How should an industrial company start with digital twins?

Industrial companies should start by addressing a single, specific pain point rather than deploying a full-scale digital twin across all assets at once. According to industry leaders at IIoT World Energy Day 2024, common starting points include monitoring pipeline efficiency, improving Overall Equipment Effectiveness (OEE) on a production line, or simulating water treatment performance. Each completed use case builds confidence and standards for the next step.

What is a modular digital twin strategy in manufacturing?

A modular digital twin strategy adds capabilities in layers over time rather than through one large deployment. Panelists at IIoT World Energy Day 2024 described this as a Lego-like approach: starting with monitoring and visualization, then adding simulation, enterprise system integration, and AI-powered natural language tools as the organization's needs and budget develop.

Why is digital twin simulation a good first step for energy companies?

Digital twin simulation lets energy companies run what-if scenarios, such as adjusting flow rates, changing energy usage parameters, or reconfiguring a production line, in a virtual environment before making any physical changes. This reduces the risk of costly mistakes, generates visible results quickly, and creates momentum for broader digital twin adoption across facilities.

What role do people play in digital twin deployment?

Operators, engineers, and IT teams are central to every stage of digital twin deployment. Even with an incremental adoption approach, organizations need training, cross-functional collaboration, and change management to ensure each new layer of digital twin capability is embedded into daily workflows, not simply installed. People remain the constant factor across all phases of the process.

Digital Twin Adoption: Start Small, Scale Up

Industrial and energy companies can adopt digital twins successfully by starting with a single pain point, such as monitoring pipeline efficiency, improving Overall Equipment Effectiveness (OEE), or simulating water treatment performance. According to industry leaders at IIoT World Energy Day 2024, incremental adoption, not full-scale deployment, is what drives lasting results.

How Should Companies Start with Digital Twins?

The most effective approach to digital twin adoption is to begin with one specific pain point and prove value before expanding. Industry leaders at IIoT World Energy Day 2024 emphasized that each step builds confidence, establishes standards, and proves ROI, creating a foundation for scaling digital twins across facilities and processes.

Once this first use case demonstrates value, companies are better positioned to expand. Each step builds confidence, establishes standards, and proves ROI, making it easier to scale digital twins across facilities and processes.

Why Use Digital Twins for Simulation First?

Digital twin simulation offers a low-risk entry point for industrial and energy companies. Running “what-if” scenarios, such as adjusting flow rates, changing energy usage parameters, or reconfiguring a production line, lets teams test decisions in a virtual environment before making costly physical changes. This approach reduces risk and generates visible value quickly.

This not only reduces risk but also shows tangible value quickly, creating momentum for broader adoption.

What Is a Modular Digital Twin Strategy?

A modular digital twin strategy builds capability in layers rather than through a single large deployment. Panelists at IIoT World Energy Day 2024 described this as a “Lego-like” approach, where organizations add one layer at a time: starting with monitoring and visualization, then adding simulation, enterprise system integration, and AI-powered insights that evolve alongside the organization’s needs and budget.

This modular growth ensures that digital twins evolve alongside the organization’s needs and budget, while continuously enhancing resilience.

Digital Twin Adoption: Modular Layers Compared

Layer	What It Does	Primary Benefit
Monitoring and Visualization	Provides real-time visibility into asset performance	Foundation for all future layers
Simulation for Optimization	Runs what-if scenarios on flow rates, energy use, line configuration	Reduces risk of physical changes
Enterprise System Integration	Connects digital twin data to business decision-making systems	Scales insights across the organization
AI and Natural Language Tools	Makes digital twin insights accessible to broader teams	Insights easier to access across the organization

Why Do People Matter in Digital Twin Adoption?

Operators, engineers, and IT teams are central to every stage of digital twin deployment. Even with an incremental adoption strategy, training, collaboration, and change management are required to ensure each new layer of digital twin capability moves beyond installation and becomes embedded in daily workflows.

Key Takeaway

Digital twins don’t have to be daunting. By starting small, focusing on real problems, and scaling step by step, manufacturers and energy companies can unlock business resilience without the risks of a “big bang” deployment. The path forward is not about doing everything at once—it’s about building resilience one success at a time.