Can Digital Twin Unlock Your Digital Transformation?
Digital twin is currently one of the hottest trends in technology. Vendors across a range of spectrums are racing to claim that they somehow ‘support/enable digital twins’. But as with anything at its peak in the hype cycle, deciphering the noise and rationalizing the different voices is a full time job in itself.
So why is digital twin suddenly all the rage? How does it compare to existing capabilities? And how exactly do you go about establishing it within your organization?
Whilst there are myriad definitions bandied around, digital twins are widely accepted to be a virtual mirror of a physical item; a replication that simulates a real-life counterpart in all aspects. This powerful method of monitoring and analyzing any connected entity is responsive and based on real-time data collated from interconnected sensors – unlike traditional static models reliant on manual data input. By 2020, Gartner estimate there will be 20billion sensors, endpoints and digital twins, and although for many organizations the initial foray and implementation will be relatively simple, it won’t be long before enterprises are challenging themselves to implement digital twins of any conceivable asset, device or process. Gartner also go one step further to discuss ‘Digital twin of an organization (DTO), which essentially applies the concept to the whole business and every variable within it.
Nonetheless, despite the association with modern technology, the oft cited first instance of a digital twin predates the internet of things. The Apollo 13 disaster – immortalized on screen by Tom Hanks and Kevin Bacon – avoided tragedy largely thanks to an innovative set of mirrored systems in Huston, which enabled NASA to determine the best course of action by exploring the various consequences of each potential step. As an early proponent of digital twin (and customer of Orbus Software), NASA have subsequently implemented the technology throughout the organization to provide real-time representation of systems and spacecraft. This enables them to strategically plan new developments, roadmap technology and maintain their status as pioneers of space travel and research.
Digital twins drive top line revenue by mapping the entire lifecycle by providing insight into the implications of decisions on revenue, profits, return on investment and cost optimization.
Innovations are developed without the need for vast engineering overheads through experimental simulations. Product owners and data scientists can collaborate on data analysis and aggregation to explore new opportunities and gain efficiency. By connecting the business operating model with real-life data, teams can develop a plan for delivering established goals and directives. Ultimately, anything practiced within the virtual world can then be applied to the physical world, thus delivering on the promise of digital transformation.
At the same time, digital twins reduce risk by identifying complications ahead of time. Program and portfolio managers can exploit the technology to understand the implications of any change to the enterprise, or system within. No longer will there be any nasty surprises, nor will decision making be done blind and on a best guess theory.
As with most technical innovation the journey to wide spread adoption will not always be smooth. The most immediate risk is that dirty data could contaminate the effectiveness and fidelity of your digital twin. In turn the results and analysis becomes flawed, with decisions being made on misinformation.
Similarly, the software and technology must be scalable and capable of dealing with vast quantities of real-time data. Data formats and storage will no doubt evolve further and architects must be prepared, or else become constrained by technical limitations.
However, with the correct approach and investment these inevitable hurdles can be overcome. It will be possible to have digital copy of every physical entity within an enterprise, ensuring that every aspect of future innovation can be tested, created or modified in a virtual environment. In this way we can fully understand the implications of any decision or any idea before implementing in the real-world.