In dem zunehmend komplexen Geschäftsumfeld von heute ist das Management der Lieferkette wichtiger denn je. Der Bullwhip-Effekt, ein Phänomen, bei dem kleine Nachfrageschwankungen auf der Verbraucherebene zu größeren und chaotischeren Schwankungen auf der vorgelagerten Ebene führen, stellt Unternehmen vor enorme Herausforderungen. Der Einsatz von Künstlicher Intelligenz (KI) wird zunehmend als transformative Lösung zur Minderung des Bullwhip-Effekts gesehen. Eine aktuelle Studie mit dem Titel „Revisiting the Bullwhip Effect: How Can AI Smoothen the Bullwhip Phenomenon?“ von Eric Weisz, David M. Herold und Sebastian Kummer untersucht das Potenzial von KI, den Bullwhip-Effekt in Lieferketten zu verringern und liefert wertvolle Erkenntnisse für Unternehmen und die Wissenschaft.
The bullwhip effect: a constant challenge
The bullwhip effect refers to the amplification of demand fluctuations in the supply chain, leading to inefficiencies such as overproduction, excessive inventory and poor customer service. Weisz, Herold and Kummer emphasise the importance of approaching this problem from a management perspective and argue that AI could play a crucial role in smoothing out these fluctuations.
The role of AI in supply chain management
According to the authors, AI can mitigate the bullwhip effect by improving key management pillars such as collaboration, leadership and digital capabilities. These pillars are essential for the successful integration of AI into supply chains.
Collaboration: AI can foster better collaboration by improving communication and data sharing between supply chain partners. However, the study points out that while the potential of AI for collaboration is clear, the role of AI in building trust between supply chain members is limited. Trust is a crucial element for any effective collaboration, and future research should focus on how AI can help overcome trust-related challenges.
Leadership: Strong leadership is essential for the successful adoption of AI in supply chains. The study highlights that leaders must not only focus on the technical aspects of AI integration, but also master the human dimensions, including change management and managing organizational dynamics.
Digital skills: For AI to be used effectively, companies need to invest in building a digitally skilled workforce. Weisz, Herold and Kummer point to the growing digital skills gap and argue that companies need to prioritize upskilling to cope with AI-driven innovation in the supply chain. This focus on digital skills is crucial for long-term success.
Key research gaps
The study identifies several research gaps and areas for future investigation:
The role of AI in addressing the bullwhip effect: While much attention has been paid to the technical applications of AI, less attention has been paid to its role in smoothing the bullwhip effect from a managerial perspective. The authors suggest that frameworks such as their proposed Bullwhip Smoothing Framework (BSF) could form a basis for future studies.
Trust and collaboration in AI-enabled supply chains: Although collaboration is a key factor in reducing the bullwhip effect, there is limited research linking AI to collaborative practices. Further studies are needed to investigate how AI can build trust and manage conflicts of interest between supply chain members.
Leadership and digital skills for AI integration: The study finds that there is a lack of detailed research on the specific leadership and digital skills required for successful implementation of AI in supply chains. Future work should examine the structural changes and skill requirements needed for this transition.
Theoretical and practical contributions
Theoretical implications: The study makes an important contribution by extending the theories of supply chain management to include the role of AI in combating the bullwhip effect. The authors propose the BSF as a tool to analyze how AI can smooth the bullwhip phenomenon by focusing on collaboration, leadership, and digital capabilities.
Practical implications: From a practical perspective, the authors emphasize that the introduction of AI alone is not enough to eliminate the bullwhip effect, but that it must be supported by strong management practices. Leaders need to develop transparent, ethical frameworks for the use of AI while ensuring that AI performance metrics are aligned with organizational goals.
A call for further research
The study by Weisz, Herold and Kummer is an important first step in understanding how AI can mitigate the bullwhip effect in supply chains. However, as the authors themselves emphasize, the integration of AI into supply chain management is still at an early stage. There are many opportunities for further research, particularly in the areas of AI-driven collaboration, leadership and digital capability development.
As AI continues to evolve and become more integrated into supply chains, organizations that can effectively manage these three key pillars will be best positioned to reduce inefficiencies and respond to market demands. At Circlly, we are dedicated to staying at the forefront of these technological advances and providing insights on how organizations can adapt to the future of supply chain management.
For a deeper dive into the original research, you can check out the full study “Revisiting the Bullwhip Effect: How Can AI Smoothen the Bullwhip Phenomenon?” by Eric Weisz, David M. Herold and Sebastian Kummer.
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