The concept and use of the digital twin is gaining traction in complex enterprise operating environments because it allows businesses to create a detailed digital model of their physical systems.
Increased data volume and variety, driven in large part by a proliferation of IoT sensors, mean there is far more data to enrich these digital twins. Organizations must use data from across all business areas—operations, IT, finance, and more—to drive decisions and create new services. Furthermore, to get the most from their data, organizations want to apply machine learning and AI to predict the future state of assets and operations or automate workflows.
Although everyone recognizes the value of a strong data foundation, organizations continue to grapple with finding technologies and integrations that drive the business outcomes they seek.
The digital twin, when fully realized, creates an operational real-time digital model that orchestrates technology, people, and processes. As we will see, such a digital twin goes far beyond asset-centric digital twins used for important but limited functions like maintenance and reliability management.
The promise of the digital twin in making use of all of that data is not abstract: it is being brought to life in ways that benefit not only businesses but the day-to-day lives of the people they serve, which is, after all, the real recipe for sustainable competitive advantage.
This paper explains how the digital twin concept continues to evolve and break new ground. Fill out the form to download your copy.
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