Perspectives on sales and operations planning: Integrating functions, creating resilience, and using artificial intelligence

Doctoral thesis, 2026

Many organizations use Sales and Operations Planning (S&OP) to create a balanced demand and supply plan in the tactical horizon. Over the years, research has established how S&OP should be implemented, the benefits it provides, how to coordinate it, and how it could be improved and matured. Although the benefits are clear, organizations have struggled with the process. One reason is the lack of integration across the functions, which can affect the output from the process. The second reason is that recent disruptions have questioned the established supply chain processes. The COVID-19 pandemic and global semiconductor shortages have highlighted the issue of supply chain resilience as many organizations struggled. Another reason is the recent rise of artificial intelligence tools, which are expected to automate supply chains and bring changes to the process. Considering the effects of these internal and external factors on the S&OP process, the purpose of this thesis is to understand how the S&OP process responds to the challenges of integration, resilience, and AI. This thesis draws from three studies to answer this purpose and employ a multiple case study approach.

The first study explores the integration requirements within each subprocess. It conceptualizes S&OP integration by examining subprocesses within S&OP. It contributes to research on integration by developing a framework for understanding how integration is created in the S&OP process. This highlights the importance of analyzing subprocesses and showing that integration requirements vary across different planning situations, thereby extending the view that a one-size-fits-all approach to S&OP is insufficient.

The second study explores how routine and temporary SCP processes interact to build organizational resilience during supply chain disruptions. The second study also explores how organizations transform from a routine state to a disruptive state. It contributes to resilience research by linking supply chain planning to resilience and clarifying the roles of both S&OP and temporary planning processes in enabling organizations to respond to disruptions. This study also contributes to the responsiveness view of the supply chain from the perspective of supply chain planning.

The third study examines the role of AI in S&OP. It highlights opportunities and barriers in the implementation of AI in S&OP. This study also analyzes existing AI implementation cases. It contributes to the emerging literature on AI in S&OP by conceptualizing AI-enabled S&OP and explaining, through a CIMO-based perspective, the mechanisms and contextual conditions that shape successful AI implementation. This study also provides conceptual guidance on how AI can support various activities in the S&OP process.

Overall this study contributes to the development of the S&OP process and how it responds to these challenges. S&OP is a dynamic process that accommodates these challenges and evolves in response to remain relevant and useful to the organization. A summary of the different contexts, interventions, mechanisms, and outcomes is provided, which synthesizes the findings across all studies in this thesis. This provides practical guidance for organizations seeking to design, adapt, and improve their S&OP processes in ways that are responsive to contextual challenges and supportive of sustained organizational performance.