Digital twins allow businesses to repeatedly simulate and optimize complex multivariable problems, reducing the learning costs associated with physical world experimentation. Previously exclusive to large corporations, small and medium enterprises (SMEs) can now leverage AI to create advanced digital twins.
This five-step process involves: 1) Defining a clear business objective; 2) Outlining a clear process flowchart; 3) Identifying and structuring necessary data; 4) Building the digital model of the flowchart; and 5) Testing, implementing, and iterating the model. The execution of a strategy is its riskiest phase as any miscalculations incur tangible costs. One way to mitigate this risk is to repeatedly execute a process in an experimental setting, refining it incrementally each time. This echoes Toyota's renowned continuous improvement systems. However, this process can be challenging due to the constant monitoring of data and numerous micro-decisions required in response.