Implementation of Business Intelligence to Support Data-Driven Decision Making in Sales Activities
Keywords:
Business Intelligence, data-driven decision making, sales analysis, dashboard, business analyticsAbstract
As transaction data accumulates, sales operations require a clearer method to transform sales records into a foundation for decision-making. Business Intelligence (BI) is often cited as the solution. However, existing research remains fragmented across various perspectives, meaning the benefits of BI in sales and the prerequisites for its success have not yet been comprehensively summarized. Therefore, this study examines the role of BI in supporting data-driven decision-making within sales activities, while also identifying its benefits and the factors influencing its success. The study employs a qualitative literature review covering publications on BI, business analytics, dashboards, data-driven decision-making, and organizational performance. Findings from these publications were categorized by theme. The review reveals that BI processes transaction data into decision-making inputs through six stages: data collection, data preparation, analysis, visualization, interpretation, and decision action. Dashboards facilitate the monitoring of revenue, products, and sales periods. One field experiment even recorded a 3.6% average increase in revenue for online sellers after they were provided with data-rich dashboards. Five factors determine the success of BI: data quality, alignment with business processes, dashboard design, organizational capabilities and user acceptance, and the way managers interpret information—a process that still involves intuition. Thus, BI should be viewed as a capability to support decision-making rather than merely a tool for generating reports. Future research could test these findings using real-world sales data, for instance, by measuring decision-making time, data accuracy, dashboard ease of use, and business performance.
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