In recent years, the growing complexity of competitive environments an‎d the rapid expansion of organizational data have rendered traditional performance eva‎luation approaches inadequate for contemporary decision-making needs. Consequently, the necessity of employing integrated models that can encompass both financial an‎d non- financial dimensions of performance alongside data-driven analyses has become increasingly evident. This study aims to design an‎d eva‎luate an integrated model combining the Balanced Scorecard (BSC) an‎d Business Intelligence (BI) frameworks, in order to demonstrate how their simultaneous application can enhance performance assessment systems an‎d organizational effectiveness. Within the research framework, key performance indicators (KPIs) aligned with the four classic BSC perspectives—financial, customer, internal processes, an‎d learning an‎d growth—were identified an‎d used as the conceptual foundation. Subsequently, based on expert opinions, business intelligence was introduced as a fifth dimension of the model to examine its role in reinforcing data-driven decision-making an‎d linking other perspectives together. Data were collected through questionnaires an‎d internal documents from a medium-sized information technology company an‎d analyzed using the Fuzzy Best–Worst Method (F-BWM). The results indicate that incorporating the BI dimension strengthens the interconnection among perspectives an‎d improves overall organizational performance. The integrated model provides a more comprehensive an‎d dynamic view of cause-an‎d- effect relationships, thereby facilitating more effective managerial decisions. Overall, the integration of analytical BI capabilities with the managerial framework of the Balanced Scorecard emerges as an efficient approach for enhancing performance eva‎luation systems an‎d advancing data-driven decision-making within organizations.

بهروز ارباب شيراني

صبا صارمي نيا , حسين خسروشاهي