IMPACT OF BIG DATA AND VALUE STREAM INTEGRATION ON RATIONALIZING COST DECISIONS: A LEAN ABC MODEL
DOI:
https://doi.org/10.17977/um066.v6.i6.2026.3Keywords:
Big Data Analytics (BDA), Value Stream Mapping (VSM), Cost rationalization decisions, Lean ABCAbstract
This research seeks to show the important integration of BDA and VSM strategy in rationalizing operative and manufacturing cost reduction decisions from a serval application within industrial and metallurgical zero-growth sectors, alleviating some pre-determined constraints of conventional cost accounting under the Unified Accounting System. In pursuit of this aim, it employs a descriptive-analytical approach to ground the theoretical foundation, reinforced by an applied simulation method. A complex quantitative and analytical simulation model was built using the macro-indicators and relative weights related to the financial statements (FS) of Fayadh Al-Qasim Industrial Company? FS for 2020. In this model, Lean Activity-Based Costing (Lean ABC) with variance and digital cost-driver analysis is developed on a sample of 5,616 units actual production and assembly cycles for the complete 2.5-foot air cooler production line consisting of plate cutting, chassis pressing and components/Motor assembly. These analyses and empirical results resulted in the unequivocal endorsement of an overarching comprehensive integrative hypothesis. The findings show that industrial cloud computing, IIoT and unified digital platforms can help the management accountant achieve a microscopic view of resources and the factory floor. This functionality also allows for identifying and driving out non-value-added activities and waste costs that were previously masking true product costs and responsibility centers, while improving overhead & production services tracing efficiency by 54.34. Thus, this integration resulted in a 31 reduction for total cost per unit, achieving unit savings of IQD 60628 and resultant annual accumulation of the costs for plant of 340486848 IQD without affecting quality control conditions and religion for final product inspection. The study explicitly advises investing in big data and computer numerical control (CNC) technology infrastructures, moving towards automated pull systems for documents and materials, as well as training the economic and technical staff on Process Mining tools to ensure guaranteed proactive cost containment measures for proper sustainable competitiveness.
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