The physical and digital worlds are blending and we, as humans are becoming increasingly comfortable with rapid digitization and the logistics sector, is no different. The accelerated growth of E-commerce and Q-commerce and the linear positive graph of hyperlocal has made it necessary or businesses to be equipped to pivot operations in real-time and achieve enhanced supply chain agility. This is where digital town technology and big data are making a huge difference. Digital twin technology is transforming industries be it manufacturing or healthcare. The global digital twin market is predicted to be worth $48.2 billion by 2026.
Digital twins are simulations or virtual representations of real-world assets. A digital twin is used to identify bottlenecks and optimize operations. It helps businesses in assessing data and taking predictive measures. For supply chains to become more evolved and responsive, businesses need to be responsive as well. With a digital twin, companies can test predicted supply chain shifts and bridge gaps before they occur in the real world.
These applications augment real-time visibility. Realtime visibility helps businesses access, monitor, manage and respond to live information in the supply chain. Advanced data analytics and digital twin help in understanding bottlenecks and eco-systems to not only prune and predict situations but also furnish solutions in real-time to optimize operations, time and cost.
Here are a few key advantages of Digital Twins:
Digital twin technology is a vital representation of the real-world supply chain ecosystem. A blueprint of operations and systems crafted from the monumental, accessible, real-time data accumulated across channels. Digital twins are operationalized to automate workflows, mitigate risks and corrective action predictive measures to drive better real-time visibility and a resilient supply chain.
Digitizing the supply chain with digital twins allows all silos of a process to be continuously monitored. Data generated from any entity, system, device etc al is shared and accessed for analysis. This accumulated data helps keeps all the parties involved in the supply chain appraised about the entire supply chain on a minute-to-minute basis.
Data intelligence and digital twin models build transparency. Thus, promoting cross-organizational collaboration. With data and digital twins, any variance or disruptions are flagged in real-time. Once these are identified, businesses can render solutions rapidly. Predictive modelling is also possible with digital twins and helps businesses test various scenarios and prepare contingency plans for supply chain failures, disruptions, and supply-demand fluctuations.
Digital twins augment the safe sharing of secure information/components with the partners in the ecosystem. This collaboration aids transparent communications regardless of location. Automated workflows and predictive intelligence across supply chains are driven by Digital twins with AI/ML and low-code/no-code scripts. With an ensemble of digital twins, real-time visibility highlight any duplicates/discrepancies if any no matter where in the supply chain it occurs. This collaboration further aids real-time visibility.
Supply chain disruptions especially during COVID-19 accelerated digital transformation and adoption. Digital twins are now furthering this cause by helping businesses scale up technological advancements while reducing risks with predictive measures and real-time visibility.
Businesses are now equipped to gain better insights into every process of a product cycle from sourcing, and manufacturing to consumption.
With real-time visibility, digital twins help reduce costs. By having more visibility over your operations, a digital twin can help reduce costs. Data collection is dirty promotional to the accuracy of the digital twin which in turn helps mitigate unnecessary losses.
This article has been authored by Rahul Mehra, Co-founder of Roadcast – a vehicle telematics & delivery automation SaaS platform.