Latest news with #UmeshKumarSharma
Forbes
07-08-2025
- Business
- Forbes
Future-Proofing The Chip Supply Chain: Planning For Agility And Growth
Umesh Kumar Sharma is a Specialist Leader in Global Supply Chain Transformations. Semiconductor supply chains are among the most complex and globally distributed in the world. These highly specialized networks involve intricate processes, multiple geographies and deep interdependencies between front-end and back-end operations. Recent disruptions, from pandemic shutdowns to geopolitical tensions, have exposed the structural fragility of these supply chains. For example, the 2021 chip shortage alone cost automakers $210 billion in lost revenue and reduced vehicle production by 7.7 million units. For semiconductor manufacturers, supply chain reliability has escalated from an operational challenge to a boardroom-level priority with strategic implications. In response, companies are significantly ramping up production capacity, with some semiconductor majors committing $100 billion over three years and others announcing $20 billion U.S. fab expansions. However, throwing capital at the problem isn't enough. To truly future-proof operations, supply chain leaders must rethink how to plan holistically across both front-end (wafer fabrication) and back-end (assembly, test and packaging) stages. The path forward demands a cohesive strategy that unites long-term capacity planning, digital integration and synchronized execution across global nodes. Aligning Strategy With Capacity Strategic planning begins by ensuring that semiconductor capacity decisions are tightly aligned with long-term business objectives. As the global chip market is projected to surpass $1 trillion by 2030—fueled by megatrends such as artificial intelligence, electrification, autonomous vehicles and 5G connectivity—the stakes have never been higher. To capture this growth and remain competitive, semiconductor companies must go beyond reactive planning. They need to proactively quantify future capacity requirements, model investment timing and scenario-plan for various macroeconomic, regulatory and technological shifts that could impact demand and supply. This means considering not just how much capacity is needed but where it should be located, what technologies it should support and how flexible it must be to accommodate shifting product mixes. For instance, site expansions in regions like Arizona exemplify efforts to geographically diversify manufacturing footprints and mitigate risks related to geopolitical tensions or concentrated supply chains. Synchronized Front-End And Back-End Planning One of the semiconductor industry's greatest challenges is decoupling the long lead times of wafer fabrication (6-8 weeks) from the shorter cycles of back-end packaging (1-2 weeks). Without tight coordination, supply bottlenecks or excess die inventories are inevitable. To address this, companies must employ synchronized planning practices across both horizons—Sales and Operations Planning (S&OP) for front-end operations and Sales and Operations Execution (S&OE) for back-end processes. On the front-end side, S&OP focuses on mid- to long-term planning to establish an optimal wafer start plan that aligns with demand forecasts and strategic capacity goals. This plan serves as the foundation for manufacturing continuity and resource optimization. In contrast, back-end operations demand a responsive, short-term focus. S&OE enables planners to manage incoming orders, monitor material availability and swiftly respond to demand and supply fluctuations. This near-term agility ensures that packaging and testing operations remain aligned with real-time customer needs and service commitments. Agile Implementation Through Pilots As discussed in my previous article, an agile, pilot-based implementation model is critical when introducing new supply chain technologies and planning solutions. Rather than launching end-to-end transformations immediately, organizations benefit from initiating controlled pilots that test tools like AI-driven planning engines within specific products or plants. These pilots serve as learning grounds, helping validate assumptions, measure impact and refine workflows in a lower-risk environment. Once successful, the solutions can be scaled systematically across the broader supply network. This method reduces disruption, enhances team adoption and aligns planning innovations with real-world operational dynamics. Empowering Talent And Collaboration Advanced planning systems are only as effective as the people using them. Semiconductor supply chains demand highly specialized expertise, ranging from yield optimization to test protocols and lead-time management. So, upskilling the planning workforce is essential. Forward-looking companies are creating hybrid roles like 'supply chain data scientists,' who blend domain expertise with analytics to turn complex data into clear business outcomes. According to Gartner's "Supply Chain Top 25 for 2025" research, organizations that invest in analytics talent and cross-functional alignment consistently achieve higher inventory turns, improved forecast accuracy and faster decision-making. Embedding Resilience And Sustainability Future-ready semiconductor supply chains must be designed for both resilience and environmental responsibility. The CHIPS Act is catalyzing a wave of domestic investments, with over $200 billion in new U.S. semiconductor projects already in motion, according to the Semiconductor Industry Association. To meet the demands of this new landscape, companies are rethinking network design. Geographic diversification and dual sourcing strategies are becoming essential, not only to mitigate geopolitical risks but also to ensure operational continuity during regional disruptions. Organizations are actively building flexibility into their manufacturing footprints by establishing distributed assembly hubs and creating buffer capacity closer to end markets. The Path Forward Semiconductor supply chains are at an inflection point. With long lead times, rapid demand shifts and mounting geopolitical risk, companies must move from reactive to proactive planning. By aligning strategy, integrating front-end and back-end processes, embracing digital tools and fostering collaboration, supply chain leaders can build the resilience and agility needed for the decade ahead. Those that succeed will not only weather future disruptions but lead the next wave of semiconductor innovation and growth. They will set new benchmarks for responsiveness, sustainability and strategic foresight in a world where technological cycles continue to accelerate. As chips become central to everything from AI to green energy, supply chains must evolve from cost centers to enablers of competitive advantage. The organizations that invest today in intelligent, end-to-end planning will define the semiconductor landscape of tomorrow. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
29-04-2025
- Business
- Forbes
Digital Twins In The Supply Chain: Transforming Operations
Umesh Kumar Sharma is a Specialist Leader in Global Supply Chain Transformations. getty As supply chains grow more complex, organizations are increasingly turning to advanced technologies to enhance efficiency, resilience and decision-making. Among these innovations, digital twins have emerged as a transformative force in supply chain management. These virtual replicas of physical assets, processes and systems leverage real-time data, AI and predictive analytics to optimize operations. By providing a dynamic, data-driven approach, digital twins help businesses anticipate disruptions, streamline logistics and improve overall performance. A digital twin is a real-time digital counterpart of a physical object, process or system, continuously updated with live data from various sources. In supply chains, these digital models represent elements such as warehouses, production facilities and transportation networks. Unlike traditional supply chain models that rely on static historical data, digital twins integrate Internet of Things (IoT) sensors, enterprise resource planning (ERP) systems and AI tools to provide immediate insights. This dynamic approach allows organizations to monitor operations, simulate scenarios and proactively address potential disruptions before they escalate. According to McKinsey, digital-twin technologies can drive a revenue increase of up to 10%, accelerate time to market by as much as 50% and improve product quality by up to 25%. The adoption of digital twins is revolutionizing supply chain efficiency by offering unprecedented visibility and predictive capabilities. Businesses can track inventory levels, production schedules and logistics operations in real time, allowing them to quickly identify and resolve bottlenecks. Predictive analytics plays a crucial role in forecasting demand fluctuations, potential supply chain delays and equipment failures, enabling companies to implement proactive strategies. By simulating different operational scenarios, organizations can refine production schedules, optimize logistics and reduce costs. Moreover, AI-powered insights can enhance decision-making, allowing businesses to make data-driven choices regarding procurement, warehouse management and transportation. Beyond efficiency, digital twins help contribute to sustainability by reducing waste, optimizing inventory management and improving energy consumption. The fusion of AI and digital twins is driving even greater advancements in supply chain management. AI-powered demand forecasting models analyze historical data alongside external market trends to improve prediction accuracy, aligning production and inventory strategies more effectively. Companies that have adopted value chain digital twins have experienced up to 30% improvement in forecast accuracy. AI-driven automation enables supply chains to make real-time adjustments, such as optimizing delivery routes, balancing inventory levels and dynamically adjusting production schedules. Additionally, AI-powered virtual assistants enhance interactions with digital twins, streamlining decision-making across the supply chain. In manufacturing, AI-driven quality control systems integrated into digital twins use computer vision to detect defects in real time, ensuring high-quality standards are maintained. Digital twins are rapidly evolving from a futuristic concept into indispensable tools that transform real-world operations. Companies across various industries now harness these virtual replicas to simulate, predict and optimize physical processes. One of the most vivid examples comes from the automotive sector. In Regensburg, Germany, there are two versions of a BMW factory: one is a conventional physical plant while the other is an exact virtual 3D replica accessible via a screen or VR headset. According to TIME, the virtual factory mirrors real-time operations, such as painting frames, sealing doors and moving machinery, thereby providing engineers and managers with an interactive environment to simulate changes and optimize production processes before any physical modifications are made. This case illustrates how digital twins can streamline factory operations and accelerate innovation. Digital twin technology is also revolutionizing warehouse management and logistics. Companies are creating digital replicas of warehouses to monitor operations in real time. These virtual models allow managers to test various layouts and workflows—such as reconfiguring order picking paths and adjusting storage systems—without disrupting daily operations. This approach results in more efficient space utilization, lower operational costs and improved responsiveness to fluctuations in demand. Similarly, in the logistics domain, digital twins are being used to simulate end-to-end transportation networks. As explained in McKinsey's article, digital twins enable companies to forecast and optimize routing decisions, predict potential delays and adjust fleet operations dynamically. This integrated digital approach helps reduce fuel consumption, minimize delivery delays and lower overall logistics costs while enhancing service quality. Digital twins are also making an impact in other domains like healthcare, where digital twins are used for medical training and simulation. Fetal Heart VR, for example, allows doctors to virtually examine a precisely replicated human fetal heart. In aerospace and defense, virtual replicas are used to simulate high-stakes test scenarios that enhance safety and streamline the development of prototypes without risking physical assets. Despite their advantages, the adoption of digital twins presents several challenges. One significant barrier is the high initial investment required for IoT sensors, AI tools and data infrastructure. Integrating diverse data sources, including sensors, ERP systems and external providers, is another hurdle, requiring careful coordination to ensure data consistency and integrity. Cybersecurity risks also pose a concern, as digital twins rely on vast amounts of real-time data, making them potential targets for cyberattacks. Organizations must implement robust security protocols to protect sensitive information. Additionally, workforce training and change management are critical to ensuring employees can effectively utilize and adapt to this technology, requiring significant investment in skill development. As emerging technologies continue to advance, digital twins will become even more integral to supply chain operations: • AI-powered self-learning systems can enable digital twins to autonomously adapt to changing conditions, improving responsiveness and efficiency. • Blockchain integration can enhance data security and transparency, fostering greater collaboration among supply chain partners. • The rollout of 5G networks can facilitate faster data transmission, improving the real-time effectiveness of digital twins and enhancing operational agility. • Augmented reality (AR) applications can provide supply chain professionals with immersive data visualization, offering new ways to interact with and interpret complex supply chain dynamics. Digital twins are redefining supply chain management, offering real-time simulation, predictive analytics and AI-driven insights that drive efficiency, reduce risks and enhance sustainability. By strategically leveraging these digital replicas, organizations can be better prepared to transform their supply chains into agile, data-driven ecosystems ready for the challenges of tomorrow. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
