Integrating Artificial Intelligence into Sales and Operations Planning A Case Study for Operational Efficiency at Ascom

Sammanfattning

Artificial Intelligence is increasingly discussed to improve supply chain planning, butits value depends on how it is integrated into existing organizational processes. Thisthesis investigates how AI can support operational efficiency and quality performancein Sales and Operations Planning at Ascom Global Supply Chain. The study is basedon a qualitative case study, where interviews, document analysis, observations andliterature review were used to analyze the current S&OP process and its conditions forAI integration.The findings show that Ascom’s S&OP process has a formal monthly structure, but thatexecution is constrained by fragmented information flows, manual consolidation,spreadsheet dependency, forecast uncertainty and uneven cross-functionalcoordination. These challenges reduce operational efficiency through recurring reworkand manual interpretation. They also weaken quality performance by making planninginputs and outputs less reliable and less fit for use.The main conclusion is that AI should not be understood as a standalone solution toS&OP maturity problems. Instead, AI could create value when used as human-supervised decision support within clearly defined planning routines. Its most relevantcontribution is to improve the usability, comparability, validation and traceability ofplanning information before decisions are made. AI can support activities such as inputvalidation, forecast review, deviation learning and scenario evaluation. However, itcannot by itself resolve weak ownership, unclear handoffs, inconsistent regionalroutines or conflicting functional incentives.The thesis concludes that successful AI integration in S&OP depends on organizationaland process-related conditions as much as on technological capability. Seven enablingconditions are identified, including governance, process alignment, data quality,performance evaluation, implementation capability, trust and long-term adaptability.For Ascom, the most realistic path is therefore to introduce AI gradually throughtargeted use cases that strengthen the existing S&OP process, while keeping finaljudgment and accountability with human planners and established decision forums.