Year: 2024
Type: article
Abstract: Customer satisfaction is a critical driver of business success, particularly in industries where order management directly impacts client experience. This study explores how the implementation of SAP Order Management Automation enhances customer satisfaction by streamlining order processing, improving accuracy, and reducing lead times. Traditional order management systems often rely on manual processes that are prone to errors, inefficiencies, and delays, resulting in customer dissatisfaction. By leveraging SAP automation, organizations can integrate order management with supply chain functions, ensuring seamless data flow and real-time order tracking. The paper examines key features of SAP Order Management Automation, including automated data entry, real-time inventory updates, and proactive issue resolution. These capabilities enable businesses to minimize order inaccuracies and optimize resource utilization. Additionally, the study highlights how automation reduces dependency on manual interventions, freeing up human resources for strategic tasks and ensuring consistent service delivery. Through case studies and quantitative analysis, the research demonstrates measurable improvements in order cycle times, customer response rates, and overall satisfaction scores post-implementation. Challenges such as initial investment costs, employee training, and change management are also addressed, providing a comprehensive view of the transition to automated systems. The findings underscore the pivotal role of SAP Order Management Automation in fostering customer loyalty and operational efficiency. Businesses aiming for sustainable growth can benefit from adopting such systems to meet evolving customer expectations in a highly competitive market. This study serves as a guide for organizations looking to align their operational strategies with customer-centric objectives.
Authors: Nagender Yadav, Sneha Aravind, Mahaveer Siddagoni Bikshapathi, Prof. (Dr) MSR Prasad, Shalu Jain, Prof. (Dr) Punit Goel
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4414829645
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