To compete in today’s market, it’s imperative that companies employ digital technology that can mirror business processes both internally and externally. Management of the modern-day supply chain requires a “digital twin” to detect threats, simulate possible outcomes, and model corrective actions.
A digital twin is a clone of physical and digital processes. Thirteen percent of organizations implementing Internet of Things (IoT) projects already use a digital twin, while 62 percent are either in the process of establishing one or plan to do so, according to a recent IoT implementation survey by Gartner, Inc. The market size of this technology is expected to reach $15.66bn by 2023.
As supply chains mature, they experience waves of change. They have evolved from siloed physical distribution management to experiential-based management, naïve modeling such as the Beer Game, and academically inspired mathematical simulation and optimization. Digital convergence, dubbed Industry 4.0, represents the latest wave in supply-chain maturity. It embraces orchestration and synchronization, resulting in the creation of enterprise supply networks (ESNs).
To date, supply-chain managers have experience little operational success in their attempts to forecast network variability and constraints. Time delays and amplification still whipsaw the supply chain. A digitally based ecosystem holds the promise of reducing latency in supply-chain management.
The notion of a digital twin begins with the conversion of manual and physical business processes into an automated form. The resulting digital copy simulates the physical entity through the use of IoT, sensors, artificial intelligence (AI) and machine learning, augmented reality, and cognitive data analytics.
Many companies today have access to real-time data, yet struggle with harvesting that information and converting it into meaningful insights. Siloed organizational structures can’t harmonize and share information horizontally or cross-functionally. By contrast, those that have embraced digitalization are able to connect physical functions through a digital twin, leading to the creation of control towers that can synchronize demand flows.
A digital twin allows companies to realize the theoretical ability to sense, shape, and respond to customer-demand variability in real time. Vertical functions continue to execute key business processes — you can’t eliminate physical siloes — but digitization make sit possible to orchestrate and synchronize horizontally.
The shift to digital processes becomes a competitive imperative, as markets move to e-commerce and customer expectations begin to model the pattern of a fruit fly — seemingly no pattern at all. Same-day, last mile-delivery is quickly becoming the norm at all levels of the supply network. Smaller and more frequent orders, shorter lead times, product customization and disintermediation are disrupting market ecosystems.
Alternative realities need to be simulated, tested and applied well before they become market reality. A digital twin enables the supply network to run a parallel version containing the same supply entities, parameters and financial targets. In the process, companies can identify, diagnose and remove potential rocks in the road.
The digital twin uses cognitive analytics to detect patterns and identify variability from plan of actual demand. Its analyzes the level to which demand can rise or fall, arranges alternative supplies (if feasible), or tests promotions in different regions to shape demand in the most expeditious and profitable manner.
On the supply side, the twin can predict and prescribe planning remedies such as freeing up capacity or booking additional external capacity. In the aviation industry, for example, when a particular aircraft type is growing in popularity due to higher operating efficiency, the planning twin can emulate rising demand by identifying the most popular routes, regions and customer choices, then simulate the best initiative to ensure faster deliveries. In a cost-intensive, high-precision industry, the twin considers such factors as compliance and supplier quality.
On the fulfilment side, companies are already piloting driverless trucks that are outfitted with operational sensors, radio frequency identification (RFID), electronic parts catalogs and barcodes. Using digital twin technology, logistics partners can apply predictive maintenance techniques to ensure better fleet management, minimize supply disruptions, and ensure timely deliveries.
Before digital twins can rule the market, numerous obstacles must be overcome, especially on the human side. Acceptance is likely to take considerable time due to the tendency of people to trust their own instincts in the face of new technology. In addition, methods must be standardized in order for the twin to replicate the original’s physical behavior and generate fruitful outcomes. Lastly, the technology that forms the backbone of the digital twin needs to be scalable and robust enough to incorporate ever-increasing volumes of data. It must be able to learn new tricks of the trade as time passes.
Nevertheless, digital twins are rapidly emerging as a means of managing increasingly complex supply networks. As e-commerce continues to create disruptions, companies must respond or face extinction.
Sudeep Dayal is a consultant, and Richard Sherman is senior fellow with Tata Consultancy Services.
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