Paul Walsh, Vice President of Weather Analytics and Meteorologist at The Weather Company spoke with Marni Edelhart, Pivot’s Director of Content and Experience to discuss weather data measurement and new analytics tools that will impact various industries. Read on for the complete interview.

 

Marni: Hi, this is Marni Edelhart, Director of Content and Experience for the Pivot Conference. I’m on with Paul Walsh, Vice President of Weather Analytics and Meteorologist at The Weather Company, Paul helps companies use weather and climate big data to create and execute weather strategies that lead to more effective and profitable business outcomes. Since 1997, he has helped business leaders in many of the largest corporations in North America and Europe use weather and climate intelligence to increase sales and maximize profit. Good morning, Paul.

Paul: Good morning Marni.

Marni: I’m so glad to get to speak with you again and learn a little bit more about your work.

Paul: Yeah, great.

Marni: We first met when you spoke at Pivot in 2012 after only a year with The Weather Company. Now three years later what do you see as the biggest changes in your role and priorities?

Paul: Well a great question, Marni and first of all I just can’t believe three years has gone by already. In terms of changes in my priorities of course I joined the Weather Company three plus years ago to really help build out the use of weather data and analytics to create additional sort of products and services for the weather company in general. And we started specifically in the advertising and media space. So when we chatted in 2012 I really focused on how we were leveraging weather data to build out effectively and add platforms to be able to sense when the weather was going to be driving demand by market, and then be able to serve relevant ad messages.

That has since become a really central part of our digital business and more and more our cable business. On the media side that’s been tremendously successful. We have since built out a pretty large organization that is continuing to build out that technology. I’ve been over the last I’ll say two years now and even more so now focused more on two things. One is sort of evangelizing weather and weather’s impact on consumers and I am doing that both on air as well as doing blogging and speaking engagements.

But then secondarily and more importantly sort of the second part of my vision when I started and what we’re doing now is really taking the same sort of techniques that we’ve been using on e-advertising and media side, and scaling that up to include supply chain applications and focusing on retail and CPG companies globally as well as insurance companies and risk management companies. So we’re really building on what we had started three or four years ago. And Pivot in 2012 was the first time that, that we were really out there talking about this sort of vision.

Marni: Yeah I can’t believe it’s been three years either. And that you guys have come so far in that time and it’s exciting to hear about.

Paul: Yes, we have.

Marni: In recent conversations I’ve heard the term big data and small data as well as many different approaches to collecting and analyzing all this data. Can you share any insight into how you determine which data points to measure and how you think about data in a way that helps you be still learning in a clear and meaningful way for your colleagues and audience?

Paul: Yeah, you know Marni, I think one of the problems with big data is that it is – and I’m using air quotes here now – It’s big and because it’s so big it’s very easy for companies to get lost and get sort of buried in the big data. What I’ve learned and what I’ve known since being in the data business is it’s the 20% of data that really delivers that 80% of value. One of the hardest things to do and the most important things to do is to separate out the data points that not only are the most interesting, but are the most actionable and therefore can drive the most or align the most value. And sometimes that means walking away from things that look to be really exciting and interesting and focusing more on the things that are going to have the biggest impact on the business.

Once that part is solved then the technologies that are available to us now, the analytical tools, the ability to quickly measure the outputs and frankly, the ability to predict outcomes, is really important. The other thing that’s really, really important is that once you have those kind of insights and if I look at this from a weather-centric mode, the really important thing to do is to be able to literally mash up those data points with other data points. Because where the real insights come in is not from one discrete data point, but it’s from multiple data points. From a weather perspective the effect that weather has on consumer demand varies by market. It varies by time. It varies by on the retail side by price point, by promotion, by holiday.

There’s all sorts of other things that go into it. But we live in an age now where it’s possible to really be able to model that in a way that’s meaningful and to do it in a way that’s fast. And once you have those kind of insights then you really are positioned to start to take advantage of that kind of information, and start to drive revenue.

Marni: Got it. I think avoiding the paths that seem really exciting, but aren’t necessarily relevant might be the hardest piece for a lot of organizations, a lot of people, that bright shiny object, challenge is hard to avoid.

Paul: Sure, yeah.

Marni: So what new technology or do you consider most exciting and why?

Paul: Well certainly from our paradigm, one of the things that I think is exciting is this whole concept of the Internet of Things, and data points that are pulling in new types of data and the ability to sort of pull those data points in, and create you know additional value points. The reason that it’s exciting for me of course is I’m in the weather business and creating weather forecasts that are highly local and highly accurate really requires a lot of data. As we are able to pull in these new data points, for example, we are now within the weather company pulling down data directly from airplanes, turbulence data and temperature and humidity data that you would never see as a consumer – unless of course you’re flying in an airplane. You might see the results of it.

Now we’re pulling that into our weather forecasting technology. Also cell phones, or mobile phones most of them now contain sensors that have humidity and other types of pressure sensors for example. More and more of those data points are going to be available to be pulled in and tied into forecasts. Because of that we’re able to now create weather forecasts that go down as far as a half a kilometer and cover the entire globe. So we basically have two billion data points that we predict the weather for and we predict the weather at those two billion data points every five minutes. Because we’re able to do that then, we’re then able to create weather forecasts that you get on your mobile phone that are specifically for you.

They’re created for you, for your location exactly when you are asking for it, and give you a prediction that is just amazingly accurate. And that’s where we are now in 2015. So you can only imagine the kind of data and technology that we’re going to have available for you, for just consumers in general in five years or ten years. It’s just amazing and exciting the way that the technology is advancing forward.

Marni: Yeah, I mean what you are describing makes me envision a very near future where my phone goes beep, beep, beep and it tells me get under an umbrella or inside right away, because I am about to be caught in a downpour.

Paul: It already does that. In fact we have existing technologies now that we provide to the insurance industry that are white labeled, that will give you the same beep-beep if there is a prediction of a large hail that’s about to hit your car. And you’ll get a message that will say Marni, in 30 minutes one inch hail is going to hit your house, go home and put your car in a garage. And of course the benefit of that kind of service is that for the insurance company they are able to avoid a loss. And for the person that is being insured by that insurance company, they love that insurance company because they helped them avoid a loss. So that kind of technology actually exists today, and so the trajectory of the kind of things that we’re all going to have in the near future is very, very exciting.

Marni: It is exciting, and helpful. It’s pretty clear why it’s helpful for me as an individual to know when it is about to rain. But can you talk a little bit more about the value for brands in this weather-related data?

Paul: Well the value for brands is really directly because it’s valuable for you, and you buy from brands. That same exact example that we gave you from an insurance company perspective, as we expand that out and more and more retailers, for example, use this type of technology to help them both manage their supply chains, manage their pricing and tie that back into advertising. Of course we’ve got a pretty big footprint now and lots of technologies that relate, as it relates to advertising. But now if you connect basically the demand chain which is advertising back into the supply chain, then you start to create organizations that are very, very resilient.

They’re able to be more responsive to what their clients or their customers are going to need and are able to do it proactively. Because of the weather, not only does the weather have a huge impact on driving consumer demand and consumer sentiment, but the weather forecast has a huge, huge impact. And it’s really because of the way that we use weather forecasts. Well you know when you check the weather on your iPhone or your Android, you are not doing it for academic reasons. You’re doing it because you’re planning your whole life, and that might be just for today. It might be for a weekend.

You might be planning on where you’re going to go eat and what you’re going to eat. And because all of that insight is measurable and because it’s all knowable from a forecast perspective, the ability for brands to be able to leverage that data to become much more relevant, and useful and valuable for their customers is really significant.

Marni: So basically your data can help a brand treat me better at every point of the customer experience including the point where they are selling themselves to me as a brand, and selling their value to me.

Paul: Exactly, exactly, exactly. Because they’re able to communicate to you in a way that’s relevant and local and specific to you, and ties back to either something you need now or you will need in a couple of days. And then the whole — the supply chain perspective of this means that they will get better at being able to make sure they have it. I mean it’s one thing to tell you that they’re going to have something that you’re going to need in a day or two, but it’s another thing to make sure that they actually have it on the shelf.

Marni: Right and that gets me to our next question –  you have a recent partnership with IBM and I’d love for you to describe that for me and talk about how that partnership is going to help transform business processes?

Paul: It’s a great question and it’s a really exciting partnership. Because what this is really going to enable us to do with our partners at IBM is to help brands rethink the weather, just completely rethink how they plan for, and how they execute against the weather. You know traditionally the weather paradigm from a brand perspective has been one of what I like to call cope and avoid. So the thinking was “well we know the weather has a huge influence on our customers, and therefore our business but we can’t change it”. To some point the cynics out there will say, you can’t predict it so let’s just plan our businesses and just hope for the best.

Well the new paradigm is really one of anticipate because you can anticipate certainly from a historical perspective how the weather is going to influence your consumers. And then you can anticipate what’s going to happen because the forecasts are so sort of built into the way that we all live our lives, the way that we use information is so ingrained into our mobile phones. Most of us check the weather two or three times a day so you can actually anticipate what people are going to be able to need and then execute against that.

What this partnership with IBM does is it really enables us to take the weather data that we’ve got, those billions of points that we predict for and that we measure around the globe and then integrate that back into IBM’s both technology capabilities as well as their service capabilities.  They’ve got, from an analytical perspective, 20,000 plus consultants around the world, and they have obviously deep knowledge of business processes across a bunch of different industries. What this is going to enable us to do is to really unlock the value of weather.

And we’re going to be able to help companies start to leverage as opposed to being victimized by the weather. I think it’s going to transform businesses, frankly. I think it’s just in time because there’s more of us out here, there’s more people and the weather is just you know continues to be highly impactful, highly volatile. And to help people better prepare for that, brands need to be tied in a way where they’re able to measure, monitor, predict and then, most importantly, execute against this information. This IBM plus The Weather Company partnership really is a game-changer. I think it’s the sword in the stone where now we’re able to pull that sword out of the stone and unlock these insights, and start to turn them into something that’s going to help us. It’s just in time too because again, the weather is not getting any calmer, and there’s more of us.

Marni: Yeah, well there’s a bar here in Seattle called Damn the Weather. And I think that that sort of attitude a lot of people felt about weather in general. So there’s one reason or another to complain about it, but what you guys are doing with IBM like you said instead of being victimized by it, you can take advantage of the opportunities just knowing leveraging the knowledge we have about it.

Paul: Yeah.

Marni: So thank you so much, Paul. It’s really splendid to speak with you and to be working with you again.

Paul: Yes thank you, Marni and yeah three years – yeah three years and then I will do it again three more years. We’ll see where we are.

Marni: Perfect.