We write a lot about digital transformations on this blog.

We also talk about it a great deal in our podcast episodes, and the speaker faculties of our events always have a lot to say about it too.

I sometimes worry that there’s not a lot left to say in this space without getting into specifics that by their very nature start excluding people. No one case study or example can cover everything or speak to everyone, right?

Then this morning I was reading something about Edge Computing, and it occurred to me while I have heard people talk about Edge Computing over the last few years, I can’t point to a piece of content I’ve made that uses that term specifically. Why don’t I fix that today?

What is Edge Computing?

Why don’t we start off by saying what Edge Computing is, for those who don’t know. That is sort of the point of these articles, isn’t it? There are going to be subject matter experts who quietly roll their eyes that this sort of thing even needs to be talked about at such a basic level, and on the other side of the spectrum there will be readers who are not confident they could have a five-minute conversation about Edge Computing without looking foolish, so why don’t we give those two groups some common ground?

Let’s imagine a computer network like a spiderweb, for a moment. In a spiderweb, All the threads lead to the center of the web, and that’s where the spider waits for the telltale tremble of a fiber announcing dinner is about to be served in one particular direction, or perhaps a repair is in order in another direction. Most computer networks have a central repository where data is collected, stored, and processed. That’s like the spider at the center of the web. Data flows in from many different places, just like the vibrations along the spiderweb threads, but it is up to the spider to take that input and then make decisions upon it.

Now imagine instead of one spider at the center of the web, there were many spiders throughout the web and especially out on the periphery. The spiders are aware of each other and do share in the vibrations they feel in the web, but they also have the authority and autonomy to eat whatever fly lands in the web closest to them, or mend the nearest hole. Think how much faster the web maintenance would go, and how much less time an insect would spend waiting for its demise?

Edge Computing is about processing and analyzing data where the data is generated without waiting for it to be transmitted to a central repository. Edge computing is a distributed computing architecture that allows and empowers decision-making where the action is happening as it happens without referring to or relying upon a distant point of authority. If we imagine our computer network —our spiderweb— stretching across the entire world, we can quickly start imagining the advantages of many decision-makers acting on local data very quickly.

Abandoning the spiderweb metaphor (you’re welcome), let’s acknowledge that the Internet of Things and the Industrial Internet of Things is very quickly generating more data than we reasonably know what to do with in most cases, and that tidal wave of data is only growing and accelerating. Does it make sense for a data center in California to be making decisions about a QA/QC system in a factory in China? Should software running on hardware in a corporate headquarters in London or New York or Tokyo be worried about tracking how a delivery truck is making its way from its pickup to its dropoff while trying to avoid traffic? For high-volume, high-speed decisions like controlling an autonomous vehicle or monitoring the emergency shutdown triggers for expensive equipment, you also start facing the real challenge of data latency and bottlenecking within system architecture where there are physical limits to what is even possible to do reliably at a distance.

All this is to say there are many examples where giving local systems the power to make their own decisions while reporting those decisions up to the ‘one source of truth’ data center after the fact create faster and more efficient business decisions.

What Else is Edge Computing Good For?

Of course, the benefits of regional autonomy don’t stop at speed. Another huge advantage is reliability, resiliency, and redundancy. A network of computers each given authority to take care of the processes closest to it is not vulnerable to outages, loss of connectivity, or other unplanned downtime in the same way a centralized network can be. In this era of ever-increasing disruption, there is a powerful argument to be made for allowing Edge Computing to do the heavy lifting on most tasks rather than the other way around. The economies of scale offered by data centers only apply to some tasks, challenges, and opportunities. There are many functions where the possibility of that data center being out of contact with its network are a much greater risk than localized computing lacking the processing power or data storage compared to a dedicated and centralized network hub.

Another strong advantage for Edge Computing is by its very nature it currently sits at the forefront of IIoT innovation. As sensors are designed to passively gather enormous amounts of information and communicate them M2M, focusing on Edge Computing is only going to incentivize further capabilities. Do you want your operations to track its own inventory, its own productivity, its own environmental performance? Great! Rather than rely on a piece of software running on a machine on the other side of the continent, have all of that happen within the walls of the facilities where the data is actually generated, and allow the IT and OT infrastructure within that local network to make its own analysis of that data, and perhaps even take corrective action. Build that in an open structure where assets are backwards and forwards compatible with other assets as they plug into the system, and before you know it, things are being invented by and for the people who are actually doing the work wherever that work is being done, rather than it being designed for them by people they have never met who are working with an idea of how they think things get done. The local Edge Computing system will by its vary nature inspire and sustain bespoke solutions based on local conditions.

Are There Other Pros and Cons?

Edge Computing probably will not completely replace the hub-and-spoke model of traditional computer networks, but shifting to a hybrid model will —over time— help curb the environmental impact of large data centers.

On the other hand, Edge Computing’s advantages of reliability, resiliency, and redundancy distributed decision-making also create more risk of data breaches and cyber-attacks. In a world where CIOs and CTOs are constantly working to keep their data centers a step ahead of the people looking for vulnerabilities, delegating and distributing data and data analytics throughout a network is spreading around a lot of what traditionally has been best kept gathered together and guarded in one place. For all Edge Computing’s powerful potential for good in the future of the Digital Revolution, cyber security is going to be an ongoing challenge without easy answers.

So what should we take away from today’s article? Without pushing on this point too hard, almost certainly everyone whose organization is undergoing Digital Transformation —and that’s everyone— is already doing some form of Edge Computing whether they know it or not. Having a clearer picture of what is it and how it fits into the larger conversation about digitizing operation is important. Is your company making the most of what distributed data analytics and autonomous decision-making can offer? Are the AI tools currently being implemented built around centralization, or can they work as part of a larger ecosystem? When was the last time cyber-security policies were reviewed, and has Edge Computing’s increased risk profile on that issue been factored into forward strategy?

Edge Computing isn’t going anywhere, and it is only going to become more important as everyone moves forward on their Digital Transformation Journey. Knowing what it is and thinking about how it fits into everything else is important. Give it some thought. Come up with good questions, and go looking for good answers. You may now be ready to have that five-minute conversation with those subject matter experts without fear of the ground falling away beneath your feet.

As for Executive Platforms’ content? I don’t know how soon I will be talking about Edge Computing as a topic of its own again, but I will feel a lot happier including it in other conversations about Digital Transformation having given it a chance to shine here, so thank you for letting me talk about this at some length this time around.

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Geoff Micks
Head of Content & Research
Executive Platforms

Geoff joined the industry events business as a conference producer in 2010 after four years working in print media. He has researched, planned, organized, run, and contributed to more than a hundred events across North America and Europe for senior leaders, with special emphasis on the energy, mining, manufacturing, maintenance, supply chain, human resources, pharmaceutical, food and beverage, finance, and sustainability sectors. As part of his role as Head of Content & Research, Geoff hosts Executive Platforms’ bluEPrint Podcast series as well as a weekly blog focusing on issues relevant to Executive Platforms’ network of business leaders.

Geoff is the author of five works of historical fiction: Inca, Zulu, Beginning, Middle, and End. The New York Times and National Public Radio have interviewed him about his writing, and he wrote and narrated an animated short for Vice Media that appeared on HBO. He has a BA Honours with High Distinction from the University of Toronto specializing in Journalism with a Double Minor in History and Classical Studies, as well as Diploma in Journalism from Centennial College.