The Fourth Industrial Revolution has begun: Now’s the time to joinon October 15, 2020 at 5:00 pm

2020 has created more than a brave new world. It’s a world of opportunity rapidly pressuring organizations of all sizes to rapidly adopt technology to not just survive, but to thrive. And Andrew Dugan, chief technology officer at Lumen Technologies, sees proof in the company’s own customer base, where “those organizations fared the best throughout covid were the ones that were prepared with their digital transformation.” And that’s been a common story this year. A 2018 McKinsey survey showed that well before the pandemic 92% of company leaders believed “their business model would not remain economically viable through digitization.” This astounding statistic shows the necessity for organizations to start deploying new technologies, not just for the coming year, but for the coming Fourth Industrial Revolution.

This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review’s editorial staff.

Lumen plans to play a key role in this preparation and execution: “We see the Fourth Industrial Revolution really transforming daily life … And it’s really driven by that availability and ubiquity of those smart devices.” With the rapid evolution of smaller chips and devices, acquiring analyzing, and acting on the data becomes a critical priority for every company. But organizations must be prepared for this increasing onslaught of data.

As Dugan says, “One of the key things that we see with the Fourth Industrial Revolution is that enterprises are taking advantage of the data that’s available out there.” And to do that, companies need to do business in a new way. Specifically, “One is change the way that they address hiring. You need a new skill set, you need data scientists, your world is going to be more driven by software. You’re going to have to take advantage of new technologies.” This mandate means that organizations will also need to prepare their technology systems, and that’s where Lumen helps “build the organizational competencies and provide them the infrastructure, whether that’s network, edge compute, data analytics tools,” continues Dugan. The goal is to use software to gain insights, which will improve business.

When it comes to next-generation apps and devices, edge compute–the ability to process data in real time at the edge of a network (think a handheld device) without sending it back to the cloud to be processed–has to be the focus. Dugan explains: “When a robot senses something and sends that sensor data back to the application, which may be on-site, it may be in some edge compute location, the speed at which that data can be collected, transported to the application, analyzed, and a response generated, directly affects the speed at which that device can operate.” This data must be analyzed and acted on in real time to be useful to the organization. Think about it, continued Dugan, “When you’re controlling something like an energy grid, similar thing. You want to be able to detect something and react to it in near real time.” Edge compute is the function that allows organizations to enter the Fourth Industrial Revolution, and this is the new reality. “We’re moving from that hype stage into reality and making it available for our customers,” Dugan notes. “And that’s exciting when you see something become real like this.”

Business Lab is hosted by Laurel Ruma, director of Insights, the custom publishing division of MIT Technology Review. The show is a production of MIT Technology Review, with production help from Collective Next.

This podcast episode was produced in partnership with Lumen Technologies.

Show notes and links

“Emerging Technologies And The Lumen Platform,” by Andrew Dugan, Automation.com, September 14, 2020

“The Fourth Industrial Revolution: what it means, how to respond,” by Klaus Schwab, The World Economic Forum, January 14, 2016

“Why digital strategies fail,” by Jacques Bughin, Tanguy Catlin, Martin Hirt, and Paul Willmott, McKinsey Quarterly, January 25, 2018

Full transcript

Laurel Ruma: From MIT Technology Review, I’m Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic today is building a connected platform for the Fourth Industrial Revolution, which, granted, is a concept that is still being refined in practice, but is undoubtedly here, as data, artificial intelligence, network performance, and devices come together to better serve humans. Two words for you: next-generation apps.

My guest is Andrew Dugan, who is the chief technology officer for Lumen. He has more than 30 years of experience in the telecommunications industry and, unsurprisingly for his time as an engineer, more than 20 patents filed. Andrew, welcome to Business Lab.

Andrew Dugan: Thanks Laurel. I’m very happy to be here.

Laurel: So, launching a new company during a pandemic may not be the most ideal situation, but a great opportunity to rise to the occasion. How has the covid-19 pandemic helped Lumen prepare for, perhaps unexpected, customer needs?

Andrew: Well, covid has been difficult. It’s certainly had a terrible impact on the world, but one of the positive parts of it is that I’ve been really pleasantly surprised at how our team has responded and how our customers have responded. And covid gave us a really good opportunity to show how our infrastructure and our services are scalable by being able to turn up emergency bandwidth for our customers in a record time, surprisingly quick. Covid has also had a measurable increase in our customers’ understanding of how important digital capabilities are because those organizations that fared the best throughout covid were the ones that were prepared with their digital transformation.

We’ve watched how our customers’ needs have changed throughout covid. Early on, we did surveys and found the early concerns were around supply chain. “Will I be able to get the things that I need to be able to continue to run my business? Will I be able to keep my employees safe?” And we’ve seen a shift towards more of the digital concerns. “Is my new way of operating secure? Do I have the right type of security measures in place? Do I have the right type of network for my remote employees or maybe for my customers to be able to consume my services?” A lot of businesses are looking forward and saying, “How do I create new forms of revenue in this covid world?” And so they’re looking at technology to help them with that. And we’re finding that the services that we have available at Lumen can really help them with that need. So, it’s been a difficult time, but also one that’s exciting from a technology perspective.

Laurel: It has that, hasn’t it? We interviewed the CIO at Boston Children’s Hospital and he said that in the early days of covid telehealth visits skyrocketed from 20 visits a day to 2,000. Obviously, there’s been a bit of a decrease as patients returned to in person visits, but clearly this is a huge disruption to the way that things were done. What opportunities during this time of great global disruption do you think could be actually accelerated?

Andrew: As I mentioned, I think businesses have really recognized the power of digital capabilities in today’s world. And I think covid has helped accelerate a lot of businesses in that digital transformation. The longer-term cultural changes that I think will result here, those usually take generations to occur. And when you’re forced into an environment like covid has put us into, it can help accelerate some of those changes. Whether it’s more work from home, the way that health care is provided through more virtual and online services, the way that people market and sell their services. Who would have thought that the number of home sales or cars that were sold through virtual visits would be a normal way of doing things? Also, the way that people interact. From my own personal experience, I’ve done more social interaction through game nights online. I even did an online wine tasting myself with my family and it was quite fun. So, I think we will see continued evolution of products and services, new revenue streams for companies as they embrace the possibilities of what technology can bring to them.

Laurel: Do you have any examples of what you’re hearing from your customers? Just kind of those, “Oh, we didn’t know we could do X, but now we can and maybe it’ll work out.” Just those off-handed conversations that sometimes you have.

Andrew: Well, I think a lot of our customers were surprised at how quickly they were able to transform to a remote work environment. So, they were able to move the majority of their workforces home with little or no disruption to their business. We certainly found that in our business. So I think that was one thing that was surprising for our customers was the usefulness of online learning. I’m not sure that many people before this would have expected that we could support this level of online learning or online healthcare. So I think those sorts of things, many people did find surprising at how quickly and how ready the technology was to support them.

Laurel: Yeah, to be able to do that, whether it’s education or telehealth, a complex and fast edge network needs to be built in most places, right? And expanded in others. So when you think of these complexities, how do companies best handle their plans for not just the edge, but also growing data infrastructure that’s needed to support all of these services?

Andrew: One of the key things that we see with the Fourth Industrial Revolution is that enterprises are taking advantage of the data that’s available out there. There’s a lot more data being generated through things like IoT and smart devices, and the way that enterprises, I think, get to take advantage of those is they are going to have to do a couple things. One is change the way that they address hiring. You need a new skill set, you need data scientists, your world is going to be more driven by software. You’re going to have to take advantage of new technologies. Edge compute is one of those that’s emerging and becoming more available. And they’re going to have to learn how to build that into their applications and their processes. And they’re going to have to look at how the data can make them more efficient, what sort of new revenue streams they can create. So, those are going to be challenges that they may not have faced before. They may not have had to learn how to use AI and machine learning tools. But I think that those will become more critical as the Fourth Industrial Revolution develops for enterprises to be successful.

Laurel: And that’s one of those things where if the old saying is true, that if every company is a technology company, then the technology demands today have advanced pretty greatly, pretty quickly, especially in the face of covid, but in general as devices get smaller and faster and edge compute becomes more real.

Andrew: Yeah, I think that statement is really true that every company is a technology company. I’ve got a family member that owns hair salon business, and you wouldn’t think that that’s a technology company, but how you interact with your customers, you need to have a digital presence. You need to have digital tools that may be less data-driven, but over time will become more data-driven. So, I think you’re absolutely right, that almost all businesses are becoming technology businesses to some extent.

Laurel: Especially with AI and ML [machine learning]. You add this all together with edge compute, AI, better devices, faster devices [and you have something new]. So, the World Economic Forum says the Fourth Industrial Revolution isn’t just accelerating but exponentially advancing technological breakthroughs. How specifically does Lumen, or do you, define the Fourth Industrial Revolution?

Andrew: We see the Fourth Industrial Revolution really transforming daily life, not just people’s personal life, but organizations, as we talked about enterprises are becoming technology companies. And it’s really driven by that availability and ubiquity of those smart devices. Those smart devices are generating data, and enterprises and businesses, their ability to be successful is really being driven by their ability to acquire, analyze, and act on the data coming from those smart devices, to be able to improve their products and services, improve their outcomes as a business and differentiate themselves from competitors. And for us at Lumen, it’s about how do we enable those businesses to use that data and help them build the organizational competencies and provide them the infrastructure, whether that’s network, edge compute, data analytics tools, to help them implement insights using software to improve their business.

Laurel: So, thinking about that acquire, analyze, act on the data, what are some of those challenges that enterprises have with data and processing it?

Andrew: One of the biggest challenges as this transformation occurs, and as it’s centered around that data, it really does come back to that skill set. If your business is being driven by the data, you have to have the people that are able to understand that data and extract value from it. And that’s data science, and more businesses are going to require a data scientists, that skill set to be able to acquire, analyze, and figure out how to act on that data. That’s going to be driven by software, so I think there will be an increasing need for those software skill sets. Those are certainly challenges that they’re going to face. They’re also going to face technology challenges. How do you deal with the new architectures that are going to be required, whether that’s edge compute or more of the AI machine-learning technologies, to be able to deal with all of that data and extract that value. And then how does that affect their processes? A lot of times their processes today aren’t built around data. Those processes can be too slow. Data provides them a real opportunity to improve that efficiency, improve the speed, give them more of an ability to make real-time decisions as they automate the analysis of that data. So, having skills for things like robotic process automation across the organization to help take advantage of that, I think are going to be important, too. So, improving their people’s skill set, how they take advantage of technology, and how that affects their process are all going to be challenges that they have to deal with.

Laurel: That’s an excellent point. It’s not just one thing, is it? You really do have to improve the entire system down the line. And the focus on some companies may be hiring. And then on some other companies may be those apps and solutions and deployment because they have the infrastructure already built. As we know, the data has come out, and the companies that have done better during this time are ones that have already started or are in process with their digital transformation. So what specifically are some of those characteristics you can see forward-looking companies or companies who have started their digital transformation or in the process of it? What kind of technologies and thinking are they using and deploying?

Andrew: Yeah, I think that varies by industry. We talk to a lot of larger enterprises. People who are building smart factories as an example, and they’re dealing with, how do they make better use of robotics? How do they build that infrastructure? How do they run that infrastructure? How do they make it more secure? We see other enterprises out there that are looking to collect information about how their services are used, what their customers want to do with it and collecting that data and trying to figure out how to use AI and machine learning to better predict what their customers will need. So, it really varies by industry, but it’s the software tool sets that are out there to help them solve their business problems through data, but also the infrastructure that they’re going to need to be able to run things like smart factories with robots that are connected through wireless technologies. Feeding data back through sensors to their applications, which may not be located on-site. How do you run and operate those applications? How do you connect it all together and make it work seamlessly? Those are some of the things we’re seeing.

Laurel: And it’s a very complex issue for sure. So, speaking of robots, there’s always this discussion about automation in the work that robots can do instead of people, specifically those “tedious tasks,” that allow humans to do more creative work. What kind of opportunities do you see with robotics and automation?

Andrew: Oh, I see quite a bit. That’s a way for businesses to become more efficient, produce a better quality product, have a safer environment. Going back to that smart factory example, we’re talking with customers who are trying to figure out, how do they take advantage of the advancements in robotics and how do they build out the infrastructure? One of things that we found is that customers need help with deploying and managing those applications. They need help with the connectivity of those robots, to the network. They need to ensure that the infrastructure that’s supporting them can support the real-time processing. That’s so important in these robotics applications and looking for somebody who can help them design these solutions end-to-end from their enterprise locations where the factory is through the edge to the centralized cloud is something that we’re in a good position to help them with and has been a more recurring conversation as those enterprises try to figure out how to take advantage of the automation that robotics provides.

Laurel: Yeah, speaking of that competitive advantage, where are you seeing it? Smart factories and those edge devices? Are there any unexpected places that you’re starting to see that advantage come through?

Andrew: Yes. There are. There are some things that I think are less obvious. One of our customers is a retail food chain, and you wouldn’t think that these technologies and the applications, the processing of data would be as important as it is. When you drive up to a restaurant, you want to go through the drive-through and get something. And you see the line wrapping around the building. There are certain restaurants where you look at that and you say, “Oh, that line is going to take me too long, but there are other restaurants where you look at it,” you say, “Yeah, that line does wrap around the building, but I know from my experience that I can get through that line in just a few minutes.” The fact that those restaurants run an efficient line like that, it’s not by accident, it’s not by necessarily just hard work with the employees, although they do work hard. It’s because the applications that they’re using have created a more efficient operation, whether that’s automation of the food preparation inside, how they collect the orders from customers, how they process the orders, the process that it allows them to operate as a business. So, it is affecting every parts of the business. Even those that you wouldn’t think are highly dependent upon data, highly dependent upon applications, like a retail food establishment. Their business success is becoming increasingly more dependent on the things that are enabled by the Fourth Industrial Revolution.

Laurel: That’s really interesting because when you think about just that one example, there are so many edges there, right? And that doesn’t even go into supply chain and efficiency across the entire retail chain, across a certain geographic area. When we think about this kind of real-time response rate, yes we have this example in a retail food chain, but why is it so important? Why is real-time processing that key component to the Fourth Industrial Revolution?

Andrew: I think there’s a couple of reasons why. One is that the lifetime of data in many cases has a very short useful life. And whether it’s that robotics example or other examples like smart energy grids, you’ve got sensors out there. Those sensors are collecting information. The applications that are being written to react to those sensors are being written for real-time response. Whether it’s in going back to the robotics example. When a robot sensors something and sends that sensor data back to the application, which may be on-site, it may be in some edge compute location, the speed at which that data can be collected, transported to the application, analyzed, and a response generated, directly affects the speed at which that device can operate. And so the ability to manage that data process, that data in real time is critical for those types of applications. When you’re controlling something like an energy grid, similar thing. You want to be able to detect something and react to it in near real time. Other examples of safety examples, where you’ve got video processing managing the movement of something around a campus. The ability to see something in the camera sense it, detect ,and react to it is critical for safety. So we’re seeing a lot of applications that their dependency on fast processing of data is becoming very important to them.

Another reason for real time is the amount of data being generated out there is just huge. And that data is moving quickly and you don’t have necessarily to store it over a long period of time. And as that data is coming in, you want to be able to process it as quickly as you can, extract whatever value you can out of it, and then dispose of that data. And so you don’t want to get behind in that processing and the ability to handle it in real time is also important.

Laurel: Yeah. Kind of focusing on that sense, detect, and react that of course has a lot to do with the security as well. So the attack surface of what enterprises are looking at now is growing, right? So it’s every device, every network connection, every point. How is security tackled and how is this a priority for businesses?

Andrew: Yeah, this is a really interesting problem, I think. Years ago, an enterprise would build a private network and they would protect it largely with perimeter based security. You make sure that data or people getting into that network are the people and data that you want there. And you could protect a lot using a perimeter model like that. As applications distribute, as they become available on the public internet, that perimeter based security is not the only thing that you can rely on. You have to think about security at every layer. And the layers that I think you have to worry about today is your network.

One, operating system, application security and your data security. From a network perspective, you want to ensure that you’re operating on a network that is inherently secure. One of the things that we do at Lumen to help with that is we have a group that we call Black Lotus Labs. It’s a research group inside the company and their job is to analyze data available through the internet. Through analyzing internet traffic patterns and detecting malicious actors out there, and then build that protection into our networking and enterprise security products. By doing that, we can make the network inherently more secure at the operating system level and application level. You need to make sure that you’re continually patching. That you’re understanding what exposures might exist in that operating system that’s running your applications and the applications themselves. And ensuring that you’re continuing to close any gaps that are found. And as data becomes more available, as we’re extracting more and more valuable information about our customers and users using that data analytics, data privacy and security are becoming even more important. And so, use of data encryption where appropriate, ensuring that you have the right data security and controls in place is also critically important. So yeah, we’ve changed quite a bit from a perimeter model to one where you need to think about it at every layer of the network and layer of your application.

Laurel: And that makes sense as everything becomes much more integrated and like you said, the data at every layer demands that sort of response. So when I’m thinking about customers, that’s a broad category. And Lumen obviously is a bit behind the scenes to their customers’ customers, but still very important. You need to care about how everyone is using the network devices. And how do you instill that curiosity into your organization where you look out and you are responsible for the experiences of many different people and many different applications. And it’s hard to, I guess, sometimes square what a smart factory does with a food retail outlet, but at the same time, you’re still reliably giving them that network connectivity securely, quickly to allow them to do what they need to do.

Andrew: Well, I think you hit on it there. Even though it’s our customers’ customers that have a lot of the experience that we’re trying to drive, we really do have a direct effect on that. As you outlined, it’s the network experience. We provide a lot of the underlying infrastructure and the performance of our network directly affects those end customers’ experience. So, that’s really important. How secure we make our network, how secure we make our infrastructure also directly affects those end customers. So, we try to instill in our employees, in our products and services, that recognition that we are here to create a great customer experience for our customers and indirectly to their customers. And I think we do a good job of that. I think everybody recognizes how critical the services are that we perform and provide and that our customers rely on us.

Laurel: Absolutely. So one last question, as an engineer yourself, we’ve touched on so many different aspects and we could easily talk for days about certain parts of this conversation, especially security, but what are you most excited about or curious and what gets you just really happy to read the news, to get going, to do the hard work that really helps companies do those amazing things?

Andrew: Well, I get excited about technology being an engineer. There’s so much that we can help our customers do to improve their businesses but improve society overall. I look at that technology as being a real tool that we can make available to our customers to make things better. And it’s really fun for me to be involved in the development of the technologies that empower them to take advantage of this Fourth Industrial Revolution. One of the ones that gets me up on a daily basis recently is the developments around edge and edge compute and supporting these applications that are becoming more performance sensitive. How do we build and manage the infrastructure that lets those applications operate with a high degree of performance so that they can provide that real-time feedback to our customers and real time improvement? So, it’s pretty exciting that the edge compute part of what we’re building is relatively new. The conversation’s been around in the industry for a couple of years, but it’s now becoming real and we’re moving from that hype stage into reality and making it available for our customers. And that’s exciting when you see something become real like this.

Laurel: It is. Anything to get away from the hype and into the reality. Andrew, thank you so much for joining me today in what has been just a fantastic conversation on the Business Lab.

Andrew: Thank you very much. Enjoyed it.

Laurel: That was Andrew Dugan, who is the chief technology officer for Lumen, who I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River. That’s it for this episode of Business Lab. I’m your host, Laurel Ruma. I’m the Director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology. And you can find us in print, on the web and at dozens of events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.

This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Collective Next. Thanks for listening.

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