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beyond buzzwords ais practical impact on supply chain operations

Beyond Buzzwords: AI’s Practical Impact On Supply Chain Operations

Share to Facebook Share to Twitter Share to Linkedin Richard is the CEO of LeanDNA, a purpose-built analytics platform for factory inventory optimization. getty In today’s hyperconnected world, supply chain management (SCM) stands at the forefront of complexity and innovation. Traditional methods struggle to keep pace with the demands of modern business, where agility, precision and foresight are paramount. Fortunately, as manufacturing organizations grapple with these challenges, a beacon of innovation emerges in the form of artificial intelligence (AI). AI is poised to revolutionize supply chain operations and transform the role of supply chain teams for the future. The pressure on supply chain executives to navigate disruptions while maintaining optimal inventory levels is palpable and intensifying. According to insights from a supply chain readiness survey conducted by Wakefield Research and our comapny, a staggering 96% of supply chain executives say they face pressure to balance preparedness for major disruption with avoiding excess inventory. This underscores the urgent need for adaptive strategies and technological solutions that provide real-time insights and enable agile decision-making. While many organizations have embarked on digital transformations and are investing in advanced technologies, a significant gap remains. Despite these investments, a whopping 76% of organizations lack a predictive view of supply and demand. This gap hinders strategic planning and limits the ability to anticipate and mitigate potential disruptions. One of the primary challenges supply chain professionals face is the pervasive reliance on manual data handling. Despite technological advancements, supply chain teams spend an average of 35% of their time on manual data manipulation. This slows down processes and increases the likelihood of errors and inefficiencies. Moreover, with over nine in ten executives admitting to relying on gut instinct for decision-making at least some of the time, the need for data-driven predictive guidance becomes increasingly evident. MORE FOR YOU Cannes Film Festival 2024: Stars Arrive On Red Carpet For Annual Event TelevisaUnivision 2024-25 Slate Touts Latino Culture, ViX Growth, Juanpa Zurita, William Levy Deals Judge Says Up To 20 Million Fintech Depositors Are At Risk From Synapse Bankruptcy Enter AI—a transformative force poised to revolutionize supply chain operations by harnessing the power of data and analytics. By leveraging AI algorithms and machine learning, organizations can unlock unprecedented visibility, efficiency, and agility across their supply chains. From inventory optimization to critical shortage prioritization, AI enables organizations to make smarter decisions faster, thereby gaining a competitive advantage in a volatile marketplace. A recent Harvard Business Review article goes into further detail on how machine learning will transform supply chain management. However, to fully realize the promise of AI in supply chain management, we must move beyond the buzzwords and delve into the “why” and “how” of AI implementation. There’s an urgent need for organizations to evolve their approach, focusing not just on adopting AI technologies but on understanding where and how AI can truly drive value in the market. Dispelling the mystique behind the buzzword, we must emphasize practical applications and tangible benefits that AI can bring to supply chain operations. Moreover, connecting the survey results to the promise of AI reveals a clear path forward. By addressing the gaps identified—such as the lack of predictive views and overreliance on manual data handling—organizations can leverage AI to bridge these deficiencies and drive tangible outcomes. Whether it’s optimizing inventory levels, prioritizing critical shortages or streamlining decision-making processes, AI offers a myriad of opportunities for supply chain transformation. The impact of AI goes beyond just optimizing existing processes; it will fundamentally transform the role of supply chain teams. In the AI-enabled supply chain of the future, human workers become strategic orchestrators, leveraging AI-driven insights to anticipate issues impacting production readiness, identify opportunities and proactively initiate prioritized actions to optimize supply chain execution. By augmenting human intelligence with machine learning capabilities, organizations can unlock new levels of productivity, efficiency and supply chain resilience. However, the journey towards AI-driven supply chain excellence is not without its challenges. One significant hurdle is the issue of change management. As organizations seek to adopt AI technologies and transform their supply chain operations, they must navigate a myriad of cultural, organizational, and technical barriers. To overcome these challenges, organizations must adopt change management strategies that foster a culture of innovation, collaboration and continuous learning. This includes clear communication about the benefits of AI adoption to your supply chain teams, providing adequate training and support for employees, and creating a supportive environment that encourages experimentation and risk-taking. By addressing these challenges head-on, manufacturing organizations can accelerate their journey toward AI-driven supply chain excellence and unlock new opportunities for growth and success. Developing a comprehensive implementation roadmap is essential for successful AI integration. This roadmap should encompass several key components: Assessment and planning: Begin by assessing the current state of the supply chain and identifying areas within your organization where AI can drive the most significant impact. Common areas of opportunity are action prioritization and confidence scoring with automated execution. Technology infrastructure: Ensure that the necessary infrastructure is in place to support AI implementation. Data quality: Establish robust data management processes to ensure quality, reliability and security of supply chain data. This may include data cleansing, normalization and integration efforts to create a unified data environment for AI analysis. Training and skills development: Provide comprehensive training programs to equip supply chain teams with the skills and knowledge needed to leverage AI effectively in their daily workflow. This may involve both technical training on AI tools and platforms as well as soft skills development in areas such as data interpretation and decision-making. Scaling with user-based workflows: Once proven successful, scale AI initiatives across the supply chain and integrate them into day-to-day operations with purpose-built workflows for key roles such as production planners, material buyers and suppliers. The future of supply chain management is AI-driven, and you need to prepare your teams for these newly emerging roles. As organizations embrace AI technologies and empower their teams with data-driven insights, they will unlock new opportunities for innovation and growth. The journey toward intelligent supply chain execution is underway, and organizations that innovate and harness the power of AI will emerge as leaders in the new era of supply chain management. With a comprehensive implementation roadmap and a commitment to change management, organizations can navigate the AI revolution and drive transformative change across their supply chain teams. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? Follow me on Twitter or LinkedIn. Check out my website. Richard Lebovitz Editorial Standards Print Reprints & Permissions

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