, market changes and consumer behavior based on the analysis of large volumes of data. This opens up new opportunities for developing strategies based not only on current conditions, but also on predictions that help companies proactively respond to possible challenges and changes. Predictive analytics combines methods of statistics, machine learning and artificial intelligence to identify hidden patterns in data, which allows for a more accurate assessment of the company's competitive position and its ability to adapt to a rapidly changing environment. This allows not only to increase the efficiency of the decision-making process, but also to create more flexible and adaptive strategies that allow maintaining or strengthening leadership positions. The purpose of the presented paper is to analyze modern models of assessing competitive strategies based on the use of predictive analytics. The main methods presented in the work are: methods of analysis and synthesis, logical method, comparison method, comparison method, analytical method, induction and deduction methods. Models for evaluating competitive strategies based on the use of predictive analytics significantly increase the effectiveness of strategic management and allow companies to make informed decisions based on the analysis of big data and predictions of future trends. The use of predictive models helps not only to assess the current competitive position of the enterprise, but also to predict possible changes in the market, analyze the behavior of consumers and competitors, which makes it possible to timely adjust strategies and maintain or gain leadership in the market. The integration of predictive analytics into the process of evaluating competitive strategies allows companies to adapt to changes in the external environment, respond promptly to new challenges and opportunities, and also provide more accurate and reliable forecasting of the results of various strategic initiatives. In particular, thanks to the use of technologies such as machine learning and artificial intelligence, enterprises are able to automate analysis processes and receive up-to-date data faster, which reduces risks and increases competitiveness. That is why the use of predictive analytics in the assessment of competitive strategies is becoming an essential tool for businesses that seek not only to respond to current market needs, but also to proactively create strategies based on accurate forecasts that guarantee long-term success and stable development in a dynamic business environment.