The evolution of Digital Twin technology

John Hill at Silico explores how creating a virtual representation of the real world can enable organisations to run a variety of scenarios that help to underpin effective and timely decision making

 

Digital Twin technology continues to be a top digital transformation trend. A recent study estimates that the market size for Digital Twins surpassed $8 billion this year and will grow at a compound annual growth rate (CAGR) of 25% between 2023 and 2032.

 

But what is a digital twin, and how can it support enterprise transformation and growth?  

 

A Digital Twin is a virtual representation of a real-world process. Digital Twins enable an accurate simulation of an entity, on which scenarios can be run to understand the impact of different decisions. They replicate the impact of decisions in real-time, providing information on effectiveness, performance, and possible future bottlenecks.

 

Through these simulations, businesses can transfer the learnings obtained in a digital setting to the real world and determine the best course of action. 

 

The genesis of Digital Twin technology  

Historically, Digital Twins have been used for high-value projects involving mechanically complex systems to monitor product performance and quality. Digital Twins have also been used in space, with NASA using basic twinning ideas in the 1960s to operate and maintain systems without the need for a person to be physically present.

 

The application of Digital Twins has the potential to go far beyond these examples; to dramatically accelerate and de-risk innovation across multiple industries of society and the economy. 

 

For example, by 2024, Chevron intends to have installed digital twin technology on equipment in oil fields and refineries, saving millions of dollars in maintenance expenses. 

 

Digital Twins of the enterprise 

Technological innovations in this space mean that it is now possible to incorporate Digital Twins into organisations’ non-physical systems. Business process simulation (BPS) enables organisations to build twins of their whole enterprise. This provides several commercial advantages, such as increased frequency and speed of scenario planning and better alignment of business and financial objectives. 

 

Businesses can generate forward-looking analytics by using ’what if’ scenarios by creating a large-scale Digital Twin, based on real-time metrics. Monitoring processes and predicting future challenges enables businesses to make strategic decisions and take proactive measures.

 

Having seen their simulated outcomes within a Digital Twin, a business can then execute these changes – or not – in the real world. For example, BPS can optimize peak and low-volume capacity to improve customer satisfaction and decrease handling times while raising income and customer retention. 

 

Many companies operate in an increasingly unpredictable economic environment so strategic plans need to remain flexible - especially if market conditions differ from historical data. To navigate this, it’s essential to use advanced forecast models to understand how changes today will impact business decisions.

 

For example, many companies are experiencing labour shortages and increased expenses due to macroeconomic factors. By creating a Digital Twin of the enterprise, businesses can demonstrate how they can make the most optimal decisions to prepare for challenges with staff shortages and rising operational costs they may face in the future.  

  

A further benefit of BPS is the ability to accurately forecast margins and identify how they could be increased. A margin forecast is crucial to guarantee that the correct funding is available without leaving unnecessarily large buffers. Businesses can make dynamic margin forecasts by building an end-to-end Digital Twin that gives a single view of margin on a product-by-product basis.  

 

The analysis stage of BPS uses ‘what if’ scenarios to evaluate the as-is process of a business and identify where challenges may arise in the future. BPS can then ensure that resources are concentrated on process adjustments that solve upcoming issues. It can determine how changes throughout a business may affect its processes and, in turn, business objectives by connecting various processes across teams and departments and connecting them to business outcomes.

 

Importantly, users are not restricted to historical values or statistical distributions when creating such scenarios. Instead, Digital Twins can serve as a reflection of future expectations and policies to help determine how prospective changes will impact each step in the process.  

 

In essence, a Digital Twin analyses the effects of a system-wide change; the costs and advantages of changing the core support systems for processes. The twin is then able to outline which immediate disturbances need to resolve. Particularly now with costs rising amid inflation, companies are hesitant when it comes to implementing system-wide change.

 

By creating a Digital Twin, businesses can trial variations they wish to make, see their impacts, and make a strategic decision on whether to commit to making the change to their real-world systems.  

 

By identifying variations between intended and achieved outcomes over time, BPS can assess if additional process adjustments are necessary to accomplish goals. Process experts can then take proactive action throughout the deployment to enhance outcomes and client and customer satisfaction. 

 

One example of a Digital Twin is the order-to-cash process. Process owners can use the order-to-cash Digital Twin as a management, planning, and controlling tool. For example, process owners can use the Digital Twin to estimate delivery dates. The Digital Twin helps them foresee any changes affecting the process to intervene proactively.

 

Process owners may use spreadsheets, presentations, or business intelligence dashboards to report on the order-to-cash process. BPS Digital Twins are the best representations of a process with the most current information from live data sources. Incorporating the underlying process structure allows forward-looking simulations that are actionable beyond historical or real-time information.

 

The future of Digital Twin technology  

While Digital Twins will continue to transform aerospace and manufacturing, they will also enable better planning and management of complex organisations crucial to our economic progress.

 

The next generation of decision-makers will routinely plan and optimise their business outcomes by using simulations and scenario analysis. A Digital Twin of every complex enterprise will be created in the future of Intelligent Enterprise Automation.  

 

Data-driven decisions are essential for businesses to survive in today’s competitive market. With simulations, what is discovered in a digital environment can be applied to the physical world, and the resulting agility enables businesses to respond quickly to rapidly changing conditions.  

 

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John Hill is CEO and Founder at Silico

 

Main image courtesy of iStockPhoto.com