Digital Twins Aren’t Just for Big Businesses

Digital twins enable companies to iteratively simulate and optimize complex multivariable problems, reducing the learning costs that come with experimenting in the physical world. Once the exclusive domain of large enterprises, small and medium-sized enterprises (SMEs) can now use AI for advanced digital twins that enable them to repeatedly simulate and optimize complex multivariable problems. Creating these twins is a five-step process that includes: Setting a clear business goal; drawing up a clear diagram of the process you are twinning; identifying and structuring the data you will need; building a digital model of that flowchart; then testing, implementing and repeating the model.

Strategy execution is its riskiest moment because it is the point when any misjudgments have a tangible cost. One way to reduce that risk is to repeat the process over and over again in an experimental environment, improving it just a little more each time. This is the kind of thing that Toyota’s continuous improvement systems are known for. But this can be difficult because it involves continuously monitoring data and making many micro-decisions in response.