Jonathan Rosenthal: 0:04

Our system, our platform looks at this very differently. It's not a ledger based system. It's a location based system. And so we look at that and then we apply location intelligence to give predictive analytics. Whereas every other system is a ledger based system. It's looking in the rearview mirror.

Tom Raftery: 0:32

Good morning, good afternoon, or good evening wherever you are in the world. This is the digital supply chain podcast, the number one podcast focusing on the digitization of supply chain. And I'm your host, global vice president of SAP. Tom Raftery. Hi, everyone. Welcome to the digital supply chain podcast. My name is Tom Raftery, with SAP and with me on the show today I have my special guest, Jonathan. Jonathan, would you like to introduce yourself?

Jonathan Rosenthal: 0:59

Sure. My name is Jonathan Rosenthal, I'm the CEO of ESP logistics technology, which is inspired by the ESRI Sabre partnership. And I live here in Los Angeles, but we're a global business. And I've been in logistics business and supply chain for a little over 30 years and focused on information technology and and hardcore functional operating businesses in supply chain.

Tom Raftery: 1:28

Okay. And as you said, you've you've been in this area for 30 years or so. But with some significant experience, can you talk a little bit about some of the the bigger stories you have, from your your history and supply chain?

Jonathan Rosenthal: 1:46

Yeah, sure. So I look at supply chain and logistics in particular, you know, people, you say, logistic, you're in the logistics business and people right away think, oh, trucking and warehousing. And we don't think of it that way. So we're, we're really a combination of logisticians, and data scientists, information technology people. And we think of logistics as any asset that moves within a network. So we don't, we don't care that that asset is a truck, or a trailer. So we have done a lot of work in the airline business, for example, the asset there is an airline seat, it moves through a network. And so when when we're looking at an airline, when we're investing in an airline and trying to help an airline reorganize, we're always thinking about, how does that see move through that network? And how can we reduce systemic impedance or friction. That's what it's all about. It's all about trying to maximize the utilization of the underlying asset, minimize the amount of infrastructure, it serves the network. So that's what we're focused on. So again, we've done airlines, we've we've been heavily involved in utilities, most people don't think of the utility as a as a logistics system. But it really is, it moves an asset, the asset happens to be an electron, and it moves through our network. And so what you're trying to do, you're trying to reduce the cost of moving those assets, you're trying to minimize the amount of assets that you have to input into the system to get the required output. So you need to think about this in terms of flow. As opposed to GE, I run a trucking company. And so now, having said that, about 10 years ago, Tom, we really thought that the freight ecosystem, the movement of freight around the world was very, very antiquated. It was under enable, technologically, so things were very people were using antiquated methods, logistics, they don't, they don't think about it, like like we do. And so we started focusing on that business. Now, in order to make an impact on a system. You got to understand how the system works. And so very, very important. You can't just sit at 30,000 feet as a Information Technology person, or data scientist, you have to understand, how does a truck pick up a container at a port? What happens? How do the union's impact that how do they have How does congestion work? How does that how does that container move from the port to a warehouse, so you really have so we went out and we bought companies in the trucking business. We bought a warehousing company, we operate about five and a half million square feet of warehouses. These are very large facilities and we we own container just tribution centers and things like that. So before tackling the job of fixing data information flow, before fixing that we really wanted to understand how the heck

Tom Raftery: 5:13

Okay, in something like a utility, because this, this is an interesting one for me in something like a utility, how do you reduce friction in the flow.

Jonathan Rosenthal: 5:25

So the utilities job is to deliver either, you know, some kind of asset, so it'll deliver reader water, or it will deliver an electron, or really deliver gas, you know, natural gas. So they got an asset, you're trying to deliver that asset through some kind of network. And so you can find points of friction, it gets a little harder with the utility than it is with the prepping company, you find points of friction by understanding the movement of that asset. So if you can see the movement of that asset, you can begin to focus on points of impedance, if you can't see the movement of the asset, you can't focus on those points of impedance. So I'll give you an easier example. A trucking company, a trucking company, our our trucks, for example, at the Los Angeles Harbor, we have several trucking companies, they pick up containers, our trucks wait in line to get into the terminals, somewhere between two and four hours, our trucks, their dwell time, inside the terminal, trying to find a container is around an hour and 45 minutes. So those are points of friction. And you know, it doesn't sound like a lot. But in a big port, like Los Angeles, you know, you've got about 50,000 Gate loads a day. So you've got trucks waiting in line, it's about 25,000. Trucks moving in and out. So again, zooming out. And so when you compound that, that you see a diesel truck, waiting in line for two to four hours, you're paying for the labor, you're paying for the fuel, and you're not able to move as much cargo. So it's just inefficiency. So there are lots and lots of every network, Tom is going to have inefficiency. And so you're looking for those points of inefficiency, the one thing I've learned for sure, is that no matter what system you're looking at, inefficiency is bad. And efficiency is good. I've not I've not yet found anything about inefficiency, that's good. It's always it seems to always be bad. And I don't even mean that. Critically, I've just not seen it so so you're always looking to make the system more efficient. And in a distribution system where you're trying to distribute something that means being able to distribute the assets you're distributing more rapidly, with less infrastructure with less cost less time. So that's, that's always what we're what we're looking at.

Tom Raftery: 8:52

And I'm just gonna say in a, in a situation that you described there, like the Port of Los Angeles, where the trucks are anywhere from two to four to six hours waiting to collect their cargo. And you know, if, if a truck driver works eight hours a day, that's at least half of their time, just waiting to pick up that cargo. And you know, the the engine is probably idling for that time as well. So as a waste of diesel, it's pollution, it's the whole thing. So that's a that's an identified point of impedance. How do you fix that?

Jonathan Rosenthal: 9:27

Well, it's uh, so. So most people in the business, look at it as an asset problem. That is we need more trucks, we need more highways, we need more terminals. The truth is, we don't. The truth is we have plenty of terminals, we have plenty of trucks, we have plenty of containers and plenty of warehouse space. What we don't have is good information. We don't have good real time information. And the big one of the big problems in the industry is that every one of those nodes along the supply chain, whether it's a trucking company, or terminal, or warehouse or rail yard, every one of those nodes along the supply chain has its own operating system. It has its own software. Those are not in your operable. So those systems are generally ingesting information. That's not enough. necessarily in real time, because it's typically scan information. And so it's only as real time as the scan, right. So you scan something in a warehouse, it's real time for a second, and then two minutes later, it's no longer real time. So one of the problems, I think that in order to make it interoperable, there are a few companies out there who are saying, well, we need to be able to allow these operating systems to communicate, so that the customer, the beneficial cargo owner, for example, can have end to end visibility. So they can see all the way across their supply chain, from from ship to truck to yard to rail. But they're doing this using data that is stale. It always has latency. What we focused on is sense data. So we decided that we're going to do this differently, we think of those scale systems as ledger based systems. So it's ingesting, it's putting it into a ledger. And then it's trying to communicate between ledgers very difficult to do, and always has inherent latency. Sometimes, you know, if you only scan something in a warehouse once a month, it doesn't give you any location intelligence, it just says this item is now in the warehouse. So it's possessory information as opposed to real location, what we've done is we've worked with our partners at ezri, on location intelligence, so this to be it. So once once you look at the it the location of something through sensor technology, so we know that the world is going to be sent and connected, these assets are going to have sensors on them, they already do to some extent that sensor technology is growing very, very rapidly. The price is coming down on sensor technology, the price of data, you know, you've got things like lowers orbit satellites, you've got 5g, the price of data is coming down, because the amount of capacity for data is going up the amount of information so for sure, I think you'd agree top. You know, five years now, the world is going to have, you know, a lot more sensors and sensors up the wazoo. Sensors up the wazoo. Now every one of those sensors is going to be transmitting data of some sort. Here's where I am, here's my temperature, here's my weight, have I been tampered with, you know, it's going to be transmitting some kind of information. And it's doing that in real time with no latency. So what we said is, okay, so the amount of data that's available in real time is going up chromatically. That's what we're focused on. Once we have data about where something is, and how it's moving, we can begin to apply location intelligence. So we can overlay our, or our platform overlays, we have 5300 data layers that can be overlaid, and produce what what in in the, in the GIS world, a geographic information world is called mapping. So we can actually visually seek ingestion, we can visually see weather patterns. So you can we can actually point and click, you can build your own tools, you can say, here's my network. Here are the assets in southern flowing. Now I'd like to see what are the impacts of weather on my system. And you can actually point and click overlay a data set. And it will tell you what the impact is going to be now the what people want. What what you really want, is you want predictive analytics, because it's in supply chain. If I tell you 30 days in advance that you're going to have disruption because you're not going to have enough space. Or you're gonna have disruption because there's not enough trucking capacity by giving you that if I tell you that 30 days from now, you know, 3030 days in advance, you can do something about it, you can figure out ways to solve that problem. We just have an issue here in North America where you know, ships off the coast or you seize the news or pop up and the Burlington Northern Union Pacific Railroad, shut down the rail going to Chicago and they did it very, very quickly. They really provided no warning they had no they had no alternative because the yards in the Midwest filled up with containers and Nowhere to go to. So today, today we have about 20 trains, these are three mile long double stack sitting on a rail outside Chicago. Well, that's a horrible, not only is the container not getting where it's supposed to go, but those trains are tied up. And those trains are part of the infrastructure that needs to bring back empty containers, to put on ships to get back to Asia to get filled with whatever they need to fill. So our system, our platform, looks at this very differently. It's not a ledger based system. It's a location based system. And so we look at that, and then we apply location intelligence to give predictive analytics. Whereas every other system is a ledger based system, it's looking in the rearview mirror. Now it may be looking in the rearview mirror 30 seconds ago, or maybe looking in the rearview mirror a month ago. But it has a great deal of difficulty providing predictive analytics. And that's really the that's the holy grail, the Holy Grail, Tommy is if I can tell you sometime in advance, what's going to happen to your your network add to those assets that you're trying to move. You're it's very, very valuable to you, because you can try to mitigate those issues.

Tom Raftery: 16:57

Okay, and we're in a particular point in time now, it's, you know, October 7, as we record this first week of October. And there's about 70 ships tied up off the Port of Los Angeles at the moment, and many more up and down the coast, both sides. And that's just us supply chains globally, seem to be in trouble. You know, here in Europe procedures, the UK is having horrendous issues. A big part of that is due to Brexit. How do well, first of all, how did we get into that? Because I mean, you mentioned flows of containers to and from China. And suddenly, that's an issue now. But the flows between the two places haven't changed that much I got I think from a year ago, or two years ago, or whatever it was, it's just suddenly this thing has arisen where there's far more containers on one side than the other. And there's a shortage in one side, and there's a, you know, an excess on the other. And, you know, what's brought about all this? I mean, everyone's blaming COVID, and in the UK, they're blaming Brexit, what do you think?

Jonathan Rosenthal: 18:05

Well, it's a, you know, it's a, it's a complex problem. And there's, it's not it's not one thing, you know, we have sort of a perfect storm. It's it's a number of things that I think are contributing to it. But it starts with the fact that we have a very fragile system, the system and has no resiliency. And so anytime something breaks in the system, the system collapses. And it collapses much more rapidly, then it should, because it has no it doesn't have that resiliency. And part of the I think the core problem is this information, we just don't know where things are. And when you don't know where things are, you can't you just can't manage the system where you're flying blind, you know, go into a warehouse, turn off all the lights, and then try to, you know, pack a container, right? Like you don't know where anything is. And that's what we're doing. If you I mean, that's probably not a bad analogy, right? You're hunting and pecking. You go into a terminal, you don't know where your containers are. I mean, you're absolutely right, that today, I'm told we have a million containers off the coast of the West Coast of the US a million containers sitting on ships. Now, when you think that through, and you say, you know, a lot of that stuff is Christmas stuff. And that Christmas stuff doesn't sell very well in February. So that, you know, it's a huge problem. I mean, I think that to some extent, we're now really focused on it. And I think people are beginning to understand that it's an data and information problem. Large largely, and that if we had better transparency, visibility, we can do a heck of a lot better job managing those assets. Would it be perfect? No, we would still have issues. But if you look at the supply chain, and you look back, you know, I don't know if you remember a couple years ago, we had the 100 bankruptcy. So the Hanshin bankruptcy caused, they had about 250,000 containers around the world. In comparison to what we're talking about today, that's nothing but they because the company went bankrupt. They all of a sudden everybody lost this ability. So where's my container, they pick up the phone they call home. And nobody answers because they're bankrupt. And they you know, and so now they had, they had no visibility into where the containers were. But the whole system began to collapse as a result. Because, you know, people had containers on chests containing 400 containers. Okay, so if you if your chassis, what do you want you get rid of my 100 and get rid of that container, I need to do chassis, I gotta go pick up another customers, okay, well, I'm not going to take your picture here. They're invaders, I don't get stuck with your container. So then what happens? Well, I don't know if I'm going to have enough chassis to move what I need to move. So I'm going to start hoarding chances. And that's exactly what happened. So there was hoarding that went on again. And we had the visibility to see where things were, and move them in the right places. So we here in the US, and I think we probably had the same problem. You remember that when COVID first happened, and people said, Oh, my God, we don't have enough ventilators. And people were dying in New York. And they right away, the government said, let's let's manufacture more ventilators? Well, that's not the answer. The real problem was we had plenty of ventilators, we just had no idea it would work. So if we were able to take those ventilators and move them to places that had a need for ventilators, we know where the hotspots are for COVID if we were able to move those ventilators predictively. And so that's, that's the issue at the court, you need great information. One of the things I'm working on with the federal government is here in the US is we're going to be investing a couple of trillion dollars in infrastructure. And it's very, very important for us to build smart infrastructure, not dumb infrastructure. If you think if you think about it, the infrastructure that we use today, roads and bridges, and ports and things like that, most of those were built 30 4050 years ago, you know, 50 years ago, nobody was thinking about the internet, no one was thinking about connectivity. And no one was thinking about sensor technology and satellites and 5g. They weren't thinking about that, right? So. So we know those assets, those that infrastructure, is what I would call dumb infrastructure. It has no connectivity. So we're crazy today to not build smart infrastructure. So that as the as the technology, SAP is a great example of companies that are investing billions of dollars in innovative technology to solve these problems. But the expensive part of infrastructure to pour in the cement, right? If you don't think about creating smart infrastructure that can adapt to the evolving technology, you're crazy. So I'm really pushing very, very hard that we, we need here in the US, and I think globally, to think about building smart infrastructure, and to increase our capacity for digital infrastructure.

Tom Raftery: 23:38

And so I mean, we are now hopefully coming out the other side of COVID, you know, at least here in the first world, many of us have been vaccinated at this point. I'm in Spain, where at 78% of people are vaccinated. I understand in other countries, they're not quite there yet. But we're heading that direction in a lot of countries, I hope. So we are going to come out the other end of it. How do we get our supply chains back to the way they were before all this fell apart?

Jonathan Rosenthal: 24:12

Well, I think we'll we'll dig out, I think it's going to take longer than people think I think the supply chain problems are going to be with us for a couple of years, probably not not as critical as maybe they are today. But we'll we'll work out. But it's going to happen again, if we don't address the core issue, which is inflammation, and the ability to to collect real time information, to curate that information to organize that information to and to understand what that information tells us. And so that's

Tom Raftery: 24:49

really that's that's information not just from your own sensors or your own devices, but it's from partners and people in your ecosystem as well because you got to see what's happening all around you because the supply chain isn't just you. It's everyone that you interact with.

Jonathan Rosenthal: 25:06

And that's a great point, Tom. For whatever reason in supply chain logistics business, people have been very siloed I don't want to share my information with you. It's top secret, okay. Well, the truth is, I don't really need to know that it happens to be a Walmart container. That that information, especially now with blockchain, all of that information can be anonymous. What I need to know is how is the system working? How are those assets flow? And I completely respect someone who, who says like, I don't want anybody to know that the inventory inside a container is my inventory, that's fine. Now, using blockchain technology, you know, you can easily say, well look, you know, you may not want the world to know, but you may want your trucking company to know, you may want your shipper to know that it's your stuff. And so you can very easily say, well, these people should know, these people should not know, and so that you but but you have what are called Data lakes. And this is something that our partner at ezri has been an expert at, especially when you begin to look through a lens of location. So there's only there's only really one thing that all assets have in common. And that is, they all have a place at a point in time, right at a point in time, every asset has a place a latitude or longitude and altitude. And so ezri has for 50 years, has been building data lakes, and understands how important that information is, looking at systemically and then being able to analyze it. So they, they really not focus so much on the logistics piece of this. And our partnership has given us exclusivity on the every platform to build out a glass pipeline, so that you do have transparency, but that that transparency is very, very secure. So they built platforms for the CIA, and, you know, I mean, the intelligence agencies and things like that. So these are very, very secure platform. But when we first met ezri, about three or four years ago, and we were discussing these issues about the lack of information, transparency, and we realized that they had not really focused on just explore them so much. JACK dangermond, the founder said to me, he explained to me more what you do. He said, Well, we host 45% of the geospatial information on the earth. Now that's a staggering, a staggering number. So they they really focus on the question of where, you know what, and then supply chain A lot of times, you know, where's my stuff? Yeah, that's the question, Where am I except we're focusing on that question. Where's my stuff? But we're focusing on a little bit different question as well. We're focusing on the why question. Why is your stuff where it is? Okay, why isn't? Why isn't my stuff where it needs to be? You know, why isn't it going to be in the warehouse two weeks from now? So we're very focused on the where question, because without answering the where question, you can't answer the why question.

Tom Raftery: 28:38

What about the wind question? Because, you know, as a consumer, it's, that's the one that's important to me is okay. I don't even I don't give a rat's ask Where? Where are the devices? Right? Now what I want to know is, when is it going to be at my front door?

Jonathan Rosenthal: 28:54

So yes, absolutely. And that's that's really the that's really the question. So when you you have something you're we use here a lot of ways, right? or Google Maps. And so you know, when you plug in, you know, I'm going downtown, I'm, you know, go to dinner someplace, you're asking the question, When am I going to get there? And what's my best route to get there at a particular time? So you're you're right, the question is When? When am I going to get there? I don't care where I wait when I'm going to be at various points. But it unless you understand the where question, which is, where am I five minutes from now? 10 minutes from now, 15 minutes from now, you can't ask the why question, which is, well, why am I going to be in in traffic? Why am I going to make a left turn instead of a right turn? And by the way, one of the biggest problems that you'll find is that the technology oftentimes tells you to do things that are counterintuitive. The the technology actually smarter than we are. And so you've done this, right? You've been driving along and the technology says make a left turn he goes back there absolutely wrong. It's a right turn. I gotta make a right turn. And And sure enough, what do you do? You do the same thing I I use my brain I turned right. And I'm writing traffic. And I go, the technology was smarter than me

Tom Raftery: 30:25

happened a bunch of sales to me too.

Jonathan Rosenthal: 30:27

Yeah. So and so that's normal. One of the biggest problems with Technology is getting adoption, because we're all human beings, you know, telling a person, you know, we have some friends that ups and they have, you know, just incredible system called Ryan. And, you know, it tells their drivers how to go where they need to go, right. So the technology was not an impossible thing to do. It was a technology that was built on industry backbone, but very hard to get the drivers to do what the technology said, because the technology said, Look, I know you're going to pass two stops. But keep going, don't stop, you're going to, you're going to get those on the way back. Right? So the driver at it, you know, he was like, No, no, I gotta stop. So all of a sudden, they had to start building incentives for compliance, right? So they tried to incentive people to go ahead and do what the technology said to do. So how compliant? Are you with the technology? Because the technology knows better than you do? That's a big problem, because we're all people

Tom Raftery: 31:41

to find fascinating study and change management.

Jonathan Rosenthal: 31:44

Yes, it is. It is. Especially now, because we're, we don't we're, you know, it's interesting that we're, we're very early in supply chain in digitalization. We really are. I mean, I know people would think maybe, or not, but we're, you know, how many containers are there in the world in 20 million containers or something? How many smart containers? Very, very few, right? How many smart chassis? How many smart ports do we have? How many, you know, we're very, very, very early in the digitalization of the supply chain. You know, we're talking to people with our platform in things like road equipment, you know, tractors and bulldozers and things like that. We're just digitalising that industry. Now that, you know, I can guarantee you that industry is going to be compete, believe me, digitalized as they move to autonomous, autonomous vehicles. Yeah. So

Tom Raftery: 32:43

there's a big difference, though, between those vehicles. And containers.

Jonathan Rosenthal: 32:48

Oh, cute. Yes. Well,

Tom Raftery: 32:50

so that the ratio, the ratio of container price to sensor price, versus autonomous vehicle price to sensor price is very different?

Jonathan Rosenthal: 32:59

Well, yes and no, because think about it's not the container that you care about. It's the value of the inventory inside the container. Sure. Right. So so that becomes, you know, pretty valuable information about the nothing, you don't care where the container is, what you care about is where's my stop? Right? So, so it does become valuable. And and you're right, that there's a relationship between the sensor, the cost of the sensor, but the cost of sensors is going down dramatically. I mean, we've, you know, we've seen companies that have come out with sensors that are less than $1. So So I think, you know, we have to chart a course. And we all have to look at the world and say, Look, let's not build a world for yesterday, what we're doing, we're all moving into perfection, we're not going to stop that, right? We're going to become more connected, more connected in terms of technology, the IoT is going to be, you know, more prevalent. Assets are going to be more connected, we're going to have more information. I mean, I always try to as a as an operator and an investor, I always try to separate. What do I know, from what do I think? So what am I willing to accept as fact? And what I want to be very careful to say, What am I What am I thinking you might be fact, but it's actually opinion? Because I can be wrong on pain? I shouldn't be wrong, on fact. So at least for us, I believe that the statement that the IoT is going to grow, the Internet of Things, and the connectivity of assets is going to grow dramatically. I believe that's a fact. I don't think there's any, I don't think there's anything we can do about it that you and I decided to retire tomorrow, that's going to happen with the censoring of assets is going up dramatically. And that's a fact that it's not it, you know, we are censoring assets. And we help facilitate that. But with or without us that's going to happen. So so as you censor up, the amount of data is going to go up dramatically. That's a fact. Now, are we going to be smart enough to to collect that data and curated and are we going to look through a lens of location intelligence. Or are we going to continue to look through an old lens of a ledger technology? And that's that ledger technology where things are just, you know, they're in a database, but they're, but they're not related to a place you can't see the movement in real time. That is an antiquated technology, will we move to a location based technology? I think we will, because it's so much more powerful. But I would say that's my opinion. That's not a fact.

Tom Raftery: 36:00

Okay, Jonathan, we're coming towards the end of the podcast. Now, is there any question I haven't asked that you wish I had? Or any topic? We've not broached that? Do you think it's important for people to be aware of?

Jonathan Rosenthal: 36:11

Well, I, you know, I just, I think that this is one of the most important times and the introduction of location intelligence, is maybe the greatest innovation in supply chains, it's containerization, I really do think it's a monumental leap. And people don't really understand the power of location intelligence, one of the things I'd like to offer is that, you know, we have a seven minute demo of how location intelligence works, and why it's important and how we're applying it to all kinds of assets. And we apply it to not only container two, we apply it in your, in your homeland, you know, you have a company called pistol helicopters, we you know, we have a system that brisco uses to track their helicopters track where they are, do geo fencing, all kinds of things you can do with location. So I'd like to just offer to send you a link and anybody can, you know, look at it and try to understand the see what what location intelligence is all about. And, you know, we're out in the marketplace today, building an investor base that understands location intelligence, and wants to wants to see how that's going to impact the world could impact the world in, in a big way. And I just think people should think about the importance of data and the importance of digitalization, it's really going to have an enormous impact on how we do things, it's going to have an enormous impact on the environment. You know, the movement of things, people and freight is the single largest contributor to global warming, inorganic contributor to global warming. So if we can somehow using information, we can make the system more efficient, we can reduce the environmental impacts dramatically. Super, super.

Tom Raftery: 38:10

Jonathan has been really interesting if people want to know more about yourself, ar e. Sp, ar any of the topics we discussed in the podcast today. Where would you have me direct them.

Jonathan Rosenthal: 38:21

So all you'd have to do is put in your browser, actually our parent company, which is callled Saybrook, S A Y B R O O K. And ESRI, if you put those two words, it'll get you to link on the every website. And you can see what else is doing. You can see what we're doing. So Saybrook ESRI, and you'll be off to the races.

Tom Raftery: 38:49

Fantastic. Fantastic. Jonathan. That's been great. Thanks a million for coming on the podcast today.

Jonathan Rosenthal: 38:55

Great, thanks.

Tom Raftery: 38:57

Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about digital supply chains, head on over to sa p.com slash digital supply chain or, or simply drop me an email to Tom raftery@sap.com. If you'd like to show, please don't forget to subscribe to it and your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.