Automation has brought significant benefits to organizations that have taken the necessary steps to adopt it, but let’s face it, the journey to successful automation is typically not an easy one. Despite the best plans, automation programs continue to be plagued by barriers and bottlenecks, creating bottlenecks, suffocating scale and limiting better returns.
Given the challenges of automation – heavy maintenance burdens can erode ROI, for example, and lack of visibility on automation farms can lead to layoffs and high costs – it’s no wonder that digital twinning and its innate ability to successfully tackle problems has taken off. to resonate.
Digital twinning in automation has its origins in NASA’s space program in the 1960s and is best defined as a digital copy of an automated process residing in a separate repository of the robotics process automation (RPA) platform where the actual automation is performed. developed, implemented. and orchestrated.
Benefits of digital twins
The main advantage of the digital twin is that it evolves as automation evolves. As a result, if changes are made to the automation in the RPA platform, those same changes will be reflected in the twin, ideally in real time or at least near real time.
Operational stats (including runs, last run, number of issues, usage, and success rates) are also accessible and show where the twin is located so it can be monitored and continuously improved.
In addition to changes and operational metrics, a digital twin in automation enables an organization to compile and maintain accurate documentation and detailed audit trails for the entire automation domain in a single, centralized repository. This not only addresses the problem of misplaced or lost process design documents, but also solves one of the biggest pain points of automation: the inability to visualize and understand how automation has changed over time.
Maintaining digital twins for all automations in a central location – regardless of the RPA platform in which they are designed, deployed, and orchestrated – greatly improves automation standardization, management, and visibility. Particularly for companies pursuing a multi-platform automation strategy, a single repository provides greater visibility into the complexity of all processes, as well as the systems and applications they interact with.
This not only greatly improves the overview of the entire automation fleet, but also ensures faster recognition of potential problems and redundancies and identification of automations that can be retired to reduce costs and increase efficiency.
Less maintenance required
Digital twinning also reduces the need for maintenance. Serving as a canvas for automation, a digital twin can be quickly assessed to determine where an error has occurred and how to correct it, saving both time and money.
It also changes the change management process. Instead of waiting for an automation to fail before taking corrective action, digital twins enable proactive steps to be taken as soon as a potential failure is detected or prior to a regulatory change or application update.
Finally, digital twins enable accelerated and simplified RPA platform migrations because the feasibility assessments to evaluate the effort required to switch destination platforms are easier to perform. Because a digital version of up-to-date automation exists, exporting automation with a mapping engine that requires only minor adjustments drastically reduces the effort required and eliminates the need for manual recoding.
Forging new partnerships
This will prove to be particularly important in the coming year as more organizations look to migrate from their legacy RPA platforms to next-generation intelligent automation solutions.
Migrations will become even more complex as new partnerships are formed between established providers of solutions that leverage information from the Internet of Things (IoT). At least three industry standards groups focused on digital twins have already sprung up to push the technology forward.
While there is little doubt that digital twins in automation provide a tangible resource for understanding what delivers value (and what doesn’t), implementing digital twins is likely to become more complicated as parameters, design principles, and even basic assumptions change.
Some digital twins still rely on older simulations and monitoring, while others have built-in AI solutions that rely on evolving data to keep parameters up to date.
All of this suggests that while the benefits are likely to vary from organization to organization, digital twins are bound to see even wider use in the future. With compound annual growth rates generally expected to approach 40% per year, some analysts are already predicting 2023 as a peak year for the digital twin.
Spurred by new advancements – including the ability to proactively search and collect data – we expect the digital twins market to grow from its current $6.9 billion level to more than $73.5 billion by 2027. More organizations will recognize the persistent issues that digital twins can address and the benefits, from increased efficiency to greater ROI they provide.
Dan Shimmerman is president and CEO of Blueprint Software Systems
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