As part of my Startupinformatik initiative (in German), I’m trying to motivate student startups. Here, I want to talk about student startups coming out of a Master’s program. These are different from startups coming out of my research lab, which are based on work with my Ph.D. students. Master student startups are typically smaller, not based on significant intellectual property, and my working relationship with the team has been much shorter than with my Ph.D. students.
What are the three most important factors that make a startup successful? As the old saying goes: Team, team, and team. There is plenty of advice on the web on finding and building teams. I have a bit to add to this as well, but will do so in a different post. Here, I would like to focus on the next two most important success factors, which are product and passion. Without a good product there is no money to be made, and without passion, the startup will fall apart too quickly.
Sadly, being a student, having a good product idea, and having passion for it are factors that are hard to align. The following figure helps illustrate the problem.
One of those cultural things: German financial services websites (but then: all of them) will remind you upon logging in that you did not properly log out last session. Streamlining social behavior at its best, even if it makes little sense. At least it is a good example localized semantics for an HCI course.
Schufa is a German credit rating agency. By law it is required to provide information to consumers (while it makes all its money, for now, off corporate customers). As a consequence, its password and login screens have been designed, I suggest, to be as unusable as possible. Below please find a screen-shot of the PIN setting dialog, (The pin is the second of two passwords you need to login.) There are plenty of requirements. My favorite requirement is “use at least one special character but don’t use any illegal special characters”. Also, kind of amusing, the admonishment “to think really hard to remember your PIN”.
Stack Overflow of the “full stackoverflow programmer” fame just published a developer survey. Among the items was a question asking developers, what they prefer for indenting their code: Tabs or spaces?
The majority of developers prefers tabs over spaces by a reasonable margin. What worries me, though, is the conclusion or the “trend” that the summary writer sees in the data: That more experienced developers prefer spaces over tabs.
“AI” (or just smart algorithms, if you will, where smart will be plain in a few years and dumb in 10 years) is on the rise, no doubt about it. As a consequence, I’ve been having fun with “AI challenges” of the sort: Could a computer figure this out? As an example, take a look at the advertisement below. It is for a conference of University chancellors in Germany (administrative leaders of their universities). Could a computer figure out the disconnect between the depicted young people, presumably students, and the more advanced-in-years chancellors of their universities?
A student of mine pointed me to this article about who founds companies. It is a well-known fact (or at least lore as I have no reference at hand) that the highest success rate as a founder is with those around age 40 (38 according to the article). At that age, a founder has worked in his or her industry, knows it well, is connected, and probably has a reasonable business idea to begin with.
The article referenced above, however, wrongly suggests the next big-time entrepreneur will be one of those fourty-somethings. Maybe. But statistically, despite the high success rate, not likely. Why? Because business ideas that someone at that age typically comes up with are “reasonable” and “rational” and “rooted in reality”. Because they are based on a lot of experience. Which may well blind the entrepreneur to the more far-out ideas that, if successful, provide the home-runs that VCs are looking for.
Abstract: Today’s software systems build on open source software. Thus, we need to understand how to successfully create, nurture, and mature the software development communities of these open source projects. In this article, we review and discuss best practices of the open source volunteering and recruitment process that successful project leaders are using to lead their projects to success. We combine the perspective of the volunteer, looking at a project, with the perspective of a project leader, looking to find additional volunteers for the project. We identify a five-stage process consisting of a connecting, understanding, engaging, performing, and leading stage. The underlying best practices, when applied, significantly increase the chance of an open source project being successful.
Keywords: Crowdsourcing, open source software, open source communities, volunteering process
Reference: Riehle, D. (2015). The Five Stages of Open Source Volunteering. In Crowdsourcing. Li, Wei; Huhns, Michael N.; Tsai, Wei-Tek; Wu, Wenjun (Editors). Springer-Verlag, 2015, 25-38. Republished from The Five Stages of Open Source Volunteering. Friedrich-Alexander-Universität Erlangen-Nürnberg, Dept. of Computer Science, Technical Report, CS-2014-01, March 2014. Erlangen, Germany, 2014.
The paper is available as a PDF file and as HTML on this site.