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Why Distributedness is a Measure of Digital Maturity

multi-cloud
(Credit: Pattadis Walarput / Alamy Stock Photo)

When we decided to dig into the digital maturity of enterprises, we based our model on the six key technical capabilities needed to operate a digital business:

  1. IT Infrastructure
  2. Data
  3. Observability and Automation
  4. Apps and App Delivery
  5. Security
  6. SRE Operations

Now, one of the technical indicators of digital maturity for infrastructure, as well as apps and app delivery, is distributedness. That is, the ability to seamlessly operate infrastructure across core, cloud, and edge.

Distributedness is important not only to efficiently operate across multiple locations, which is the norm today, but to establish the ability to take advantage of new technologies as they emerge.

Now, you might be asking, what does distributedness have to do with that?

Thanks for asking! Let me explain by looking at generative AI, which wasn’t on anyone’s radar when we developed our digital maturity model.

Let’s assume that, as an organization, you had established distributedness for IT infrastructure. You’re able to operate infrastructure across core—traditional and cloud—as well as take advantage of public cloud and some edge computing.

Very few organizations are adopting generative AI on-premises. Oh, some technology companies are because of IP and data privacy concerns, but most of them are not that different than enterprises, and they're taking advantage of cloud-hosted services that support the need for privacy and security while allowing them to quickly stand-up services for their employees and developers.

They’re able to do that because they have a high degree of digital maturity in IT infrastructure. They’re able to operate in the public cloud as easily as they do on-premises. That means they already have the skills and talent necessary to embrace generative AI services being offered in the cloud and begin exploring how best to leverage this emerging technology.

Benefits of digital maturity

Organizations who haven’t matured their infrastructure practices to include public cloud and edge can still take advantage of generative AI, but they aren’t able to tailor its usage to fit their business or address any privacy or security concerns.

The real goal of modernizing enterprise architecture is to become a digital business. Becoming a digital business means being able to take advantage of technologies as easily as embracing new markets, suppliers, or distributors on the business side.

Now, not everyone has the talent or budget to mature their IT infrastructure and apps and app delivery practices to be "digitally mature." It takes a lot of work and a variety of skill sets to make that happen from the ground up.

That’s why multi-cloud networking (MCN) exists as a market and why it continues to gain traction. Its entire raison d'être is to establish the capability to seamlessly operate across core, cloud, and edge without requiring a formal IT project with a budget bigger than the 2022 GDP of Vermont. (That’s about $40B, for those wondering).

The benefits of adopting MCN aren’t just about checking off one (or two) of the key technical capabilities needed to become a digitally mature business. It’s about being able to take advantage of new and emerging technologies and capitalize on the competitive advantages of an early adopter.

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