Sustainable Inventory Management Algorithms in SAP ERP Systems
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I2P112Keywords:
SAP ERP, Sustainable Inventory Management, Green Supply Chain, Predictive Algorithms, Economic Order Quantity (EOQ), Machine Learning Forecasting, SAP S/4HANA, Optimization, Circular Economy, Just-in-Time (JIT)Abstract
Inventory management is now an important element in ensuring the sustainability of the enterprise in line with the global sustainability principles. The deployment of intelligent algorithms into SAP (Enterprise Resource Planning) systems has become a game-changer, enabling a balance between operational efficiency, cost reduction, and sustainability. This paper discusses the algorithmic models like EOQ (Economic Order Quantity), ABC Analysis, Just-in-Time (JIT), forecasting models based on Machine Learning, and Green Supply Chain Models, which can be applied in the SAP ERP modules like SAP MM (Materials Management), SAP WM (Warehouse Management), and SAP S / S/4HANA. It presents a global evaluation of sustainable inventory optimization under a multi-objective in the sense of reducing waste, carbon footprint and maximizing service. The research employs a comparative approach, examining traditional deterministic models versus more contemporary predictive Artificial Intelligence-based models. Results indicate the changes in decision-making that occur when sustainability-conscious algorithms are combined with SAP real-time analytics and the tracking of IoT data. The paper ends by suggesting a hybrid algorithmic framework that integrates predictive analysis, optimization models and circular economy concepts towards a long-term sustainable inventory management
References
1. Erdos, F., & Farhat, R. (2023). Sustainability Approach of SAP Application Management Service Solutions in the Field of Warehouse Management. Chemical Engineering Transactions, 107, 259-264.
2. Perumallaplli, R. (2015). Inventory Management Automation in SAP using Machine Learning Algorithm. Available at SSRN 5228691.
3. Nadukuru, S., Singh, D. S., Jain, S., Goel, O., & Agarwal, R. (2021). Integration of SAP Modules for Efficient Logistics and Materials Management. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 9(12), 96.
4. Aggarwal, P., & Aggarwal, A. (2023). AI-Driven Supply Chain Optimization in ERP Systems: Enhancing Demand Forecasting and inventory Management. International Journal of Management, IT & Engineering.
5. Shah, S. (2021). Analyzing and Benchmarking 5 Potential Software of New ERP for a better Inventory Management System for the case company.
6. Kulkarni, S. (2019). Implementing SAP S/4HANA. Implementing SAP S/4HANA.
7. Haas, T., & Sander, H. (2020). Decarbonizing transport in the European Union: Emission performance standards and the perspectives for a European Green Deal. Sustainability, 12(20), 8381.
8. Aro-Gordon, S., & Gupte, J. (2016). Overview of the classic economic order quantity approach to inventory management. The Business Age, 1(1), 1-20.
9. Kumar, R. (2016). Economic order quantity (EOQ) model. Global Journal of finance and economic management, 5(1), 1-5.
10. Arikan, E.; Fichtinger, J.; Ries, J. M. Impact of Transportation Lead Time Variability on the Economic and Environmental Performance of Inventory Systems. International Journal of Production Economics, 2014, 157, 279–288.
11. Schwarz, L. B. (2008). The economic order-quantity (EOQ) model. In Building intuition: insights from basic operations management models and principles (pp. 135-154). Boston, MA: Springer US.
12. Vallas, V. (2019). Planning & Implementation of a Kanban Scheduling System.
13. Kepczynski, R., Dimofte, A., Jandhyala, R., Sankaran, G., & Boyle, A. (2018). Implementing Integrated Business Planning: A Guide Exemplified With Process Context and SAP IBP Use Cases. Springer.
14. Rolia, J., Casale, G., Krishnamurthy, D., Dawson, S., & Kraft, S. (2009, October). Predictive modelling of SAP ERP applications: challenges and solutions. In Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools (pp. 1-9).
15. Pattnaik, S.; Nayak, M. M.; Abbate, S.; Centobelli, P. Recent Trends in Sustainable Inventory Models: A Literature Review. Sustainability, 2021, 13, 11756.
16. Abubakar, M., & Volikatla, H. (2021). AI and ML Algorithms for Optimizing SAP Cloud ERP. Available at SSRN 5197240.
17. Battini, D., Calzavara, M., Isolan, I., Sgarbossa, F., & Zangaro, F. (2018). Sustainability in material purchasing: A multi-objective economic order quantity model under carbon trading. Sustainability, 10(12), 4438.
18. Tseng, S. C., & Hung, S. W. (2014). A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management. Journal of Environmental Management, 133, 315-322.
19. Malladi, K. T.; Sowlati, T. Sustainability Aspects in Inventory Routing Problem: A Review of New Trends in the Literature. Journal of Cleaner Production, 2018, 197, 804 814.
20. Fazel, F. (1997). A comparative analysis of inventory costs of JIT and EOQ purchasing. International Journal of Physical Distribution & Logistics Management, 27(8), 496-504.
21. Mudunuri L.N.R.; (December, 2023); “AI-Driven Inventory Management: Never Run Out, Never Overstock”; International Journal of Advances in Engineering Research; Vol 26, Issue 6; 24-36
22. Sengupta, K., Heiser, D. R., & Cook, L. S. (2006). Manufacturing and service supply chain performance: a comparative analysis. Journal of supply chain management, 42(4), 4-15.
23. Pappula, K. K. (2020). Browser-Based Parametric Modeling: Bridging Web Technologies with CAD Kernels. International Journal of Emerging Trends in Computer Science and Information Technology, 1(3), 56-67. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I3P107
24. Rahul, N. (2020). Optimizing Claims Reserves and Payments with AI: Predictive Models for Financial Accuracy. International Journal of Emerging Trends in Computer Science and Information Technology, 1(3), 46-55. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I3P106
25. Rusum, G. P., Pappula, K. K., & Anasuri, S. (2020). Constraint Solving at Scale: Optimizing Performance in Complex Parametric Assemblies. International Journal of Emerging Trends in Computer Science and Information Technology, 1(2), 47-55. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I2P106
26. Enjam, G. R., & Chandragowda, S. C. (2020). Role-Based Access and Encryption in Multi-Tenant Insurance Architectures. International Journal of Emerging Trends in Computer Science and Information Technology, 1(4), 58-66. https://doi.org/10.63282/3050-9246.IJETCSIT-V1I4P107
27. Pappula, K. K. (2021). Modern CI/CD in Full-Stack Environments: Lessons from Source Control Migrations. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(4), 51-59. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I4P106
28. Pedda Muntala, P. S. R. (2021). Prescriptive AI in Procurement: Using Oracle AI to Recommend Optimal Supplier Decisions. International Journal of AI, BigData, Computational and Management Studies, 2(1), 76-87. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I1P108
29. Rahul, N. (2021). Strengthening Fraud Prevention with AI in P&C Insurance: Enhancing Cyber Resilience. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 43-53. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P106
30. Enjam, G. R., Chandragowda, S. C., & Tekale, K. M. (2021). Loss Ratio Optimization using Data-Driven Portfolio Segmentation. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2(1), 54-62. https://doi.org/10.63282/3050-9262.IJAIDSML-V2I1P107
31. Rusum, G. P., & Pappula, K. K. (2022). Federated Learning in Practice: Building Collaborative Models While Preserving Privacy. International Journal of Emerging Research in Engineering and Technology, 3(2), 79-88. https://doi.org/10.63282/3050-922X.IJERET-V3I2P109
32. Pappula, K. K. (2022). Modular Monoliths in Practice: A Middle Ground for Growing Product Teams. International Journal of Emerging Trends in Computer Science and Information Technology, 3(4), 53-63. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P106
33. Jangam, S. K., & Pedda Muntala, P. S. R. (2022). Role of Artificial Intelligence and Machine Learning in IoT Device Security. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(1), 77-86. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I1P108
34. Pedda Muntala, P. S. R. (2022). Detecting and Preventing Fraud in Oracle Cloud ERP Financials with Machine Learning. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 57-67. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P107
35. Rahul, N. (2022). Enhancing Claims Processing with AI: Boosting Operational Efficiency in P&C Insurance. International Journal of Emerging Trends in Computer Science and Information Technology, 3(4), 77-86. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P108
36. Enjam, G. R., & Tekale, K. M. (2022). Predictive Analytics for Claims Lifecycle Optimization in Cloud-Native Platforms. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(1), 95-104. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I1P110
37. Rusum, G. P., & Pappula, K. K. (2023). Low-Code and No-Code Evolution: Empowering Domain Experts with Declarative AI Interfaces. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 105-112. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P112
38. Pappula, K. K., & Rusum, G. P. (2023). Multi-Modal AI for Structured Data Extraction from Documents. International Journal of Emerging Research in Engineering and Technology, 4(3), 75-86. https://doi.org/10.63282/3050-922X.IJERET-V4I3P109
39. Jangam, S. K., Karri, N., & Pedda Muntala, P. S. R. (2023). Develop and Adapt a Salesforce User Experience Design Strategy that Aligns with Business Objectives. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 53-61. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P107
40. Pedda Muntala, P. S. R., & Jangam, S. K. (2023). Context-Aware AI Assistants in Oracle Fusion ERP for Real-Time Decision Support. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 75-84. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P109
41. Rahul, N. (2023). Transforming Underwriting with AI: Evolving Risk Assessment and Policy Pricing in P&C Insurance. International Journal of AI, BigData, Computational and Management Studies, 4(3), 92-101. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P110
42. Enjam, G. R. (2023). AI Governance in Regulated Cloud-Native Insurance Platforms. International Journal of AI, BigData, Computational and Management Studies, 4(3), 102-111. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P111
43. Pappula, K. K., & Rusum, G. P. (2020). Custom CAD Plugin Architecture for Enforcing Industry-Specific Design Standards. International Journal of AI, BigData, Computational and Management Studies, 1(4), 19-28. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V1I4P103
44. Rahul, N. (2020). Vehicle and Property Loss Assessment with AI: Automating Damage Estimations in Claims. International Journal of Emerging Research in Engineering and Technology, 1(4), 38-46. https://doi.org/10.63282/3050-922X.IJERET-V1I4P105
45. Enjam, G. R., & Tekale, K. M. (2020). Transitioning from Monolith to Microservices in Policy Administration. International Journal of Emerging Research in Engineering and Technology, 1(3), 45-52. https://doi.org/10.63282/3050-922X.IJERETV1I3P106
46. Pappula, K. K., & Anasuri, S. (2021). API Composition at Scale: GraphQL Federation vs. REST Aggregation. International Journal of Emerging Trends in Computer Science and Information Technology, 2(2), 54-64. https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P107
47. Pedda Muntala, P. S. R., & Jangam, S. K. (2021). Real-time Decision-Making in Fusion ERP Using Streaming Data and AI. International Journal of Emerging Research in Engineering and Technology, 2(2), 55-63. https://doi.org/10.63282/3050-922X.IJERET-V2I2P108
48. Rahul, N. (2021). AI-Enhanced API Integrations: Advancing Guidewire Ecosystems with Real-Time Data. International Journal of Emerging Research in Engineering and Technology, 2(1), 57-66. https://doi.org/10.63282/3050-922X.IJERET-V2I1P107
49. Enjam, G. R., & Chandragowda, S. C. (2021). RESTful API Design for Modular Insurance Platforms. International Journal of Emerging Research in Engineering and Technology, 2(3), 71-78. https://doi.org/10.63282/3050-922X.IJERET-V2I3P108
50. Rusum, G. P. (2022). Security-as-Code: Embedding Policy-Driven Security in CI/CD Workflows. International Journal of AI, BigData, Computational and Management Studies, 3(2), 81-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I2P108
51. Pappula, K. K. (2022). Containerized Zero-Downtime Deployments in Full-Stack Systems. International Journal of AI, BigData, Computational and Management Studies, 3(4), 60-69. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I4P107
52. Jangam, S. K., Karri, N., & Pedda Muntala, P. S. R. (2022). Advanced API Security Techniques and Service Management. International Journal of Emerging Research in Engineering and Technology, 3(4), 63-74. https://doi.org/10.63282/3050-922X.IJERET-V3I4P108
53. Pedda Muntala, P. S. R., & Karri, N. (2022). Using Oracle Fusion Analytics Warehouse (FAW) and ML to Improve KPI Visibility and Business Outcomes. International Journal of AI, BigData, Computational and Management Studies, 3(1), 79-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I1P109
54. Rahul, N. (2022). Optimizing Rating Engines through AI and Machine Learning: Revolutionizing Pricing Precision. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(3), 93-101. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I3P110
55. Enjam, G. R. (2022). Secure Data Masking Strategies for Cloud-Native Insurance Systems. International Journal of Emerging Trends in Computer Science and Information Technology, 3(2), 87-94. https://doi.org/10.63282/3050-9246.IJETCSIT-V3I2P109
56. Rusum, G. P. (2023). Large Language Models in IDEs: Context-Aware Coding, Refactoring, and Documentation. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 101-110. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P110
57. Pappula, K. K. (2023). Edge-Deployed Computer Vision for Real-Time Defect Detection. International Journal of AI, BigData, Computational and Management Studies, 4(3), 72-81. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I3P108
58. Reddy Pedda Muntala , P. S. (2025). Process Automation in Oracle Fusion Cloud Using AI Agents. International Journal of Emerging Research in Engineering and Technology, 4(4), 112-119. https://doi.org/10.63282/3050-922X.IJERET-V4I4P111
59. Rahul, N. (2023). Personalizing Policies with AI: Improving Customer Experience and Risk Assessment. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 85-94. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P110
60. Enjam, G. R. (2023). Optimizing PostgreSQL for High-Volume Insurance Transactions & Secure Backup and Restore Strategies for Databases. International Journal of Emerging Trends in Computer Science and Information Technology, 4(1), 104-111. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P112
61. Pappula, K. K., & Rusum, G. P. (2021). Designing Developer-Centric Internal APIs for Rapid Full-Stack Development. International Journal of AI, BigData, Computational and Management Studies, 2(4), 80-88. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I4P108
62. Pedda Muntala, P. S. R. (2021). Integrating AI with Oracle Fusion ERP for Autonomous Financial Close. International Journal of AI, BigData, Computational and Management Studies, 2(2), 76-86. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I2P109
63. Rusum, G. P., & Pappula, kiran K. . (2022). Event-Driven Architecture Patterns for Real-Time, Reactive Systems. International Journal of Emerging Research in Engineering and Technology, 3(3), 108-116. https://doi.org/10.63282/3050-922X.IJERET-V3I3P111
64. Jangam, S. K. (2022). Role of AI and ML in Enhancing Self-Healing Capabilities, Including Predictive Analysis and Automated Recovery. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 3(4), 47-56. https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P106
65. Pedda Muntala, P. S. R. (2022). Enhancing Financial Close with ML: Oracle Fusion Cloud Financials Case Study. International Journal of AI, BigData, Computational and Management Studies, 3(3), 62-69. https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I3P108
66. Rusum, G. P. (2023). Secure Software Supply Chains: Managing Dependencies in an AI-Augmented Dev World. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(3), 85-97. https://doi.org/10.63282/3050-9262.IJAIDSML-V4I3P110
67. Jangam, S. K., & Karri, N. (2023). Robust Error Handling, Logging, and Monitoring Mechanisms to Effectively Detect and Troubleshoot Integration Issues in MuleSoft and Salesforce Integrations. International Journal of Emerging Research in Engineering and Technology, 4(4), 80-89. https://doi.org/10.63282/3050-922X.IJERET-V4I4P108
68. Reddy Pedda Muntala, P. S., & Karri, N. (2023). Voice-Enabled ERP: Integrating Oracle Digital Assistant with Fusion ERP for Hands-Free Operations. International Journal of Emerging Trends in Computer Science and Information Technology, 4(2), 111-120. https://doi.org/10.63282/3050-9246.IJETCSIT-V4I2P111
69. Enjam, G. R., Tekale, K. M., & Chandragowda, S. C. (2023). Zero-Downtime CI/CD Production Deployments for Insurance SaaS Using Blue/Green Deployments. International Journal of Emerging Research in Engineering and Technology, 4(3), 98-106. https://doi.org/10.63282/3050-922X.IJERET-V4I3P111
