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A Data-Driven Cost Management Model for Improving Strategic Financial Planning and Performance Evaluation

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Oduleye, Titilayo Elizabeth, Medon, Jonathan Jemine·2021·International Journal of Multidisciplinary Research and Growth Evaluation
DOI 10.54660/.ijmrge.2021.2.6.524-537
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Abstract

Effective cost management is central to strategic financial planning and performance evaluation, yet many organizations struggle to translate transactional cost data into actionable strategic insights. This presents a data-driven cost management model that integrates granular cost capture, activity-based costing (ABC) principles, and advanced analytics to align operational spending with strategic objectives and performance metrics. The model ingests multi-source financial and operational data ERP transactions, procurement records, project schedules, and resource-utilization telemetry into a harmonized cost ontology. Using driver-based allocation and causal mapping, costs are attributed to products, projects, and business capabilities with higher fidelity than traditional ledger-only approaches. Analytical layers apply time-series forecasting, variance decomposition, and cost-behavior classification to distinguish recurring structural costs from transient operational anomalies. A constrained optimization module suggests resource reallocation and cost-reduction levers (procurement renegotiation, process automation, capacity rationalization) subject to service-level and strategic constraints. Scenario-analysis and Monte Carlo simulations quantify downside exposures and trade-offs under demand volatility and supply-chain disruption. Performance evaluation incorporates normalized KPIs cost per unit of output, contribution-margin volatility, and cost-to-serve enabling comparable benchmarking across business units and product lines. By embedding continuous monitoring dashboards and automated alerting for anomalous spend, the model shortens decision cycles and operationalizes corrective actions. Implementation considerations emphasize data governance, master-data alignment, and change management to ensure model credibility and adoption. The framework supports phased rollout pilots on high-spend processes coupled with measurable ROI metrics (cost savings realized, forecast accuracy improvement, cycle-time reduction). Empirical case studies demonstrate substantial improvements in cost transparency, strategic agility, and board-level reporting quality. Overall, a data-driven cost management model transforms cost accounting from retrospective reporting into proactive strategic steering improving capital allocation, competitiveness, and long-term financial performance.

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Metadata

Authors
Oduleye, T. E., & Medon, J. J.
Venue
International Journal of Multidisciplinary Research and Growth Evaluation
Publisher
Anfo Publication House
Published
2021
Volume
2
Issue
6
Pages
524-537
ISSN
2582-7138 (ISSN-L)
DOI
10.54660/.ijmrge.2021.2.6.524-537
OpenAlex
W7106313519
Cited by
10
References
0
Citations by year
2026: 1 · 2025: 1 · 2023: 3 · 2022: 4 · 2021: 1
FWCI
1.98
Type
journal article
Language
en
Open access
Locations
International Journal of Multidisciplinary Research and Growth Evaluation (publishedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Accounting › Accounting and Organizational Management
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Corporate Governance and Management
Keywords
cost management, strategic financial planning, performance evaluation, activity-based costing, cost allocation, cost prediction, variance decomposition, resource reallocation, process automation, supply chain disruption, scenario analysis, Monte Carlo simulation, contribution margin, cost transparency, data governance, master data management

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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. https://doi.org/10.54660/.ijmrge.2021.2.6.524-537