Thus, digital twins are more affordable as well. Similarly, AI and data analysis have become more affordable and available. One reason is that computing technology has been evolving enough to support the widespread use of digital twins it’s no longer the sole domain of well-funded research departments. Why has the buzz been getting louder of late? For example, the digital twin of a computer manufacturing plant would get real-time data from sensors built into the production machines a utility grid would get real-time usage data, and so on.Īn article in SAP Insights takes the interconnectivity of digital twins a bit further, noting that in the future, “digital twins will form their own networks, which experts call a “digital thread.” If a digital twin enables us to create a digital representation of a piece of equipment or facility, then a digital thread is the continuous, connected stream of information provided by an intelligent asset throughout its life cycle.” Why Digital Twins Are Generating Buzz Right Nowĭigital twins have been around for decades, and they’ve been hovering in the business collective consciousness for several years now. Under this definition, you could use the illustration that a predictive model is like examining one part of the production line, while a digital twin is like monitoring the status of the entire production facility.Ī key difference between digital twins and other computer models is the quality and timeliness of incoming data digital twins have a real-time connection to the thing they represent. Instead of looking at just a handful of outcomes in one precise area, it can generate a picture of the whole. Instead of testing for just a few variables, it can take many variables into account. Instead of using stored data, it uses dynamic, real-world data streams. In this case, we can say that a digital twin is a more precise and complicated version of a predictive model. how price changes might affect product sales). The second answer refers to what business analytics users might mean by the term ‘predictive analytics.’ In this context, they might have in mind a simpler model that runs a test against limited variables (e.g.

And a digital twin is a type of model, albeit a complex one it can certainly be used in predictive analytics. Predictive analytics is an umbrella term for running real-world data against artificial intelligence systems to determine what might happen under different future scenarios. One is that predictive analytics uses digital twins. There are two subtly different answers to this question. So what’s the difference between digital twins and predictive analytics?

Predictive Analyticsĭoes some of this sound a bit familiar? Don’t we already have predictive analytics to run scenarios against? Yes, of course. As such, digital twins can be used to proactively monitor the current state of an object (such as a traffic grid) and to run various simulations, from simple what-ifs to complex predictive scenarios and routines. What is a digital twin, you ask? It’s a computer model of a real entity there have been digital twins made to match supermarkets, human organs, public utility systems, and entire cities. Will 2022 be the year of the digital twin?

Soon afterward came data analysis and then data analytics, Big Data, AI, machine learning, predictive analytics, natural language processing … The list of ‘Big Things’ in the business analytics world seems to get a new addition every year.

The next big thing in business