Summary: Digital twins have quickly evolved from a niche technology used in physical product simulations to a critical component in modern business operations. As highlighted by recent discussions in The Economist, these virtual replicas are now driving enhanced efficiency, innovation, and decision-making across various industries. However, as businesses increasingly recognize the strategic value of digital twins, it's essential to adopt them thoughtfully. A measured approach focused on well-defined use cases can help avoid the common pitfalls of overhyped technologies, ensuring that digital twins become a sustainable, competitive advantage.
Digital twins rapidly emerge as a transformative force in business operations and processes, moving far beyond their origins in physical product simulations like jet engines, space missions, or Formula 1 cars. Recent articles from The Economist highlight the expanding role of digital twins in enhancing efficiency, driving innovation, and redefining how companies operate. However, despite their potential, businesses need to adopt digital twins strategically and thoughtfully to avoid the common pitfalls that often come with overhyped technologies.
The Growing Importance of Digital Twins in Business Operations
The Economist outlines several compelling examples of how digital twins are making a significant impact
Enhanced Operational Efficiency
Digital twins offer a comprehensive digital replica of a company’s operations, enabling real-time adjustments and optimization. For instance, Uber, uses a sophisticated digital twin to manage dynamic pricing and optimize routes, leading to improved customer experiences and more efficient operations. Digital twins are making companies more efficient, The Economist.
Imagine a retail landscape where every store, customer, and employee is part of a dynamic, interconnected digital ecosystem. In this environment, digital twins, could enable a retailer to precisely orchestrate its workforce, especially in sectors where most employees are part-time or gig workers. Instead of relying on rigid schedules or static staffing models, a digital twin could simulate and predict customer behavior and store traffic patterns, dynamically aligning staffing levels to meet real-time demand. This ensures the right number of employees are in place at the right time, allowing workers to choose shifts that fit their availability while keeping the store optimally staffed. Such agility could make the difference between easily meeting peak demand or losing customers due to long wait times.
This same concept extends to managing the broader gig economy. For companies aiming to tap into this growing workforce, a digital twin of the store and its customers would be essential to navigate the complexities of dynamic demand across multiple locations. By visualizing and simulating potential scenarios, businesses could rapidly adjust staffing, inventory, and promotional strategies to capture every sales opportunity without overburdening their workforce or overspending on labor costs. The result? A more agile, efficient operation that adapts seamlessly to the ebbs and flows of consumer behavior.
Improved Decision-Making
Companies can make faster and more informed decisions with a constantly updated virtual model. Amazon leverages a digital twin to forecast demand, manage inventory, and optimize its supply chain, achieving substantial cost savings and responsiveness to market changes .
Now, envision a supply chain that thinks for itself, reacting in real-time to predictable and unpredictable changes. Digital twins allow businesses to manage supply in line with demand dynamically. Imagine a grocery chain that, thanks to its digital twin, can immediately detect when a sudden surge in demand for specific products is emerging due to an unexpected heatwave or a popular social media trend. The digital twin, constantly fed by data from every part of the supply chain, could instantly adjust procurement orders, reroute shipments, and even tweak in-store promotions to ensure that shelves are stocked with exactly what customers want when they want it. This is supply chain management with a human touch, guided by real-time data, where stockouts and overstocks become relics of the past.
Similar principles apply in manufacturing. A digital twin can allow real-time adjustments to production lines, responding dynamically to changes in customer orders, equipment health, or raw material availability. Instead of reacting to disruptions after they occur, manufacturers can proactively adjust schedules, optimize production runs, and manage inventory levels, keeping costs down while maintaining high levels of service.
Predictive Maintenance and Risk Management
Digital twins enable real-time monitoring of equipment and processes, predicting failures before they occur. Rolls-Royce uses digital twins to monitor aircraft engines, helping prevent costly downtime by addressing potential issues proactively. Digital twins are speeding up manufacturing. The Economist
Think of a world where equipment doesn’t just fail less often but never fails unexpectedly. Digital twins provide this potential by continuously monitoring equipment and processes, predicting failures before they happen, and suggesting proactive interventions. Imagine a city’s public transportation network using digital twins to monitor every train, bus, and station, identifying potential issues like wear and tear on train brakes or unexpected spikes in passenger volume before they become problems. This would allow transit authorities to schedule maintenance at the most convenient times, avoiding costly breakdowns and ensuring that public services run smoothly, regardless of the demand placed on them.
The Case for a Strategic Approach to Digital Twin Adoption
While the advantages of digital twins are evident, companies must avoid adopting this technology simply because it is trending. The key to success lies in starting with well-bounded, impactful use cases likely to demonstrate clear value and generate momentum for further adoption. Instead of attempting to transform entire systems at once, businesses should begin with specific areas, such as a particular manufacturing process or a segment of the supply chain, where digital twins can deliver measurable improvements in efficiency or cost savings.
This approach mitigates risks and allows for learning and adjustment before broader implementation. Early successes in controlled environments can help build internal support and ensure that the technology is scalable and adaptable to the organization’s broader needs.
Challenges in the Current Digital Twin Landscape
One of the primary challenges facing businesses today is the limited expertise available in the market. Despite the growing interest in digital twins and overall AI hype, there is a shortage of professionals with the skills to design, implement, and maintain these complex systems effectively.
Additionally, the market for digital twins is fragmented. Many technologies are labeled as digital twins, leading to confusion and unrealistic expectations. For instance, Nvidia's 3D digital twins primarily focus on visual representations and simulations of physical spaces, which, while useful, might be overkill for a specific use case. Similarly, process mining tools, which analyze and visualize process flows, are often mistaken for digital twins, despite lacking the simulation capabilities. Simulation tools, another category frequently mislabeled, offer predictive capabilities but do not provide model calibration and continuous, real-time data updates.
This confusion can lead to misguided investments in technologies that do not fully meet a company's needs, resulting in wasted resources and stalled digital transformation efforts.
Digital twins offer tremendous potential to revolutionize business operations, but realizing their benefits requires a measured and strategic approach. Companies should focus on clearly defined, high-impact use cases that can demonstrate value quickly and build momentum for broader adoption. At the same time, it is essential to be aware of the limited expertise in the market and the fragmented, overhyped nature of the current technology landscape.
By adopting a thoughtful, strategic approach, businesses can harness the full potential of digital twins to drive meaningful, long-term improvements in their operations, turning this powerful technology into a true competitive advantage.
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By Pavel Azaletskiy
Editor Viktoryia Karalionak