By Peter Bailis - June 22, 2021
Sisu’s mission of Operationalizing the World’s Data isn’t possible without major investment in our product and core user experience. Steering our product strategy and investments is Berit Hoffmann, Sisu’s Chief Product Officer.
Berit and team are on a roll – in the first months of this year, Sisu landed a complete redesign of our product’s core user experience, launched industry-first features like Smart Waterfall Charts, and charted an ambitious path forward for the future of data in the cloud.
To reflect on these recent successes and her first 18 months at Sisu, I asked Berit to share a few thoughts on her path to Sisu, what she’s learned over her time at Sisu, and where she wants to take the team going forward.
Ultimately, I was excited about the massive opportunity we have at Sisu. We’re building on an explosion of both the complexity and dimensionality of data, and it’s inevitable that with access to so much more data, the way people use and extract value from that data has to evolve. Sisu is in an incredible position to shape and drive that evolution.
I also got excited about the chance to bring together world-class technical innovation and human-centered design. We have the underlying technology built off of your research at Stanford, which the team here has carried forward to create a robust, ML-driven engine that can analyze data at today’s unprecedented scale and complexity.
At the same time, Sisu has a real commitment from the top down to build a world-class, intuitive product experience grounded in insights from user research. We’re reimagining how to drive better decisions with data, acknowledging that analysis is only one part of a multi-user, multi-step decision-making workflow.
When you combine that with an excellent team on the Go-To-Market side, I wanted to be a part of this opportunity to bring a new product experience to market and get sophisticated and impressive users engaged with Sisu.
I’ve definitely learned a lot of the past year and a half, but three things stand out:
First, I’ve realized that every startup is different. There are common types of challenges and problems when I compare Sisu vs. the early stage at other companies I’ve worked at, but the way you end up solving those problems is unique. We have to figure out what works for our team, our culture, and adjust to that. I think that’s been a fun experience but definitely a learning experience as well.
Second, I’m continually amazed by the amount of innovation in the data ecosystem. I knew coming in that it was a space undergoing a lot of change, but I’ve developed a deeper appreciation for just how much innovation is happening across the data stack at so many different levels. From storage, to pipelines, to data modeling, to data observability. There’s so much happening in this space, and it’s been exciting to learn more about that and dig into it.
Finally, I’ve learned so much from our customers. I knew intuitively that customers would be at different stages in their data journey. Still, it’s been interesting to see just how much variability there is in the data maturity of different companies – from just beginning to invest in data infrastructure to those in the middle of migrating to the cloud, to those who seem to have been data-focused from day one. It’s been intriguing to see the different ways companies value and think about data, and in particular how those that have really invested in collecting and setting up the infrastructure to use their data can move faster and make better decisions.
There’s a lot I could say here, but my main advice is to put the user first, and all else will follow. You need to be hyper-focused on getting in front of customers and prospective users as you build your product. It’s easy and tempting to fall in love with your own ideas or your team’s ideas, and while those may be great, they often need to be evolved and tweaked. Talking to customers and grounding your ideas in their feedback and needs will guide what needs to be adjusted.
For building early-stage product teams, it’s about looking for people who don’t just navigate ambiguity but thrive in ambiguity. They need to love big, nebulous problems because every day early stage product teams are thinking through an enormous amount of open-ended things.
To start, I want to ensure we uphold and accelerate the velocity of enhancements and additions to the product we’ve delivered so far. We did a pretty significant redesign that we launched in February that was an opportunity to rethink and improve the usability of Sisu, but it’s also intended to be a foundation to build on by increasing the velocity of what we’re adding to the product. Being able to execute here will be critical.
Second, I want to be thinking longer term. As startups grow and begin to get more traction, it allows you to constantly be pushing your thinking a little bit further out. I’m looking forward to spending even more time on the long term vision of Sisu and partnering closely with the Go-To-Market team to determine how Sisu needs to evolve to support those strategies.
In our user research, one thing that’s become incredibly clear is that so many of the tools people use for analysis were not built with collaboration in mind. Yet, data analysis and the decision-making process is an inherently collaborative, multi-user process.
To realize our vision of making Sisu a decision intelligence engine, we have to take this opportunity to make that collaboration process easier and facilitate discussion and decision-making. For our product roadmap, that may mean meeting them where they are by working in general productivity tools or building within Sisu. This focus will shape both what we build and where we integrate.
In the next five to ten years, I think the most significant shift will be that people won’t necessarily see analytics as a separate industry – analysis will just be a part of what you do with your data. We won’t see as many products that “just do analytics.”‘ Instead, it will be much more about what comes after the analysis – whether that’s driving towards a decision or acting on an insight. We’ve historically thought of analytics just as the process of doing an analysis. Instead, the goal will not be analysis but rather taking action.
Additionally, I don’t think this will be an industry where suddenly technology replaces humans. Instead, it’s going to free up time for analysts and data engineers to be more of that human-in-the-loop with business expertise, enabling those roles to be increasingly strategic.
I’m also hopeful that we’ll continue to see more and more women in the data world – whether they are building data products or leading data teams. In fact, one of our recent customers has an all female data team, which was pretty awesome to see.
There are two things I would share. First and foremost, seek out other female mentors and sponsors. Find companies with female leaders who can help you navigate – and they don’t just have to be leaders in product. Some of my mentors, particularly female mentors, have been in other functions. Finding places where you have strong women you can learn from and lean on is incredibly important and beneficial.
Second, it’s essential to figure out what is authentically “you” in terms of your strengths and your ways of interacting with people and really own those. It can be easy to second guess these things, especially with articles that say things like, “You shouldn’t do this or don’t say sorry too much or don’t talk like this, talk like that.” This advice can cause people to get in their own heads, and it’s essential not to let how other people think you should act get in the way of how you are leading. The most authentic and compelling leadership style is going to be whatever is authentically you.
One thing we need to do to get more women in product-facing roles is to start by changing our expectations of who can be a product leader. Especially in the valley, I think sometimes we have a concept of what a product leader needs to look like – it has to be that they studied CS and attended certain schools or took particular courses. I don’t totally fit that mold, and it’s something I avoided letting people know at the beginning of my career. I didn’t tell people I was a History and Economics major because I knew that I wasn’t “supposed” to be in product. I’ve been lucky to find a way into product and learn on the job.
The reality is, there are so many different types of skills that make people great product leaders, and they’re not all technical. If we can broaden our view of what a product leader can look like, it opens up the aperture for the types of people you can hire.
My favorite trivia topic definitely has to be that I can answer any question about Law and Order SVU. I’ve seen every episode, more than once, and it’s my dream to be on the show as an extra.
Interested in joining Berit’s team to help build the technology and systems that will help every business make the best possible decision with data? We’re hiring!