Algorithmic Process Optimization and Cost Reduction: A Review of Simulation Modeling and Financial Impact Assessment
Abstract
Organizations that embedded simulation-based optimization into operational and financial decision processes between 1990 and 2022 reported cost reductions ranging from four percent to 38 percent, yet fewer than one in five published studies traced those reductions through to audited financial statements, leaving a persistent disconnect between operational evidence and financial verifiability. This systematic review examines how algorithmic process optimization and simulation modeling have been linked to cost reduction and to formal financial impact assessment across three decades of accounting, finance, and operations scholarship. Following PRISMA 2020 reporting guidance, the review screened a structured corpus of peer-reviewed and refereed sources and synthesized the evidence around three themes: the methodological landscape of simulation and algorithmic optimization as applied to cost-bearing processes; the mechanisms through which optimization translates into measurable cost reduction; and the financial impact assessment frameworks that convert operational gains into verifiable economic value. The synthesis shows that discrete-event simulation, metaheuristic optimization, and system dynamics dominate the methodological field, that cost reductions concentrate in inventory, throughput, procurement, and overhead allocation, and that financial impact is most defensible when modeled returns are reconciled against realized accounting outcomes rather than projected savings. A recurring counter-finding is that optimization gains frequently fail to persist once modeling assumptions diverge from operating reality, and that reported savings are systematically overstated when assessment relies on ex ante projection. The review argues that the credibility of cost-reduction claims depends less on algorithmic sophistication than on the rigor of the financial verification that accompanies it. Theoretical, methodological, and policy implications are developed for accounting researchers, financial controllers, and practitioners seeking defensible, auditable evidence of optimization value.
Keywords
simulation modelingactivity-based costingmetaheuristic optimizationfinancial impact assessmentprocess reengineeringcost reductiondiscrete-event simulationreturn on investment
References
Adesuyi, M. O., Walawalkar, G., & Kalu, A. (2022). Predictive budgeting models using operational and market signals. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(5), 818-837. Agbabiaka, J., Okonkwo, C. S., Ogunwole, O., Mayo, W., & Okeke, O. T. (2019). Supply chain risk management model for EPC and gas processing projects. IRE Journals, 3(2), 968-980. Aifuwa, S. E., Oshoba, T. O., Ogbuefi, E., Ike, P. N., Nnabueze, S. B., & Olatunde-Thorpe, J. (2020). Predictive analytics models enhancing supply chain demand forecasting accuracy and reducing inventory management inefficiencies. International Journal of Multidisciplinary Research and Growth Evaluation, 1(3), 171-181. Akinleye, O. K., & Adeyoyin, O. (2021). Process automation framework for enhancing procurement efficiency and transparency. Shodhshauryam, International Scientific Refereed Research Journal, 4(4), 356-387. Akinleye, O. K., & Adeyoyin, O. (2022a). A negotiation optimization model for reducing procurement costs in manufacturing firms. Shodhshauryam, International Scientific Refereed Research Journal, 5(5), 398-435. Akinleye, O. K., & Adeyoyin, O. (2022b). Supplier relationship management framework for achieving strategic procurement objectives. Gyanshauryam, International Scientific Refereed Research Journal, 5(4), 565-598. Anderson, M. C., Banker, R. D., & Janakiraman, S. N. (2003). Are selling, general, and administrative costs 'sticky'? Journal of Accounting Research, 41(1), 47-63. Anderson, S. W., & Young, S. M. (1999). The impact of contextual and process factors on the evaluation of activity-based costing systems. Accounting, Organizations and Society, 24(7), 525-559. Anichukwueze, C. C., Osuji, V. C., & Oguntegbe, E. E. (2020). Designing ethics and compliance training frameworks to drive measurable cultural and behavioral change. International Journal of Multidisciplinary Research and Growth Evaluation, 1(3), 205-220. Anichukwueze, C. C., Osuji, V. C., & Oguntegbe, E. E. (2021). Blockchain-based architectures for tamper-proof regulatory recordkeeping and real-time audit readiness. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 485-504. Banker, R. D., Potter, G., & Schroeder, R. G. (1995). An empirical analysis of manufacturing overhead cost drivers. Journal of Accounting and Economics, 19(1), 115-137. Banks, J. (Ed.). (1998). Handbook of simulation: Principles, methodology, advances, applications, and practice. Wiley. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Bellman, R. (1957). Dynamic programming. Princeton University Press. Bola-Sadipe, D., Eboh, E. E., & Odihi, F. (2022). Advances in data-driven tax compliance and financial reporting systems in banking institutions. Shodhshauryam, International Scientific Refereed Research Journal, 5(1), 366-403. Brealey, R. A., Myers, S. C., & Allen, F. (2011). Principles of corporate finance (10th ed.). McGraw-Hill. Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032-1048. Cooper, R. (1990). Cost classification in unit-based and activity-based manufacturing cost systems. Journal of Cost Management, 4(3), 4-14. Cooper, R., & Kaplan, R. S. (1988). Measure costs right: Make the right decisions. Harvard Business Review, 66(5), 96-103. Dantzig, G. B. (1963). Linear programming and extensions. Princeton University Press. Datar, S., & Gupta, M. (1994). Aggregation, specification and measurement errors in product costing. The Accounting Review, 69(4), 567-591. Dixit, A. K., & Pindyck, R. S. (1994). Investment under uncertainty. Princeton University Press. Dorigo, M., & Stutzle, T. (2004). Ant colony optimization. MIT Press. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2021). Framework for data-driven operations management and performance improvement in educational institutions. Gyanshauryam, International Scientific Refereed Research Journal, 4(6), 127-158. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022a). Conceptual framework for sustainable procurement practices in local manufacturing enterprises in Africa. Gyanshauryam, International Scientific Refereed Research Journal, 5(6), 248-266. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022b). Conceptual model for data-driven lean supply chain optimization in manufacturing and retail operations. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(2), 703-734. Fishman, G. S. (2001). Discrete-event simulation: Modeling, programming, and analysis. Springer. Forrester, J. W. (1961). Industrial dynamics. MIT Press. Foster, G., & Gupta, M. (1990). Manufacturing overhead cost driver analysis. Journal of Accounting and Economics, 12(1-3), 309-337. Glover, F. (1989). Tabu search: Part I. ORSA Journal on Computing, 1(3), 190-206. Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley. Goldratt, E. M., & Cox, J. (1984). The goal: A process of ongoing improvement. North River Press. Gosselin, M. (1997). The effect of strategy and organizational structure on the adoption and implementation of activity-based costing. Accounting, Organizations and Society, 22(2), 105-122. Holland, J. H. (1992). Adaptation in natural and artificial systems. MIT Press. Hopp, W. J., & Spearman, M. L. (1996). Factory physics: Foundations of manufacturing management. Irwin. Ike, P. N., Ogbuefi, E., Nnabueze, S. B., Olatunde-Thorpe, J., Aifuwa, S. E., Oshoba, T. O., & Akokodaripon, D. (2021). Supplier relationship management strategies fostering innovation, collaboration, and resilience in global supply chain ecosystems. International Journal of Multidisciplinary Evolutionary Research, 2(2), 52-62. Ittner, C. D., Lanen, W. N., & Larcker, D. F. (2002). The association between activity-based costing and manufacturing performance. Journal of Accounting Research, 40(3), 711-726. Johnson, H. T., & Kaplan, R. S. (1987). Relevance lost: The rise and fall of management accounting. Harvard Business School Press. Kaplan, R. S., & Cooper, R. (1998). Cost and effect: Using integrated cost systems to drive profitability and performance. Harvard Business School Press. Kelton, W. D., Sadowski, R. P., & Sadowski, D. A. (1998). Simulation with Arena. McGraw-Hill. Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, 4, 1942-1948. Kennedy, T., & Affleck-Graves, J. (2001). The impact of activity-based costing techniques on firm performance. Journal of Management Accounting Research, 13(1), 19-45. Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671-680. Kleijnen, J. P. C. (2005). An overview of the design and analysis of simulation experiments for sensitivity analysis. European Journal of Operational Research, 164(2), 287-300. Labro, E., & Vanhoucke, M. (2007). A simulation analysis of interactions among errors in costing systems. The Accounting Review, 82(4), 939-962. Law, A. M., & Kelton, W. D. (2000). Simulation modeling and analysis (3rd ed.). McGraw-Hill. Lawal, O. A., & Oduleye, T. E. (2018a). A conceptual model for financial analytics driven enterprise value creation in technology firms. IRE Journals, 2(2). Lawal, O. A., & Oduleye, T. E. (2018b). A review and conceptual framework for tax governance and cross-border compliance analytics. IRE Journals, 2(5). Lawal, O. A., & Oduleye, T. E. (2021). A conceptual decision model for capital allocation using financial analytics. Gyanshauryam, International Scientific Refereed Research Journal, 4(2), 269-295. Mbonu, I. S., Aliliele, C., Iwuanyanwu, U., & Uzoka, E. (2021). A conceptual framework for risk based business intelligence architecture in financial technology platforms. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 731-746. Mbonu, I. S., Aliliele, C., Iwuanyanwu, U., & Uzoka, E. (2022). A conceptual framework for AI enabled IT general controls and SOX audit automation processes. Gyanshauryam, International Scientific Refereed Research Journal, 5(5), 384-414. Medon, J. J., & Oduleye, T. E. (2022). A comprehensive financial reporting model for strengthening compliance and organizational accountability systems. International Journal of Multidisciplinary Research and Growth Evaluation, 3(6), 768-777. Nnabueze, S. B., Ike, P. N., Olatunde-Thorpe, J., Aifuwa, S. E., Oshoba, T. O., Ogbuefi, E., & Akokodaripon, D. (2021). End-to-end visibility frameworks improving transparency, compliance, and traceability across complex global supply chain operations. International Journal of Multidisciplinary Futuristic Development, 2(2), 50-60. Noreen, E., & Soderstrom, N. (1997). The accuracy of proportional cost models: Evidence from hospital service departments. Review of Accounting Studies, 2(1), 89-114. Oduleye, T. E., & Medon, J. J. (2021). A data-driven cost management model for improving strategic financial planning and performance evaluation. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 524-537. Okonkwo, C. S., Agbabiaka, J., Ogunwole, O., Mayo, W., & Okeke, O. T. (2020). Model for demurrage elimination and port logistics efficiency in emerging economies. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 552-562. Okonkwo, C. S., Agbabiaka, J., Ogunwole, O., Mayo, W., & Okeke, O. T. (2021). Conceptual model for materials readiness and maintenance-driven supply chain performance. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 584-594. Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018a). Framework for strategic procurement optimization in oil and gas operations. IRE Journals, 1(7), 153-168. Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018b). Model for inventory availability and plant uptime improvement in energy facilities. Iconic Research and Engineering Journals, 2(4), 160-172. Okonkwo, C. S., Ogunwole, O., Okeke, O. T., & Mayo, W. (2019). Conceptual framework for cost reduction through contract negotiation and vendor governance. IRE Journals, 2(9), 468-482. Owoade, O. A., Moneke, K. C., & Anioke, S. C. (2022). Leveraging business intelligence to optimize resource allocation in mental health and substance abuse centers. Journal of Scientific and Engineering Research, 9(12), 210-235. Patrick, M. C. A., Okonkwo, C. S., Mayo, W., & Okeke, O. T. (2020). A GIS enabled framework for modern ERP procurement processes. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 499-508. Robinson, S. (2004). Simulation: The practice of model development and use. Wiley. Sanni, J. O., Ajiga, D., & Atima, M. E. (2020). Analytical models addressing measurement challenges of marketing return on investment. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 636-648. Sanni, J. O., & Atima, M. E. (2021). Business intelligence dashboard frameworks resolving executive visibility gaps in strategic marketing governance. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 633-646. Seyi-Lande, O. B., Arowogbadamu, A. A. G., & Oziri, S. T. (2022). Cross-functional key performance indicator frameworks for driving organizational alignment and sustainable business growth. International Journal of Multidisciplinary Futuristic Development, 1(2), 1-18. Shapiro, J. F. (2001). Modeling the supply chain. Duxbury. Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. McGraw-Hill. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533. Trigeorgis, L. (1996). Real options: Managerial flexibility and strategy in resource allocation. MIT Press. Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548-577. Williamson, O. E. (1985). The economic institutions of capitalism. Free Press. Womack, J. P., & Jones, D. T. (1996). Lean thinking: Banish waste and create wealth in your corporation. Simon & Schuster.
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