Company Expenses Allocation to Product Category with Enterprise Resource Planning (ERP) Category Algorithms
DOI:
https://doi.org/10.30587/jurnalmanajerial.v13i02.11306Keywords:
Cost Allocation, Profitability Analysis, Enterprise Resource Planning (ERP), FMCG Industry, Management AccountingAbstract
Background – Accurate allocation of indirect expenses remains a critical managerial challenge in fast-moving consumer goods (FMCG) companies, particularly in the toiletries sector, which operates across numerous product categories and market areas. Conventional manual allocation practices are often time-consuming, rely heavily on subjective judgment, and may slow down the decision-making process. Recent developments in enterprise resource planning (ERP) systems offer opportunities to integrate algorithm-based allocation approaches, enabling more accurate and timely profitability analysis.
Aim – This study aims to develop and evaluate an ERP-embedded Category Allocation Algorithm to improve the accuracy, efficiency, and managerial usefulness of indirect cost allocation within a large Indonesian toiletries manufacturing company.
Design / methodology / approach – Using a design science research approach combined with a single-case study, this research utilizes actual ERP transaction data from May 2023. The dataset covers IDR 188.2 billion in sales (67% domestic and 33% export) and IDR 36.0 billion in indirect expenses distributed across 397 general ledger sub-accounts. The allocation algorithm was constructed based on predefined product-category patterns and market-area rules and implemented through ERP Business Objects reporting. Evaluation was conducted based on allocation accuracy, processing efficiency, and the usefulness of managerial insights generated.
Findings – The results demonstrate that indirect expenses were automatically and transparently allocated across more than 25 product categories, generating detailed category-level Profit and Loss reports. Compared to manual methods, the ERP-based approach improved allocation accuracy, reduced processing time from several days to minutes, and enabled near-real-time profitability reporting.
Conclusion – This study shows that integrating a Category Allocation Algorithm into an ERP system can improve the accuracy, efficiency, and transparency of indirect cost allocation in the FMCG toiletries industry. The embedded ERP approach reduces time spent on manual processing and enables automated profitability reporting at the category level, supporting more data-driven managerial decision-making.
Research implication – This study contributes to the literature on management accounting and information systems by demonstrating how algorithmic cost allocation can be systematically embedded within ERP environments. The findings offer a scalable solution for FMCG companies seeking greater cost transparency, shorter reporting cycles, and data-driven strategic decision-making.
Limitations – The study is limited to one company and a one-month observation period. Future research can extend the model to multiple firms, longer time horizons, or different sub-sectors of FMCG, to increase generalisability.
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