Olga Tsubiks created Data for a Cause to leverage data, story, and visualization to make the world a better place. Listen to her talk about her strategies and results turning data into change for social good.
(upbeat music) - So now it's time to talk to Olga Tsubiks who is the founder of Data for a Cause which works with NGOs and non-profits to essentially help them tell their stories via data visualization working with volunteers. So Olga, thank you very much for joining me to talking, for talking about Data for a Cause today. - Thank you for having me, great to meet you. - So I'd love to find out more about Data for a Cause as an organization maybe, you can just tell us a little bit about it, just to start off.
- Sure, so Data for a Cause will help non-profits, NGOs, charities and other mission driven organizations to tell their stories with data. The way it works, there is three steps to it. First, non-profit reach out to us with the questions, problems, concerns for any kind of data work that they have on hand. We work with them to shape the project, define the goals and objectives and really help them finalize how we will work with them, and how we will help them.
Then the competition starts. So all the volunteers that signed up for Data for a Cause, I invite you to participate. And everyone is welcome, we have volunteers from 40 countries around the world. From students to seasoned professionals, we get together to help the organization to deliver on their mission. So the data is released to volunteers and it take about two weeks to complete their data visualization. And the third step is to take the work that they've done, compile it together and implement and help the non-profit to use it and take it further.
So the competition is there to select the best data visualization work. And select the strongest volunteers among Data for a Cause, but that's not really the goal. The goal is to help the non-profit deliver on their mission. - Okay, that sounds great. So it's volunteers who are, want to support a good cause, who are doing work. And first step is to sort of win the opportunity to do that work and then they do the work.
My question I was wondering is these organizations, you know, they obviously have a lot of challenges they have to deal with. In this particular context, is it that they need help with data visualization and data storytelling primarily, or do they even need help on the data analytics side and sort of teasing out what the data is even saying? Or is it both? - Right, it really depends on the non-profit. For the most part, they lack time and skills within their team.
Sometimes, it's both. So if the non-profit is helping with education of children in Africa, for example, then they're busy with building schools and delivering on their mission and not necessarily focused on collecting the data and hiring the data analyst and data visualization developers on their team full-time. But there are other cases too. So sometimes it's a way for them to brainstorm how they can look at their data better and use their data better.
So you're really going in and dig for the insights and sometimes it could be attracting attention to the data they collect. For example we worked with Institute for Economics and Peace and what they do, they produce indexes to help governments and non-governmental organizations make decisions. So for example they produce terrorism index. And it's really hard to take a picture with to show it on the website.
It's a data that's the core of the organization so data visualization is really a great way to put something visual in front of people to help them continue on their mission. Sometimes they need help with analysis and visuals to put in their end of year report to show to their stakeholders, to prove their income and apply for the next grant for example. - Yeah, yeah so sometimes their mission is data, as you mentioned.
Sometimes it's to raise money, sometimes it's to communicate around a cause and try to maybe you know, light a fire. It's like a campaign I imagine. When it's that category, actually campaign driven, data communications, I was actually looking at some research recently about persuasion. And you know there have been studies that have shown that visuals can be more persuasive than tables of numbers, for example. But one study I was looking at recently pointed out that when your audience is hostile to your content, that you're actually better off not providing data visualization, you're actually better off providing the raw data and tables and numbers.
Because a hostile audience is more likely to question you. So I was wondering you know, how you deal with that. Whether you come across that with some of your clients for Data for a Cause. And you know, what their strategies are in doing data visualization, especially in a more politicized, you know, fraught subject matter. - Yeah so I don't disagree with that study. It really depends on the data too. If you can summarize your message in a nice concise table and it would make sense to the viewers, then it's, tables are appropriate.
And we do have a lot of tables in our work. We do use tables, but for some other cases, it's challenging to look at the very large table that has a lot of categories that has lot of data in it. So in this case, we have to use other ways to visualize the data. So to give you a few examples, we worked with Global Fishing Watch recently.
And we helped them visualize illegal fishing around the world for the whole globe. So the data that they have is robust that showing it on a, as a table wouldn't make sense because it's just too much information. And the viewer wouldn't be able to absorb it as efficiently as showing it on a map or showing it in other ways that could really help the viewer to absorb the information.
So it's all about absorbing the information and looking into the details. - Yeah that makes sense. So one thing I wanted to ask you was you know, I really like the format that you follow in terms of using, you know, finding volunteers who then compete in order to be chosen by these organizations. And I know it's not crowd sourcing, these organizations actually choose the winners themselves, and I guess what I'm wondering is organizations like these are looking for help in a particular way.
And I'm wondering if you've seen any trends, if there are any insights into what kinds of work are tending to win these contests. Like what kinds of things are these organizations looking for, maybe repeating patterns. So that people who want to do work for a cause maybe sort of know what types of things are successful, desired, etcetera. - There are definitely some things that are common among all the visualizations that came close or won the competition.
One of them is using the best practices for data visualization. So clarity of the message, design of the visuals, this things are really important and they come across naturally to the non-profits. The non-profits that are looking at our work, they aren't always the data visualization designers big trait. But they know when they see a good design, and they know when they see the clear message.
And it's easy for them to understand. There are other things as well. So when volunteers are work with the non-profits, they usually don't know, didn't know what they were before they started working on the project. So the most successful visualizations would be coming from the volunteers that really went through all the information about non-profit that they could find on the internet.
They've really researched and understood what it is they're doing, read their blogs and things like that. So they really absorbed everything they could about the non-profit and include it into their visual. So it's important to understand what data you're working with, and we are helping with that by providing additional information and sending links. But the ability to absorb that and then show it in the data visualization is a skill of its own, understanding your client.
And non-profit in this case is sort of a client. And looking at their audience and thinking how they think and how they will see the information is a skill that is rare and something that most of them try to learn and perfect. So really not just getting the best visual out there, but getting the visual that would communicate the message, help the understanding and really take it all the way.
- Yeah that's a great answer. I mean, it makes perfect sense. I was actually going to ask a follow up question about skills to develop but you just said it all because you know, first of all, best practices matter. And I think it's a very good point that even non-professionals, they recognize good stuff when they see it. They recognize flaws when they see it, even though they might not be able to necessarily define what the problems are, but they know best practices maybe intuitively. I think it's also a very, very good point that you make that the best design across the board, nevermind data visualization, but really all design, is when you understand your client, and when you understand what they're doing.
And so that consultative process, I find that's the thing people sort of miss the most. It's like really try to think about what you do and understand your audience on what they're trying to do and if you do that, then your output is going to be 100 times better. So thank you for sharing that. We're actually out of time but I did want to thank you very much for you know, joining me here in this conversation today. I know that people who do this work, you know, obviously they love data, obviously they love communications and you know, many of them want to do important work that helps humanity.
I thank you for the work that you're doing to do that and I really appreciate your talking to me and help me share some insights for our audience who wants to do that as well. So again thank you very, very much Olga, for joining us. - Thank you Bill, all the best.