Data Analysis in Business Management: Evidence-Based Decision Making

In the current era, data is recognized as a strategic resource in business, management, playing an unparalleled role in analyzing the current situation identifying opportunities and threats, and making informed decisions for organizations. On the other hand, increasing competition, the growing trend of big data, and the prevalence of new technology tools have made data analysis a. serious necessity for managers (Golshani, ۲۰۱۹; Mohseni-Nezhad et al., ۲۰۲۱),Evidence-Based Decision Making means the systematic use of accurate data scientific analysis, and empirical evidence to improve the efficiency and effectiveness of management (Soltani, ۲۰۲۲). In this article, we will first examine the key concepts and necessity of data analysis in business, and then analyze the process of data collection, cleaning, and interpretation. In addition, we introduce new data analysis tools and methods, including artificial intelligence and machine learning, to highlight the role of technology in promoting more transparent decision-making (Habibi, ۲۰۲۳). A vital part of the article is the examination of implementation challenges and obstacles, including cultural issues, lack of analytical skills, data quality, and ethical and information security concerns (Zare, ۲۰۲۰). Also, by reviewing several case studies from Iranian and international companies, the impact of organizational data analysis on improving, operational processes and increasing profitability is demonstrated. In conclusion the need to develop a data-driven culture, improve key management skills, and invest in data infrastructure to move towards a more agile and decisive organization is highlighted. The findings of this research can pave the way for the development of organizations based on scientific evidence and data-drivenanalysis, and provide a comprehensive model for managers to effectively cope.with the competitive environment

Keywords:

Data Analysis , Business Management , Data-Driven , Artificial Intelligence , Organizational Culture , Data Security