Data meets geography at Esri, a billion-dollar company whose mapping technology enables feats like predicting flash floods, managing supply chains in real time, and cutting disease outbreaks off at the pass. Some 350,000 customers around the world in disparate fields ranging from oil exploration to city management use Esri’s GIS (geographic information system) software to layer data over maps and conduct spatial analysis.
Jack Dangermond, cofounder of the Redlands, California–based company, and CEO since 1969, described his business now as the “science of where.” He has managed Esri through every tech cycle, from mainframes to the cloud. Here, he discusses how mapping solutions turbocharged with real-time data and cloud connectivity are guiding today’s organizations toward better decisions, and how this geo-mapping giant of a company is plotting a course for the cities of the future.
Technology has always played a role in how people run organizations, but recently that process has accelerated. What’s so different about today’s technology?
It’s real-time and connected. The planet is being wired up. Sensor networks like the internet of things means that everything that moves and changes will be measured. Everybody will be connected. I’m more excited about what we’re doing right now than at any other time in our history.
And what role does mapping play in this evolution?
For us, there is a huge transformation that includes leveraging real-time and big data, richer analytics, and moving to the web and the cloud. We have about 1,000 real-time servers in utilities, transportation companies, and government, which are measuring information flows like movement of vehicles. “Smart” connected cities are a new and fast-growing market for us. In Dubai, which wants to be the “smartest” city in the world, our technology will integrate real-time data into everything from energy use to social media to traffic.
Data is often hailed as a magic bullet, but the reality is more complicated than that. What challenges does the tsunami of new data present?
The challenges lie in analyzing the vast amounts of data that are being produced by these new technologies. If I have a hundred points of, say, banking transactions, I can very easily see patterns on a laptop. I can do 1,000 points, even 10,000 points, or, through spatial aggregation, 100,000 points. But when I get to a few million, I’m lost. From a visualization standpoint, you can’t do it. The computational time could take weeks.
So what’s the solution?
What we’ve done is put very large spatial data quantities in multiprocessor environments. We basically jumped the chasm between providing customers space on a single server and tapping into the broader “cloud” of networked servers. We can now analyze very large volumes of data, in the hundreds of millions and billions of observations, or tens of thousands of images from spacecraft or aircraft. That also means we can display 3-D very easily. Our government and real estate customers, for example, can allow someone halfway around the world to remotely zoom in and look through rooms and buildings or entire cities from one of our servers.
What does this look like in practice? How do companies use tools like these to make better decisions?
Maps are a way to create and communicate understanding very rapidly, but they are just the beginning. The thing that is extraordinary is the spatial analysis behind the maps. You can see relationships in space—what’s near what, what’s on top of what, what drives success.
Package delivery firms, like UPS, and trucking companies are using spatial analysis to make logistics more efficient and are saving millions of dollars. Large retailers like Starbucks are using GIS to do site selection with machine learning. With this technology, they can lay out their existing successes on the map, overlay that with other layers of geographic data, then perform advanced statistical analysis that can guide them toward the most strategic places to locate new stores. We have a base map for the whole world with hundreds of layers of authoritative data, everything from geology to climate change and demographics. That complements our users’ information.
Is this a new business segment for Esri?
We’ve been doing this kind of analysis for some time, but the new analytics tools and the ability to easily interact with very, very large data sets of demographic and consumer data is making this very popular among retailers and the real estate community. Business is one of the fastest-growing areas for us.
As demand for this sort of analysis increases, how do you stay ahead of the game?
Part of our success stems from not alienating our customers. We invest in things our users need and want, not just flashy stuff. Our software has an evolutionary architecture, and we spend a lot of money coming out with new releases that go out to our existing customers. We spend 27% of our revenue on R&D. That’s more than five times what Apple does, and more than double what Microsoft does. We partner with big companies and startups alike, and we think of them as colleagues, rather than try to reinvent what they’re doing.
Where do you see the industry heading next?
Mapping is becoming a platform rather than a focused technology. For example, Shell Oil went from a few hundred users—geospatial technical people involved in exploration—to thousands of people across the organization who can look at the maps other teams are making, make some of their own, and do analytics.
There is a vast and growing community of users who are committed to this kind of information system—using it, sharing it, and applying it in various ways. There’s a culture of collaboration that’s emerging. It feels like we’re just a drop in a river that’s moving very quickly.
This article was created for and commissioned by Cognizant.