Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal International Journal of Management Science and Information Technology (IJMSIT)
Lambok Rommy Sulaeman
Politeknik Takumi
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Tableau-Based Business Intelligence Analysis For the 4P Strategy and Product Sales KPIs in Vending Machines at Minori Group Lambok Rommy Sulaeman; Chowal Jundy Kumoro; Syaban Maulana; Davina Clarissa Rabbani
International Journal of Management Science and Information Technology Vol. 5 No. 2 (2025): July - December 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v5i2.5979

Abstract

This study aims to analyze the application of Business Intelligence (BI) using Tableau in supporting data-driven decision making in the marketing mix strategy (4Ps) and Key Performance Indicators (KPIs) for vending machine product sales at Minori Group. With the increasing need for efficiency and competition in the South Cikarang industrial area, Minori Group faces challenges in integrating marketing and sales data scattered across various sources. The research method used is a descriptive quantitative approach with the following stages: data collection from vending machine applications, data cleaning using Excel, integration into Tableau for visual analysis, interpretation of visualization results, and preparation of strategic recommendations. The results show that visualization with Tableau is able to provide a comprehensive picture of product performance based on the aspects of Product, Price, Place, and Promotion. The main findings show that inconsistent product placement per slot (BIN) causes sales analysis to be less accurate, while KPI calculations reveal significant variations in performance between products. Tableau has proven to be effective in helping management identify sales patterns, high-performing products, and areas that need to be optimized through promotional strategies and slot rearrangement. The integration of Marketing Mix theory, Business Intelligence, and Technology Acceptance Model (TAM) confirms that Tableau not only serves as a visualization tool, but also as a strategic platform in building a data-driven organizational culture. The implementation of BI through Tableau is expected to increase marketing effectiveness, operational efficiency, and company profitability.
How Modified BCG Matrix-Based Product Portfolio Optimization Changes Consumer Purchase Behavior: Evidence from Vending Machine Transactions Chowal Jundy Kumoro; Lambok Rommy Sulaeman; Gredinov Sumanta Malsad; Mochamad Arya Maulana
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8278

Abstract

Product portfolio optimization is essential in automated retail because vending machines operate under severe storage constraints, requiring every Stock Keeping Unit (SKU) to contribute effectively to overall sales performance. However, conventional portfolio management approaches, including the Boston Consulting Group (BCG) Matrix, rely on market-level indicators that are difficult to apply in vending machine environments where external market share data are unavailable. This study proposes a Modified BCG Matrix by replacing Relative Market Share with Relative Sales Performance (RSP) and Market Growth Rate with Sales Growth Trend (SGT) to enable SKU-level portfolio optimization using internal transaction data. A quantitative longitudinal design with an Interrupted Time Series (ITS) approach was employed using 167,018 valid transactions collected from 11 smart vending machines operating in Cikarang, Indonesia, between September 2025 and June 2026. The Modified BCG Matrix guided operational decisions, including facing allocation, replenishment priority, product rotation, replacement, and product delisting. The implementation reduced the active product portfolio from 253 to 146 SKUs (42.3%), increased average daily transaction volume by 28.53%, increased average daily sales revenue by 22.19%, and produced statistically significant immediate intervention effects based on segmented regression analysis. These findings demonstrate that data-driven product portfolio optimization not only improves operational efficiency and sales performance but also reshapes consumer purchase behavior. This study extends the application of the traditional BCG Matrix from the Strategic Business Unit (SBU) level to the SKU level and provides an evidence-based decision-support framework for automated retail portfolio management.
Co-Authors Chowal Jundy Kumoro Davina Clarissa Rabbani Gredinov Sumanta Malsad Mochamad Arya Maulana Syaban Maulana