The Juice of It Presents: Shimon Elkabetz

Co-Founder & CEO of Tomorrow.io shares what it takes to build the world's most powerful weather intelligence platform

To start, tell us about how you grew up. What and who shaped you?

I grew up in a moshav in the Galilee, right next to the border with Lebanon. When I was 13, I moved to a military boarding school in Haifa. I spent four years there, and it was probably the most influential experience I’ve had growing up that really shaped me. You know, no 13 year old is designed to be prepared to go to a military boarding school that is very demanding and requires such a high level of discipline. The Hebrew Reali School of Haifa, was established by Ben Gurion and is a very selective institution, so there is high pressure to succeed both within the educational and military training sense. It was challenging, intense but also inspiring, because leadership is the focus of the school. You had guys like Gaby Ashkenazi and Amir Baram, a very inspiring group.

Reali School’s Vision: “To be a leading and a pathfinding quality educational institution, which encourages its pupils to be worthy human beings- actively involved and impactful in the Israeli society“

So, what’s the founding story of Tomorrow.io?

Tomorrow.io was born in Boston. I went to Harvard and my co-founders, Rei Goffer and Itai Zlotnik went to MIT. We realized we had a good opportunity to start a business during the two years we were studying, and we immediately agreed to focus on weather the first time we met. We were passionate about the area from personal experiences, so our journey started right then and there. Towards the end of 2016, during our second year of school, we raised our seed round and by the time we graduated — we had a small startup.

What was the biggest challenge you encountered when building the solution? How did you overcome it?

On the one hand, I think one of our biggest disadvantages was that we didn't have deep technical expertise, and we were walking into the most complex domain of technology. It’s hard to imagine it today, as we now have our satellites, weather models that turned into AI models and our software. It’s easy to think we didn’t make mistakes along the way but we did. We wasted a lot of money on poor choices and the way we built solutions in the beginning.

On the other hand, we were completely in love with the problem, and all we cared about was solving it and creating impact.

So we weren’t married to any technical idea or solution. This in my opinion, is the secret sauce to our success.

We were able to basically say ok, our job is to help countries and businesses manage the weather. We know climate will lead to challenges in times of climate change. Okay so, what does this mean that we need to build? Back then it wasn't about building satellites. But since we were so?technology agnostic, or solution agnostic, and there was no emotion about the specific solution we chose, the emotion was instead behind the mission, we were able to stay open minded and adapt. At the time, satellites were not the answer, it was models. So that’s what we did, we built models. Then we realized models can’t be accurate without a specific set of data, okay so how do you get this data? You have to go to space. Okay so we’ll go to space. This is the mindset we had, and what was our disadvantage at first I believe turned out to be one of our main advantages because it allowed us to think this way. We were lucky that this was our disadvantage and we were able to overcome the penalties that came with it.

Tell us about your product strategy. How did you start and then pivot?

You know it’s interesting because people tend to look at pivoting as a negative thing. I don't believe it's negative, especially when you’re starting a business, pivoting is actually just natural evolution. If you took me back to the beginning of the company in 2016, I wouldn’t go and do satellites back then. It was premature, it would have been crazy to do it back then. So as always, we started with the problem, which was how do we help countries and businesses make better solutions? We knew that we're going to do two things on a very high level. One, is we're going to build a solution that helps customers make decisions, i.e. the software product subscription that helps customers make the decision. The second thing was that for that software to be useful, we have to generate and build very accurate weather technology. That was there from the beginning.

There are two things that you need to think of when you start a business in the context of productizing:

1. The innovation of the product itself
2. The market.

What is this product, what's unique about it versus other products in the market and to which markets are you going to go after? Because you can decide to focus on a specific vertical. In our case, we could choose to focus on aviation. We knew aviation from the military. And it's much simpler to build a product for aviation. You know who the users of the market are, it's very easy, but then the TAM is limited. What's the size of the aviation industry? Not very big, not very attractive. Or you can say, you know, I'm going to build a solution that works for every vertical or several verticals. The obvious advantage is that the TAM is much bigger. Its disadvantage is that it is much more difficult to build a multi vertical product, it's more expensive. It takes longer, you can lose focus, and you might even not be successful in doing it eventually because you will always miss something for someone. Despite the disadvantage, we were laser focused on becoming multivariable.

At the beginning, we weren't very good at it, but then around 2019 — we had a breakthrough.

We realized that what customers really need is not the forecast, as in what the temperature or winds will be. What customers need is the business insight, what action do they need to do as in, cancel the game, staff more people, reroute your vehicle, etc. So what's the action you need to do? We understood this once we started talking to our customers and understood their decision making process was very manual, for example talking to a meteorologist, having an in house meteorologist looking at data and doing analysis on the data. So we learned that there is a room for digital transformation, and that’s when we decided that our product will be what we now call weather intelligence.

So now to space and beyond. Tell us how you evolved into space?

It started with accuracy. When you think of accuracy in the weather intelligence world, it's zero to one. One is accurate as in 100%, zero is nothing, and we have 50% as in the flip of a coin. In this image, the gray line is an old model. The red, orange and pink lines are AI models. So you can understand here with AI, you get better than a flip of a coin.

To be able to know what's happening in real time is not any model, it's the data source going into the model. So in our case, we're talking about radar data. Ok great so we need radars. Where's the problem? This is the problem. This is radar coverage in the world. 5 billion people do not have radar coverage. Even with the best AI model in the world, it's a flip of a coin in terms of knowing if it's raining or not in Mumbai, Mexico City or Rio de Janeiro.

So at this point, we said okay, if we don't solve this problem, we'll only get this lower accuracy data. We knew it would take a year, two or three — doesn't matter. The answer was that the only real way to solve this problem was to put radars on satellites and cover earth with radars. This was the only solution. The problem was that there was only one radar in space for weather back then. And that radar was created by NASA and cost NASA close to $1.5 billion. That satellite, which is called GPN, samples every point on earth every three days. So it's useless for forecasting, because that was never its purpose, it’s designed to be a research satellite.

So the challenge ahead of us was, can we build a radar that will be much smaller, but keep its characteristics in terms of the solution and what it's trying to do, in order to keep costs down?

This was the concept we came to a board meeting in August of 2020, right after COVID started and said. You know we were usually raising money for a SaaS company, not for a satellite company. The investors knew nothing about satellites, but they believed in the problem, and they believed in the plan we presented and so last year, we launched our first satellites. They generate amazing data from space. The data that they create is almost one to one correlated with the ground radar system over continental US. A system worth $3.5 billion.

When it comes to exit execution and trying to execute on a vision as a leader, how do you keep your team on track?

There isn’t one universal answer, and every CEO has her or his own methods, but for us, we meet as a team frequently, every two to three weeks we meet in a company wide setting. We always keep talking about the vision and why we do it. We'll bring in customers to talk about the impact of using our product and what it did, how many lives it saved, how much money it saved or what good impact it created for their organization. This motivation is super important. I believe most people who joined Tomorrow did it because of the mission, it always starts with the mission.

The second thing is very clear KPIs. We work with OKRs in the company, so every person understands the objectives of the business at any given moment, and how the key results they're working on are connected to their objectives. Things are very methodological in terms of timelines. For example when you build a satellite, if you don't build it on time, you will be late to the launch – literally.

If you could give one piece of advice to founders to help them succeed, what would it be?

Problems grow if you don’t solve them, and they grow exponentially. So if you know that something doesn’t work, tackle it as soon as possible, otherwise you’ll pay the price of the problem plus interest.

Whether it’s the wrong person in the wrong role, market fit or the wrong investor, don’t ignore it. Deal with it head on.

And that's the Juice of It! Stay tuned for our next guest.