Five in Five
Five key facts at a glance!
- A convergence of challenges, from the pandemic to geopolitical conflicts and ESG regulations, has disrupted global supply chains, affecting purchasing, production, energy and logistics costs, and labor markets.
- CFOs are turning to AI-powered supply chain optimization to improve forecasting, enhance resilience and efficiency, reduce or contain costs, and mitigate and manage risk.
- AI and Machine Learning (ML) technologies provide substantial benefits to supply chain and logistics operations, including cost savings.
- The adoption of AI in supply chain and logistics faces hurdles including infrastructure complexity, scalability costs and data quality issues.
- To transform supply chain management, CFOs must first evaluate existing digital technologies, recognize their limitations, and reorganize their operations.
In an era defined by unprecedented challenges, the importance of resilient and efficient supply chains has never been more evident. The ongoing geopolitical disruptions have laid bare the vulnerabilities of traditional supply chain systems.
CFOs are now recognizing the urgent need for transformative digital solutions to fortify the supply chain operations of their companies, limit production disruptions, and regain a competitive edge.
The potential of Artificial Intelligence (AI) to revolutionize various sectors and functions is undeniable, and the supply chain is no exception.
Various leading entities have approached the topic, examining it from different perspectives:
- A recent survey by BCG (Boston Consulting Group) reveals a sobering reality: despite the concerted efforts of supply chain leaders, the true potential of AI remains largely untapped within the sector.
- Gartner envisions a promising future driven by the Industrial Internet of Things (IIoT). This transformative force promises to empower supply chains to offer differentiated services to customers with greater efficiency.
- Meanwhile, PwC forecasts a staggering potential for AI applications, projecting contributions of up to $15.7 trillion to the global economy by 2030.
In this landscape of innovation and adaptation, IBM is designing models to craft supply chains that are not only responsive and intelligent but also sustainable and highly automated.
The company’s vision includes the creation of reusable AI-infused toolkits spanning critical functions such as demand forecasting, inventory positioning, omni-channel fulfillment, returns management, and multi-tier network analysis – all essential tools for CFOs who want to stay on top of things.
The fusion of technology and innovation holds the key to reshaping the future of supply chains worldwide.
In this article, we embark on a journey to explore the dynamic landscape of AI-driven supply chain optimization and the profound impact it promises to deliver to the modern CFO.
Technological challenges of using AI in the supply chain
The global supply chain landscape has been significantly impacted by a confluence of factors, including the COVID-19 pandemic lockdowns, the Russian-Ukrainian conflict, and evolving ESG (environmental, social and governance) regulations.
The Russian invasion of Ukraine has not only resulted in local human suffering and economic turmoil but has also disrupted the global energy market, leading to surging gas and oil prices. Moreover, it is affecting the availability of commodities such as fertilizer, industrial metals, wheat, grain and oilseeds, and now also the supply of soft woods for wooden pallets and packaging, crucial for various industries.
Lockdowns and the war have caused shortages in raw materials and in elements vital to producing essential parts, such as semiconductors and electric vehicle batteries, while unrelated incidents like Brexit, the Suez Canal blockage, and container shortages have further disrupted global logistics.
Moreover, the rising focus on sustainability and ESG goals necessitates a fundamental transformation of logistics and supply chains.
Key concerns for CFOs of European and multinational companies include higher shipping and production costs and delivery disruptions.
These crises have forced companies to prioritize technologies like AI, advanced automation, digital twins, and simulation software that offer new tools for supply chain optimization.
Savvy CFOs adopt new tools to digitalize the supply chain process
To meet the challenges of managing today’s supply chain, CFOs in supply-chain-intensive industries are increasingly investing in digital capabilities.
This investment aims to support new business initiatives, enhance supply chain efficiency and productivity, streamline production lines, reduce waste, improve decision-making, and bolster resilience in the face of ongoing challenges.
Achieving this alignment requires a combination of technical skills such as supply chain analytics; business acumen for cross-functional collaboration and data-driven decision-making; financial forecasting and analysis; data accuracy and security; and adaptable risk mitigation and management behaviours.
The benefits of leveraging AI in supply chain management
AI and Machine Learning (ML) technologies offer substantial benefits to supply chain and logistics operations.
McKinsey reports that the implementation of AI has reduced costs for 61% of manufacturing executives and increased revenues for 53% of them – key figures for cash-strapped CFOs.
Crucial advantages from the use of AI in supply chain management include:
- Enhanced planning and scheduling through end-to-end visibility: AI can help streamline production scheduling, forecast bottlenecks and disruptions, and plan responses based on available company resources for more efficient operations thanks to real-time identification.
- Actionable analytical insights: AI analyses data to detect patterns and quantify trade-offs, supporting timely and intelligent decision-making.
- Inventory and demand management: AI can more accurately forecast future demand, helping to plan and achieve optimal stock levels, and prevent stock-outs or overstocking, thereby increasing operational efficiency.
- Greater production efficiency: AI can help monitor and analyse metrics such as forecast precision, timely delivery, unit output, average duration of work in progress, yield, waste, order completion rates, workstation productivity, and lead times. In the current geopolitical landscape, a single manufacturing problem can delay entire shipments and cause enormous production backlogs — a clear, recent example is the effect of the semiconductor shortages on the automotive industry.
- Streamlining ERP: AI streamlines complex supply chain processes in ERP systems, enhancing adaptability and data-driven decision-making.
Additional advantages of AI in supply chain management include:
- Back-office automation
- Accurate inventory management
- Warehouse efficiency
- Enhanced safety
- Reduced operating costs
- On-time delivery
Additionally, AI-powered tools assist in providing region-specific demand insights for customized fulfillment and for more accurate demand prediction.
On the other hand…
The adoption of AI in supply chain and logistics faces significant challenges too, including system complexities requiring substantial upfront investment for high initial setup costs, and time-consuming personnel training.
Additionally, AI adoption requires a cultural shift, involving significant change management as well as the implementation of critical procedures and technologies to ensure data privacy and security in compliance with regulations, which all need to be taken into account by a CFO considering the idea of implementing new technologies.
Despite these obstacles, the potential benefits, such as increased efficiency and reduced costs, make the deployment of AI in supply chain management a transformative technology worth pursuing.
First steps in approaching new technology
The path to transforming supply chain management in an increasingly complex and unpredictable world involves a multi-faceted approach, starting with a critical evaluation of existing digital technologies.
Selecting the right technologies is just the first step; a fundamental reorganization within the company is equally vital.
Many organizations share a common problem: various functions—such as procurement, manufacturing, logistics, and quality assurance—operate in isolated silos which results in the lack of a unified strategy for resilience in the face of adversity.
To address these challenges, CFOs should establish a cohesive, global team comprising supply chain strategists, execution experts, and technologists.
Moreover, a digital twin—a virtual replica of the actual supply chain—becomes a valuable tool. It allows organizations to model and evaluate the potential long-term consequences of different crises and related action plans, facilitating informed decision-making.
By investing in advanced forecasting techniques, CFOs can even identify early signals of future demand patterns based on historic and real time data as a crisis evolves.
In this dynamic and challenging landscape, adopting a holistic approach that combines technology, organization-wide collaboration, and real-time monitoring is the key to ensuring a resilient, adaptable and financially efficient supply chain capable of thriving in both routine and turbulent times.