• For digital systems to have control of the physical world, they must represent it, control its representation, and apply this control to reality.
  • Furthermore, the virtual representation has to be perfectly accurate in order to be useful. This extends to their behavior.
  • The digital twin of an aircraft engine is not only statically replicated; it also works like its real counterpart. As a result, all engineering changes, test runs, and maintenance can be performed on it before being performed in the real world,


  • The notion of “twin objects” can be expanded to digital representations of people, thought and business processes, and even complete enterprises.
  • These models not only contain current states and connections, but also observed and projected behavior.
  • All thought and decision-making processes use these digital representations, removing the discontinuity that separates virtual and real worlds.

How to?

  • Entering Twin Worlds requires a mindset change to understand how digital systems actually reflect and control the real world.
  • Accepting errors, inaccuracies, or latency is replaced by the constant demand for both accuracy and control. It requires a consistent data landscape where governance, trust, and accessibility are core concerns within the fabric of the Twin Worlds.
  • A virtual representation of the real world needs to be built up step by step, incorporating an increasingly better understanding of the key real-world assets and an improved ability to translate them into digital terms.

So what?

  • The digital twin of a physical object can be tangible enough but augmented or virtual reality can make it life-like even if the complex ones are difficult to recreate.
  • The twins of persons, processes, or institutions are less tangible, and are consequently challenging to grasp.
  • The key is to constantly take a virtual world perspective: how do consumers, corporations, and products behave digitally, and how is this translated into the next-generation digital IT landscape?