Abstract
Purpose
This research aims to examine the potential tensions and management strategies for adopting artificial intelligence (AI) within Sales and Operations Planning (S&OP) environments.
Design/methodology/approach
We conducted in-depth interviews with eight S&OP professionals from different manufacturing firms, supplemented by interviews with AI solutions experts and secondary document analysis of various S&OP processes, to scrutinize the paradoxes associated with AI adoption in S&OP.
Findings
We revealed 12 sub-paradoxes associated with AI adoption in S&OP, culminating in 5 overarching impact pathways: (1) balancing immediate actions with long-term AI-driven strategies, (2) navigating AI adoption via centralized systems, process redesign and data unification, (3) harmonizing AI-driven S&OP identities, collaboration and technology acceptance, (4) bridging traditional human skills with innovative AI competencies and (5) managing the interrelated paradoxes of AI adoption in S&OP.
Practical implications
The findings provide a roadmap for firms to proactively address the possible tensions associated with adopting AI in S&OP, balancing standardization with flexibility and traditional expertise with AI capabilities.
Originality/value
This research offers (1) a nuanced understanding of S&OP-specific paradoxes in AI adoption, contributing to the broader literature on AI within operations management and (2) an extension to Paradox Theory by uncovering distinct manifestations at the AI–S&OP intersection.
This research aims to examine the potential tensions and management strategies for adopting artificial intelligence (AI) within Sales and Operations Planning (S&OP) environments.
Design/methodology/approach
We conducted in-depth interviews with eight S&OP professionals from different manufacturing firms, supplemented by interviews with AI solutions experts and secondary document analysis of various S&OP processes, to scrutinize the paradoxes associated with AI adoption in S&OP.
Findings
We revealed 12 sub-paradoxes associated with AI adoption in S&OP, culminating in 5 overarching impact pathways: (1) balancing immediate actions with long-term AI-driven strategies, (2) navigating AI adoption via centralized systems, process redesign and data unification, (3) harmonizing AI-driven S&OP identities, collaboration and technology acceptance, (4) bridging traditional human skills with innovative AI competencies and (5) managing the interrelated paradoxes of AI adoption in S&OP.
Practical implications
The findings provide a roadmap for firms to proactively address the possible tensions associated with adopting AI in S&OP, balancing standardization with flexibility and traditional expertise with AI capabilities.
Originality/value
This research offers (1) a nuanced understanding of S&OP-specific paradoxes in AI adoption, contributing to the broader literature on AI within operations management and (2) an extension to Paradox Theory by uncovering distinct manifestations at the AI–S&OP intersection.
| Original language | English |
|---|---|
| Pages (from-to) | 1-27 |
| Number of pages | 27 |
| Journal | International Journal of Operations and Production Management |
| Volume | 45 |
| Issue number | 13 |
| Early online date | 30 Dec 2024 |
| DOIs | |
| Publication status | Published - 2025 |
Keywords
- Interviews
- Machine learning
- Paradox theory
- S&OP
- Supply chain management
ASJC Scopus subject areas
- General Decision Sciences
- Strategy and Management
- Management of Technology and Innovation