Brought to you by VANTIQ
Episode 21
Cities are Sinking
Cities are sinking under a flood of real-time data, IoT devices, and competing priorities. Smart City initiatives – if conceptualized properly – can help. Join Smart City expert and consultant Daniel Obodovski in a discussion about the future of cities and how they will achieve it.
Chief Marketing +

Product Officer, VANTIQ
Founder and CEO at The Silent Intelligence

Blaine: Joining me today is Daniel Obodovski, Founder and CEO at The Silent Intelligence. I’ll let Daniel tell us more about The Silent Intelligencein a moment, very intriguing name. But, before we do that, I’ll also mention that Daniel is an Internet of Things thought leader and a frequent keynote speaker. We have had the pleasure of speaking at the same event a number of times in the last couple of years which is how we first met. Prior to starting The Silent Intelligence, Daniel worked as Director of Business Development at Qualcomm. After leaving Qualcomm in 2013 he authored “The Silent Intelligence: the Internet of Things“, one of the first books about the upcoming technology revolution that we’re all in the midst of right now which the following year became a Top 10 book on technology and investing on Amazon. Thanks for the time, Daniel. We’re gonna have some fun!

Daniel: Thanks a lot, Blaine!

Blaine: Well, I really appreciate your time. I’m very glad we got this opportunity after speaking off and on for the last couple of years. Why don’t you start by telling us more about your firm, The Silent Intelligence, a very intriguing name. If I was naming a company now, I’d probably go for something exciting and interesting like that.

Daniel: Thank you. I’ll tell you a little bit about the sound challenges. I’ll tell a little story on how we came up with the name.The Silent Intelligenceis a professional services firm focused on digital transformation of enterprise. Essentially, what we mean by that is we help companies not just deploy technology, but also understand the problems that they’re trying to solve using technology.

We help them think about how to extract the value from the data they already have and from the data they’re going to have by implementing technology. Extracting value can range from direct monetization through third parties to developing services that are going to help them optimize their costs or optimize and generate new revenue services.

In addition, we work with technology companies to help them commercialize technology. That’s actually my background primarily is commercializing technology. Back in the time when I was at Qualcomm, my job was to look at interesting technologies that were coming out of either corporate r&d or another part of the company and built an ecosystem and built partnerships, found customers to actually commercialize those technologies.

As you know, a lot of companies these days operate on technology looking for a problem. That’s okay. In a lot of cases, technology is being developed based on technology capabilities, not necessarily what problem we’re trying to solve. But, at some point of time, somebody needs to think really, really hard, “What are the problems we are going to want to solve with that and how does the technology align with that problem and the use cases?” That’s where we come in.

Blaine: Very interesting. How did you personally get into this space, this combination of bringing technology to bear on solving business problems? What’s your story?

Daniel: To be honest, it was a long and painful path because for a professional services firm, figuring out product market fit can be also a very painful process. But, ultimately, when you zoom in on your clients and you start understanding what your clients are paying you for, what they value the most, you start adjusting and you start changing your approach. I used to work at Qualcomm and before Qualcomm I worked at Motorola. I would say I had a very heavy hardware/networks background, thinking of the world in terms of sensors, boxes, connected devices, and connectivity and so on.

When I started thinking about working on “The Silent Intelligence” the book, the book came out five years ago and that thinking of me being a semi conductor guy, a hardware and connectivity guy, very heavily influenced that book.

Have you seen the TV show called “Halt and Catch Fire“?

Blaine: Yeah I loved it! An amazing show. Recommended to anybody on the podcast here!

IoT is not this thing. It is the thing to get you to the thing. That was the realization. What is the thing? Is it the data? Not really. We have the spirit we are really heavy on the data, understanding the machine learning algorithms, understanding AI and realizing data is actually not the thing. The thing is: how do I solve a set of problems in my enterprise? Whether it’s improving my customers metrics and KPIs by the way they run their business, improving my own workflow processes reducing them from months to hours, or whether it’s something else.

Blaine: Or whether it’s fundamentally creating new business models, transforming the organization in some critical way, right?

Daniel: Very true. Very true. Although, we would like to say there is a finite amount of business models and they’re just being applied in a different way.

Blaine: Very good point. Most digital transformation or disruption initiatives aren’t creating something totally new, but it’s the Uber of something or something like that.

Daniel: Yeah. Very true.

Blaine: That’s actually probably a good segue into a little bit on your data monetization work and background. I want to talk about smart cities for sure. But, you talked about the value of data and being able to take advantage of the data that is flowing in and around your enterprise and your organization. Enterprise data monetization has a soft spot in my heart because I used to run products and marketing for a company in that space. I’d love to know where you think organizations are at these days in terms of truly being able to derive all the value and fundamentally even monetize the data that they’re increasingly gathering.

Daniel: Today, we’re at very, very early stages. I would say certain industries are further ahead and certain industries are behind. If we take retail, retail has actually been doing some form of data monetization for years, before IoT and so on. At least mentally they understand the value of data. They don’t necessarily have the right systems in place. They don’t necessarily have the real-time data in some instances. But, at least mentally they understand the value of data. And plus, retail, based on the margins, they are squeezed so hard right now, there’s a lot of willingness and an interest on figuring out how do you monetize data.

Now, the other area that’s been going on data monetization pretty fast I would say is transportation logistics starting with fleets. I’ll give you one example. There’s this new type of animal which is called “data brokers”. There are several companies that have been emerging and trying to be a data broker.

Without going into specific names and going how much money they raised, just in the ballpark, some kind of a generic data broker companies that you have seen that kind of approach multiple verticals, they today raised less than 10 million dollars each. They’re still trying to figure out how they’re going to scale, how they’re going to grow. If you go to transportation logistics and look at the data brokers in that particular area, they’re more like 40-50 million dollars raised to date.

Blaine: Give us an example of what kind of data they would be brokering. Take us down another level of specificity so we know what use case they are fundamentally solving.

Daniel: If you just start with fleets, delivery fleets or trucking, basically, we have three types of data that comes out of the vehicle. One is vehicle related, asset management related data, engine related data, tire pressure, basically the health of a vehicle as an asset. That’s the first type of data. It usually comes from either OBD2 or any other type.

The second set of data is the driver related. By the way, that’s not order of priority. That’s a deployment of ELD devices, electronic logging devices, which actually the primary function was to monitor hours of service. They are not always as accurate as we would like them to be, but that is what they do. What information does it give us? It gives information of asset availability. Does that driver have enough hours left that they can be utilized or not?

There’s also other driver-related data that we can collect which is the safety track record of the driver. Are there any issues that we need to be concerned about? Are there any things like how we can take care of the driver so they can do their best work? Is there any semi-autonomy functions that can make their job easier so they don’t have to pay attention to as many things happening at the same time and don’t get distracted. This is driver related stuff.

Finally, the third group of data is cargo-related data: what’s inside the vehicle. That’s where we start looking at the position location, temperature difference, which batch it is, where it’s supposed to be, if it has been loaded/unloaded, chain of custody, so on and so on. Different players have access to different parts of the data. If you’re a telematics company right. You have either you own ELD device or you have a software platform utilizing third party ELD device. You have a lot of that type of data and you have the driver-related data.

Now, in some cases you also have access to the engine data. In some cases, you don’t. You have all those sets of data. What it comes down to is what problem we’re trying to solve. The problem we’re trying to solve is how do we manage capacity better. How do we improve the safety, perform track record of fleet? We look at the things like how can I forecast demand. I can manage capacity, but it’s usually a retailer who has the insights into the demand not the carrier.

So, the shipper has the demand data but the carrier does not. That puts them into an unfair situation in terms of price negotiation. How can they use some of the data that we just talked about to have a better visibility into demand forecasting? Those are some examples.

Blaine: And you’re saying, though, there’s a category of companies, a brokerin the middle, which is orchestrating, literally, the sale of these data streams back and forth between these players?

Daniel: Yeah there are several companies in this space who have basically just been buying data and selling data and making money in the market. They haven’t necessarily figured it all out. They’re basically saying, “OK. There are people who have data who don’t know what to do with it. We’re going to buy their data. And there are people who need data. There are shippers who need the data. There are some carriers that need that data. We’re going to sell it to them and we’ll let the market decide over time what the pricing should be, as long as we’re making margin.”.

If you’re somebody who is selling your data to the broker, you might ask yourself, “Am I getting a top dollar or not? Am I really thinking about the value of my data, not basically just putting it on the market and letting the market decide what they want to pay for it?” Depending what your strategy is and depending on how many resources you want to allocate, you might decide that you would much rather sell your data at a premium because you understand what value it provides versus just putting it out there and letting somebody else decide how much they want to pay for. That’s different in strategies, strategies we advise our clients on.

Blaine: Now is this data real time yet or are we still really talking about batch data, daily logs of what a vehicle did or what was shipped yesterday, not actual real time data? Where are we in terms of making this ecosystem real time?

Daniel: As you know, real-time data comes at a cost. It could be a connectivity cost. It can be data volumes, data storage, and so on. That’s why we’re increasingly seeing more things handled on the edge. It’s not necessarily the real-time data you need. It all depends on the use case that you’re trying to solve.

If your edge gateway that you have in the vehicle can get rid of a lot of unnecessary data and just get to drive your KPIs and running your metrics, it’s good enough. Because, while seller connectivity is pretty low cost, in some cases you might use satellites. Satellite is more expensive.

You need to think about all those factors when deciding if you really need real-time data or not. But, to answer your question, in some cases we can get access to the real-time data. The question is: do you really need it?

Blaine: Well, Daniel what was a very interesting discussion. Actually, you didn’t even know we were going to have this discussion because my original talk with you was going to be about smart cities.

This notion of data monetization and the impact of real-time data is so relevant to what we’ve been talking about here I thought it was worth surprising you with that topic so great job!

Daniel: As you can tell, I’m super excited about that. It’s one of my favorite topics thinking through that and working with our clients helping them think through that the same way.

Blaine: Excellent. Having said that, I want to shift gears now back to discussions we’ve been having especially over the last couple of weeks. We were actually recently at a smart cities event in the last couple of weeks. I’m really interested in learning more about what you are up to in the area of smart cities. Then, let’s talk a little bit more about what’s really going on there.

Daniel: In addition to The Silent Intelligence, about 18 months ago, we started a company in San Diego called ScaleSD(Scale San Diego). Scale stands for Smart Cities Accelerator Labs and Environments. The goal of Scale or the mission of Scale is to bridge the gap between technology and urban challenges or urban problems which range from traffic, transportation, parking, water, energy, but actually also things like helping undisturbed neighborhoods, addressing problems like homelessness, or digital transformation of the city of overall. You’d be surprised how many of these areas can be solved with – let’s put it this way – not solved, but dramatically improved with data, with utilizing/analyzing data, applying machine learning algorithms to the data as the data volumes grow.

Blaine: I wouldn’t be surprised, but I bet some would! [laughter].

Daniel: Being a data company, yeah totally.

The thing is, what we quickly realized is the city has data coming at them with such a speed, they just don’t have the capacities or capabilities to handle all the data. Just think about that. They have the open data portals. They have the existing data that’s coming at them from whether it’s digitization of permits or blueprints or maps, financial budgets, stuff like that. But then, now you have the IoT data, all the sensors, and that’s just growing exponentially.

Right now, it’s been estimated about 20,22,23 percent cager of data growth a year. We’re going for over 30 percent cager. Basically, the volumes of data are doubling every two years. You’re trying to pour water out of the boat, but more water’s coming. If nobody’s helping you, you’re just going to sink. And that’s unfortunately what’s happening with these cities. Cities need a lot of help not only processing data, but more importantly, how do you apply this data to the urban challenges they have today which are very analog. They don’t have an obvious technology solution if you look at them. That’s the mission of scale.

Blaine: What are they doing about that? You just posed a big problem statement: the cities are sinking. They need to apply this ever-growing mountain of data, increasingly real-time data to solving fundamental urban challenges. So, what is the answer to this conundrum or what are cities actually doing?

Daniel: Let me actually felt a little bit more into that conundrum. Let’s say a city deploys a system. Maybe it’s a sensor system, maybe it’s a software system or something like that. Because everything is transparent and city finances are transparent, people ask, “You guys just spent 20 million dollars of our money. What are we getting for it, we the citizens who live in the community, who live in the neighborhoods? You guys could have spent that money on improving that school are like giving to the school district or building a hospital. What are we getting for it?

That’s a tough situation to be in unless you have a well-defined answer. Unless you understand, “Here’s how it’s going to improve your lives. Here is how it is going to improve the lives of communities. Here’s how it’s going to generate new jobs. Here is how it’s going to improve the traffic, which ultimately is going to save you time when you go downtown or when you go to certain areas. Here it is going to reduce your time looking for parking. If you are an owner of a retail store downtown or somewhere, here’s how it’s going to improve the traffic to your store.”

Those are the answers that cities need to formulate. Somebody needs to help them think about how the data that I have today and the data that is coming my way can be utilized to solve those problems and how we can build a story that they can take back to the community and say, “Here is how we are helping you guys, ultimately.”

We at ScaleSDare joining the communities together. Anybody who cares about urban innovation and also has a certain set of skills and talent that they can utilize is universities that we have here, UCSD and SDSU. There are a lot of groups that we have in the city meet ups that have people that are really eager to build something, but they don’t necessarily understand what problem they need to solve and don’t necessarily have the technology tools.

The trick about smart cities, even though a lot of problems are similar, a lot of things are defined by the communities and a lot of priority is defined by the communities. If you are from this community and you have the data science, AI, solution engineering, design thinking, or social entrepreneurship skills, you can apply those skills onto your local problems utilizing the best technology that is available. That’s how we bring all these parties together.

What we would call the Smart Cities Accelerator, Labs and Environment, environment is bringing the community together which we do in form of events, workshops, hands-on workshops, reverse-pitch competitions, innovation programs, hackathons, and so on.

Blaine: So, how long do you think it will be before, say in this particular initiative, that San Diego starts to see a real, concrete value? I think a lot of folks listening to what you’re saying might say, “Wow, that sounds good, bringing the communities together, all good.” But is this going to be 20 years before somebody in San Diego actually sees something concrete as a result of this initiative?

Daniel: That’s an excellent point, Blaine. I think things are happening a lot faster than they used to. Things are happening very, very fast. The amount of things you can produce for that short period of time with the newest tools and technology is amazing. I would like to mention the program that we’re starting in San Diego which is we are partnering with US Ignite on the smart gigabit communities and with the city of San Diego on bringing about solutions to a set of problems.

That’s why we’re partnering with technology companies. We’re bringing in technology companies, actually more of an ecosystem approach; networks, connectivity, edge gateways, sensors, but very importantly, data companies, companies that can help analyze data, visualize data, apply algorithm to the data. We’re helping them to understand what problems there that need to be solved and how they can actually implement those things, not just build them, not just pilot them, but actually implement. They align with the city priorities. They align with budget, not necessarily city budgets, but other partners’ budgets and how these things can be implemented.

Blaine: Have you aligned on any specific use cases yet or are you still in the ideation phase for how you might use this ecosystem of companies and universities and partners together?

Daniel: We actually have quite a few use cases.

Blaine: Give some examples.

The interesting thing about cities is almost anywhere you touch, there’s an opportunity. One thing is digitization of underground data, underground mapping data. There’s this thing in California called DigAlert. Today, if you need to do digging, you need to call DigAlert and within a certain amount of time, you will have a guy or gal with a can of spray paint who is going to paint on the ground where you’re not supposed to dig. 21st century. Right?

As it turns out, a lot of this data is available. They’re not in one place. The city has data on the underground piping and sewage. They have the data on the water or piping. You have the utility energy data. You have the telecoms. They’re just all in different places. There’s no one place where you can have it. Some of it I would call semi-digitized. By semi-digitized, I mean it’s in a PDF file. Basically, creating a map, an aggregate map where within seconds, you can have a pretty good idea whether there’s something underground where you are at. This can save a lot of hassle.

The other thing is adaptive transportation. How do you shorten the time of an emergency vehicle after they get an alert? Today, they’re operating on 80s technology. They beam a strobe light at the traffic lights to make it change the light from red to green. That’s what the emergency vehicle does today. Again, we’re in the 21st century. How do you think a little bit further ahead? How can you clean up the street ahead of time and route an emergency vehicle throughout the city from point A to point B more proactively and shorten the time it takes?

Another example: when there’s a major event in the city like a marathon or any other type of significant event, how can you ensure they can still get from point A to point B without taking three hours. There’s a lot more, but those are just some examples of the use cases.

Blaine: Makes perfect sense. One of my final questions on the smart city topic is who are fundamentally the drivers of smart city initiatives in your experience? Is it city CIOs? Is it the politicians? Who’s really trying to drive this or make it happen? Who’s instigating these initiatives?

Daniel: I would say it’s somebody who cares. Whatever the title of that person is secondary. It’s somebody within the city who deeply cares about their city and community and also thinks innovatively. This can be a CIO. It can be the Chief Data Officer. It can be the Head of Performance and Analytics Department or it can be Chief Operating Officer or can be Head of Economic Development or Head of Sustainability Department. Or, maybe all of these people. But, there’s somebody who really, really, really cares and wants to drive it.

Blaine: It’s interesting how you didn’t list any politicians on that list, though. These are organizational executives in functional areas, but not the mayor or the councilmen. What’s their role in this in your experience?

Daniel: I think their role is very critical. But, I think sometimes you need to help them connect the dots. What I mean by that is, again going to the where we started, it how is it going to help the communities? Ultimately, the mayor and the city elected officials and they serve the community. They need to have a very, very clear understanding how this system we’re thinking about deploying or redesigning, what not, how is it going to help the community. It needs to be very straightforward message for them to communicate. You understand that. Then, you meet and talk with them and I think they’re very responsive to that.

Blaine: Interesting. Makes a lot of sense. Well, this has been a great conversation. Let’s wrap it up with a few questions that I ask many guests. First of all, is there an area of conventional wisdom that you would just like to call bullshit on? Most people are thinking X, but you actually think Y is the right way to go. What’s that area for you?

Daniel: I try to read less. I try to cut out a lot of noise. I used to be trained to follow every single article that’s coming out. Over time, I realized it’s been counterproductive for me. I read a lot of books. I read both technology books and business books. I also like talking to people, our clients, partners, mentors, and so on. I find if I just cut down a lot of posting and reading a lot of articles and just reduce it to a minimum, yeah maybe I didn’t know that the latest thing that happened. By the way, I also read a lot of financial reports. I do read earnings report. Those are the things that I read. Sometimes, you learn a lot more from those than from reading a lot of articles. So, I just try to stay away from reading [news articles]. I only have one newsletter that I read.

Blaine: So, you’re calling BS on the notion of embracing the digital flood, just trying to keep up with everything and read everything, you’re saying “no” to that.

Daniel: At least for me, it as has been totally counterproductive. I like to take a step back and shut down the noise and hopefully, start seeing a lot better. At least, it’s working out for me.

Blaine: I think it makes a lot of sense exceptfor VANTIQ TV. VANTIQ TV is definitelya valuable source of information and insight from experts like you. [laughter] But other than that I agree, shut her down. I’m with you Daniel.

Any technology or business predictions for 2019 or maybe about the intersection of technology and business?

Daniel: I’m actually fairly bullish on blockchain. I think it’s going to take longer time than people anticipate. I think it has a huge potential. I think there are certain problems that need to be ironed out in terms of protocols and data acquisition for blockchain. But, in transportation logistics and global supply chain, it has a huge potential.

Blaine: The interesting thing about that prediction is about half our guests so far have used their call bullshit opportunity to talk about blockchain. There’s a lot of fud and a lot of bullshit out there as well about blockchain, of course definitely about crypto currencies for certain. But, obviously you’re not talking about bitcoin or crypto currencies. You’re talking about the fundamental blockchain distributed secure ledger itself.

Daniel: Exactly. If you look into the technology and even with a bitcoin, bitcoin exists completely in digital reality. When we start thinking about global supply chain, if you want to track the food supply or the origin of mangoes, one of the favorite use cases that people talk about, they’re physical. They are not digital. You have this gap into how do you ensure that the data that we’ve captured about this mango or the batch of mangoes is accurate? The moment it got on blockchain, I know it’s accurate. Now I know there’s data integrity.

But, when somebody was scanning that barcode or reading the RFID tag, can you ensure that piece of the data integrated at that level? Like I said, there are certain things that need to be figured out, ironed out and there’s people looking very closely into those and the conversations that we are having.

The potential of block chain in traceability for just the food industry is really [promising].

Blaine: Well thank you for that. Let’s wrap it up with any key takeaways or tips you might have for business or city leaders that are trying to drive the digital transformation of their organization.

Daniel: Look at the problem you’re trying to solve. Understand the problem you’re trying to solve. Understand the use cases of that problem and only then think about technology.

Blaine: Don’t start with technology?! [kidding] Yes. I get it. And I think that’s very wise advice. Well, Daniel that wraps it. Thank you so much for joining us today. It was a great conversation.

Daniel: Thanks, Blaine, I really enjoyed it.

Blaine: You bet. Those interested in hearing more of Daniel’s thoughts should check out You can also follow @silentintellon Twitter. Finally, check out ScaleSD.comto find out more about the San Diego smart city initiative that Daniel was talking about. Once again, thank you Daniel.

Daniel: Thank you!

Blaine: You can reach out to me anytime at [email protected]

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