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Abstract

This study delves into the complexities of SAP migration, employing the PROMETHEE method to scrutinize four divergent strategies. Key performance indicators such as system performance, sustainability, data security, scalability, cost efficiency, and downtime are meticulously analyzed. Notably, the research explores SAP's transformative journey—from conventional on-premise systems to cutting-edge cloud-based architectures—paying particular heed to the deployment of SAP S/4HANA and its profound role in reshaping enterprise digital landscapes. The methodology leverages the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) technique, a robust multi-criteria decision-making framework, to assess four distinct migration strategies: Migration to SAP S/4HANA with Minimal Customization, Full Migration incorporating Extensive Performance Optimization, Hybrid Cloud Deployment facilitated through HPE Green Lake, and a Comprehensive Security-Focused Migration approach. By employing weighted criteria and pair wise comparisons, the analysis delves deeply into identifying the most advantageous migration path. Remarkably, the Comprehensive Security-Focused Migration strategy emerged as the leader, achieving a net flow score of 0.3266. Trailing behind, albeit significantly, was the Full Migration with Extensive Performance Optimization at 0.1448. Crucially, the research underscores that long-term strategic gains should eclipse the allure of short-term cost reductions when selecting migration methodologies. By furnishing decision-makers with actionable insights, this investigation accentuates the indispensability of a holistic evaluation framework, advocating for a shift away from myopic technical or financial considerations towards a more comprehensive, criteria-encompassing perspective.

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How to Cite
Ramancha, N. K., & Suresh Deepak Gurubasannavar. (2023). A Comparative Study of SAP Migration Approaches: Integration of PROMETHEE Method for Strategic Decision Making. International Journal of Intellectual Advancements and Research in Engineering Computations, 11(4), 23–38. https://doi.org/10.61096/ijiarec.v11.iss4.2023.23-38