A Predictive Model for Optimizing Cash Flow and Working Capital Management in Corporations
Open accessAbstract
Effective management of cash flow and working capital is critical to corporate sustainability, operational efficiency, and strategic decision-making. This study presents a predictive model designed to optimize cash flow and working capital management in corporations, integrating historical financial data, operational metrics, and market indicators to provide forward-looking insights. The model applies advanced statistical techniques, regression analysis, and predictive algorithms to forecast cash inflows, outflows, and liquidity requirements, enabling organizations to anticipate funding gaps, reduce financing costs, and improve overall financial resilience. By systematically analyzing components of working capital—such as accounts receivable, accounts payable, and inventory turnover—the model identifies bottlenecks, optimizes resource allocation, and enhances operational efficiency. In addition to operational optimization, the model supports strategic decision-making by linking cash flow projections to investment planning, risk management, and corporate growth initiatives. Scenario analysis allows corporations to evaluate the impact of market fluctuations, seasonal demand changes, and policy shifts on liquidity positions, ensuring proactive management of financial risks. Furthermore, the predictive approach enables continuous monitoring and feedback, fostering adaptive strategies that align short-term operational priorities with long-term corporate objectives. Empirical validation across multiple industry sectors demonstrates that organizations adopting this predictive framework experience improved liquidity management, reduced working capital costs, and enhanced financial planning accuracy. The model also strengthens accountability by providing management with transparent and actionable insights into cash flow dynamics, enabling data-driven decision-making and improved stakeholder confidence. Overall, this research contributes to corporate finance literature by offering a robust, data-driven methodology for predicting and optimizing cash flow and working capital, reinforcing the strategic importance of liquidity management in sustaining growth and operational stability.
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Cost control supports credibility with donors and boards because it demonstrates that leaders are capable stewards of entrusted resources.
“Cost control also supports credibility with donors and boards because it demonstrates that leaders are capable stewards of entrusted resources (Akomolafe, Agu & Bello, 2023, Liadi, 2023, Oduleye & Medon, 2023, Tawose, Ekeocha & Oluwadele, 2023).”
From Conceptual Model for Financial Sustainability and Strategic Resource Allocation in Nonprofit Organizations (2025) · cites this paper as Oduleye & Medon, 2023
A passage on the model’s significance says robust cash-flow and working-capital management strengthens stakeholder confidence by demonstrating prudent financial stewardship. It names investors, creditors, and regulators—not donors or boards—and does not specifically link cost control to their confidence. (LLM, conf=0.85)
Experimental — accuracy not yet measuredLimited managerial capacity can make it harder to negotiate effectively with donors, build diversified revenue models, implement reserve policies, or redesign allocation strategies in response to changing conditions.
“Furthermore, limited managerial capacity can make it harder to negotiate effectively with donors, build diversified revenue models, implement reserve policies, or redesign allocation strategies in response to changing conditions (Akomolafe, Agu & Bello, 2023, Liadi, 2023, Oduleye & Medon, 2023, Tawose, et al., 2023).”
From Conceptual Model for Financial Sustainability and Strategic Resource Allocation in Nonprofit Organizations (2025) · cites this paper as Oduleye & Medon, 2023
The Introduction (p. 740) says static cash-management approaches limit an organization’s ability to respond proactively to emerging challenges, and describes a model that helps management adjust priorities and allocate capital. It does not link these difficulties to limited managerial capacity or discuss negotiating with donors, diversifying revenue, or implementing reserve policies. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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Aliliele, C., Eboh, E. E., & Odihi, F. (2025) · International Journal of Scientific Research in Computer Science Engineering and Information Technology · doi:10.32628/cseit251117154
- Authors
- Oduleye, T. E., & Medon, J. J.
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2023-09-12
- OpenAlex
- W7172128855
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Working Capital and Financial Performance
- Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
- Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
- Keywords
- cash flow forecasting, working capital management, liquidity management, predictive modeling, accounts receivable, accounts payable, inventory turnover, scenario analysis, financial risk management, corporate finance, financial planning
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