Digitalization of Strategic Decision-Making in Manufacturing SMEs: A Quantitative SWOT-TOWS Analysis

The transition of contemporary manufacturing processes from digital to post-digital paradigms within the framework of Industry 5.0 necessitates the integration of both technological advancements and human-centered perspectives. This shift demands a high degree of customization and personalization in production processes, impacting both core and supporting operations. This study investigates the development of a software application designed to facilitate strategic goal-setting in manufacturing Small and Medium-sized Enterprises (SMEs) by leveraging a digitalized Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis. The research focuses on the use of this tool to collect, compare, and rank SWOT factors provided by employees and managers, in order to support data-driven strategic decision-making. The initial phase of the study involved a sample of 520 entrepreneurs and business owners from Poland, Slovakia, the Czech Republic, Hungary, and Serbia, which led to the identification of an extensive list of 83 strengths, 92 weaknesses, 78 opportunities, and 86 threats. These factors were stored in a Google Cloud Database, enabling subsequent comparisons with new data. A further 63 senior decision-makers tested the application by entering their own SWOT factors, comparing them with existing ones in the database, and ranking their significance for strategic planning. The rankings were calculated automatically, with the top-ranked factors forming the basis for further analysis. In the final stage, these rankings were reviewed by five experts from the research consortium, who conducted pairwise comparisons and employed Analytic Hierarchy Process (AHP) analysis to develop a Threats, Opportunities, Weaknesses, and Strengths (TOWS) matrix. This matrix identified potential strategic actions to optimize operations within the investigated region. The findings demonstrate the potential of the software tool to enhance strategic decision-making and improve organizational performance in manufacturing SMEs. The results offer practical insights for decision-makers seeking optimal strategies for operational optimization in their organizations.