Answer these 5 questions to fine tune your digital twin strategy

CV Ramachandran, digital transformation and operations improvement expert at PA Consulting, discusses digital twin strategies.

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Imagine a city water utility with a software tool based on sensor and telemetry data combined with customer service, billing, and other kinds of data. The tool allows the utility to not only monitor the water supply systems in real time but create forecasts on water consumption and simulate the impact of equipment failure

Aguas do Porto (AdP), a Portuguese utility that supplies the city of Porto, has such a tool. It's an example of a digital twin, a software model that represents physical objects or processes using data.

A digital twin can be of great value in a variety of applications, but people make a lot of mistakes getting started. Use these five questions to get grounded and set your project up for success.

What do you mean by a digital twin?

Digital twin has many definitions. Something as simple as an online transaction balance can be a digital twin, since the digital record represents actual money, says Lin Nease, chief technologist for IoT at Hewlett Packard Enterprise. Some claim a static 3D representation of an object is often good enough. For others, only a dynamic 3D representation with real-time updates about the state of every component—and even its service history and maintenance requirements—is a full digital twin.

In a February 2022 Forrester Research report, principal analyst Paul Miller describes design twins consisting of 3D CAD designs and simulations, process twins including simulations of factory floors and devices, and service twins that use operational data to simulate a product's performance in the field.

What do you want from your digital twin, who will use it, and for what purposes?

CV says that in the manufacturing, healthcare, and innovation-driven industries he serves, most clients have a clear business goal for their digital twins. Such goals include increased productivity, higher quality, and the creation of new product designs. An increasingly important benefit, he says, is the use of digital twins in training new workers quickly, helping to ease staff shortages.

How smart or knowledgeable do you need your digital twin to be?

CV continues: "The tricky part is how much detail you put into the digital twin" to achieve the business goal. "You could spend all your time collecting data and almost get lost in that." If the goal is to reduce the percentage of scrap in a production process from 15 percent to 7 percent, he says, the digital twin can't contain so much detail that the costs of that data outweigh the benefits. Such costs can include wireless communication, analysis and data visualization, security, and the training required to make the digital twins usable.

Industry expertise can help determine which data will be most useful in a digital twin by allowing its designer to quickly develop a list of what-if hypotheses that are most worthy of testing. The data needed to test those hypotheses are thus most worth spending time and effort on. In pharmaceutical production, says CV, a modest investment in more frequent tests of the raw material in a digital twin of a production line can deliver "huge" returns by improving production yields.

How will you manage the required data?

Data is both the enabler of a digital twin and a huge cost. Practitioners recommend not only determining how much and what types of data to gather but also creating an integration and management layer to ensure the right data can be easily shared among current and future digital twins.

How do you build for the future?

To get the maximum return on investment from a digital twin, a business may want to expand it over time to simulate more physical devices or add detail so it can be used for additional purposes, such as training. That's why practitioners recommend creating a data and deployment strategy that can support those expanded uses.

Two areas into which digital twins will expand is simulating the state of objects not only within one company but across the value chain, from suppliers to customers, and to incorporate data from new sources such as text and video, CV predicts. "We're in the first inning of a baseball game. We're miles away from the potential that digital twins are going to take us."