What Does Enterprise Metaverse Mean for IT/OT Convergence?

Jie Li, the founder and CEO of DataMesh, illustrates the relationship between IT and OT, the key challenges of the convergence, how the Digital Twin/Enterprise Metaverse can be a solution to that, and what a digital twin platform should be like in today’s cloud era.

About a decade ago, I worked as a Program Manager for Microsoft SharePoint and Office 365. At that time, we were exploring the possibilities to empower more users through mobile + data + cloud, rather than only focusing on the traditional information workers Microsoft Office suites were targeting.

One of the potential areas I investigated was frontline workers with AR glasses – yes, I was probably the first and only Microsoft employee who wore a Google Glass every day at the Redmond campus without taking it off.

Then something came to me. Although the Google Glass project was largely seen as a failed attempt (remember glasshole?), the concept of AR + data experience gave me a glance at the future of digitalization – IT infrastructure will be the foundational support of frontline workers. The operation data will look for those in need (instead of waiting to be discovered), maximizing their ability to achieve the best results in the team. And IT will be the new guy in production operation support; the platform will enable the future of the modern workplace revolution.

Before the cloud transformation, which has become a new mandate amid the pandemic, IT and OT were two isolated workloads – IT workloads were all about daily IT support, capacity planning, high availability, cybersecurity, compliance, e-discovery, etc. IT Pros ensure information workers can have practical productivity tools to create content, but most of the content does not make sense to the IT Pros – that’s the breaking point of IT and OT. Even today, although more CIOs have started to have IT-OT responsibilities, it is still tough to implement a data-driven culture and move towards a data-driven organization.

See More: Why OT Environments Are Getting Attacked And What Organizations Can Do About It

Think about a scenario where a maintenance worker needs the BIM and IoT sensor data of a specific engine room. How can IT provide that immediately? That information is inside the professional data silos that are not traditionally accessible to IT pros or frontline workers. Of course, you can create customized solutions using BIM engines and IoT hubs, but the maintenance cost of such a system becomes stupid over time. Those solutions are more like a snapshot than a living document – ​​they don’t grow with your operations. We need a digital twin platform focusing on dynamic processes to solve this problem.

It may not be very straightforward to understand, but now there’s a fancy name: Enterprise Metaverse. The name itself doesn’t matter – what matters is why we need Digital Twin or Enterprise Metaverse to converge IT/OT.

What Are the TEMS Motivations?

here comes the Motivation Principle. The essential motivations for organizations to adopt digital twin-based frontline solutions can be summarized into the following four categories – the TEMS motivations:

  • Training and guidance: Based on the digital twin and 3D instruction of the equipment, IoT data, and the environment, we can improve the ability of frontline workers to operate and maintain the facilities and increase productivity. Compared with traditional operational training, we have seen >60% training cost reduction and >30% productivity increase within many manufacturing customers.
  • experience: By fully visualizing the digital twin of facilities and equipment, the new experience allows potential buyers and learners to quickly improve their knowledge of unfamiliar environments at a lower cost without interfering with the production environment.
  • monitor and control: A well-connected digital twin environment can enable better operations based on real-time data, with maintenance, inspection, and remote control capabilities. The idea of ​​monitor and control sounds pretty straightforward, but this is the most challenging work in the real world – lacking existing meaningful data collection and control mechanisms are common issues today.
  • simulation: Simulation based on the digital twin of facilities and equipment. With a gamified approach to building and running the digital twin environment of the facility, it can now be operated like a simulation game, like SimCity. Such simulation emphasizes the relationship and operation mechanism between equipment. Digital Twin Objects can be defined with behavior trees and AI, making them act like NPCs in games. Production data can be injected into such simulation runtime – to make it a living environment for large-scale planning, training, prediction, and remote management.

Frontline workers need to be empowered with TEMS motivations

Frontline workers need to be empowered with TEMS motivations

Frontline workers need to be empowered with TEMS motivations
Source: DataMesh

With the motivation goals set, we need to understand the adoption barriers. There are two significant barriers when we talk about digital transformation: the technology barrier and the data governance barrier. The same applies to the digital twin and enterprise metaverse. Where is the data? Can the data only be accessed by the right person with the right permissions? Does the data type meet the application consumption requirements? Does the data need to be converged and integrated? Do we understand our business nature? How do we solve the business pains with the data?

Understanding the Right Enterprise Assets for Convergence

For CIOs to converge IT/OT, we not only need to understand the development environment, 3D tools, ERP, and MES but also should think of product and platform standardization. It can be very easy to fall into the customization development trap and go from failure to failure. Therefore, we must process enterprise assets with the right digital twin platform and tools. The platform needs to be able to provide standard digital transformation capability for different enterprise assets.

  • Data assets: For a well-established digital twin platform, the effective use of the organization’s data assets must be one of the platform’s standard capabilities. Accessing different data types at low cost and having these data standardized and organized is one of the long-term issues of enterprise data governance. One of the theoretical advantages of the metaverse/digital twin is the structured presentation of 3D data, which is more conducive to the visualization and use of data assets with non-professionals. Therefore, the standard transformation of existing 3D data, such as CAD/BIM, must be a high priority. In this way, the biz-app developers can have a standard way to access 3D assets and can focus on connecting IoT, business, and processes.
  • Process and workflow assets: The enterprise process is always the critical asset to the operation. These processes represent the embodiment of real business. Traditional enterprise process management often focuses on approval, reimbursement, document flow, and other operational matters, which have been well resolved in existing collaboration platforms. However, in manufacturing, construction, facility operations, and maintenance industries, operation process systems are generally isolated, making it challenging to describe and reuse these processes across systems. Getting process assets into the digital twin platform will break the information silos and directly empower frontline personnel.
  • collaboration assets: People and organizational relationships are the keys to quickly leveraging the capabilities and resources of experts. These collaboration relationships and histories are also essential in the digital twin platform, and the platform must be able to access and integrate with enterprise LDAP and people systems.
  • knowledge assets: The knowledge referred assets to here are the knowledge accumulated in the collaborative process, usually in knowledge management systems, work order systems, and massive document archives. The future digital twin/enterprise metaverse platform needs to have automated knowledge mining and natural language processing capabilities to process such data and generate knowledge graphs that can automatically assist frontline personnel.

See More: The Business Metaverse and the Future of Work

Disrupting the way call centers work through mixed reality

Disrupting the way call centers work through mixed reality

Source: DataMesh

Converging for Enterprise Success

A “metaverse” that can only be rendered on large screens and high-grade GPUs will only stay in showrooms and will not help the frontline workers benefit from digital transformation. For organizations to achieve IT/OT convergence, the platform must ensure ease of use. It needs to simplify design processes, reuse digital assets, and provide a robust SDK requiring low and zero code capabilities. After all, it is impossible to train end users to use game development engines like Unity3D and Unreal to do enterprise process design, a blocker to mass adoption. The democratization of digital twins should be a goal of adoption.

Do you believe the enterprise metaverse must be democratized? Share your thoughts on Facebook, twitterand LinkedIn. We’d love to hear from you!


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