Digital Twin Design Process

Digital Twin Design Process (DTDP)

The Digital Twin Design Process (DTDP) is a structured, iterative process for designing digital twins and applied AI solutions (e.g. agents). The DTDP is covered in detail in the book "Designing Digital Twins", by Rob Foster, available on Amazon.

This template covers 2 key steps:

- Defining the Problem

- Connected Action Mapping

Defining the Problem

What: Problem definition is the process of defining problems with sufficient detail, context and impact for an organization to be able to decide if they should invest to solve the problem.

Why: Digital twins and Applied AI are immature and frequently technology led. Far too many twins reach 6-12months after deployment and cannot show ROI or justify why they were built in the first place.

How: BYO process & consultants, or: Ideate with the cross functional team, test and seek to invalidate the problem statement, draft final Problem statements that the team believes are valid and clear.

Use a repeatable template for your problem statements to force you to be specific.

The example we use is:

The Problem is [What], it affects [Who, Where and When]. We need to [Change], because [Why].

Connected Action Mapping

What: Measures of Success give the solution team clear metrics or numbers in the real world to target for change. What are we going to change?

Why: Digital twins and applied AI as products or projects are frequently unbounded by real world measures of success. Software measures, such as testing and user acceptance and model accuracy, frequently do not cause success in the real world. Twins require clear measures of success in the real world, to show how the changes they create are solving the Problems being targeted.

How: Develop clear changes in the real world that can be measured and are direct or proxy proof that the Problem is being solved.