Digital Twin Technology and Human Decision-Making

Introduction

People frequently refer to a digital twin technology when talking about factory facilities, machinery, and even smart cities. A digital twin is an abstract copy of some physical object. It receives continuous updates based on information from the physical object. The majority of the attention paid to the concept focuses on its ability to increase efficiency. It focuses on minimize downtimes, and perform predictive maintenance. At the same time, there is another dimension of use of digital twins which people rarely considered. It is the impact that such twins can have on human decision making.

How Digital Twin Technology Goes Beyond Physical Assets

Historically, industries have employed for the management of physical assets, including machines, cars, and infrastructure. They do this by acquiring real-time data through sensors.

In today’s context, digital twins are also going beyond asset management. They are being utilized for business processes, supply chain management, customer experience journeys, and other organizational processes. These digital models allow decision makers to gain insight into how certain decisions may impact a process within a whole system.

Digital Twin Technology for Human Decision Simulation

Among some of the notable ones is the adoption of the technology for assessing the decision-making process in humans. Companies can develop digital twins of workflow procedures where there is engagement from humans.

For instance, an organization can make use of a digital twin to test how managers react to disruption. It is in the supply chain management processes. Various scenarios can then be tested to ascertain what types of decisions would yield the best results.

Enhancing Strategic Planning with Digital Twin Technology

Strategic planning usually has elements of uncertainty since it is impossible to predict all future circumstances accurately. The use of digital twins assists in reducing such uncertainties as decisions makers can experiment with various scenarios in the digital world.

The decision makers do not rely only on past performance but can understand what the impact of changing any policy or operations would mean for their performance in the future.

Digital Twin Technology and Organizational Learning

One of the less mentioned benefits of digital twins includes the ability of these tools to contribute towards organizational learning. Knowledge transfer is always a difficult task for businesses because there are usually barriers to sharing knowledge between experienced and new employees.

In this case, digital twins can simulate the operation of the system, allowing employees to see the system’s reaction under different circumstances.

Governance Challenges in Digital Twin Technolog

In light of the evolving complexity of digital twins, issues surrounding governance and accountability are becoming more prominent. The use of models to make decisions may play a role in determining resource allocation, performance evaluation, and policy making in an organization.

It is crucial to maintain transparency on how digital twins are developed and utilized. It is imperative for the organizations to have an awareness of the assumptions within digital twins. Simulations are not infallible truths.

Conclusion

The evolution of digital twins has been from a means of monitoring physical equipment to an instrument used to aid humans in decision-making, strategy formation, and learning. The use of digital twins in industrial processes is quite clear, but less clear are the possibilities of using them in modeling human-influenced systems. In any case, as the development of digital twins continues, they may turn out to be some of the most significant contributions of technology in the future.