Businesses that want to be digital leaders in their markets need to embrace automation, not only to enhance existing capabilities or to reduce costs, but to position themselves to successfully maneuver the rapid expansion of IT demand ushered in through digital innovation. John Roese is global chief technology officer at Dell Technologies. It becomes impossible to keep up with the growing opportunity to become a more digital business if you don't have autonomously operated operations.
The main hurdle to autonomously operated businesses is psychological. He says that you have to be open-minded to the idea of balancing the work between human beings and machines. All the products and solutions we can deliver to you will not help if you are resisting it.
Technology and infrastructure-driven artificial intelligence and machine-learning discussions are expanding beyond IT into finance and sales, meaning that technology has direct business implications. Data and artificial intelligence can give you better insights and the ability to be more contextually aware and responsive to your customer, says Roese. The economics and performance of all parts of the business can be changed by data, artificial intelligence and machine learning technologies.
As companies gather, analyze, and use data at the edge, they become even more of a business necessity. 70% of the world's data is going to be created and acted upon outside of data centers in the future, meaning in edges. The impact of edge and distributed topologies is huge, but it is almost as important to have a strong investment in the right systems to make it work.
Show notes and references.
What is the difference between autonomously operated and autonomously operated operations?
Perspectives on the impact of operations.
Full transcript.
Business Lab is a show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Increasing innovation through operations is our topic today. Organizations need to re-examine their IT strategies and determine how to level up human-machine partnerships, not only to improve workflows and enhance existing capabilities, but to increase innovation and transformation, if the next step in technology's evolution is autonomously operated operations. There are two words for you.
John is the global chief technology officer at Dell Technologies. John is in charge of the company's technology strategy. He holds more than 20 pending and granted patents in areas such as policy-based networking, location-based services and security. Business Lab is produced by Dell Technologies. John, welcome to the world.
John is great to be here.
John, when we spoke last year, you clearly defined two possible paths for innovation. One path was a huge jump in capabilities, something that would change society, but the other path was a bit more realistic and measured. I quote you, "An augmentation to the cognitive tasks that human beings typically do." Does that still hold true?
John thinks the evidence supports his view. We don't have self-driving cars. There are no terminators running loose in the streets, and by and large, machine intelligence has been incorporated into our lives, improving everything from how our homes operate to how batteries are maintained and kept efficient. Our cars have become safer over the last two years because of machine intelligence, the ability to detect objects, and other small improvements. We seem to be on the path of incremental improvement. After two years, it's fun to ask how the world is different. The world is much more self-sufficient today than it was two years ago. Dramatic changes in society have not been caused by the change in autonomy, which is the way technology should roll out most of the time.
How do you define autonomously? Why is that important for business?
John: Yeah, yeah. The idea of an autonomously system is just saying it's a function that happens below the level of human effort. Things that can be done without humans being involved are generally things that have been absorbed into the realm of autonomy. That applies to everything from cars to IT technology. Most people understand that, but they don't see it very often. It's similar to the commodity curves that we deal with where a technology is highly differentiated and a couple years later the commodity line moves up and it's no longer interesting. Imagine a world where you saw your first high-definition TV. It was unique, you were willing to pay a premium, and here we are a decade later and it's accepted as the norm. The same principles apply when we shift things below the line of human effort into the world of operations.
Why are there so many autonomously operated machines in modern IT? How do they help relieve the IT resources?
The biggest challenge in the IT world is always related to scale, demand. We're in a cycle where there isn't a business in the world or an industry in the world that isn't in a digital transformation, and we're not trying to become a more digital business, to use technology, to use data. There is a dramatic expansion of demand on the people and the organizations and the budgets that are able to deliver technology to those enterprises. If the demand of IT capacity is growing rapidly, we can either hire more people and do it the same way, or we can divide the work between people and machines.
I think the majority of enterprises want to be a digital leader. You want to use data to your advantage in digital transformation. If that's true, the sheer scale of those tasks exceeds the human capacity of your IT organizations and the budget that you have to use just pure human effort to solve those problems, which inevitably leads you to looking for ways to shift the work into the infrastructure. It becomes impossible to keep up with the growing opportunity to become a more digital business using just human effort if you don't have the ability to autonomously operate.
How much has the last two years affected this, being in a time when everyone is online and digital first?
There were a lot of downsides of the last two years, but one of the things that people may not have been aware of is that we think the path to success. It moved quickly. Suddenly, you found yourself in a place where you didn't have the luxury of using humans to do the work. You couldn't do it the same way. When it was easy to just use humans to accomplish the task in the same, you didn't need to do it when you were evaluating as a business. You started to look at technology as a way to accomplish those tasks when you didn't have that luxury.
Technology works, that's what we found. It is available. The adoption of technology within our businesses accelerated dramatically because of that. Two years ago, the reaction to all three of those phrases would have been negative. Over the long term, you might have been a little bit positive. When we use those terms in business, drones are great. They can deliver things. They can do a lot of things that humans can't do. The importance of robots is critical. As long as your package shows up, it's okay for a robot to deliver your food.
We've started to see how it's transformed health care, how it's made our communication systems more intelligent, our transportation networks works better, and that's something that we now view as an augmentation, a positive aspect and not a threatening thing. In the last two years, there has been a big shift in open mindedness to technology and the adoption rate of technology. We think that the digital transformation journey has been accelerated for three to five years.
It is three to five years. Not every company was ready for that. How can a company be tech-forward?
John: Yeah. Digital transformation had a bell curve before covid and most people were at the back of the pack. Everybody else was behind the curve when it came to digital disrupters, and there were industries where that was just one digital disrupter. In order to execute a digital transformation successfully, you had to do most of the work. There weren't any products that were part of a package. Companies were not set up to do it for you in a way that was easy to consume without a lot of expertise inside of your company. Almost every company that supplies technology or can help you navigate that maybe wasn't delivering easy-to-consume products suddenly showed up in force during the last two years because of the demand cycle.
One of the biggest changes in our portfolio has been moving more and more of it to be delivered as a service, which means we take the responsibility and use tremendous amounts of automation to make it easy and cost effective, but we shift There was huge demand for it over the last two years. We needed to have more scale and better economics and push the burden into the technology took huge cost and complexity out of the system. In this period of aggressive digital transformation, covid resulted in a better supply base.
The result of that is that you don't have to be forward in terms of your capability set. You don't need a big data science team. You don't need to make your own software. You don't need to build your own infrastructure. You can consume it from any number of sources of supply that are delivering to you highly advanced and almost complete outcomes for many of the situations. You have to be open-minded to the idea of a rebalancing of work between humans and machines in environments that are both logical and physically present. All the products and solutions that we can deliver to you will not help if you're not embracing and wanting it to happen.
To really accelerate the entire ecosystem forward, I think, is the one kind of last threshold that people have to start to get comfortable with, is the idea that the future will be different between the work that people do and the work that machines will do. If you start to look at how to live in that world, you can start to tap into a far expanded supply base of technology and capabilities delivered from industry that are actually significantly easier to consume than anything we had two years ago.
The shift to self-awareness and embracing it was accelerated with the last two years, but it was nagging in the background. There was a lack of skills, employees, and the ability to find people to do the work to keep everyone moving as quickly as possible.
John: Yeah, yeah. Absolutely. We used to go and talk to customer A in an insurance or financial services industry, and we would see some amazing things they were doing, but it was them doing them. The company had resources and people in house. They had to be able to capture the talent pool to really develop their own technology or be down in the weeds. You would go to another company in the same industry that didn't have the same level of human competence and they wouldn't do anything. This is a have-and-have-not scenario. We still need smart people. It's very helpful and important, but you have examples where customers with smaller software development teams can use low code applications and containerization and automation tools to develop really interesting software assets with a much smaller footprint.
A much smaller data science team can use the platforms and capabilities that exist out there to get almost better work done than what companies could do two years ago. A company that has a small IT organization but is embracing the autonomously operated infrastructures they can consume today, can deliver a much bigger, moreScalable infrastructure, can have a multi-cloud strategy, and can also have a small IT organization. It was gated based on human capacity, so it was a theory. The providers of that technology have unlocked a tremendous amount of democratization of moving forward together, as opposed to having haves and have nots, because of the progressive shift towards smarter systems, more autonomy, different consumption models, ways to shift the burden away from the customer and towards technology.
Other benefits of an operation that is not controlled by a central authority include benefits for the business, as well as IT here. Cost savings and monitoring for cyber threats are some things.
John: Yeah. Yeah. Two very good examples. At Dell, we have hundreds and hundreds of artificial intelligence and machine learning projects going on at any given time. It was mostly a technology- and infrastructure-driven discussion several years ago. The discussion of finance and sales has a direct business implication. Some of the hallmark projects that we talk about are improving our time to repair or our ability to service customers or putting our sales force on target, improving revenue performance and ability to close deals. The people who are embracing those and benefiting from them understand that advanced technology adoption is the reason they're able to do that.
It's interesting to hear the head of sales talk about artificial intelligence, and it's fairly common these days. If it isn't happening in your company, you should ask why, because there's a third party that can help you and that can give you better insights and be more contextual. I think most business leaders understand that there is a third party in the relationship and that's why technical terms like artificial intelligence and machine learning are now part of the business dialogue. The economics and performance of their part of the business can be changed by the technology that they use.
This is the first area where autonomy was not just nice to have, but it was necessary in order to maintain security. Over the last four or five years, the security threat landscape has dramatically expanded because of digital transformation, meaning it created a target. There have been a lot of cyber threats and there have been dozens of ransomware attacks. Years ago we realized that there was no way that you could protect an enterprise and run a security environment without a tremendous investment and adoption of machine intelligence. Today, we find that it's just the status quo.
If you look at certain industries like security event and information management, people like Secureworks, a part of the Dell family, you can't have a competent offering detecting threats if a human being had to look through billions of threats events that are coming in. It's already done because you have to outsourcing that to a machine. It is moving into the other parts of security. That's the piece that tells you something. The prevention and response pieces are becoming more independent. Let's make sure that we don't create a vulnerability. Human error is probably the single source of vulnerabilities that get created or not having enough human capacity to keep your software patch, to properly inspect your code as you're creating it, to be able to move fast and move fast with security.
When an event occurs, it turns out that it isn't causing damage immediately. If you could move faster than the attack to mitigate it, it wouldn't cause problems. An automated response means the ability to push a button and change the behavior of your network or to push a button and isolated users, or maybe not even push a button at all. In the security world, the absence of artificial intelligence as a full participant in the end-to-end stack means that you're probably the only one. It's definitely the lead horse in this shift because of necessity.
Yeah, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, yes, I think you said it perfectly. If it's an automated attack, you need an automated response. That brings in tension to the relationship with humans and machines. Sometimes you call keeping the human in the loop, but what about the conversation with staff and employees who are wondering what their job looks like, and what is that like with humans? How does the conversation start?
John: Yeah. There are two questions. How do people embrace their independence in a way that isn't threatening? When autonomy takes over certain jobs, what's left? The first question is a good one and we believe that most adoption of machine intelligence, autonomy and other technologies is a function of incremental improvement. It's getting rid of things that you can't keep up with. What that means is that you are still in the loop, you are still expressing intent, and you are authorizing the behavior to happen. You're dealing with the macro-behaviors instead of understanding the micro-behaviors.
Imagine a situation where a human has to sift through logs to figure out what happened in the security world. A human has to figure out where the attack is coming from and where they can possibly dis-intermediate the attacker. A human has to manually reconfigure everything to make the attack go away. That experience is terrible. It's not even tenable these days. You're still the security operations person, but now a machine tells you there's an attack happening. In order to know what to do, you need to know where it came from, so you asked a machine to give you options. Once you decided that it was worth reacting to, you had a machine do the reconfiguration.
Number one, you're going to move a lot faster and you're going to be able to move ahead of the attack, but number two, both scenarios effectively result in the same security operations team in terms of the number of people. They are likely to fall behind and fail their business. It's a positive thing if you're in an environment where the scale is exceeding human potential. Human beings having ultimate authority of intent and decision-making are still very important pieces in any kind of autonomously operated system in IT.
If you had an entire team of people who were supposed to run around and reconfigure the infrastructures you were on, guess what? The jobs are going away. They're not going to be necessary because they can't do it as fast or as effective, and they create risk if you don't move fast and shift this to independence. You have to have a different discussion in those cases. If those jobs go away, you have to ask if something will be better. There are a lot of new jobs being created. They might be the same skills, but for instance, there's a job that I think is called an SRE, site reliability engineer, and it's the person who takes care and monitors the infrastructure. Care and feeding is needed for an infrastructure.
This is an example. If you've noticed, it's an autonomously-operated vacuum cleaner. Guess what? It will fail if you just let it run by itself for a month. It has to be cleaned and supported. An SRE in an infrastructure is similar to that. An autonomously functioning system needs to be managed, maintained, and occasionally upgraded. We've created new skills that are used to care for the systems. In manufacturing, where we move to robotic manufacturing, we created a lot of new jobs. The software for the machines is what the new jobs are about. Who does it maintain them? This pattern in manufacturing is well underway.
In the IT world, new jobs will be created because of the fact that systems are not free of human beings; they still need human beings to tell them what to do, to tune them, to basically maintain them. There are a number of jobs that aren't necessarily high- skilled. Someone who used to manually provision storage can now be an SRE to maintain the automated storage environment. Even though the amount of human effort per unit of whatever drops, the amount of human effort in aggregate is probably larger because of the scaling of the IT systems.
When these kinds of trends occur, it usually is a net positive in terms of employment and requirements for human effort. We don't have a lot of technical people in our industries right now and I think we will need more trained people and more people working in our industry in five years.
With the adoption of cloud and edge technologies, the ability to work from anywhere is definitely part of it. IT operations have to be decentralizing and capturing data from anywhere because the data collected is increasing. What does that mean for IT? Correct, more autonomously operated operations.
John: Yeah. Edge is an example of this. It was easy to put your people near your IT in a data center or a cloud environment. If you used advanced automation technology, you could scale human effort in an environment where everything was co-located with each other. The minute you start putting things out into the real world with edge, you can deploy your technology back into your stores, hospitals, schools and factories. 70% of the world's data will be created and acted upon outside of data centers in the future, meaning in edges. You have only two options when you start doing that.
Human effort is the first. You're going to need human beings to deploy the stuff, but you can use robotic and other services to operate it, and that's more important than anything else. We will not have enough people to interact with the devices manually if it requires human intervention and human presence to touch them. One of the principles of edge platform is that you have to start looking at what the platform has to offer. Zero-touch provisioning is one of the characteristics. The system can be deployed and provision itself with no human intervention so that it can be in production. A zero-touch administration that can upgrade. It can operate.
Zero-trust environments where you don't want anyone to have privilege. A well-formed edge environment is one that you want to lock the system down and have no human intervention in. The environment doesn't need a lot of human touch. It doesn't need a lot of help. We have one customer that has over 9000 retail stores across the world, so we have one customer that is no longer a couple of data centers and maybe some cloud services. We don't want to provide a human footprint to cover 9000 sites if that's the case. The remaining five will have human beings and we will cover 8,995 of them.
We're excited about edge and the new distributed topologies because they change where data can be processed. They have a huge impact on digital transformation, but it's almost as important to have a strong investment in self-sufficient systems at the edge as it is in the security industry to make it work.
How do they all help a company's digital transformation and how do they always improve innovation?
John said speed. There is only one. We're in a race. Every company is in a race. It's a race to see who can build the most efficient and effective business. One of the assets we have in that race is technology, and specifically technology that improves the speed in which we can do things, whatever those things are. Sell a product, support a customer. When we think about autonomy in general, does it make you move faster? Does it allow you to do the things that make your business profitable or effective at a faster rate than you could do it without it?
Whether it's the speed in which you can understand and operate things in your business, the speed in which you can teach a student, the speed in which you can build a product, or the speed in which you can learn what they are doing well and how they could be improved, You can change the real world by changing the digital world by building new software, putting it out into production, changing the infrastructure behavior, and actually changing the real world by changing the digital world. It's all about speed. It's not because they're friendly and nice that you need a strong partnership with them. It's not because they're cool. They allow you to move faster. You are likely to win the race if you move faster than your competitors.
Speed and scale are important to her. John, thank you so much for joining us today, we had a great conversation on the Business Lab.
John: No, my pleasure. Great discussion.
I spoke with John Roese from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River.
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