Digital Twins in Asset Management

Digital twins are gaining momentum worldwide, evolving from a concept into a transformative reality. According to analysts, the digital twin market is set to reach USD 110.05 billion by 2028, expanding at an impressive CAGR of 61.3%.

At its core, a digital twin involves creating a virtual replica of physical objects, systems or processes. For modern companies, it’s not just a tool—it’s a strategic asset that can reduce costs, improve performance and accelerate decision-making.

In the context of Industry 4.0, several trends are emerging around digital twins that are shaping the corporate agenda for the years to come.

TREND 1: Digital twin of the enterprise

In the case of an enterprise, a digital twin is a virtual dynamic model that mirrors its operations—processes, resources and interactions—in real time. This twin blends a digital model with its data-driven shadow, pulling information from multiple sources like IoT sensors, ERP, CRM and production systems to analyze, forecast and optimize the way the organization operates.

By staying in constant sync with its physical counterpart, the digital twin can predict issues, boost productivity and streamline lifecycle management. With the power of machine learning, it can simulate different scenarios and make accurate forecasts without any risk of business interruption.

Think of it as a virtual testing ground, where you can experiment with changes without affecting the real enterprise. You can predict the effects of specific decisions on production output, cost and lead times. Digital twin technology also enables smarter operations by preventing downtime on the production line, optimizing routes, forecasting workloads and efficiently allocating resources.

TREND 2: Digital twin of an employee

A digital twin of an employee is a virtual model that mirrors the real individual—capturing their professional attributes, behavior, skills and interactions with the work environment. It provides meaningful insights into various facets of an employee’s role within the organization.

The model is built using data about competencies and skills, performance metrics (KPIs, project involvement, achievements), behavioral patterns (communication style, task preferences), and internal policies and procedures. Solutions based on process and task mining—such as B1 Discoverit—collect this data from a range of business applications, including time-tracking tools, CRM platforms, corporate messengers and email systems. In some cases, the digital profile can be supplemented with data from wearable devices, for example, to assess stress or fatigue levels.

This virtual representation serves as a powerful asset for optimizing workflows, increasing productivity, supporting employee development and managing human capital risks more effectively.

TREND 3: Digital industry chains

Digital industry chains connect every stage of value creation within an industry—from raw material sourcing to the end consumer—into one integrated digital ecosystem. Powered by technologies such as IoT, blockchain, artificial intelligence and Big Data, these chains aim to automate processes, improve transparency and streamline operations. By breaking down organizational silos, they enable seamless collaboration among all stakeholders—manufacturers, suppliers, logistics providers, retailers and customers—within a unified, intelligent workflow.

The result is a transformation of traditional operations: significant efficiency gains, reduced costs and faster execution across the entire value chain.