Stefania Olafsdóttir, co-founder of Avo, has a vast experience in the data world, being one of the builders and Head of Data Science at the Icelandic startup QuizUp. The QuizUp mobile trivia game reached around 100 million users around the world and the company was later acquired by the US gaming company Glu Mobile. Stefanía‘s work led her to dive deeper into the data-driven culture and she co-founded Avo, which helps companies make their data valuable, while reducing implentation efforts. Olafsdottir spoke with Nasdaq as part of its Founders series, which aims to talk about the challenges and rewards of founding a company, as well as what drives and motivates them.
Could you tell our audience more about yourself, your background and how you arrived at co-founding a company?
I always find it amazing to think about all the coincidences that make up your life story. I’m a mathematician and philosopher who turned into a genetics researcher who turned into a data scientist who turned into a founder. I was actually on an academic track, on my way to choose between a few offers for some exciting PhD programs, including in Berkeley in California, and Oxford in the United Kingdom. Then I got a job offer to become the first data specialist at an Icelandic up-and-coming startup. They had just released the mobile trivia game QuizUp, reaching one million App Store downloads in the first week, and were in dire need for data science at scale – which I had then been doing in academia.
I thought to myself: “Those PhD programs can wait, Stefania. When is the next time you’ll get the opportunity build up a data science division for a successful startup with an amazing group of people?” So I left my Master’s program to join QuizUp. That was a decision I have never and will never regret. We grew from twenty-something people to a hundred, reached 100 million users around the world, were backed by amazing investors such as Sequoia, Tencent, Greycroft, and Boldstart, and were acquired by US gaming company Glu Mobile. Not to mention that as Head of Data Science at QuizUp I got the opportunity to work closely with the amazing executive team and a group of almost 20 data specialists to build QuizUp’s data driven culture.
I learned that creating a data driven culture is a two fold challenge; (a) ignite the entire organization’s interest in using data to answer questions, and (b) build the infrastructure that enables everyone to answer the right questions when they need to. These are two completely different skill sets that the data science team needs to encompass; storytelling skills for internal marketing, and technical ability to build a good data infrastructure.
It was rewarding to see the cultural change as the result of our work – particularly because it’s challenging to get this right, and it is never going to be perfect. Data science culture is usually very frictional and fragile. For example, data science teams have to take responsibility for data sets that they don’t produce. They need to make sense of these data sets quickly and efficiently. They must bridge the gap between expectations from business development and product management, and the data produced by software developers. Bridging that gap can be a very hidden and ungrateful process, in both directions.
After we handed QuizUp over to Glu Mobile I received a few data science job offers in exciting places around the world, but I felt burnt out and accepted none of them. I was clearly still drawn to the subject though, because I kept on doing some consulting work for creating data driven cultures, and I started summarizing my learnings in a book, which has the working title How To Measure Product When You Don’t Have Time (good that I’m saying that in public here – it might push me to start getting some drafts out there). Despite this I really thought I wouldn’t do a lot more of data science.
Now I couldn’t be deeper into it. After exploring a few options for next steps with some great friends from QuizUp, and experimenting with a completely different thing for a year, we’ve wound up building software to optimize data science for other software companies.
We’re changing best practices in analytics – and I could never have imagined a team so perfectly equipped for it. And that’s how Avo came about; the right team at the right time with the right experience and passion.
Please give us some detail and information on your company and its products or services.
Avo helps companies build great data culture. We help teams make their data valuable, while reducing implementation efforts. We build solutions to prevent the two biggest issues with data: when it’s incorrect and when it’s irrelevant.
Good data allows companies to understand their users, build better products, and make right decisions fast. That’s why companies invest heavily in tools to analyze their data, process it, visualize it, and build dashboards. They hire highly paid experts for analytics, and developers take precious time off product development to implement the analytics. But there’s something missing still. We continue to fill databases with broken data that data scientists waste 80% of their time fixing. And then they leave their roles because they’re frustrated. And developers who generally like coding, for some reason view analytics implementation as a tedious chore.
The analytics ecosystem is complicated; there are hundreds of amazing companies out there focusing on data output and data processing. But no one has solved the input part yet. And while we continue to create broken data as input, it will always be hard to deal with the output.
Avo’s novelty is to nurture the input of data. We build products that help teams build their analytics architecture. We focus on developer experience, to give software developers instant feedback that their implementation is correct. We reinvent the implementation process, so it takes a fraction of the time it used to take. Avo enables companies to prevent their data from being broken or irrelevant, making sure that analytics platforms for the data output are worth the investment.
Our personal passion is to enable developers and data scientists to focus their time on the most valuable and rewarding things; building good products and ensuring good decisions fast, instead of wrangling analytics definitions and hunting down data bugs.
What is your typical day like? (e.g., What time do you start? What are you daily activities?)
I wake up at 6:30, make a cup of coffee and take it back to bed, read my newsletters, do some writing, and complete some tasks before meeting the team at the office between 9 and 10. Except every other day is exercise morning – when I meet a group of people at 7am and we do body strength and flexibility movements together, to keep our bodies ready for whatever physical challenge we might meet. Like playing outside, or falling on slippery ice without tearing a muscle or breaking a bone.
Sometimes I don’t wake up this early, though. I’m actually an evening person attempting to be a morning person. Because if I allow myself to work very late, I tend to accidentally stay awake and focused throughout the entire night, making my next day suboptimal. I also like to organize morning meetings, rather than breaking the day in parts for meetings – and I find it hard to make sure I’m able to show up for those if I don’t maintain a routine. So I’m trying to turn myself into a person with a sleep routine.
Independent of when I wake up, I like to start the day with making coffee. Not for the coffee’s sake, but for the sake of the routine of knowing how I’ll spend the first 15 minutes of my day. Then I don’t have to think during my first waking moments. It makes it easier to “just wake up”.
When I show up to the office I re-organize my task list to make sure its priority makes sense. That’s usually distracting because then I remember so many things I should be doing. I try to choose the most important things to do that will have the highest impact for Avo’s success. The team does a daily at 10am, and then we go on with our projects. My daily activities include a bunch of different things, like emails, presentations, excel sheets, online research, customer communication, sales, maintaining a relationship with potential future investors, making contracts with customers or contractors, planning the next travel, meetings, or whatever might come about. We also do a lot of brainstorming, so we talk to each other a lot through the day; about the product, project architecture, prioritization, customers, etc. We eat lunch together at 12 and then play a game of foosball. Then back to work. I leave the office between 5pm and 6:30pm, depending on whether I have a meeting somewhere after work, or whether I’m going directly home for dinner.
I live with my favorite person in the world, and we meet people for dinner as much as we can, to grow our friendships and family relationships. Then I try to be in bed before 10:30pm. But I almost never am. I’m usually asleep around 1am.
What has been the most rewarding point in your work founding a company?
I think two things.
One, the team is amazing. We are close and work extremely smoothly together. It’s particularly great to work with a small high performing team on building something that we are all super passionate about.
Two, it’s an absolutely crazy feeling to build something you believe in, release it into the world, and find out that other people, on the other side of the world, have not only heard of it, but that it solves their problems too. This experience will never cease to amaze me.
What has been the most frustrating point as a founder?
Juggling many different balls is hard. There is a constant feeling of outstanding tasks, so it’s very hard to check out. It also means it’s hard to enter a flow state without suddenly being pulled into another role, either by your own brain or by an external trigger.
But I simply see this as a challenge to fix. I haven’t learned how to, yet, but I’m sure I will. Especially being surrounded by such amazing coworkers and advisors. It’s precious to have a network that you trust to give you advise to overcome stuff like this.
How do you develop or cultivate your company’s culture?
Through inclusion, openness and sincerity. We do retrospectives every week, where we go over the ups and downs of the week, on personal and professional levels, and create action items that make sure we are constantly improving ourselves and the way we work. That includes improving the company culture. When we have frictional moments that we have not dealt with before, we do specific retrospectives on those moments, to make sure we know how to deal with that type of friction the next time it comes up.
We try – but don’t always succeed – to have a clear short and long term goal at all times, so that we can always ask ourselves if what we’re working on is the most important thing. It’s an artful balance to be able to separate urgent things from important things. Most often they are not the same.
What is the most important management or leadership skill needed as a founder?
Listening, rallying people together, confidence, not being afraid of confrontation, and probably most importantly; the ability to separate urgent from important.
Separating urgent from important is something I had to learn how to do when building an efficient data science team. Data science is exploratory by nature and there can easily be a week of work behind a seemingly simple number. Which is why the data scientist’s most important aspect is being able to separate the urgent need-that-number-right-now requests, from the important projects. That means being good at estimating the impact and effort of answering a question – which requires always having the high level goals and business objectives in mind. And de-prioritizing a data science challenge can be particularly annoying when it seems like it would be a really fun week-long deep-dive flow-state hack project.
Separating urgent from important at a startup is particularly hard, for two reasons. (1) Understanding the business objectives is hard, because they have many dependencies, there are many unknowns, and they can change very rapidly. (2) It’s a greenfield of fun ideas to pursue. It can be hard to de-prioritize some of them.
What is your favorite app or the most utilized app on your phone and why?
My favorite app might be Instagram. I like peeking into people’s lives through Instagram stories. Spark is probably my most opened and used app. I send a lot of emails. According to my battery usage, though, it’s Spotify, Overcast, and Audible. I listen to podcasts and audiobooks on my commute, and listen to music when I focus.
What book are you currently reading and what is interesting about your choice?
My bedside has the Paper Girls comic series by Brian K Vaughan, and a couple of Icelandic poetry books. This is rare for me because I mostly read non-fiction, and often even find it hard to justify taking the time to read fiction – except when I’m vacationing. But since I co-founded Avo, I have a hard time thinking about anything other than Avo. I tend to have a hard time falling asleep in the evening in general, and it’s increased after Avo. So I had to find something to take me to another world, during the last few minutes of my evening, to make sure my heartbeat and thoughts slowed down enough for me to fall asleep.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.