The Center for Data Innovation spoke to Ondřej Tomas, co-founder of CleverMaps and CleverAnalytics, a Prague-based data visualization company.
This interview was published by Center for Data Innovation. Full post can be found here.
Nick Wallace: CleverMaps maps out companies’ business processes. Can you tell us a little more about the activities you apply this kind of visualization to?
Ondřej Tomas: When we started CleverMaps, we didn’t really know what areas we would focus on. We just started organically, and over time we developed solutions for various types of customers. One of the first groups that we worked for, and that we had solutions for, was agriculture. That includes both farmers running agricultural businesses as well as the landowners who lease the land to the farmers. The second area is large infrastructural projects and construction, like roads and pipelines. That also grew organically — we’d worked with those companies before. We also work with utility companies, retail banks, insurance, companies, retail outlets, and e-commerce firms.
We started about four years ago. Our goal was easy-to-use maps for business users. That’s why we called it CleverMaps, because the maps were supposed to be clever, not complicated. We wanted simple, straightforward clever solutions for end users.
Before this I worked for a mapping company where we gathered all kinds of location data, including aerial photography and so on, and earlier I worked for IT companies. I always had a feeling that there was something lacking — I never really found an easy-to-use mapping tool. For example, when I was working for an insurance company, we were dealing a lot with locations, and all that existed was geographic information systems (GIS). We really struggled with that in our business analytics department. So I felt that this was a space for improvement.
Wallace: Can you give an example of something unexpected that you’ve found through this kind of analysis?
Tomas: This happens all the time. Most of the surprising examples come from our CleverAnalytics location intelligence solution, where we work for banks, insurance, e-commerce and so-on, where we work with lots of interesting stuff. Very often our clients ask questions like, “we are successful right across the country, except in this one city—why?” We had a bank with that problem; they also had a city where they were very successful, and didn’t understand why. In either case, you need to understand the situation in order to manage it, and that’s where we come in.
Wallace: How is this different from GIS? What other data are you drawing from, and why?
Tomas: GIS solutions are built for GIS experts and analysts. You really have to have a person who knows how to work with GIS. He has to understand the location data, he has to understand how to build layers, he has to understand how to run queries in GIS, and so on and so on.
For example, energy suppliers usually have a large GIS department of their own, with say 20 to 30 people, who are running their own analysis based on GIS. All of these people are experts, and if they finally come to a conclusion, they build a certain picture which maybe they later on can send to management in the company.
But we’re building software for the end user, letting them view problem directly, but without requiring them to play with building or combining layers, because this is not something a normal user would understand or know how to do. The average person doesn’t know how to work with datasets, how to normalize them, which ones they can combine. We’re building solutions that utilize the map, but all these complex tasks are done in the background of the software. They’re prepackaged solutions doing very specific things, so you know what the software is doing, but you understand the outcome. It’s business end-user targeted software, not a tool for experts.
In our development phases, our people do work with some GIS solutions. Our software has a location database with the specific extensions and so on, which can run the queries, but all those processes are already pre-packaged and automated. The user just gets the result. With GIS you have to know how to cook the meal, we give you the ready-made hamburger.
When we started, we were working with over 100 datasets, we were testing and trying everything out, and found that we kept coming back to five basic ones, and built our model on those five, and then we add extra data sets when something is needed. The five datasets are census and demographic data, roads infrastructure and traffic flows, public transport data—because that gives you very precise information about the flows and concentrations of people—data about buildings, which we combine with the demographic data, and points of interest with relatively detailed information about them—for example, if it’s a hospital, how big is the hospital, and how many patients does it have capacity for?
Wallace: What benefits do companies get out of visualizing their activities like this?
Tomas: In terms of the location intelligence software, it’s the context. It helps you to understand why a particular thing is happening. If you are planning to roll-out new automatic teller machines (ATMs), and you’re getting into new places, you want to understand why the existing network is the way it is, why it succeeds in one city and fails in another one. It’s all about context.
The other benefits are mainly about reducing complexity, especially in farming. It saves a lot of time by automating basic bureaucratic tasks in large volumes, and it avoids unnecessary mistakes and errors that can cost a lot of money in fines and lost subsidies. We were able to reduce construction times in some infrastructure projects by as much as 30 percent, by mapping out the relevant information and automating processes.
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