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  Published Paper Details:

  Paper Title

Comparative Analysis of Optimizing SAP S/4HANA in Large Enterprises

  Authors

  ER. AMIT MANGAL,  DR. PRERNA GUPTA

  Keywords

Digital transformation o Enterprise resource planning o SAP S/4HANA o Large enterprises o Optimization strategies o Real-time analytics o Process re-engineering o Customization o Implementation roadmap o Stakeholder engagement o Performance monitoring o Phased implementation o Cloud deployment o Artificial intelligence o Predictive analytics

  Abstract


In the era of digital transformation, optimizing enterprise resource planning (ERP) systems is pivotal for large enterprises aiming to enhance operational efficiency and competitiveness. This research paper presents a comparative analysis of strategies for optimizing SAP S/4HANA in large enterprises. SAP S/4HANA, SAP's next-generation business suite, offers significant advantages, including real-time analytics, streamlined processes, and enhanced user experiences. However, its implementation and optimization pose challenges that vary across industries and organizational structures. This study investigates these challenges and evaluates optimization strategies to provide a comprehensive understanding of the factors influencing successful SAP S/4HANA deployment. Through a systematic review of existing literature and case studies, this research identifies critical factors for optimizing SAP S/4HANA, including data migration, process re-engineering, and customization. It highlights the importance of a clear implementation roadmap, stakeholder engagement, and continuous performance monitoring. The paper compares various approaches adopted by large enterprises, such as phased versus big-bang implementation, on-premises versus cloud deployment, and the integration of artificial intelligence and machine learning for predictive analytics and decision-making. The comparative analysis reveals that a phased implementation approach, coupled with cloud deployment, tends to offer greater flexibility and scalability, allowing enterprises to adapt to evolving business needs. Additionally, the integration of AI and machine learning within SAP S/4HANA enhances predictive capabilities, enabling proactive decision-making and improved resource allocation. Customization, while beneficial for addressing specific business requirements, is identified as a double-edged sword that can lead to increased complexity and maintenance overhead if not managed judiciously. Furthermore, the study underscores the significance of change management and training programs in ensuring user adoption and minimizing disruption during the transition to SAP S/4HANA. It also emphasizes the role of continuous performance monitoring and optimization post-implementation to sustain the benefits of the new system.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT23A4209

  Paper ID - 267548

  Page Number(s) - j367-j379

  Pubished in - Volume 11 | Issue 4 | April 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  ER. AMIT MANGAL,  DR. PRERNA GUPTA,   "Comparative Analysis of Optimizing SAP S/4HANA in Large Enterprises", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 4, pp.j367-j379, April 2023, Available at :http://www.ijcrt.org/papers/IJCRT23A4209.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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