Simulation

Companies Are Creating Digital Twins to Test Innovation

Clones and robots have long been the subject of many sci-fi thrillers, because we all find the idea of a double fascinating. If you had an android around who looked, sounded and acted exactly like you, but any consequences that befell them wouldn’t affect you… do you think you’d test out riskier ideas on them? For some companies, that opportunity is already here. A DTO, or digital twin organization, is simply a replica, and over the past few years interest in the tool has increased. Alongside human augmentation and the cloud, DTO has appeared in Gartner’s Top 10 Strategic Technology Trends for the past three years. “The DTO becomes an integral part of the hyperautomation process,” Gartner wrote in a 2020 forecast. “[The DTO] provid[es] real-time, continuous intelligence about the organization and driv[es] significant business opportunities.”

Most importantly, a DTO isn’t a static clone of a company. Just like a real company, a DTO conducts sub-processes and collects real-time data on itself. And that dynamic, life-like capacity for change is extremely important. You wouldn’t want to fly on a plane piloted by someone trained on a PDF, right? Better to learn how a process works on a flight simulator, especially one that factors in accidents, errors, and the way one mistake can snowball into a larger one down the road.

How DTO helps with efficiency and punctuality

Any company with complex real-time data use cases can mature its process improvement strategy by investing in a DTO. For Lufthansa Cityline, a digital twin of its airline company allows its teams to test new initiatives efficiently. It helps improve existing systems such as onboarding and flight duration, and the DTO even frees up engineers to begin working on new projects such as sustainability enhancements.

Philipp Grindemann, Head of Business Development and Project Management at Lufthansa CityLine said during Celosphere in 2020, “[DTO] gives us an opportunity to compare all running processes with our reference processes and identify deviations.” It’s impossible to run an experiment without using a control group, and that’s a fantastic way to use a DTO and define your company’s baseline. In many cases, it’s hard to tell how significant a process delay really is until you have something to compare it too. Because of their work with a DTO, Lufthansa CityLine was able to determine the importance of trimming every possible second off the boarding process, as lost time during boarding led to lost time during other important aspects of their customers’ journey, including catering. Without a DTO, a company is left making tweaks to a system they can’t fully see or understand.

How DTO helps with supply chain

According to IDC, Digital Twins were already poised to become a widespread phenomenon in 2020 before the global Covid-19 pandemic, which has made the tool even more useful. IDC predicted a surge in digital twinning in the manufacturing sector, writing in 2019 that the tool would prove useful to “the digital transformation of manufacturing and industrial markets overall, including smart supply chain management.” And there are few industries more directly affected by the pandemic than manufacturing and supply chain, as customers around the globe settle into their homes and order household and sanitization products online. The technology is around for good, it seems, and IDC predicts that it will be “increasingly used in many areas such as building management, healthcare, smart cities, oil and gas, smart buildings and far more.” ABB, a global leader in technology and innovation, uses DTO to “turn real-time supply chain events and data into action.” Heymen Jansen, Group VP Advanced Process Analytics at ABB Global Business Services, says, “you can do many, many things with [DTO]. [...] If you look to Process Mining, there’s always a monitoring part of it. You want to understand where you are and where you want to go, and how you’re going to get there. Certainly, you want to know whether you’ve arrived.” For Jansen and his team, DTO allows them to measure each of these benchmarks with precision. “[It] is all about understanding how we could improve and do better in root cause analysis and benchmarking. We’re trying to understand the process behind our KPIs,” Jansen says regarding DTO. It’s a sophisticated way of using data and connecting it to business outcomes by leveraging a company’s learnings. Using DTO and Process Mining, ABB has been able to discover opportunities for growth and increased efficiency by studying a dynamic digital twin of their end-to-end supply chain. That’s no simple clone, either: ABB spans over 100 countries and boasts more than 2000 reporting units, each with their own complex needs. No matter how complex a company’s processes are, a digital twin can allow many teams to study the way everything works down to the smallest detail.

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