Revolutionizing Sales and Operations Planning with Artificial Intelligence: Insights and Results

The use of Artificial Intelligence (AI) in the Sales an Operations Planning (S&OP) is an innovation in supply chain management. Extended traditional S&OP processes that involve static data, manual flow, and dispersed systems do not fit the needs of constantly evolving markets. In this paper, we consider some opportunities of AI in S&OP development and discuss the most significant changes ones, including predictive analytics, machine learning, and automation. The work being done by the research implies a case-based approach, using real-world situations in order to illustrate substantial gains in forecast precision, procedural organization and control, expenditure and financial leakage mitigation, as well as customer satisfaction. The capacity of AI that can offer to enhance decision-making and provide flexibility makes its position crucial in today’s SCMS. However, barriers including resistance from the organizational culture and employee skill deficiencies hold the key in preventing this from occurring. According to the recommendations drawn in this paper, the phases and training programmes shown in Figure 4 point the way towards bringing out the best of AI for successful S&OP modernisation.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-12-29
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.34053
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.59
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article

Revolutionizing Sales and Operations Planning with Artificial Intelligence: Insights and Results

Luis Polo
3 citations
International Journal For Multidisciplinary Research
Big Data and Business Intelligence
1.59
article

Revolutionizing Sales and Operations Planning with Artificial Intelligence: Insights and Results

Luis Polo
article en
3 citations

Abstract

The use of Artificial Intelligence (AI) in the Sales an Operations Planning (S&OP) is an innovation in supply chain management. Extended traditional S&OP processes that involve static data, manual flow, and dispersed systems do not fit the needs of constantly evolving markets. In this paper, we consider some opportunities of AI in S&OP development and discuss the most significant changes ones, including predictive analytics, machine learning, and automation. The work being done by the research implies a case-based approach, using real-world situations in order to illustrate substantial gains in forecast precision, procedural organization and control, expenditure and financial leakage mitigation, as well as customer satisfaction. The capacity of AI that can offer to enhance decision-making and provide flexibility makes its position crucial in today’s SCMS. However, barriers including resistance from the organizational culture and employee skill deficiencies hold the key in preventing this from occurring. According to the recommendations drawn in this paper, the phases and training programmes shown in Figure 4 point the way towards bringing out the best of AI for successful S&OP modernisation.

International Journal For Multidisciplinary ResearchVol. 6(6)
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Big Data and Business Intelligence
1.59
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