Dorren Schmitt:
In our history in the early years, we started with high-performance compute clusters to try to hyper-localize your observations and the weather forecast. We’ve turned to gaming technology for some of our graphics, and we’ve moved to the cloud, and now our journey is with AI.
Miles Ward:
Hi, everybody. Welcome back to Cloud and Clear. That’s the podcast where we dive deep into real-world cloud transformation stories. I’m your host, Miles Ward, CTO at SADA. Let me tell you, lately, from everything from the devastating wildfires in California to there are tornadoes now in San Francisco Bay, who knew? Weather’s on everybody’s mind. That’s why I’m especially excited. We get to do a little sneak peek into our upcoming Google Cloud next session with Dorren Schmitt. She’s VP of IT strategy and innovation at the Weather Channel. Dorren, welcome to the show. It feels like what you’re focused on is top of mind for everybody.
Dorren Schmitt:
Well, thanks, Miles. Weather’s always a topic of everybody, and it seems to have gotten busier, not only with the wildfires. There’s been tornadoes in every single state in the union. Surprisingly so, most people don’t realize that, and we’re just getting into tornado-busy season. It’s just starting to ramp up. Our busy season is starting now and we’ll go all the way through November, easily.
Miles Ward:
Wild, wild. Well look, before we dive in, maybe give us a brief overview, your role, your focus. I think most of us have seen stuff on the Weather Channel, but maybe give us something we haven’t heard of like, “Wow, I don’t know that stuff. What’s going on?”
Dorren Schmitt:
Yeah. The Weather Channel’s a 42-plus-year-old company. I’ve been there 25 years, moved up through the ranks. For about 13 of those years, I’ve led our technology operations teams, so all of our technology infrastructure, and so all of the innovations, moving to the cloud multiple times, moving to the cloud has been part of my journey. We’re part of the Allen Media group, which most people don’t realize, which has some local TV stations, as well as some other cable stations that’s part of our group.
The mission of the Weather Channel is to protect and save lives. That is core to our mission. That’s core to what we do. And so, data and technology is at the core of that. I’ve always said that we’re more of a technology company than a media company in many aspects because of what needs to take place to get all that data. In our history in the early years, we started with high-performance compute clusters to try to hyper-localize your observations and the weather forecast. We’ve turned to gaming technology for some of our graphics, and we’ve moved to the cloud and now our journey is with AI to get the data faster, to be able to get it more personable, to be able to sift through more data and provide the most relevant data to our customers now than we have ever done.
Miles Ward:
That’s funny, your framing of the Weather Channel as really a technology and data business. Adrian Cockcroft, he’s the CTO for Netflix, used to say that Netflix was a giant machine for producing log files, which occasionally allowed people to watch video. Given the sheer volume of data that you are chewing on to help predict and project the weather and so critical that information. I love the mission of saving lives. I imagine that your team faces some pretty unique challenges. What challenge brought you to the AI tools from Google, like Recommendation AI?
Dorren Schmitt:
Let’s start off with, and you bring up the massive log files of Netflix where we ingest about a petabyte of data a day of images for radar, the observation data, forecast data, the like. We generate terabytes of graphics of video data every day to make all of that data hyper-localized. We are a data machine, and of course there’s logs behind there as well, but we are certainly a data machine, and wrangling that data, saving that data, being able to put metadata on it so that we can go back and find that information is a big challenge.
Particularly for a company of our age, you can imagine the amount of video that we have. You can imagine the amount of other graphics that we’ve kept for huge events like Katrina or Ida or Andrew. I’m just naming the big hurricanes that everyone is more aware of those names. That’s one of the crux of it. But the other aspect that brought us to AI very simply is, we need to also to help our customers understand from a historical standpoint what’s happening.
Perfect example is the historical snow that just happened in Louisiana in January, where 10 inches of snow fell in the city of New Orleans in January, the most they’ve ever had in their entire history. Previous to that, it was 1895 when they had like, I think, nine or nine and a half inches of snow. We have to go back so far in history to find even relevant data of how unique that was. Additionally, just understanding the unique topologies. Think of a large metro city. Let’s take an example of the wildfires of Los Angeles. That topology, if you were in the wrong place, it was a breeding ground for fire. If you were in quote unquote the right place. It was dependent upon the winds, it was dependent upon the topology of the hills and the mountains around there and all of that, and understanding that and being able to use AI to help us understand that topology has become a game changer.
Miles Ward:
That’s totally incredible and fascinating. I mean, I think the amount of data that you have to choose through, I mean, I have lots of folks that are doing year-over-year comparisons, but not century over century like you’re talking about in Los Angeles. That’s crazy. It’s not just about finding the right information, it’s about getting it at the right time. SADA, the folks that I help work with, how did you help work together with them to get Recommendation AI implemented? What did that implementation process look like?
Dorren Schmitt:
It started out with having a challenge, having a problem, and then you’re sitting down with SADA, and what are our options? What are our options in general? Then we narrowed down to recommendation. AI looked at doing a proof of value, and we spent a number of weeks figuring out, trying to understand the foundations, coming up with some graphics, coming up with workflow, and then also looking at what’s the cost savings, what’s the cost benefit of us doing this and being able to bring this to the Weather Channel, because whether it’s saving time, saving money, saving both, which is always really nice, it’s always important. There needs to be some value that we bring to the company to… In our case, frequently the value is expediting something, being able to get data to our customers. It sounds funny, but one or two minutes faster to our customers can be the difference between someone’s life being saved because they were able to get into a closet or them perishing in a tornado, very honestly. We measure things in minutes, not in hours or days where many companies do that.
Miles Ward:
Sure, yeah. No time is of the essence. I mean, speaking of time investment, I mean, you’ve been focused on this problem with the Weather Channel for 25 years. I mean, you’ve been working in the cloud before Eric Schmidt coined the phrase, the cloud. Super excited about the credentials and not often we have PhDs here on the show. You’ve seen a lot of tech change and AI is just a roller coaster right now. I’m curious, what have you experienced lately? What’s top of mind for you as you continue to explore with the Weather Channel?
Dorren Schmitt:
One of the interesting things is, AI has been around, or at least the concept since the 1950s, and Alan Turing. Most people don’t realize that. They think it’s this thing that has just happened over the past three to five years. The ideas have been around, there’s been some really bright men who did it. I’m going to say that Google’s transformers in 2017 really transformed AI, and we are at probably the top of the hype cycle. But that doesn’t mean it’s going away. It means all the hype is, all the… I want to say unfettered. I need to do this with no rationalization. Now, I think people are realizing, just like it was with the cloud, just like it was with the internet, “We need to have more business rationalizations, better business use cases.”
It needs to be driven by just not, “I need to be there,” but driven by, “This is the right thing to do. This is how I can make a positive impact for my business. This is how much business value comes to it.” It’s not going away, just like the cloud has not gone away. Actually, I think more things are going to the cloud now than 15 years ago when it was at the top of that hype cycle. I think what’s really important is to find those appropriate business use cases, and one of the things we do is we have a innovation council that is across all of our business units and all of our internal business partners, legal, sales, the like, because business doesn’t always realize all the aspects that a technology project could touch.
In particular, AI with using our data, definitely legal needs to be involved. Sometimes HR might need to be involved in the project. It’s not only business, it’s not only IT, but there’s many more aspects to many business projects with AI than other business projects that we’ve ever had previously, where business could kind of go off and do their thing and improve their graphics, change their graphics, do whatever. Now, many more teams are involved in AI projects than they’ve ever had.
Miles Ward:
I think those are wise words. I agree with you, we’re watching business after business realize that maybe compared to some of the other technology waves, cloud and the internet, AI is one of those technologies that really touches almost every job role. And so, almost every function is necessarily a stakeholder in the outcomes you’re trying to deliver. It’s a great idea to have HR involved. We’ve been helping build tools for HR teams. I think it’s a place where some departments that maybe haven’t been touched by these technology shifts are going to start to feel this one for sure. Any other valuable lessons, places where you think folks can get started easily or next stuff they should read or places they can skill up to take advantage of what’s coming?
Dorren Schmitt:
There are lots of places out on LinkedIn. There’s many, many blogs out there with AI. Some is hype, some is not. You need to certainly be a bit discerning. I think Google does a great job of telling us some of the things that’s coming out on their platforms. It was one of the most wonderful thing for business and enterprise customers, for everybody to get Gemini. One of the things that I’m a very strong proponent of is training our people with any new technologies. One of the things that the Weather Channel and our media group are doing is we are working to train all of our people on Gemini. We’ve done several training sessions on just where to find it, how to basically use it. We’re doing training on how to write good prompts.
We need to take advantage of this technology and make people more efficient, get out of all these routine tasks that across the business people are doing. It’s just that IT needing automation or the efficiencies of routine tasks. But as you said, HR, legal, can AI summarize a legal doc? Can AI look at a doc and we know there needs to be certain things in the documents that our legal department wants? Is that there? There’s efficiencies throughout the entire business that AI can provide, not just generating new content, but actually being able to make our employees more efficient in the jobs that they do.
Miles Ward:
You’re exactly right. I remember I had a buddy who ran a small IT consultancy, and his way of finding next customers was pulling the local big tech, like a big box store and figuring out which companies were buying the most paper. They were buying a lot of paper, they were probably doing something wrong, and it was time to go in and talk to them about app development and systematizing things. Now I feel like it’s every department everywhere, somebody’s got that hidden spreadsheet where they actually keep track of what the heck is going on.
I think if you can find the departments that have the most spreadsheets for tracking their stuff, you probably can roll in there with an AI tool, help them organize information, make it more easily accessible to other people, set them up to have simpler communications. There’s all sorts of tools now that are being built to really help folks organize their business better. It sounds like you are right in the middle of capturing those opportunities. Dorren, thanks for taking all of the cycles with us today to talk it through really, really thoughtful comments. I hope everybody leans in and pays close attention. For our listeners, thank you for tuning in to Cloud and Clear. For those who are attending Google Cloud next, don’t miss the SADA spotlight session that features Dorren right there alongside Simon from the Sherlock Company, discussing both of their AI transformations. I’ll be there trying to keep it fun. Visit sada.com/next for any extra details. Looking forward to seeing you there. For everybody else on the podcast, talk to everybody soon. Thanks so much, and thank you, Dorren. Say howdy to everybody.
Dorren Schmitt:
Thank you.
Miles Ward:
Cheers.
