Alumni Spotlight: Peter Szaflarski (MBA'12)
Updated: Dec 15, 2020
This week on #SpotlightSaturday we focus on Peter Szaflarski, one of the founding members of QUAAF who completed his MBA at Queen's and then went on to be a leader in Data Engineering at Thomson Reuters. Read more about how he came from a mathematical background and found his way into the world of technology.
Give us a quick summary of you, your background prior to the MBA, and current role at Thomson Reuters. My background before my MBA is a pretty winding road. Before my MBA, I had a math and stats background from UofT and worked in the construction consulting industry, on the electrical design side. I got there mostly because my dad was already in the industry and I needed a job, but I wasn’t applying my math and stats all that much. I did my MBA specifically to transition into something more business-related. I targeted a finance-focused MBA at the time because math and stats fit into that. That’s where I was charging toward and where all my focus was.
Post-MBA, I got a job in private debt, but I wanted to transition into doing more tech, so I joined a start-up and started doing some predictive analytics on the acquisitions side. That eventually led me to getting into Data Engineering, which also fit really well with my stats background, and that’s where I am right now at Thomson Reuters. I’m applying my math and stats background and my experience from smaller tech companies to a bigger company.
Tell us about your experience as part of the founding team of QUAAF. What did you envision for the organization you originally created and looking ahead to today, what are your thoughts and opinions on where it is now? I think my original idea for QUAAF came mostly from the fact that QUIC existed (the undergrad counterpart), and it didn’t make sense to me that for a program that is only one-year, and one that helps people with a career change, that there wasn’t something running parallel with that.
I’m very happy to see where it’s going. When we started it, we only had a one-year timeframe; we were running as fast as we could to get something together that was presentable and that we weren’t embarrassed about. It went pretty well, but we left a lot of edges very rough. We had to trust that the years after us would take that up and smooth those edges, maintain the relationships we built, and make it stronger. I’m really happy to see that not only have people picked up that torch but have also evolved it into something that is a lot more polished and a lot better since we started it. It’s really brilliant. It’s awesome that QUAAF now has MMAs and MMAIs and is looking to find those synergies with the new programs. Very early on, we had the MBA and MFin programs together. I remember that the MFin program for a time was dominating the QUAAF team, which makes sense to have finance-focused people taking an interest in it.
The intersection of analytics and finance, what are your general thoughts on the trend of these industries becoming closer and closer, and how its changing given that you’re right in the middle of it all? That is a huge question… It’s difficult to answer because, given that you guys probably interview hedge fund managers and the like, they are some of the most interesting people to get an opinion from. The big thing to do when talking is to really take what they’re saying with a grain of salt. For the most part, they’re running a small business and they’re trained to pitch their view of the world. Every one of them is right 100% of the time when you listen to them, and they’re usually very smart and focused people. It’s a really interesting way to get contrarian takes on what the industry is doing, where the industry is going, where the trends are, and so on. Fund managers have cool views on it, but my personal view is that they’re all wrong.
It’s a really interesting way to get contrarian takes on what the industry is doing, where the industry is going, where the trends are, and so on. Fund managers have cool views on it, but my personal view is that they’re all wrong.
If you look at the way that we model things using stats and regression and all these tools, these are methods that the whole industry jumps on to. Once we apply these methods, there are things that are outside the model that we don’t understand and can’t predict i.e. the edge cases and the “black swan”. That black swan ends up rearing its head eventually. The interesting thing though is that as our models get better, our predictive analytics get better, and our data science gets better, that probability of that edge case happening becomes smaller and smaller and smaller. The impact of it though doesn’t necessarily get smaller.
I think what we’re seeing right now if you look at markets, other than the coronavirus blip we’ve been getting, markets are effectively at an all-time high these days, and people are also predicting a recession, but no one knows when it’s going to happen. We are seeing that heightening of both edge cases. When it hits, and I can’t say when or where it’ll be, I feel that the severity of it is not going to be diminished because we have these models. We’ll find that the edge cases just happen less frequently. Does that make sense for the way I see the way things are going, given the data and so on? The thing about the edge cases is that it’s really hard to see them coming, but that’s the whole point. As soon as someone calls it out, it loses its power. As soon as someone says, “there’s going to be a recession because of x”, that changes the game immediately. That person making the call is a player in the game themselves; someone who calls out that coronavirus is the blip that causes the downward spiral causes people to 1) incorporate it into their models, and 2) prevent against it, so take measures to downplay and mitigate it so it doesn’t happen.
It’s a lot like the MBA finance question where there’s a stock and that company presents earning which are positive - will the stock price go up or down? The answer is that it doesn’t matter – it matters what the analysts and investors were expecting. When it comes to the coronavirus and people predicting it is the edge case that will cause our recession, that prediction changes the market; the recession will be caused by something people are not expecting, because if it is expected, our bases and models will adjust to it. That’s why model building is so hard, and sometimes presenting [the models] too. If you’re presenting a model that shows you what’s going to happen in the future, a lot of the time it’s a very uncomfortable place to be because you have to know that your model isn’t 100% predictive and you won’t know what’s happening in that unpredictable area. The people you’re talking to, or pitching to, have to be comfortable with that, and a lot of the time they aren’t.
Given your math background and the path you took, for those of us wanting to get an edge and strengthen the more quantitative side of our thinking beyond the MBA or MFin curriculum? It’s not the first time I’ve been asked that question, but I can tell you what I’d like to see, and it probably won’t be what everyone else wants to hear. For me, the most important thing is what you do in your spare time. If I’m having a conversation with you and I see that in your spare time you like to go skiing. That’s awesome and I’d love to do that as well, but why aren’t you telling me what’s relevant to the work you want to do? What I want to know, or hire, is someone who’s passionate about the things that they’re doing. In my mind, there’s no substitute for sharpening these skills other than just working on them and loving that you’re working on them. For example, have you built predictive models in your spare time? Do you trade on your own, do you have your portfolio? Do you like to talk about or debate it? There is no substitute for the fact that the person I think that’ll be sharpening their skills really well is the person that I’d like to hire. They do that in their spare time because they love it, not because they want to get a job and finance their skiing on weekends. There is no substitute for the fact that the person I think that’ll be sharpening their skills really well is the person that I’d like to hire. They do that in their spare time because they love it, not because they want to get a job and finance their skiing on weekends.
For the current Master’s students at Smith, what would be your advice on succeeding as part of their team and how can they make the most of their one year? The reason that teams are difficult is because you have to work with people that aren’t you. From your own perspective, you’re the smartest in the room. You’re not going to say it out loud, but we trust our own opinion better than we trust anyone else’s opinion. I think the most effective teams have an understanding that things will get ugly and difficult sometimes, and people will disagree with each other, and get upset with each other, and that is okay. That doesn’t mean that you have an unhealthy team, that means that you’re passionate about a point, or your own point of view, and your emotions got involved in it.
If you know that this is going to happen going into a conversation, or going into your team sessions, then you can expect these things to happen and still come out the other side a high functioning and performing team. For any person who has to work on a team, try to instill that culture on your team of being flexible and understanding that others won’t have your point of view. Sometimes we expect that baseline understanding with most people, but a lot of the time we don’t and it can surprise you how far some people’s baseline understanding is different from yours. I think having that flexibility, trying to get to the core of where a disagreement is, makes the strongest teams.
Let’s shift gears and talk about venture. You were on the Hubba team...Mark Skapinker won’t stop talking about Hubba, and Brightspark is no regular VC fund. What was your experience on that and with Canadian VC in general? That’s a really fun thing to talk about. I know why Mark Skapinker talks about it, because Hubba was one of the very first Brightspark investments, as far as I know. It was one of the flagship deals, like his QUAAF, so he’ll probably be biased about in the same way that I talk about hedge fund managers in the sense that they have their own admittedly biased but not incorrect view.
As far as VC in Canada, it’s a tough industry for Canadians. What you’re essentially doing is managing a portfolio of lottery tickets. It’s not an established industry where there are models or excel templates you can fill out for that industry. In VC, it’s pretty much all greenfield, so the models are all completely broken. You can mitigate it by looking at some industry trends, or finding a comparable or whatever else, but at their core, they are lottery tickets you’re managing. Sure, if someone has industry experience, they can supercharge the tickets and have an edge, that’s absolutely right. The point I’m trying to make is that in the States, you have 10x the startups than in Canada, and in the States, they can be sprung up and fail in a day, and then repeated. Here in Canada, we don’t have the same kind of scale like the States. What we try to do is mitigate that early stage company failure-rate; we try to get them to succeed, so we have access to a lot more holdings for early stage companies. What that causes, and I don’t have statistics but you could probably look that up, is that in Canada it’s a lot easier for a company to get that seed funding than it is in the states. There does exist that glut of companies that make it to the A round, and then can’t get to the B round. Not everything is financing, but it is indicative of the fact that we try to push our small, early seed, angel investment stage companies up that pipe but they’re having trouble making that jump.
In the US, they mitigate that through pure scale. The question is how do we mitigate that as Canadians? There are a couple strategies around how we can do that. One of them is that our VC companies have to compete with the US companies, as we invest in the US too. This has two problems 1) US companies are very aggressive and 2) we have to manage foreign exchange risk. If you stay in Canada, you won’t be competing with the states but how would you mitigate that smaller scale? More specifically, how do you find that unfair advantage? Find someone who’s done it before, who knows the path, who has the connections. The other way what I said before to choose a company where you as the VC have connections already. You can see that happening already in the Canadian industry where some investors just go for a product that they know they can make a success and don’t invest outside of that. The big struggle for Canadian VC is that we don’t have the scale that the US does. There is an opportunity to innovate on that VC model, and Brightspark is an example of innovating on that model, making it interesting and turning it on its head by essentially trying to “democratize” VC by raising a fund for each new venture.
What’s one book, movie, tv-show, or general activity you like to do when you unwind? I’m a big fan of Nassim Taleb and his views, and though people regard Antifragile as his culmination of his best work, I still go back to Black Swan. Black Swan just gets the point across the best. I know that sounds very work-related, but it’s very entertaining. For movies, they say that you’re not supposed to mention American Psycho, since he’s an investment banker in the 80s and people who invoke it tend to miss the point, but I still believe that it had one of the best book-to-movie adaptations. It’s super interesting because the book was an example of 90s grunge writing, basically a stream of consciousness, and it was very difficult to make into a movie. The movie shouts out that it was difficult for that so names of characters were changed, themes were changed, and it was all done intentionally where it all comes together very well. I like that experience of reading the book, watching the movie, and rereading to see all the little differences. I fall asleep to Star Trek: The Next Generation every night, and I love to ski. Skiing is my unwinding activity, and I love to debate philosophy. Those are all my pastimes pretty much.