Twinning is winning, what are Digital Twins

Hi. We’re Mr. Watts

We combine your data with smart technology empowering better decision making.

We build Digital Twins.


But, what are Digital Twins?

In this blog we guide you through the theory, how you start with Digital Twins, and most importantly: what’s in it for you. To conclude, we show a number of good practices to take you through the full scope of the concept, right before we proudly add our own use cases as well.


When we look at the Tesla example, we see that the last step is ‘triggering behavior’. This isn’t always necessary. At Mr. Watts, we base our Digital Twin development on several steps or phases:

Collect: We collect real-time data using Internet of Things sensors, actuators, APIs, 3D images, etc. Actually, everything related to data input.

Connect: Afterwards, we use this data to build the Digital Twin.

Replicate: We build the Digital Twin based on a behavioral model, historical and real-time data, data orchestration and device management.

Empower: We add an analysis layer through AI or other forms of analysis to gain new insights about the Digital Twin. Sidenote, what’s the difference between AI and smart analysis? The latter can, for example, simply bring up the correlation between different data streams without necessarily learning from it. Take a warehouse situation, combining the positions of products and the movement paths of forklifts to find certain hot zones. This isn’t AI, but more traditional mathematical algorithms.

Decide: The final step is to make decisions based on the gained insights. This can be done manually or automated. If it’s automated, you can start over at step 1. This is why the last step is optional but still possible.


Why use Digital Twins?

We showed you what a Digital Twin is and how we approach the setup of one. But why would you want to build one? What goals can you extract from using Digital Twins for your business?


Accurate and real-time simulations: base your decision making on data instead of feeling.


Deep and correlated insights: learn what processes cause trouble, what behavior doesn’t run smoothly or how to manage and organize your supply chain.


Data-driven decision-making: learn from predictions and precede eventual flaws or obstacles in your business processes.


Flexibility in decision-making in unforeseen circumstances: run different scenarios, allowing you to navigate smoothly instead of steering an oil tanker in a different direction when something goes wrong.

How to deploy?

Of course, we do not only build Digital Twins, we deploy them efficiently as well, helping your organization with better decision making. This is a process in three steps:


Connect: We identify and connect valuable enterprise and IoT data sources to the cloud. By combining historical and real time information we create a high quality data foundation.


Replicate: We build a Digital Twin that looks like and behaves identically to its real world counterpart. It replicates processes so you can assess and predict possible performance outcomes and issues.


Decide: We create tools that provide clarity to complex data. These allow for better decision making with large potential savings, improvements in maintenance and operational efficiency.