How Can Enterprises Leverage the Digital Twin Technology?

In the modern world, it is not an overstatement to say that every business is a software organization. A recent report states that the average firm deploys 464 custom software and for larger organizations with more than 50k workers, the figure is 788. Such widespreadness, nevertheless, has a price. Another recent study indicated that 98% of businesses now lose at least $100,000 per hour of downtime. A significant obstacle to minimizing their disruption is the growing size and complexity of digital infrastructure brought on by AI-based elements and hybrid implementations spanning cloud and on-premise computing infrastructure.

In addition to their primary functions, modern business apps are expected to support the required throughput and latency, as well as  meet other SLA requirements like dependability and resilience. Such non-functional requirements present a greater difficulty for enterprise IT systems at the scale of businesses.

Agile software development and distributed deployment expose applications to a variety of issues that can impair the performance, such as excessive latencies and unavailability. It is important to take into account both internal and external issues, including hardware failure, software bugs, memory leaks, and synchronization. External considerations include an increase in the number of users, the types of users, and the quantity of the data.

In the contemporary business environment, there is a fundamental requirement for a deeper adoption of corporate IT platforms and proactive maintenance procedures. In order to take corrective action well before a disruption, the systems should be able to detect potential faults and forecast threats at the earliest opportunity.

The Rise of Digital Twin Technology

The idea of "digital twin technology," which is a digital duplicate of a process, system, product, or service, is a powerful concept utilized for large physical systems like boilers, IoT systems, engines, and even enterprises. In fact, over the past four years (2016-2020), “Digital Twin” has been mentioned in Gartner’s Strategic Technology Trends.

A digital twin basically imitates the behavior of the associated physical object and continuously improves by ingesting data (such as load, sensor readings, etc.) from many sources in order to stay updated and operate precisely.

Digital twin technology assists in simulating the company operating architecture at the corporate level. A set of AI-powered digital twin technologies for each part of the architecture, such as the network system, database system, and transaction processing system will make up a digital twin for an enterprise IT system. They can offer deeper insights about the operation and performance of the relevant components. Enterprise digital twins have a significant impact on optimizing customer experiences, expanding businesses, locating bottlenecks in current business processes, and raising overall customer satisfaction. For instance, having a functional digital twin technology to proactively identify potential issues like poor reaction times and mitigate them can help businesses build a better reputation for themselves as an organization keen on fast service delivery.

The behavior of a corporate IT system in response to expansions and other unforeseen circumstances may also be understood via a digital twin. There are situations when an existing deployment cannot satisfy new business requirements. By employing robust simulations, aided by digital twin artificial intelligence, organizations to anticipate deployment concerns that would not have been obvious otherwise. Through proactive maintenance, a performance digital twin not only mitigates faults during real deployment, but also minimizes the turnaround time for responding to new or changing business requirements.