Virtual ExperienceJuly 6, 2022

Predictions and automation with virtual twins

Combining science-based representation through modeling and simulation with data-backed prediction
Avatar
Patrick Ball
Patrick is a Senior Communications Manager on the Corporate Publishing team here at Dassault Systèmes. An experienced journalist, marketer, speechwriter and storyteller, Patrick's words have appeared on pages and stages around the world.
This image has an empty alt attribute; its file name is data-consumption-with-virtual-twins-1024x576.jpeg

Faced with a rising tide of data, business leaders need the right platforms to enable innovation and collaboration. Productive use of data is critical for companies to compete. This is the subject of a new report from Aberdeen Strategy & Research, “The Four Building Blocks to Unleashing Continuous Innovation,” which explores the role of digital twins in powering productive data use, improved decision-making and better outcomes.

This post contains excerpts from the third building block: predictions and automation. You can also read excerpts from the first two blocks:

Building Block 3: Predictions and Automation

No surprise here: the building blocks of continuous innovation build upon one another. The first step is enabling data consumption through the use of digital twins and virtual twin experiences that allow employees to access, analyze and learn from business data from the real and virtual worlds. Once these virtual twins are in place, it’s incumbent upon the organization to determine how departments can best continuously and purposefully update their virtual twins to maintain an authentic and trusted source of unified data.

With this foundation in place, organizations can layer in the third building block – predictions and automation – using artificial intelligence (AI). Bolstered by AI, the virtual twin isn’t just a digital representation of the real – it becomes a strategic instrument that can be used to drive innovation.

AI and machine learning algorithms can take data from tests and simulations to identify patterns, assess new features and help organizations uncover opportunities to innovate. Engineering teams, for example, can easily define, test and implement potential design adjustments, while executives can confidently and simultaneously use product data and production schedules to plan realistic launch dates. Efficiency improvements abound with AI capabilities.

Aberdeen found that organizations using AI were faster, more collaborative and more productive than those who did not use AI over the past two years.

  • 20% increase in workforce productivity
  • 16% increase in decision-making speed
  • 14% increase in data sharing and collaboration

Successful companies gain the full benefits of their virtual twins by combining the science-based representation of the product, factory or company through modeling and simulation with the prediction brought by real-world data science.

Additional RESOURCES

Learn more about NETVIBES solutions that enable organizations to gain insights from their exponential data in order to make better informed business decisions.

Stay up to date

Receive monthly updates on content you won’t want to miss

Subscribe

Register here to receive a monthly update on our newest content.