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At its core, digital transformation involves modelling, simulating and optimizing end-to-end primary business processes - even processes across company borders - using IT solutions that matchenable automated matching of the identified supply and demand automatically.relations. This
approach can be applied across various operational levels, for example from matching production capacity with material requirements to coordinating freight availability with
distribution needs. And of course within specific processes on different levels of detail.
The ultimate goal is achieving seamless, real-time automated matching of demand supply relations based on live event data changes generated throughout the organization's business processes. In
many ways, this mirrors flight control systems, particularly in how they process and respond to real-time events for optimal performance by monitoring each split second the actual business state.
Here, the trick is to (re)design business processes based on domain-driven design. So you get separate layers of specific processes. State-of-the-art technology
enables you to inherit relevant real-time events occurring in one domain needed by the other. Using GraphQL makes it possible to instantly query the business
state across all domains. Now you have the capability to manage by exception and focus only on relevant data, making a clear distinction between short lived cockpit information and black box data based on your primary business processes.
The inheritance mechanism works in the same way as object-oriented programming, where program code is inherited for reuse at different levels. But now you focus
on the inheritance of business events across process domains. Thus avoiding duplication of data and enabling instant availability of the actual operational state
of the business to control, perform automated match-making between demand and supply, and implement real-time machine learning.
State-of-the-art technology also enables you to map design and implementation onto each other so effectively that "design" is "run". The explanation is that relevant
GraphQL event queries needed are actually the design specifications for the implementation.
approach can be applied across various operational levels, for example from matching production capacity with material requirements to coordinating freight availability with
distribution needs. And of course within specific processes on different levels of detail.
The ultimate goal is achieving seamless, real-time automated matching of demand supply relations based on live event data changes generated throughout the organization's business processes. In
many ways, this mirrors flight control systems, particularly in how they process and respond to real-time events for optimal performance by monitoring each split second the actual business state.
Here, the trick is to (re)design business processes based on domain-driven design. So you get separate layers of specific processes. State-of-the-art technology
enables you to inherit relevant real-time events occurring in one domain needed by the other. Using GraphQL makes it possible to instantly query the business
state across all domains. Now you have the capability to manage by exception and focus only on relevant data, making a clear distinction between short lived cockpit information and black box data based on your primary business processes.
The inheritance mechanism works in the same way as object-oriented programming, where program code is inherited for reuse at different levels. But now you focus
on the inheritance of business events across process domains. Thus avoiding duplication of data and enabling instant availability of the actual operational state
of the business to control, perform automated match-making between demand and supply, and implement real-time machine learning.
State-of-the-art technology also enables you to map design and implementation onto each other so effectively that "design" is "run". The explanation is that relevant
GraphQL event queries needed are actually the design specifications for the implementation.