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What does the "digital transformation" really mean? GigaOm CEO Ben Book and 7investing CEO Simon Erickson take a closer look inside today's biggest technology trends.
May 13, 2021– By Simon Erickson
There’s a lot of technology buzzwords flying around in the financial media these days.
“Digital transformation”, “cloud computing”, “edge computing”, and “artificial intelligence” are making their way into plenty of headlines and also into the conversations of more and more cocktail parties. The world is gaining a better understanding of what several cutting-edge trends actually mean.
But even more important than understanding them is following how these disruptive new technologies are actually being implemented. Businesses of all sizes are moving their workflows to the cloud service providers like Amazon (Nasdaq: AMZN) Web Services and Google (Nasdaq: GOOGL) Cloud Platform. They’re hiring data scientists to set up machine learning environments, and they’re assembling teams of hundreds or thousands of engineers to undertake massive new projects. There are a lot of dollars at stake as the digital transformation more firmly takes root within the enterprise.
What will all of this mean for investors? Are there ways to capitalize on the biggest trends taking shape in the tech world?
To help us answer these questions, we’ve brought in an expert who is at the forefront of innovation. Ben Book is the co-founder and CEO of GigaOm, who is helping IT decision makers tackle their most complex technical challenges. GigaOm is bringing the executives of progressive companies up-to-speed about emerging technologies and then helping to implement them across their organizations.
In this exclusive interview with 7investing, Ben digs deep into what’s really going on in today’s biggest trends. He explains what the digital transformation is really all about and why we’re still just “in the second or third inning.” He describes how cloud computing is allowing companies to simplify their IT operations and how machine learning is now being used for more customized applications. Previously a healthcare consultant, Ben also sheds some insight on where tech companies have the greatest chances of succeeding in health care.
Finally, Simon asks Ben to share several other trends he’s excited about right now.
Publicly-traded companies mentioned in this interview include Alphabet (Nasdaq: GOOGL), Amazon (Nasdaq: AMZN), Datadog (Nasdaq: DDOG), Disney (NYSE: DIS), Intel (Nasdaq: INTC), Microsoft (Nasdaq: MSFT), Netflix (Nasdaq: NFLX), NVIDIA (Nasdaq: NVDA), Snowflake (Nasdaq: SNOW), Taiwan Semiconductor (NYSE: TSM), Twilio (NYSE: TWLO) and Zoom Video Communications (Nasdaq: ZM). 7investing’s advisors or its guests may have positions in the companies mentioned.[su_button url="/subscribe/" style="flat" background="#84c136" color="#ffffff" size="6" center="yes" radius="0" icon="" icon_color="#ffffff" desc="Get full access to our 7 best ideas in the stock market for only $49 a month."]Sign Up Today! [/su_button]
00:00 – Introduction: What is the Digital Transformation?
04:39 – Where Do We Stand in Cloud Computing?
11:48 – How are Companies Actually Using Artificial Intelligence?
24:26 – Where are the Biggest Opportunities for Tech in Healthcare?
31:05 – What Tech Trends is Ben the Most Excited About Right Now?
Simon Erickson 00:00
Hello everyone, and welcome to today’s episode of our 7investing podcast. I’m 7investing founder and CEO Simon Erickson.
Simon Erickson 00:07
We’ve heard a lot of headlines in technology in recent years. Whether it be cloud computing or artificial intelligence or machine learning or whatever else it might be. There’s a lot of buzzwords that are floating around out there. And today, I’m very excited to welcome a technical expert to help us drill down into a lot of those trends that are developing. My guest is Ben Book, he’s the co founder and CEO of GigaOm out in California. Ben, thanks very much for joining 7investing for our podcast this afternoon.
Ben Book 00:33
Of course, Simon. Thanks for having me.
Simon Erickson 00:35
Ben, let’s start at the 10,000 foot level. We hear a lot about the digital transformation. I know that at GigaOm, you are not only advising executives about innovative technologies that are out there. But also helping them implement it into their own organizations as well. What are your overall thoughts about this phrase “digital transformation”? What does it really mean to you?
Ben Book 00:56
Digital transformation has been a big buzzword, to your point. It’s been around for quite a while. I think most enterprises have come up with different definitions of what that really means to their business. But at the core of what it means, it means to modernize their business to build new digital products and services that support their revenue and their customers. And customers have tried; enterprises have tried to do this over the past number of years. Some of them have succeeded, some of them have failed.
Ben Book 01:21
But at the root of it, the purpose of doing digital transformation is really around Boards and CEOs wanting to be software companies and wanting to be valued as software companies. If you look at companies like Snowflake, like Zoom, you know, these unicorns that are coming out of Silicon Valley. They’re trading at really high multiples. And even the tech companies are trading at high multiples. So boards and CEOs want to have parts of their business, have higher multiples, and also have their core business start to trend to be a digital business.
Ben Book 01:50
And those picked a good time to be successful. A lot of other ones are still trying to figure out what that means to them. I think, at the core of it, it’s just digital services and modernization. And it’s challenging for companies who don’t grow up in that culture, right? I mean, if you grew up in Silicon Valley, it’s a different culture than growing up in the finance ecosystem and industry in New York, versus Texas with oil and gas. So it means something different to every industry and every enterprise. But at the core of it, it’s really about valuation and driving growth for these companies. And so you know, boards and CEOs want their IT teams and want their product teams and want their marketers and want their HR people thinking about how can you apply technology to your business so that we can 1) either be valued as a software company and get a really good valuation or 2) use technology for things like automation. To be able to cut costs and things like that.
Ben Book 01:50
So, you know, it’s always been a challenge for a company who’s a legacy company to figure out how do you work in the new economy, the digital economy. And some companies like Disney have done a good job preparing for that, like their streaming service. Other companies have prepared for that. Like Henkel, for example, they’ve modernized their data infrastructure, a lot of them did it prior to COVID.
Ben Book 03:03
So again, it’s a big buzzword. To your point, something different to everybody. And lots of companies have succeeded. And a lot of them have failed.
Simon Erickson 03:11
Sure. And if we’re in a nine inning ballgame in American enterprises doing the digital transformation. Where in the ninth inning, everybody’s converted everything over the cloud; everything has gone digital exactly how they wanted it to. And one is they’re just getting started. Where are we? Are we in the third inning? Are we in the sixth inning? Where do you think we are in America?
Ben Book 03:26
That is a good question. I think most enterprises are in the second or third inning. And, you know, the starter’s thrown about 70 pitches or so. And they’re hitting the second round or third round of batters. And they’re trying to change it up. They’re trying to switch it up. They’re trying to change the pitch that they’re throwing. And they’re still experimenting, right?
Ben Book 03:49
I think that’s a big thing. That they’re experimenting and still trying to figure out as new technologies comes out. Like blockchain, like security. It is a constant evolution. And we’ll never, I think, get to the ninth inning. To be honest, it’s a constant evolution.
Ben Book 04:06
So the companies who are you know, in the third or fourth inning, I think they’re moving along. There are some who are like the sixth inning and seventh inning. And they’ll always be there. But it’ll be pretty impossible for everyone to always be on trend. Because if you’re looking at a large enterprise, there’s just so many moving pieces. And then you have the political and government compliance issues that they have to go through, which slows them down too. So there’s more than just technology that enterprises have to have to fair with.
Simon Erickson 04:32
Fair enough. Okay, second, or third inning in the digital transformation. Sounds like a great time to go get a hot dog and a $15 beer from the ballpark.
Simon Erickson 04:39
Let’s shift gears a little bit here, Ben. You had mentioned Zoom and Snowflake just now. Two companies that have been rewarded by very high valuations by the market. They’re also very focused on the cloud. And we’ve seen a lot of software as a service companies, infrastructure as an as a service companies, platform as a service companies. Everybody seems to be moving workloads and data over to Amazon. Snowflake is allowing for multi cloud strategies, for companies that are embracing that. But we’re also hearing about other shoots from this as well, right? Edge computing is kind of a big deal, where a lot of people are trying to say, “Hey, don’t send everything out to the centralized cloud. You can do this closer to where your users are.” Where do you think we stand with cloud computing? Right now, if we’ve gone through phase 1.0 of the cloud, are we starting to see some new interesting things come out of this?
Ben Book 05:23
Yeah, I think in terms of the cloud, there’s been a big shift for enterprises to want to leverage the cloud. Specifically with issues like COVID, where companies need to meet and need to be more agile. But essentially, enterprises want to get out of the business of running IT, right? So they want to be able to move something from on premise in their own data center. Get out of the data center business and really allow their people to do what people do best. Which is innovate and build new services, instead of managing a service.
Ben Book 05:56
So that’s the big thing that most companies want to do when they move to the cloud. And then they want to think, “Okay, now we’re in the cloud, how do we access higher level services like chatbots, like DevOps, like container services to make things more efficient?”
Ben Book 06:08
A lot of companies have tried to do this lift and shift thing. The problem with that is it most enterprises aren’t familiar with the cloud. The understand that it actually is more complex to have a cloud environment sometimes than having something on premise. And then they typically don’t have the talent to manage a lot of that when it moves to the cloud.
Ben Book 06:26
There’s an idea that it’s easier to manage things when it moves to the cloud. It’s actually harder in many cases. So now everyone’s — just like you said: the third inning, fourth inning, seventh inning, ninth inning — where are we with cloud, we’re kind of in the third or fourth inning too. Companies have moved to the cloud and they’ve had a good experience. Or they had a bad experience and move back on prem. Now they’ve said, “Okay, let’s look at edge. And let’s think about some of the use cases we want to do around edge.”
Ben Book 06:51
Back to the point about Snowflake and Zoom, it’s so much easier to innovate and so much easier to start a company using cloud, right? You don’t have to have a data center to build a digital service. And that’s a huge, huge opportunity for most companies. And that’s what we’re seeing an explosion of startups. Because you can just spin something up with Amazon, Google, Microsoft, and you can be off and running. You can build an MVP and then go raise a bunch of money. And then, be a real player.
Ben Book 07:17
We worked with Snowflake back in 2015, when they came out of stealth. And we worked with them really closely for about two or three years. Before any of the other research companies caught up with them. They just pretty much took the entire market by storm, because they had the best, easy to use technology. And everybody wanted to use it. Nobody was close to them. Because the legacy companies were two to three years behind them, and it took them two or three years to catch up. Now I think it’s getting interesting for Snowflake, because now they have to compete with the legacy providers. But it just shows that a company can come out of nowhere and build a multibillion dollar company with hundreds of millions of dollars in revenue. You cannot have done that before cloud. You’d have to build a data center, you’d have to get a network, you’d have to build the security. So cloud has really leveled the playing field for innovators and people that want to start new companies.
Ben Book 08:04
And then for enterprises too, it allows them to be more agile. Allows them to be more flexible. Allows them to try new things and know that not everything is going to succeed and not have to put a huge investment into it. So it’s really just essentially created that ability to be agile. The ability to free up your people from managing a storage instance. To using that resource to help you build the next generation product. And that’s really what most CIOs what most CEOs want their IT team to do. Don’t be the janitor of your data center anymore. Use technology for business advantage. So again, we can get that software valuation.
Simon Erickson 08:41
Yes, very true. Do you see that there’s a preference for any of the cloud service providers and the ecosystems that they have? I mean, Amazon was obviously one of the first to really develop this space. But are customers and large enterprises preferring one of those over the others?
Ben Book 08:56
Yeah, I think most enterprises have a large service provider that they work with. And that has typically been Oracle and Microsoft and IBM and Amazon. That depends on the legacy that they have with those companies. So if you have the traditional Oracle’s IBM’s, the Microsoft’s, you know, they have a customer base that will likely stick with them through this transition. And then you have the new players like Amazon and Google that are coming in. Who are attacking the market to look for new customers. Amazon’s done an amazing job building new services and kind of going after a market that was untapped before. So just like we just talked about Snowflake, Amazon essentially said, “Hey, we’re going to go after the non huge enterprises, because there’s actually more of those in the world than there are large enterprises.” They did a really good job with that. They also were able to get a lot of the startups to use them. Now they’re trying to get back into the enterprise game. So they’re trying to go backwards to the legacy companies who were using Oracle, IBM, and Microsoft. And Google is looking for new customers, new workloads. I think they’re not as enterprise ready as Amazon and Microsoft. They’re still very focused on a couple of specific niches that they want to win. Like AI, for example. They do a lot of investment there. Kubernetes, for example. And Microsoft is the only company who bridges those gaps. Microsoft has a huge ecosystem. They have a huge partner ecosystem that helps sell them. They work with large enterprises, they work with mid markets, and they’re also capturing new workloads. So you have kind of the the Amazon and the Googles, who are still trying to get back into that enterprise worlds. You have the legacy companies trying to fight off Amazon and Google. And you have Microsoft sitting in the middle, who can play both of those because they have the legacy customer base. And they’re still innovating. Not always at the pace that Amazon is. I think Amazon certainly is innovating faster than Microsoft in many cases. But Microsoft’s right behind. And that’s always been their strategy. And that’s allowed them to always be a really successful company in all these spaces.
Simon Erickson 10:59
Yeah, so those existing relationships that they have are, in fact, sticky with the enterprise. But there’s also some advantages to being cloud native, like you mentioned earlier.
Ben Book 11:06
Yep. Yep. Exactly. Yeah. So I think Amazon is still going to be number one. Microsoft number two. Google number three. Oracle, and IBM will just stick around with their customers. They’re just not spending the amount that they need to spend. They’re not innovating. And to be honest, they just don’t have the culture that a lot of these other cloud companies have, in terms of the speed that they move. If you look at the way that Amazon and Microsoft and Google innovate and they constantly are delivering new services and the way that their teams move. They just move at a much faster pace than IBM and Oracle. Because that’s also what their customers are asking for. So it’s really a customer need. And as well as staying on top of the market.
Simon Erickson 11:48
Ben, another topic that’s gotten a lot of attention in recent years is artificial intelligence. Which we’re kind of progressing from that being the buzzword to “machine learning” being the buzzword. Deeper into the trenches. But you know, we’re seeing you can do some really neat things with this. Train your data centers to label data. We’ve seen GPUs explode in popularity for parallel computing. We’ve seen self driving cars, image recognition, video rendering. Things like this. But in terms of the enterprise, it seems like maybe artificial intelligence is still early in the innings of this ballgame. What are you seeing enterprises really having an interest in artificial intelligence to accomplish for them?
Ben Book 12:26
What we see with most enterprises is they do a bunch of science projects across different applications. Typically, it’s an application that’s core to their business. So for example, we worked with TransLink, which is a transit authority in Vancouver. They picked an application that allows people to track when the bus is going to come. And so that’s one example. Johnson uses it for their HVAC data. We just did a case study on a hospital ORs and how they’re using computer vision to be able to track surgeries.
Ben Book 12:58
So picking an application and then trying to figure out how you can essentially apply automation to that problem. AI right now, and the way machine learning is set up, is really just to take in a lot of data, make decisions on that data, and then output some data. It’s still not this general AI thing that a lot of people talk about. And so most enterprises are going to do a couple science projects. They get a couple wins under their belt. And then they’ll production-realize it, and then they’ll go to the next application, then they go to the next application.
Ben Book 13:29
I think the interesting thing about AI and ML is that most enterprises know that it’s going to make an impact for their business. There are verticals that have been doing this for a long time, like finance. Finance has been doing this. Insurance has been doing this. I think some of the the newer entry levels for AI and ML across industries are things like healthcare and the traditional, we’ll call them slower moving industries, because of governmental regulation. Or other larger issues. Retail is now trying to move to e-commerce. There’s a lot of AI and ML in the way that you personalize things. So you know that there’s going to be a huge mainstream adoption of AI. I think it started about a year ago. And we’re going to continue to see that.
Ben Book 14:13
We did an AI event about five years ago, and it was still very nascent. People are still trying to figure out what it meant. Now everyone’s done a couple projects, and they kind of have a feel for what it’s going to do. And then the question is, how do you operationalize it using data tools and data scientists? But again, people want to…you don’t have the infrastructure and have the technology to do the automation around it. So you don’t have to have the data scientists to do it. There’s not enough data scientists in the world. There’s not enough cloud engineers in the world. There’s not enough data engineers. So these cloud companies, these software companies are providing that kind of layer to manage the the messiness of all of these different applications once you stand it up.
Ben Book 14:54
So if you look at the web scale companies like Netflix and Twitter, they just use open source stuff. And no enterprise could have a team of 200 open source engineers to build something for their application for retail financial services. Companies would invest in that stuff because they have the people and the resources. So now we’re hitting the mainstream that can purchase technology in a box, as we like to call it. You know, the mainstream likes to purchase things in a box. They don’t want to like tweak with it and hire a bunch of really high profile engineers to build it out. So I think that’s one thing we’re seeing at the implementation layer. But also higher level up for the the enterprises who are seeing business value. And some business values like 4% or 5% ROI. Sometimes you can see a really dramatic ROI of like 25 – 30% for ML and AI. And that’s really when CEOs get excited about that stuff.
Simon Erickson 15:46
And it sounds like a lot of those enterprises are learning more about how they can use AI, right? It was for standard functions, like you mentioned, finance and things like that. But now they’re realizing, “Hey, we’ve got some unique data. Maybe the science project should actually be implemented on a commercial scale.”
Ben Book 15:59
Correct. Yep. Exactly.
Simon Erickson 16:01
Yeah. Very interesting. Are there any other bottlenecks? I mean, you said there was a shortage of data scientists and a shortage of people that can do this work. And probably just an overall education of what AI can do. Are there any other bottlenecks holding this up, on how the Enterprise’s is deploying AI today?
Ben Book 16:17
Yeah, big one is data. A lot of enterprises have lots of data, and it’s everywhere. And it’s messy. Sometimes they don’t know where the data is. So just wrangling the data has been the first step. Essentially, while everyone has been working on their little science projects for AI, they’ve also been trying to get their data in order and figure out how they can get their data in order so that they can take advantage of AI. Again, enterprises are still in the second or third inning of that, they might be in the fifth or sixth inning of building AI workloads and really doing their science project. But to be able to production-alize it. To do it at scale, you have to have the data infrastructure. Which is why these companies like Snowflake and other companies in the data space, are really growing rapidly. Because customers need to put the data in somewhere that they can access it.
Ben Book 17:04
And so in cases, you want it to be in a structured format. You want to put it in a database. You want to put it in a data warehouse. You need to have it in a place that is accessible and usable. You also have data lake companies, like Cloudera, Teradata, Microsoft. All of these companies. And specifically in healthcare, you’re seeing a lot of this. A lot of the data is trapped in PDFs. It’s trapped in a doctor’s note, right? I mean, that’s a great example. It’s not always just trapped in a database, somewhere underneath someone’s desk. It’s actually trapped in like something that’s unstructured.
Ben Book 17:39
So the big initiative now is how do we get the data out of a PDF? How do we get it out of an EMR? Once we can get it out of there, then we can do something with it. But because a lot of these industries are still very paper based, even finance, it’s really hard to production-alize that data. So that’s what I’m excited about. For example, healthcare for a long time has been very siloed. And it’s really hard to get all of the different players, the pharmaceutical companies, the providers, the insurance companies, all to work together. But now we’re starting to see that. These companies are starting to digitalize their assets. Pharmaceutical companies and insurance companies have been a little bit better than healthcare systems, because their business is built on the data. But once healthcare systems can really start to bring that data to life, that’s where it’s going to get exciting. And I think a lot of enterprises are there.
Ben Book 18:33
Then even below enterprises, a lot of mid market companies want to do this. And they weren’t able to do it before, because they weren’t able to access this type of technology. Now, they’re able to access it because of cloud services. So you know, it’s a great another example, small and medium businesses and startups can access cloud services. Mid market companies can buy this thing out of the box. They don’t have to have a bunch of open source engineers or data scientists to manage it. They can play with it. And it’s low code, no code — you’ve probably heard that buzzword too. Using things, essentially allowing anybody who can click a button and knows what they what their business needs, can now use technology. And that wasn’t the case five or six years ago. That’s why we’re seeing a huge adoption, not just in the enterprise, but now mid market and SMB, to really be able to use technology. Companies like Twilio, they went after the mid market just like Amazon did. They’re a billion dollar company. The mid market is a huge, huge market. Enterprise is great. And everyone is used to these IT companies selling in the enterprise. But the mid market is pretty big. And it’s a little bit bigger than enterprise, if you look at the whole market. So that’s what’s interesting to see. Is how not just the enterprise leverages technology, but the mid market. Because now it’s accessible via the cloud.
Simon Erickson 19:49
Yeah, so it’s not just a science project anymore at the largest companies that can afford teams of data scientists. It’s actually useful for a smaller company to be able to harness AI now.
Ben Book 19:57
Yeah. Companies who are 10 people or 20 people. 30 people, you know. As long as you have the data, you can plug your data in and the AI will take care of it. Because of all the work that Microsoft and Amazon and Google has done, to find that data and train against their own models. That’s where you get to leverage these super huge hyper scalars at scale. IBM and Oracle and those of the companies still haven’t been able to get to that scale, because they’re still focused on the enterprise and the specific enterprise help. And selling consulting services to the to them. They haven’t gotten to the scale that Microsoft and Amazon and Google have. And that’s what’s going to allow them to succeed in not just the enterprise, but the mid market.
Simon Erickson 20:39
That’s great points Ben. One perspective I’ll add to that to that, I think, that’s also a bottleneck for a lot of this right now is there’s this huge supply shortage with chips. High performance chips are needed for these AI workloads, right. It’s not so simple that they can just go and run this on any kind of processor you want. We’ve kind of seen this transition for several years now: CPUs to GPUs because it could run things in parallel. Which is much more efficient for AI accelerators for doing these workflows. Workflows are really difficult. But now we’re starting to see even some more exotic chips, right? Liike ASICs. We’re starting to see FPGAs. Stuff like this that wasn’t getting a whole lot of attention. It was just more for people that were tinkering and want to do all this engineering and play with these things. Now they’re actually deploying at scale. And it’s really interesting to see the shortage of the foundries now. The global foundries and the Taiwan Semiconductors are these kind of players of the world. How backed up they are from the demand of companies that are saying, “Hey, we want to use AI. This requires a boatload of processing to do.And we need to get a little bit smarter than just the typical processes we used.
Ben Book 21:38
Yeah, we’ve been covering AI in data centers for about 12 years now. And the challenge with data centers and the chip companies is it requires a lot of investment. Just what the Googles and Microsofts and Amazons we just talked about, you’ve got to build data centers, multibillion dollar investments. And there’s only a small number of companies who can make that type of investment. Like an Intel, for example. And then you have companies like Nvidia who are building the playbook or the blueprint for the chip, but they don’t actually don’t manufacture it. And then that’s up to the manufacturer or the engineer to do it. And then you have the companies like ARM who’s very similar to Nvidia. Where they essentially give you the blueprint. So I think that the interesting thing in our industry is, what are companies doing with chips? Yeah, they’re buying GPUs and they’re trying to get more access to those things for AI. But I think the really interesting thing is how we’re applying chips and semiconductors to IoT. IoT is something that we’ve talked about for a long time. And just like with cloud, I think we kind of hit that mainstream about a year or two ago. And also with AI, everyone wants to apply a chip to something right? A chip to your car, a chip to your your coffee mug. I have this coffee mug here. Now, I think I’m now a believer in IoT, because it’s been $150 on this coffee mug that keeps my coffee hot for eight hours
Simon Erickson 23:00
Love it. I want one!
Ben Book 23:02
So I can control with my phone. I can control the temperature. I think it’s, everyone really wants to have that kind of digital experience with everything. And that goes back to digital transformation conversation we’re having too. So I think the thing that will be prioritized by a lot of these chip companies and getting through the supply chain challenge will be, you know, the GPUs and all these things for the traditional things, I think the big need is, “Hey, for IoT, we need a trillion semiconductors.” There’s no way that no matter what investment you make, we’re going to build enough capacity. So it might slow down IoT ecosystem a little bit. But I think we’ll get through it. It’s just going to take a little investment. It’s going to take three or five years to get through it. It always takes longer than we expect. And then the companies who are the largest, like the Intels and Apples, they’ll help us get through it.
Ben Book 23:58
Then the long tail will be the smaller companies. Who then are leveraging those ecosystems. So it’s definitely going to be some very short term pain for companies like automobile companies. Who don’t have that infrastructure don’t have the partners to build that because they haven’t built a partner ecosystem. And they don’t have the manufacturing capacity either. So yeah, it’ll certainly certainly be interesting. But I think IoT will probably take the biggest biggest hit.
Simon Erickson 24:26
Great point. Speaking of things that tend to take a little longer than you expect to get up and running. Let’s double click on health care. You mentioned that so much of this is a doctor’s records in PDFs. And it’s been slow to adopt technology. We tried a couple of years ago to do a nudge with electronic health records and different regulations. Tried to push a lot of these paper patient records to digital ways of doing this. And then we’ve seen kind of Google and now Apple really trying to figure out health care, because it’s a $4 trillion market in America.
Simon Erickson 24:58
What are your thoughts on the big opportunities for health care that are actually implementable? And how does the relationship between hospitals and patient privacy and all of the other complexities of health care factor into this?
Ben Book 25:11
Yeah, so I started my career in healthcare consulting, working with hospital systems and working with insurance companies. So I got first hand experience about why those two parties don’t like working together. And really, the financial implications of that, really with healthcare it’s hard. Because you have all of these different parties and they’re all not working under the same incentive plans, to your point. So you have healthcare systems who want to control the data. They want to provide better outcomes. But at the same time, they want to control everything. And then you have the doctors working in the facilities. Who, again, don’t work for the facility. Then you have the insurance company or the pharmaceutical company.
Ben Book 25:51
So the biggest challenge with this is, how do you get everyone to share data, so that you can take better action on the data? So you can have better patient outcomes. I think we’ve seen, to your point with some of the hospital initiatives, over like the last five to 10 years, pushing this ecosystem to consolidate a little bit so that you can get more sharing of information. That didn’t actually happen. All he did was get consolidation. And then these companies just got bigger, and it got harder for individual practices to operate because then they didn’t have as much leverage with the big insurance companies, etc.
Ben Book 26:26
But now we have more centralization with these different parties. So the question is, how do we still incentivize these parties to work together? At the end of the day, hospitals want to decrease costs. Insurance companies want to decrease costs. They’re on the same initiative there. So I think if we can get these two parties to be incentivized, again, this is very difficult, and it’ll probably still take a long time. But if you can get those two parties to work together to share the data — that again, is locked in all of these different systems — then you can start to get it to feed into the IoT devices. You can get it to feed into the devices that the patient needs. You can get it to track what’s happening in the OR. And give the insurance companies access to that information so that they can help the health hospital system make better decisions, in terms of how they do their care and how they do their claims.
Ben Book 27:17
So it’s still a very siloed ecosystem. And you know, the biggest opportunity is data and in AI. And right now, it’s just within those ecosystems. Hospitals are using it for things like surgeries to make sure surgeries go better. They’re also using it to manage the data associated with customers or patients. And then pharmaceutical and insurance companies are doing a really good job using AI so that they can process claims faster, and things like that. But I don’t see a huge impact on the sharing of data still yet. I think we still have a far way to go on that.
Simon Erickson 27:54
It’s still siloed. So you’re saying they’re using it for certain applications. But it’s not really sharing all healthcare data everywhere? Correct?
Ben Book 28:01
Yep. So you can have an individual patient outcome and you can have a great outcome. But there’s nothing that the insurance company is able to leverage from that and learn from that. And I think a lot of what in the technology ecosystem here in California, in Silicon Valley, it’s all about learning. It’s all about trying new things. And it’s hard to innovate when you’re not sharing, and you’re not collaborating. So I think, you know, we’ll see new models come up like a hospital system work having its own insurance company. That’s interesting because then they can share the data and they can actually be more effective and efficient. So I think, we still certainly have a long way to go.
Ben Book 28:36
But I’m excited about the opportunity with IOT devices in healthcare. I’m excited about using AI on automation and surgeries for better patient outcomes. So there’s always like little use cases everywhere, but nothing huge. And, you know, really mega mega trend for the industry currently.
Simon Erickson 28:55
Yeah, speaking about San Francisco. Do you think that Google or Apple is making more progress in healthcare today?
Ben Book 29:03
So, you know, I think Apple has a leg up because of the way that they use data, and the way that they consume data, and the way that they they access with consumers. You know, Google has Android and they have a lot of devices and platforms in the field. But the way that Google does things, I don’t see them making a long term bet on health care and really enabling it. They have a cloud, which is great. They have an initiative to go after healthcare. But you know, I think it’s really going to come back to the patient and what the patient wants to give up. And I think Apple has has a leg up within on that. So we’ll see how that how that progresses. I know, Google’s tried a lot of things over the years. I think Apple will probably do a little bit better in that game in the short term. I think if Google keeps investing — and again, it’s about an ecosystem and a partnership — so if Google can build partnerships with the healthcare systems and with the providers. The problem is I don’t think a lot of customers trust Google. And patients trust Google. And the consumers trust Google. So I think they’ve kind of fallen into the same issue that that Facebook has come up with, which is trust. And I think Apple has that trust. So if if Apple can exploit the trust, and work with customers to get the data that they need, then they can provide, you know, additional services on top of it. So they each have their own opportunities, but each have their own challenges for sure.
Simon Erickson 30:31
I certainly agree, then, you know, and you saw that a couple of years ago, when when Google was kind of beta testing this with Nightingale. They got embedded with some patient data, and there was just kind of this backlash. We don’t want Google to have access to all of this. And Apple certainly seems to be controlling the narrative of privacy paramount. And I think that, as we’re shifting to devices and consumer facing healthcare, they certainly seem to be in the driver’s seat for that.
Ben Book 30:55
Yeah. Yeah. Google should should buy a company invest in a company that’s not called Google to do healthcare. They might get get a couple things from that.
Simon Erickson 31:05
Yeah, fair enough. Ben, last question for you. Our audience 7investing is mostly individual investors who really want to get a first hand view of the trends that you look at every day. You’re deploying a lot of these technologies. We hit on several of them today. But there’s a lot we haven’t talked about yet. Whether it’s quantum computing or blockchain or any of the other cool stuff that’s out there. Is there anything else that you’re looking at right now that you think is particularly attractive? And bonus gold star points if it’s not something that’s already in the headlines everyone else is talking about?
Ben Book 31:36
Yeah, fair enough. Well, quantum computing is certainly interesting. It’s a long way away from we’re liking the first the second pitch of the first inning or something like that, right back to your analogy. It’s certainly interesting. But we’re a long ways off from that. I think things like just everything in security right now is just exploding. The reason why it’s exploding is because for a long time enterprises, mid market, SMB, again, haven’t been able to access the things that they need, or they didn’t want to spend the money on it. And now they have to spend the money on it, because everyone is getting breached. Everyone’s getting malware, everyone is getting hit from every direction. Because again, they’re building these digital services. So everything in security is super hot. And when you work with an enterprise, they don’t always need a really good reason to buy security. It’s just a mandate, or like, we need to have this thing. So every everything else in technology, it’s what’s the ROI? What’s the TCO? How’s this going to help me get time to value security. It’s like it’s binary. And it used to be, well, we don’t really need it to zero. Now, it’s like, we kind of need everything, and let’s buy it all. So, you know, that’s why every technology company, even a lot of the companies, like DataDog and these kind of newer companies who are coming from different spaces, is all jumping into the security bandwagon. And there’s good reason for that. One, because customers need it and to because they can make a lot more money and have a much larger target addressable market. So that’s where we’re seeing an explosion of in the security space, we’re investing a lot in security. The challenge is also to there’s not a lot of, there’s not enough talent in security, right? So just like with the data space, the cloud space, there just is not enough talent to be able to support the innovation need that we have there. So we’re really excited about security and excited about how enterprises are going to attack it.
Ben Book 33:28
And again, be more proactive than reactive. I think everyone has been reactive in security for a long time. Again, we don’t really need that thing, we’ll deal with it if we have a problem. Now everyone knows how many problems they can have, and how it’s going to really disrupt their business and affect their job. You’d get fired, for example. So everyone is a lot more hypersensitive to it. So they’re trying to, in our industry, we say shift left. Essentially, like put the security in the design versus like, handle the problem later down the line. Solve the problems so you don’t have the problem later, right? So a lot of the companies that we’ve tracked, for example, in the DevOps space in the cloud space, are essentially providing that kind of shift left. Or that ability to be more proactive than reactive.
Ben Book 34:15
In terms of other types of technologies that we’re looking at, you know, we covered data, we covered AI, we covered edge, we covered cloud. You know, I think that this idea around low code, no code, or the ability to use applications and build applications without having to be an engineer. Again, there aren’t enough engineers in the world. You have services now that can give you access to data and be able to manage data. So you know, just up leveling, the ability to use a technology without having to be a technologist is a huge deal. So anyone who’s providing a service like that. And again, Snowflake’s a great example. Snowflake built a data warehouse that anyone can use, and that’s why they’ve gotten so much traction early on. Because all the other data warehouses were very hard to use, and you had to be a DBA or an expert to use. Google, for example, is really good about this. They all of their products are so well designed, it’s so easy to use. So, you know, that’s a huge mega trend that we’re going to see in the application space in the SaaS space. You know, moving forward.
Ben Book 35:15
So I’d say those are two of the things that we’re tracking really closely. And then just on the more, you know, blockchain side. Blockchain, you know, has been around for a while. Everyone has been looking at different use use cases to use again, I think we’re kind of in the second or third inning of the blockchain people have experimented to see what what it can do. We’re writing a report about distributed blockchain with storage. Everyone’s trying to figure out how can I use blockchain to intersect with my technology. So it becomes the underlying platform, because it is pretty cool. No one just had a really good business reason to use it. It was just a technology thing. So those are some of the things that we’re looking at and are pretty excited about.
Simon Erickson 35:53
Yeah, definitely a good list. There have been really an exciting conversation from somebody at the front lines of these emerging technologies. Once again, Ben Book is the co founder and CEO of GigaOm. That is “GigaOm”. You can check out a lot of the great research that they’re doing. I checked out your website. I was fascinated by how thorough and how much breadth you have of information. Ben, it was a real pleasure. Thanks for joining me on the podcast this afternoon.
Ben Book 36:18
Alright Simon, thanks for having me.
Simon Erickson 36:20
And once again, thanks for tuning in to this episode of our 7investing podcasts. We are here to empower you to invest in your future. We are 7investing.
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