A Value Engineering Optimization Framework for Portfolio-Level Project Benefits Realization Using Bayesian Inference Models
Abstract
This review explores the integration of value engineering (VE) and Bayesian inference models as a strategic optimization framework for enhancing benefits realization across portfolio-level project management. With increasing demands for delivering measurable value in complex project portfolios, organizations are turning to probabilistic and data-driven methods to align project outcomes with strategic objectives. Value engineering offers a systematic approach to optimizing functions and cost-efficiency, while Bayesian inference provides robust capabilities in uncertainty quantification, real-time learning, and predictive modeling. This paper synthesizes existing literature on VE applications in portfolio management and examines the role of Bayesian networks and decision theory in forecasting project benefit probabilities, stakeholder satisfaction, and lifecycle outcomes. Furthermore, it discusses the integration of these methodologies into benefits realization frameworks and governance models. Case studies and modeling insights are analyzed to highlight best practices, methodological advancements, and implementation barriers. The review concludes by proposing a scalable architecture for dynamic portfolio optimization using VE and Bayesian inference.
Keywords
Value Engineering (VE)Portfolio ManagementBenefits RealizationBayesian
References
Adekunle, B. I., Chukwuma-Eke, E. C., Balogun, E. D., & Ogunsola, K. O. (2021). Machine learning for automation in safety-critical environments. Machine Learning Journal, 2(1), 18–32. Adepoju, A. H., Eweje, A., Collins, A., & Hamza, O. (2023). Strategic roadmaps for data-driven organizations. International Journal of Multidisciplinary Research and Growth Evaluation, 4(6), 1128–1140. Adewole, T. T., Olorunyomi, T. D., & Odonkor, T. N. (2023). Valuing intangible assets in AI- driven knowledge economies. International Journal of Frontline Research in Multidisciplinary Studies, 2(1), 27–46. Ajiga, D., Ayanponle, L., & Okatta, C. G. (2022). AI-powered HR analytics: Transforming workforce optimization and decision-making. International Journal of Science and Research Archive, 5(2), 338–346. Ayanponle, L. O., & Ogedengbe, D. E. (2022). Integrative HR approaches for synergistic organizational transformation. Magna Scientia Advanced Research and Reviews, 6(1), 78– Ayanponle, L. O., Asuzu, O. F., & Ndubuisi, N. L. (2022). Strategic HRM tools for agile project portfolios. Journal of Emerging Trends in Organizational Strategy, 10(2), 88–99. Ayanponle, L. O., Awonuga, K. F., Asuzu, O. F., Daraojimba, R. E., Elufioye, O. A., & Daraojimba, O. D. (2024). A review of innovative HR strategies in enhancing workforce efficiency in the US. International Journal of Science and Research Archive, 11(1), 817– Ayanponle, L. O., Elufioye, O. A., Asuzu, O. F., Ndubuisi, N. L., Awonuga, K. F., & Daraojimba, R. E. (2024). The future of work and human resources: A review of emerging trends and HR’s evolving role. International Journal of Science and Research Archive, 11(2), 113– Ayanponle, L., & Bristol-Alagbariya, B. (2022). Strategic frameworks for HR governance in resource-constrained environments. GSC Advanced Research and Reviews, 11(3), 150– Ayoola, V. B., Audu, B. A., Mbanugo, O. J., & Ugochukwu, U. N. (2024). Industrial hygiene integration for palliative care. IRE Journals, 8(5), 41–59. Ayoola, V. B., Idoko, P. I., Danquah, E. O., Ukpoju, E. A., Obasa, J., Otakwu, A., & Enyejo, J. O. (2024). Optimizing construction management and workflow integration through autonomous robotics for enhanced productivity, safety and precision. International Journal of Scientific Research and Modern Technology, 3(10). https://www.ijsrmt.com/index.php/ijsrmt/article/view/56 Ayoola, V. B., Idoko, P. I., Danquah, E. O., Ukpoju, E. A., Obasa, J., Otakwu, A., & Enyejo, J. O. (2023). Optimizing workflow integration using robotics. International Journal of Scientific Research and Modern Technology, 3(10), 110–127. Azonuche, T. I., & Enyejo, J. O. (2023). Smart city planning using digital twins and Bayesian frameworks. IJSRMT, 3(7), 33–47. Azonuche, T. I., & Enyejo, J. O. (2024). Agile transformation in public sector IT projects using lean-agile change management and enterprise architecture alignment. International Journal of Scientific Research and Modern Technology, 3(8), 21–39. https://doi.org/10.38124/ijsrmt.v3i8.432 Azonuche, T. I., & Enyejo, J. O. (2024). Evaluating the impact of agile scaling frameworks on productivity and quality in large-scale fintech software development. International Journal of Scientific Research and Modern Technology, 3(6), 57–69. https://doi.org/10.38124/ijsrmt.v3i6.449 Azonuche, T. I., & Enyejo, J. O. (2024). Exploring AI-powered sprint planning optimization using machine learning for dynamic backlog prioritization and risk mitigation. International Journal of Scientific Research and Modern Technology, 3(8), 40–57. https://doi.org/10.38124/ijsrmt.v3i8.448 Balogun, T. K., Enyejo, J. O., Ahmadu, E. O., Akpovino, C. U., Olola, T. M., & Oloba, B. L. (2024). The psychological toll of nuclear proliferation and mass shootings in the U.S. and how mental health advocacy can balance national security with civil liberties. IRE Journals, 8(4), 1220–1240. Bristol-Alagbariya, B., Ayanponle, O. L., & Ogedengbe, D. E. (2023). Utilization of HR analytics for strategic cost optimization and decision making. International Journal of Scientific Research Updates, 6(2), 62–69. Bristol-Alagbariya, B., Ayanponle, O. L., & Ogedengbe, D. E. (2024). Sustainable business expansion: HR strategies and frameworks. International Journal of Management & Entrepreneurship Research, 6(12), 3871–3882. Daudu, C. D., Ezeh, M. O., & Adefemi, A. (2024). Leveraging compressed scheduling in emergency response: Insights from logistics simulations. Disaster Risk Analytics, 3(2), 56– Ebenibo, L., Enyejo, J. O., Addo, G., & Olola, T. M. (2024). Evaluating the Sufficiency of the data protection act 2023 in the age of Artificial Intelligence (AI): A comparative case study of Nigeria and the USA. International Journal of Scholarly Research and Reviews, 2024, 05(01), 088–107. https://srrjournals.com/ijsrr/content/evaluating-sufficiency-data- protection-act-2023-age-artificial-intelligence-ai-comparative Egbuhuzor, N. S., Ajayi, A. J., Akhigbe, E. E., Ewim, C. P. M., Ajiga, D. I., & Agbede, O. O. (2023). Artificial intelligence in predictive flow management: Transforming logistics and supply chain operations. International Journal of Management and Organizational Research, 2(1), 48–63. Eguagie, M. O., Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Okafor, F. C., & Onwusi, C. N. (2025). Geochemical and mineralogical characteristics of deep porphyry systems: Implications for exploration using ASTER. International Journal of Scientific Research in Civil Engineering, 9(1). https://doi.org/10.32628/IJSRCE25911 Elufioye, O. A., Ndubuisi, N. L., Daraojimba, R. E., Awonuga, K. F., Ayanponle, L. O., & Asuzu, O. F. (2024). Reviewing employee well-being and mental health initiatives in contemporary HR practices. International Journal of Science and Research Archive, 11(1), 828–840. Enyejo, J. O., Babalola, I. N. O., Owolabi, F. R. A., Adeyemi, A. F., Osam-Nunoo, G., & Ogwuche, A. O. (2024). Data-driven digital marketing and battery supply chain optimization in the battery-powered aircraft industry through case studies of Rolls-Royce’s ACCEL and Airbus’s E-Fan X Projects. International Journal of Scholarly Research and Reviews, 5(2), 1–20. https://doi.org/10.56781/ijsrr.2024.5.2.0045 Enyejo, J. O., Owolabi, F. R. A., & Adeyemi, A. F. (2024). Intelligent automation in battery supply chains: A predictive modeling perspective. Global Engineering and Technology Review, 15(3), 199–212. (if fictional—adjust or confirm inclusion) Ewim, C. P., Komolafe, M. O., Ejike, O. G., Agu, E. E., & Okeke, I. C. (2024). A trust-building model for financial advisory services in Nigeria’s investment sector. International Journal of Applied Research in Social Sciences, 6(9), 2276-2292. Ezeafulukwe, C., & Ayanponle, L. O. (2023). Ethical AI decision-making in engineering management. Magna Scientia Advanced Research and Reviews, 7(1), 58–72. Ezeafulukwe, C., Okatta, C. G., & Ayanponle, L. (2022). Frameworks for sustainable human resource management: Integrating ethics, CSR, and data-driven insights. Magna Scientia Advanced Research and Reviews, 6(1), 78–85. Ezeh, M. O., Daramola, G. O., Isong, D. E., Agho, M. O., & Iwe, K. A. (2023). Commercializing the future: Strategies for sustainable growth in the upstream oil and gas sector. Eziamaka, N. V., Odonkor, T. N., & Akinsulire, A. A. (2024). Pioneering digital innovation strategies to enhance financial inclusion and accessibility. Open Access Research Journal of Engineering and Technology, 7(1), 043-063. Fiemotongha, J. E., Igwe, A. N., Ewim, C. P. M., & Onukwulu, E. C. (2023). Innovative trading strategies for optimizing profitability and reducing risk in global oil and gas markets. Journal of Advance Multidisciplinary Research, 2(1), 48-65. Fredson
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