A fleet manager monitors the location of three hundred trucks, and their up-to-the minute mechanical fitness, speed and fuel consumption. The maintenance crews in a city inspect the infrastructure and services for underground structures such as water systems from a remote location in real time. These scenarios give us a glimpse of the potential of digital twins.
A digital twin is a digital representation of a physical object. It includes the model of the physical object, data from the object, a unique one-to-one correspondence to the object and the ability to monitor the object.
Digital twins offer strong potential to achieve better insights on their objects and drive better decisions.
“The adoption of, and hype around, digital twins is growing,” said Roy Schulte, vice president and distinguished analyst at Gartner. “Digital twins are the next step in the Internet of Things (IoT) driven world, where CIOs are increasingly leveraging IoT technologies in their digital business journey.”
Digital twins add value to traditional analytical approaches by improving situational awareness, and enabling better responses to changing conditions, particularly for asset optimization and preventive maintenance. They can lower operating expenses and potentially capital expenses too, by extending the life of the object they represent and optimizing the performance of the asset as it runs.
CIOs can exploit the digital twin concept to enable stakeholders to monitor and make informed decisions about the state of the actual physical things, their context, and take action to optimize their future state.
How to start
Physical objects that CIOs and their business unit stakeholders can apply a digital twin to are broad. They range from people, things and places to complex environments, such as buildings, factories or cities..
“CIOs should drive discussions with their business unit peers on the potential business value of digital twins, their limitations and policy on their architecture and use,” said Schulte.
Digital twins offer strong potential to achieve better insights on their objects and drive better decisions. However, there are inherent risks, like adding unnecessary complexity. They could be technology overkill for a particular business problem. There are also concerns about cost, security, privacy and integration.
CIOs looking to use digital twins to enable disruptive IoT solutions and business outcomes should:
- Focus on objectives: Understand the key business benefits from digital twins before investing to build them.
- Assess readiness towards adoption: A parallel element to this is understanding the readiness of the enterprise to adopt IoT initiatives that will leverage digital twins.
- Seek simplicity: Avoid building a digital twin if business objectives can be met with basic indicators from sensors on critical performance issues.
- Include checks and balances: Develop leading indicators with metrics that can be used to measure the progress of digital twin initiatives, which may require a few years to realize financial objectives.
In the long term, Gartner sees new business models emerge, facilitated by digital twins, such as selling physical object-related performance data or charging for objects based on performance data.
