ENHANCING STRATEGIC DECISION-MAKING IN INDUSTRIAL COMPANIES: A POWER BI-BASED SALES ANALYTICS DASHBOARD IMPLEMENTATION USING ACTION RESEARCH METHODOLOGY
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Date
2026-01-22
Authors
Sakhel, Abd Al-Nasser
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Journal ISSN
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Publisher
An-Najah National Universirty
Abstract
In today’s highly competitive business environment, data has become a critical asset for
supporting strategic decision-making in industrial companies. The complexity of sales
operations and the massive amount of data generated from diverse sources make it
challenging for managers to extract actionable insights using traditional methods. Business
Intelligence tools, particularly Microsoft power BI, provide advanced capabilities to
integrate, analyze, and visualize sales data in an interactive and user-friendly manner.
This study aims to design and implement a power BI-based sales analytics dashboard within
an industrial company to support strategic decision-making and improve overall business
performance. The research adopts an action research methodology, which follows iterative
cycles of planning, acting, observing, and reflecting. Through this approach, the study seeks
to identify key performance indicators relevant to sales analysis, build an effective data
model, develop an interactive dashboard, and evaluate its impact on decision-making quality
and operational efficiency.
The expected results of this study include a practical dashboard that integrates diverse sales
data sources, provides accurate and timely insights into sales performance, and enhances
managers’ ability to identify trends, forecast demand, optimize pricing strategies, and
strengthen customer segmentation through methods such as ABC and RFM analysis. By
applying Power BI in this context, the research contributes to bridging the gap between
theoretical frameworks of BI and practical applications in industrial environments.
In conclusion, the study emphasizes the transformative role of BI tools in fostering a culture
of data-driven decision-making, supporting sustainable competitiveness, and enhancing
operational performance in industrial companies.
The importance of the study lies in presenting an applied model that integrates Power BI as
an analytical platform with the ABC and RFM models as strategic tools for classifying
customers and understanding their purchasing behavior