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AI-Powered Digital Twins Revolutionize Business Optimization for SMEs

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Digital Twins,AI,Business Optimization

This article explores how AI-powered digital twins are transforming business optimization, particularly for SMEs. It highlights the five-step process of creating these twins and how they enable businesses to reduce risks and costs associated with strategy execution.

Digital twins allow businesses to repeatedly simulate and optimize complex multivariable problems, reducing the learning costs associated with physical world experimentation. Previously confined to large corporations, small and medium enterprises (SMEs) can now leverage AI to create advanced digital twins.

This five-step process involves: defining a clear business objective; outlining a process flowchart; identifying and structuring necessary data; building a digital model of the flowchart; and finally testing, implementing, and iterating the model. Strategy execution carries the highest risk as any miscalculations have tangible consequences. One way to mitigate this risk is by repeatedly testing a process in a simulated environment, making incremental improvements each time. This approach, similar to Toyota's continuous improvement systems, involves continuous data monitoring and numerous micro-decisions.

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Digital Twins Revolutionize Business Optimization for SMEsAI-powered digital twins enable businesses, particularly SMEs, to simulate and optimize complex processes, reducing risks and costs associated with traditional experimentation.
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