Why Enterprise Architecture Management May Be Better Positioned as a Digital Twin for the Enterprises #4

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A blog series by Brian Halkjær, Partner at Konfident, and Thomas Teglund, Lead Enterprise Architect at Securitas.

In the previous post in this blog series, we discussed the key prerequisites for success with a Digital Twin of the Enterprise. We explored the critical importance of great data quality and data quality assurance in reaching the full potential of data-driven EAM applications.

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A data driven EAM application, which we discussed in a prior blogpost, should be perceived as the key technology enabler for a digital twin of the enterprise. It will also serve as the missing link – the mediator – required to establish an ecosystem. It removes the boundaries of information/knowledge, enabling us to re-purpose all this pre-existing information, elevate it to a higher level of abstraction, and knit it together to make a coherent representation of the enterprise.

Creating an ecosystem of applications with trustworthy data that can be perceived as a digital twin as it offers numerous benefits as explored in this blog series. Here are some key advantages:

• Enhanced Decision-Making: By having a digital twin, you can simulate and model performance in various scenarios, predict outcomes with higher certainty, and make more informed decisions. This is particularly useful for optimizing operations and planning future projects.
• Improved Efficiency: Digital twins allow for real-time monitoring and analysis of systems, which can lead to more efficient resource management and reduced downtime. This can result in significant cost savings and improved productivity.
• Better Collaboration: An ecosystem of interconnected applications facilitates better collaboration between different departments and stakeholders. This ensures that everyone has access to the same accurate and up-to-date information, leading to more cohesive and coordinated efforts.
• Increased Innovation: With a digital twin, you can experiment with new ideas and innovations in a virtual environment before implementing them in the real world. This reduces the risk associated with new initiatives and accelerates the innovation process.
• Enhanced Experience: By leveraging trustworthy data, you can create more personalized and responsive services for stakeholders. This can lead to higher satisfaction and adoption.
• Regulatory Compliance: In a more regulated world, maintaining high data quality and governance standards ensures compliance with regulations and reduces the risk of data breaches and other security issues.

Not all areas are equally mature from an EAM application capability perspective at present, but all are relevant dimensions of a digital twin of the enterprise.
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How To do This

Ecosystem thinking is important, as it will greatly boost momentum of an EAM (or digital twin) initiative by means of tapping into synergies. But of course, it begs the question of how to do this. McKinsey has shared some quite relevant thoughts on this: Data ecosystems made simple

And to add to this perspective:

1. Integration: Is not trivial, but essential, so when exploring EAM applications and looking to create an ecosystem, make sure to evaluate the following:
   
   a) Connectors:
   Relevant out-of-the-box connectors takes a lot of complexity out of the equation, getting you on track for creating an ecosystem much faster.
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   b) API's:
   Good API’s and documentation ensures you are able to integrate anything – not being bound alone to the connectors.
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2. Continuous Improvement: This is not built in one go. You must start small and incrementally build a more capable digital twin. The more capable it gets, the more ideas will surface, and you need to be able to prioritize. Our recommendation would thus be to create a product team around your digital twin ecosystem – applying a DevOps approach.
   
   Get the foundation right early, with a (deliberately) limited meta-model, and expand as you mature (exercising the right level of governance of course). And remember – celebrate your wins along the way! 😊
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3. Collaboration and Training: Successful adoption also requires collaboration between different departments and stakeholders. Providing targeted training and support to employees can help them understand and effectively use the digital twin technology.
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The Ecosystem

The below pictures illustrate what type of “capabilities” needs to be supported, where LeanIX can represent the IT. What applications do you need to cover all bases? What is your starting point? How well/easy do they integrate with each other? Imagine having data flow (almost) frictionless between these applications, so that you have the information you need at hand for decision making. Both tactical and strategic decisions on "where to play and how to win" based on various scenarios and understanding of impact downstream and upstream.
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Below is a depiction of examples (usual suspects) of applications that could contribute to such an ecosystem (exemplified with LeanIX as the EAM application / digital twin technology).
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Synergy is the main reason for this ecosystem being value-adding. The ecosystem cares about the same information concepts (e.g., Applications, IT Components, Processes, etc.), with enough shared interest to drive synergies, but supporting different viewpoints, so that we are not duplicating efforts.

If we use the concept of business applications as an example. It is a concept of interest for our digital twin, as we must ensure we have the right portfolio to support our business goals and objectives going forward. This means that we care about the portfolio and are planning for the future. On the other hand, the ITSM system also cares about the same applications. It needs to be able to service requests, changes and incidents. For this it needs different details – more related to operational/run perspective. As an example, it’s important to know which environment the user experienced an issue within. Below this, we have the CMDB, where we care about how that application is configured, for a specific environment, both today, and in the past.
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Data Collection and Data Exchange

There are two important dimensions/aspects regarding data collection:

• People: Despite of “discovery” being an important aspect, in the end, a lot of the data needs to be managed by people, either directly in the EAM applications or in any of the ecosystem applications. This means that we need a holistic perspective on data governance.
• 2-way traffic: As discussed, data can flow both ways - both to and from the EAM application. Often times structural elements flow from the EAM application to the surrounding ecosystem. From the other way, we can also receive structural elements, but just as importantly, aggregated analysis results and conclusions, which may support holistic decision making in our digital twin. Hence, the importance of defining what the system-of-records are for each piece of information.

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Closing Statements

By following these steps, organizations can effectively integrate digital twins into their existing systems and leverage their full potential to drive innovation and efficiency. 4 blog posts into this journey, we are even more excited about this analogy of the EAM application being a digital twin for the enterprise. The vision of equipping the boardroom with ready-made answers on "where to play and how to win" remains strong!
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There are still a lot of unexplored alleys we can dive into from here, but we are curious to hear what you think about our reflections so far – or what could be interesting perspectives to explore in future posts.
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Sources:

• Abdulla, A., Janiszewska-Kiewra, E., & Podlesny, J. (2021, March 8). Data ecosystems made simple. (Mckinsey & Company) Retrieved from mckinsey.com: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/data-ecosystems-made-simple

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