The original inspiration for Saberr started from my studies in Harvard business school. I was a student of a professor who’d done a lot of research about why start-ups succeed or fail and his research pointed to the fact that in two thirds of cases the failure could be traced back to team dynamics. My background is in aerospace engineering, I like to think fairly logically about things, so it didn’t make much sense that this was the leading cause of failure when who you work with is one of the few things you have control of in a start-up business. I started to dig into what is it that makes people work well together. Can data start to shed a bit of light on this so that we can make some predictions to help avoid mistakes? That was the original genesis.
From there, we started researching ways that you could measure relationships using data. We started with online dating, looking at millions of profiles to see if we could spot patterns in the data of successful matches. We defined a successful match as two people who meet online and then close their accounts because they’re in a relationship with each other. It turns out that there were a bunch of data points that could predict this shift, but it was around things that classical psychology wasn’t really looking at.
Of course, on their own, individual data points relatively meaningless, but when you add up a whole bunch of these little indicators, we found that we could have quite a good capability in predicting good quality relationships between people, but we wanted to apply it to business and the commercial world. We stripped out as much of the romance as possible, and combined it with some of the more consistent theories from academic behaviour research, things like - for a team with a broad range of tasks, it’s beneficial to have diverse personalities. We added all of these things together and we first tested it on a start-up business competition at the University of Bristol. We looked at the 8 teams to see if we could predict which team would win the competition without any knowledge of their skills, their experience, their demographic or the idea that they were working on. All we did was send them a little online survey, our software then ranked the teams from predicted best dynamics to predicted worst dynamics. We submitted that on the Monday, and on the Friday, our software’s ranking of the teams precisely correlated with the ranking of the teams in the competition.
This gave us inspiration to continue working on what we were doing. It’s an incredibly exciting prospect, the idea that you can start to understand the team performance, which is fundamental to almost everything that we do these days, and even predict some performance characteristics using data. That becomes a very useful and exciting prospect.
As well as the public display in Bristol where we presented our findings at the judging, we also did similar events at other high-profile entrepreneurial competitions. We were very bold with our predictions, and would make them before the results were announced. Given our ability to get them so right, it garnered a lot of interest. It didn’t take companies long before they started approaching us to discuss performance issues in their teams; things like, ‘We don’t know why some of our team members are under performing,’ or, ‘We don’t know why we’re losing great people.’
These are cases that most people would ascribe to the more intangible human element of how people work together, the culture fit, values - what are typically termed fluffy elements to team performance. They were very excited by the prospect of making fluffy things less fluffy, and starting to educate not just themselves as employers, but also the employees because we, as employees and team members, also want to have high performance at work. We want to work in an environment where we feel like part of a team, where we are encouraged to deliver our best work. So that was how we started to get that commercial traction. We started working with a range of companies from start-ups to really big companies, to help them solve some of their difficult team problems using data.
We faced all of the normal challenges of starting a company, finding funding, hiring people, getting the sales pitch right, but those we found not insurmountable at all. The challenge I think we face, and it’s actually a challenge of the whole people analytics industry right now, is that we are trying to use computers to better understand human beings. This is a novel concept, and one that is taking us as a society, time to get our heads around. It’s navigating how to deliver the analysis, and the predictions that we make, so they’re easily adopted by the people who are going to use them.
We did, of course. There are nine of us on our team, six here in London and a team of three in Belgrade, in Serbia. We used our own software to build our team, and even used it on our investors.
Our first funding round was about £1 million, and we used our software on the angels that we were considering having coming into the round. For the most part, they scored very well! We are embarking on some really interesting opportunities, and some very novel technology in a market space that is enormous. It’s important that we have the right team on board, not just our employees but also the wider team and that includes our investors. Having them on board with their knowledge, expertise, network and direction is extremely important for us, so it made sense to use our software to get it right.
We looked at a range of financing options for both funding rounds. We knew we wanted to take investment either from angels, or from a VC because we were so early, and we knew we were in a very new space of people analytics. Nobody knows where the market’s going to go, what’s going to work, what’s not going to work. We knew we were in a volatile place, so we wanted a group of investors who would be supportive of trying different routes to market and experimenting with the technology. In Europe, we found that the VC climate more focussed on revenue from a very early stage, and while we are very focussed on revenue we didn’t want the pressure of finding revenue too early. We wanted the ability to figure out where we would be able to make sustainable, long-term revenue, rather than short-term revenue. We think we’ve found that now and our small group of investors that we brought on board, being angels, all support that.
They have, we’ve made use of them in the past, and we will continue to do so. Those central government initiatives are fantastic but we would love to see more free movement of people because talent is at the base of what we are doing. Everybody wants to work with great people, and great people come from all over the place, not just the UK. I think the UK government have been supportive of the entrepreneurial ecosystem. We are in one of the best places in Europe to build a business, and particularly the tech scene in London, is an extremely fertile environment to grow an early stage business. We’ve got exceptional talent here, good finance options and a brilliant customer base.
No, Brexit has not meaningfully impacted our ability to fundraise yet. While entrepreneurs regularly seek to turn disadvantage into opportunity, at this early stage and period of heightened uncertainty there have emerged no benefits for the UK tech sector post-Brexit.
Team design is what our first product was aimed at, bringing new hires into the business, or designing internal teams to staff projects, but what we are finding an increasing demand for is coaching and development of existing teams. So, the direction that we’re extremely excited to be working on now is what we’re calling a digital team coach, which is essentially using software and data to help coach individuals and teams to work really well together. We want to start being able to coach teams using their context, really understanding not just them as people, but also the context that they’re operating in. The future of Saberr is quickly becoming a team coach to help teams at a local level diagnose and solve any challenges that they’re facing. Think of it like an enterprise grade employee engagement tool combined with a consumer grade learning and development tool.
It’s going to sound like a cliché, but I’m most proud of the team that we’ve built. We’ve got some really exceptional talent and a team environment that allows that talent to be maximised to its full potential. We’ve been operating together for three years now under enormous pressure, and we still remain extremely functional as a team, optimistic about the future of what we’re doing, and very excited to work here.
Advice is a difficult one because it really depends on what you’re doing, and what you’re trying to achieve. The one thing I think works universally is persistence. If you can find a way to survive, and you’re still excited for what you’re working on, you will find the answer. If you can just have persistence, then you’ll make it.