Startups vs. Academic Research Groups: FIGHT!

There are many similarities between startups, defined here as (relatively) young and agile companies with a few bright people trying to change the world by working on some cool idea(s), and academic research groups, defined here as (relatively) young and agile units within academic institutes with a few bright people trying to change the world by working on some cool idea(s). Err, yes.

Fortunately there are also many differences, so I have something to write about here. For some years now I’ve been running the TU Delft Medical Visualization research group, an experience that shall serve as the primary source of information for this piece. I’ve also had some experience of startup culture, first as one of two (and later three) engineers in a new business unit of Crusader Systems (now CSense) designing an embedded image processing product called FrothMaster, then at Stone Three as employee #1, then later at Treparel as a co-founder and architect, and more recently as scientific advisor to Clinical Graphics and co-founder of TimeScapers. In spite of this healthy dose of exposure, I’ve never actually run a startup as my main activity, so I will have to extrapolate and sometimes revert to wild guesses. I am trusting that some of the startup-involved readers will pipe up in the comments!

An academic research group works more or less as follows: Someone, usually a member of faculty (in this case me) at some university has a number of (crackpot) research ideas. Said someone pours buckets of sweat into further developing these ideas into over-detailed research proposals, which are then all rejected by the national and international research funding agencies that they are sent to. Somehow, said someone manages to keep going at this, resulting in proposals that describe projects that have nothing to do any more with the original research ideas, but are works of buzz-word art.

At some point, to the complete surprise of said someone, a number of proposals get approved. This means that buckets of money are handed over to the hosting university. Doh. Faculty member can now put in official requests to make use of these funds to employ a number of bright Ph.D. candidates for 4 years each, to buy toys for said candidates and to pay for visits to parties, I mean conferences, all around the world. Ph.D. candidates work on research project, supervised by faculty member, and each publishes on average 4 good research papers, followed by a thesis, at which case they usually have to be kicked out.

Some of the freshly-minted doctors decide to stay in academia, eventually breaking out of their postdoc cocoons as beautiful faculty members themselves, most often at other academic institutes. Some of the rest even decide to start startups!

At a startup, the main goal is to develop a new product or service, and then sell so much of it that the company turns a huge and sustainable profit. Alternatively, the startup’s product or service and/or people are so sexy that a much larger company decides to buy the whole thing up for a very large bundle of cash, instantly making the founders quite rich. This is called an “exit”. Initial funding strategies vary greatly. Startups can have any mix of bootstrapping (generating little bits of income to feed itself hopefully leading to more income), self financing, venture capital or angel investment. A startup is “ramen profitable” when it is just able to pay for the founders’ living expenses.

Financing: Here we see the first significant difference. In academia, a competition upfront determines whether you get financing or not for a particular research idea. Only when you have sufficient financing to appoint people and buy equipment for the duration of the project (generally 2 to 4 years), the relevant project is allowed to start. Faculty salaries are paid by the hosting institute. A startup can start whenever at least one founder is able to get by on their own resources for a few months. The startup is able to get by on very little, but does need to generate income throughout its lifetime, and that income ideally needs to increase steadily so that the company can grow.

Risk: The second big difference is related to this. At a startup, all the rewards go to the startup, for a largest part to its founders and to a lesser extent to its employees. People work their behinds off, because the payoff could be huge and your chunk is considerable. If your idea happens to change the world (see Dropbox), also the non-monetary kick can be life-changing. However, the risk is also all yours. If your idea bombs and your company blows up into a million pieces, you get to keep each and every piece! Even worse, you actually have to deal with the fallout in some or other fashion. In practice, this could mean bankruptcy of the company, but it could even go as far as directly impacting on the financial status of the founders.

In academia, there is certainly some risk in exploring in new territory, but it is accepted that not all ideas pan out equally well. You’re allowed to fail now and then, as long as you do OK on average. If you fail all the time of course, you’ll probably have a harder time finding new grants and collaborators to continue with your research, but you’ll still have the job. On the other hand, your reward in case of a successful project is that the relevant publications get mentioned by other researchers in their articles. You now have made what is called “impact”, and your h-index will hopefully start reflecting this soon, making it ever so slightly easier for you to get that next research grant. On a less cynical note, you sometimes are privy to the real kick of scientific discovery, where you’ve managed to cook up something that other scientists (and maybe in 20 years some real people) get really excited about. This latter aspect is in my opinion the actual driver, and the aspect that can make the science business so addictive.

Focus: A startup needs to have laser sharp focus. You need to pick one thing, service, expertise, product or concept, and become the absolute best at that. This seems to be a recurring theme looking at successful startups. If you do decide to go do something else, you have to call it a “pivot“, but you cant’t do too many of those, else people think you don’t know what you’re doing. In academia, you should definitely also have a research focus, but the requirements are far less stringent.

Research groups usually have a number of independent research projects, all more or less exploring some general research avenue, but a good devil’s advocate could claim that having different projects constitutes a lack of real focus. In my group for example, I currently have 6 major projects, ranging from surgical planning, through anatomical modelling and neuro-imaging to population imaging, as well as a small number of less major projects. This range is both a blessing and a curse. I have the luxury of exploring and finding cross-links between related but discrete research lines. Also, we have a higher chance of striking gold and a lower risk of striking out with this spread. However, sometimes I think that picking one idea and working on that for a few years would help us to build up more expertise concentration.

Overheads: Usually an academic research group is embedded within a hosting university. This grants certain advantages, such as infrastructure, and thousands of highly skilled colleagues, but it also means extra overhead. One of the most time-consuming components of this is teaching, an activity with which I have a love-hate relationship. Students who put in the minimum of effort  drain a huge deal of energy per each of their completely useless kilograms. Dedicated students  on the other hand are energising and in some cases decide to join the research group, further bolstering its capabilities.

In a startup, there is usually no hosting institution, and hence no such kind of overhead. I think this generally contributes significantly to the work satisfaction experienced by startuppers, as the level of self-determination is perceived to be much greater due to the lack of any externally imposed constraints. The impression I get from colleagues at my academic institute, is that the constraints or parameters imposed by the hosting institute, including administration, politics and in some cases teaching, can negatively impact on work satisfaction.

Goals: This one is interesting to think about. I think in both cases the idealistic goal is to discover or create something big that changes the world for the better. Taking a more cynical look at the day to day activities, one could think that the major goal of a research group is to setup larger and larger research programmes involving more and more people and more ambitious research goals, until finally the people at the top lose touch with the work on the ground. The cynical startup founder wants to get rich, either via a fabulous exit or market success, and then do it all again, perhaps at a larger scale.

I think it’s even more important to look past both lofty idealism and cynicism, and instead focus on something that can sustain you indefinitely: Doing something meaningful. Even if that world-changing breakthrough (startup or academia) is not yet in sight, and the bags of cash or the 50-person research group are a really long way off, coming home after work with the conviction that what you’ve done today in some way positively impacts the little world around you will definitely help to keep that spring in your step.