How (and Why) to Create an Incubation Team
By: Nate Nichols
One of the best parts of my job at Narrative Science is leading our Incubator program. Like other successful software companies, NS has a constant focus on making our products more valuable to users. A major component of this is maintaining a roadmap of potential features and improvements, informed by research into users and customers. A laser-like focus on the most valuable thing we can provide next is critical but also introduces the risk of missing the forest for the trees. Ideas that are experimental, likely to fail, or hard to reason about can be difficult to accommodate in a model focused on continually adding incremental value. Of course, it’s exactly these same ideas that are also often the most impactful. Besides regular company-wide hackathons, we’ve created an internal Incubator program specifically to explore these types of ideas that are too risky or undefined to slot into a roadmap.
About the Program
Our program has existed for a year and has heavily influenced our thinking, our roadmap, and our strategic vision for the company and the types of value we can ultimately provide our users. Our Incubator team members are also inventors on over a dozen patents coming out of this work. Not bad for a team of 2-3 people! I’ve thought about what has made our Incubator function successful, and I believe there are ultimately three things required.
3 Key Ingredients for Success
The first is that everyone, from the C-suite down, needs to be aligned with the goals of the Incubator function and what success looks like. The goal for our Incubator program is to clarify and de-risk what our products are and how they work 6-18 months from now, and our success criteria are defined with that goal in mind. We do *not* judge success by whether a project “worked” or whether we have a cool demo to show customers. (Although those outcomes are certainly appreciated!)
Instead, the Incubator is judged by whether it gives us a better understanding of what types of value we can provide users a year from now, and inform us as to how we get from here to there. Oftentimes an idea or approach failing can be just as instructive as one succeeding.
Of course, keeping a dedicated group of people working on ideas that might not work requires a lot of trust from senior management. I’ve found the best way to maintain this trust is by tying everything we do back to value to our users. We don’t take on projects because they’re neat or fun to work on, we take them on because we believe they may provide huge additional value, despite not knowing enough about the idea or approach to slot it into our ongoing roadmap.
The second critical component is having the right operational model. For us, that’s two-month long projects, built by a stable team of Incubator personnel. For each project, we also include an additional domain expert. This is typically an NS employee who has expertise in areas that are particularly relevant to that particular project (e.g. machine learning or data science). Besides bringing a lot of focused expertise and experience to the project, it also gives the domain expert a break from their typical work and lets them have a lot of impact on a more exploratory project.
Our operational model also includes relaxing our usually strict engineering requirements. Our Incubator projects focus on the risky or unknown parts of the problem we’re tackling, so concerns around coding best practices, browser compatibility, usability, maintainability, scalability, etc. are set aside. We know how to do those already, and it’s critical that the Incubator spends as much of our two-month long development cycles pushing on the parts of the problem that we don’t know.
The third critical component is having the right people on the team. Being successful on the Incubator team requires a willingness and ability to move quickly, work with a large amount of uncertainty, and avoid getting bogged down in minutiae. Not everyone has these types of skills, and not everyone is interested in this kind of environment. The key is to find the people who do have these skills and who are interested in this environment, point them at big and poorly understood problems, and then stay out of their way.
It’s easy to think of an Incubator program as a “nice to have” or something your company can afford to support at some point in the future. In some industries or at some companies, that may be the case. But at Narrative Science, we’re working to fundamentally transform the way people understand the data that’s important to them. With a goal that big, we can’t afford to focus 100% on the next piece of incremental value we can provide. To truly serve our users, we need to keep one eye on the horizon and always be working to understand the value, capabilities, and experiences we should be providing in a year or two.