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[...] This may require hiring competent professionals, investing in advanced data analysis technologies, or outsourcing certain services to fill internal gaps. - It is crucial for companies to choose robust data integration solutions and create centralized data repositories to facilitate access, analysis, and utilization of these information due to the explosion of data. - It is advisable to adopt a gradual approach to digitization. Companies have the option to start with pilot projects to test new technologies before implementing them on a large scale once they have proven their effectiveness. [...]
[...] In conclusion, competitive analysis reveals that the strategic position, supported by distinctive resources and capabilities, plays a crucial role in achieving a competitive advantage. Furthermore, agility and continuous innovation enable companies to adapt to market changes, ensuring their sustainability and success. Market study-based hypotheses This section focuses on hypotheses based on market research, highlighting the importance of understanding customer needs and market trends for marketing strategy. We will examine how consumer insights, precise segmentation, and forecasting techniques influence the effectiveness of campaigns and strategic decision-making. [...]
[...] This analysis includes evaluating competition, entry barriers, and growth opportunities. For example, using the SWOT analysis helps determine the market's strengths and vulnerabilities, facilitating the formulation of adapted strategies (Kotler & Keller, 2016)86. - Opportunity and Threat Assessment The PESTEL analysis (Politics, Economic, Sociocultural, Technological, Environmental and Legal) is a crucial tool for identifying external opportunities and threats that can affect the market. This evaluation enables companies to remain vigilant in the face of macroeconomic environmental changes and adapt accordingly (Johnson, Scholes & Whittington, 2008)87. [...]
[...] L. (2014). Consumer Behavior. Pearson. Schilling, M. A. (2010), Strategic Management of Technological Innovation, New York, McGraw-Hill/Irwin. Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2003), Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies, New York, McGraw-Hill. Smith, P. R., & Zook, Z. [...]
[...] - Limitations and Challenges of Historical Analysis - Data Reliability One of the main challenges of using historical data to forecast future trends is the reliability of the data. Historical data can be incomplete, biased, or outdated. For example, errors in data collection or changes in measurement methods can affect the accuracy of forecasts. It is therefore crucial to verify the quality of the data and adjust it if necessary (Jolliffe, 2002)77. - Unexpected Changes Historical data cannot always predict unexpected changes, such as economic crises, radical technological changes or geopolitical events. [...]
