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Realizing the Promise of Digital Twins with Process Simulation

Bruce Orcutt

March 12, 2024

The digital twin, a term now overly hyped and echoing with excitement and promise in the business world, especially in the domain of process mining tools, isn't a newfangled concept that appeared overnight. Its roots run deep into the annals of high-tech engineering, where it has been a key to more pragmatic innovation for years.

Jump to:

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Want to know more about taking your processes for a test drive with process simulation?

Picture the intricate world of engineering design—every jet engine, rocket propulsion system, or similarly sophisticated machine—where the cost to prototype and test is extremely high and the margin for error is infinitesimal. The stakes? Astronomically high. Here, the digital twin concept was conceived and perfected, allowing engineers to design, simulate, and refine complex systems in a digital realm long before their real-world counterparts were built.

As we witness the fervor around digital twins in today's business process landscape, it's essential to recognize and harness this rich heritage. The promise is tantalizing: If engineers can simulate the dynamics of a jet engine, why can't businesses simulate and "test drive" their processes to reduce costs and mitigate risks? However, just as a static design of a jet engine without simulations is of limited efficacy, a digital twin of a business process without integrated simulation capabilities remains an incomplete realization of its potential.


Why process simulation matters for business process improvement

Cost effectiveness

Just as prototyping a new airplane based solely on theory can be extremely expensive and risky, so too can introducing a new or modified business process without first confirming its performance under a variety of simulated conditions. Simulation of a planned business process can help the business avoid wasting human resources by evading the rework necessary to correct poor performance not anticipated by process designers.

Risk reduction

In the aerospace industry, a failed engine prototype could mean a loss of billions, not to mention a possible loss of lives. In business, a flawed process could mean decreased productivity, lost customers, or process compliance violations. In the case of processes whose purpose is to serve a human customer in healthcare, public safety, or other high-risk situations, these failures can be even more dire. Simulations allow organizations to identify and rectify potential failures to mitigate these risks.

Speed of innovation

Digital twins accelerated innovations in engineering by removing the time-consuming physical prototyping phase. Similarly, in business processes, simulation can fast-track changes by instantly showcasing potential outcomes, thus cutting down lengthy trial-and-error cycles and allowing implementation teams to focus all their energy on process implementation, free from the need to rework less-optimal process designs.



Examples across industries


Consider a hospital looking to optimize patient flow through its emergency department. Through business process discovery, they've mapped out the current patient journey. However, before making changes—like altering a triage system or allocating more staff during peak times—they can simulate various scenarios to identify unintended issues caused by those changes. This ensures that the proposed solutions don't inadvertently increase patient waiting times or overburden staff.


A car manufacturer wants to enhance its assembly line efficiency. Using a process digital twin, they simulate changes like reordering assembly stations or introducing robotic arms. Through simulations, they can predict how these changes would affect production times, product quality, and worker safety.


A bank wants to speed up its loan approval process. After mapping the current process through discovery, they simulate various changes—like automating credit checks, introducing digital document verification, or adjusting planned staffing levels. The simulation helps ensure that while the process gets faster, it doesn't introduce any unintended risks by inadvertently impacting the quality of required risk assessments.


An online retailer wants to optimize its product return process to enhance customer satisfaction. Simulating changes like introducing instant refunds, simplifying return labels, or providing pick-up services allows them to gauge impacts on customer loyalty, operational costs, and inventory management.


Taking processes for a test drive

The evolution from static design blueprints to dynamic digital twins in engineering was a game-changer. In the realm of business processes, we stand at a similar crossroads. Process discovery is the blueprint, but without simulation, it's like a jet engine design that's never been tested under actual flight conditions.

Process digital twin offers businesses an unparalleled view into their operations, but simulations unlock their transformative potential. By "test driving" changes in a virtual environment, businesses can innovate faster, reduce risks, and ensure cost effectiveness. Independent of the industry, the power of simulation for realizing the full potential of digital twins is reshaping the way industries approach process optimization.

Tell us about your project by filling out the form and selecting “Process Intelligence”; we look forward to joining you on your intelligent automation journey.

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Bruce Orcutt

Bruce Orcutt

Chief Marketing Officer at ABBYY

Bruce Orcutt is a passionate marketing and leadership executive focused on driving market growth and awareness in digital transformation and intelligent automation.

As Chief Marketing Officer at ABBYY, Orcutt leads the global product strategy, go to market, launch, pricing, competitive analysis, analyst relations, communications and thought leadership, win/loss analysis, and sales enablement for the entire ABBYY intelligent automation portfolio. His goal is to help global enterprises understand the hype from reality of the latest artificial intelligence (AI) technologies and ensure they leverage purpose-built AI to achieve their transformation goals.

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