Visiting Wildau

Visiting Wildau

Heikki Immonen

Principal Lecturer of Entrepreneurship at Karelia University of Applied Sciences

In March 2018 year I took participated to an intensive entrepreneurship education 2-week program at Technical University of Wildau. The event was organized by the ECMT+ project. Six students from each seven participating countries had had few months to prepare and produce rough business ideas ready for further development and testing during the intensive week. I was able to participate on the first week, during which teachers from partner universities gave lectures in the morning and student teams applied these lessons during the afternoon and evening. Because of the lessons and work done by the students, those rough business ideas sketches transformed in to a more thoroughly tested and complete business concepts.

This was my first time really experiencing Germany. My earlier experience consisted of flying from Helsinki to Munich, renting a car from the airport and driving south to Austria. Based on my 7-day stay at Wildau, I must admit that Germany felt simple and approachable. Trains are on time, streets are clean and feel safe. I think I didn’t spot any vacant commercial spaces in Wildau. (a sign of Germany’s strong economy?) Some curious cultural or practical differences also stood out: cash is everything; credit or debit cards are not often accepted in smaller shops. Shops close early and are not open during Sundays. Also, I got the sense that German organizational culture is somewhat more hierarchical compared to what I’m used to in Finnish universities. Obviously, flat and vertical structures both have their benefits. If you get too flat, it might be difficult to get coordinated collective action for any sustained period of time towards an important strategic goal. Which by the way is often the biggest issue with “creative” and “dynamic” startup teams.

Moving back to the issue of entrepreneurship education: what can we expect to get from an intensive entrepreneurship education program? According to Bae et al (2014) entrepreneurship education has no significant effect on entrepreneurial intentions, when pre-education attitude towards entrepreneurship is taken as a factor. For a group of already entrepreneurially-minded students entrepreneurship education could provide small but statistically significant boost. Intensive week as a teaching method doesn’t bring any special boost to learning outcomes. Problem-based learning and discovery-based learning improve learning, but less than average interventions (Hattie, 2008). If intensive week is seen only as a tool for promoting entrepreneurial intentions and a way to deliver entrepreneurship education, it shouldn’t be the number one choice.

What if the main benefit of an intensive week is less about the individual skill development and more about the relationships and the interactions between? We know that shared novel and exciting activities can be a significant factor in experienced relationship quality of couples (Aron et al., 2000). It is not farfetched to propose that novelty and excitement, such as the kind what you experience when you go to a foreign country to work and live together with people from different cultures, will be a good relationship builder also in non-romantical context. Thus fostering future collaboration and exchange of ideas. In fact, this exchange of ideas might the most important outcome of the intensive weeks, at least for the faculty and staff of the partnering universities. Alex Pentland and his research group at MIT have studied this so-called idea flow extensively (Pentland, 2015). Pentland defines an idea as three-part unit of knowledge: when in situation A, do B in order to get to C. When people interact and discuss, ideas flow between people. When we see others doing something in a situation similar to ours, reaching towards a goal like ours, we’re likely to imitate if this activity leads to the desired results.

With the advent of mobile devices it has become possible to study idea flow objectively. Pentland and his colleagues have discovered that idea flow is a mighty predictor of success. Intra-organizational idea flow predicts better productivity and effectiveness, while inter-organizational idea flow corrects with long-term success and innovativeness. For example the economic development of different US states is strongly correlated with the number of social ties to other states (Holzbauer et al., 2016).  It is also the increasing density of idea flow inside cities that explains the scaling of economic and innovation performance per resident in cities (Pan et al., 2013) .

So, how did I personally benefit from this idea flow in Wildau? Next are couple of ideas that stood out and certainly had an impact to my own thinking. First of these was an excellent demonstration of the “get out of the building” principle originally made famous by startup thinking pioneer Steve Blank (Blank & Dorf, 2012). As according to the “get out of the building” principle, already on the second day, students travelled to Berlin to interview and observe potential customers in hopes of discovering unsatisfied needs and other business opportunities. Students were also instructed to look for existing solution similar to the business idea they had chosen to develop further. A second trip to Berlin came later during the first week.

These excursions worked as excellent learning opportunities and as exciting relationship-building experiences (see above). For me this was maybe the best example of the “get out of the building” practice I’ve personally witnessed. It is very likely that this practice will be integrated to some educational programs we have here are Karelia UAS.

Second practice that stood out for me was the Vinn Lab, a prototyping and mockup building facility at Wildau. My personal experiences are more with “dirtier” prototyping machines such as woodcraft and metalcraft tools. Vinn Lab had a “cleaner” focus with 3D printers and simple CNC machines. What I liked especially was that together with these tools the facility had also amble room for brainstorming, dedicated computers with design software and simple building materials such as Lego bricks. It felt as if Vinn Lab was clearly organized around a specific need an innovator might have. To my estimation this need is the ability to quickly visualize business ideas as images or to produce them as simple 3D mock-ups. When a product or service idea becomes visual and physical, higher quality feedback can be gathered from outside experts and potential customers. Also, the designers themselves become aware of possible flaws and ways to improve the idea further. So-called dirtier prototyping facilities have a clearer focus on producing actual functioning prototypes. To summarize, Vinn Lab is something I feel we lack here in Joensuu.

How would I change the intensive week concept for our next implementation in 2019? Perhaps one way to improve would be to narrow the type of business models student teams can work with. If all would be working to create a physical product, it would make it easier for the teachers to design more effective learning experiences. Student teams could follow mock-up and prototype building and usability testing steps in an orderly fashion. To have even more focus, all teams could be developing a physical product to a similar kind of customer need. This would allow teachers and students alike to see performance differences between different teams and thus facilitate learning better. When everybody is working on a completely different business idea, the innovation skills might be lost in the practical details of the product or service.

Thank you team WIldau!


Aron, A., Norman, C. C., Aron, E. N., McKenna, C., & Heyman, R. E. (2000). Couples’ shared participation in novel and arousing activities and experienced relationship quality. Journal of personality and social psychology78(2), 273.

Blank, S., & Dorf, B. (2012). The startup owner’s manual: The step-by-step guide for building a great company. BookBaby.

Holzbauer, B. O., Szymanski, B. K., Nguyen, T., & Pentland, A. (2016, January). Social ties as predictors of economic development. In International Conference and School on Network Science (pp. 178-185). Springer, Cham.

Pan, W., Ghoshal, G., Krumme, C., Cebrian, M., & Pentland, A. (2013). Urban characteristics attributable to density-driven tie formation. Nature communications4, 1961.

Pentland, A. (2015). Social Physics: How social networks can make us smarter. Penguin.

Proof-of-Concept (POC) programs

Proof-of-Concept (POC) programs

Heiki Immonen

Principal Lecturer of Entrepreneurship at Karelia University of Applied Sciences

More and more universities offer not just entrepreneurship education and traditional patenting-licencing scheme, but also have built in-house commercialization processes (Munari et al, 2016). In this text, I write about the so called proof-of-concept programs (POCs). My personal experience in running one such a program at Karelia University of Applied Sciences has influenced my understanding of the topic quit a lot. For this reason towards the end of the text I raise up one of the key problems associated with POCs i.e. the problem of selecting the right ideas and teams to enter the POC stage. I hope to discuss this problem in more detail in future texts.

Commercialization of novel ideas is a process of uncertainty reduction. There are many questions (Anthony, 2014) such as: Is there a need for our product in the market place? Can we make the technology work and produce it at scale? Are there enough potential customers willing to pay a price that will earn us an attractive profit? The main idea of POCs is to use simple and low cost methods to kill bad ideas early. Ideas that survive with reduced uncertainty earn more investments at later stages of readiness. In a world of limited resources, the moment when an idea or business case is ready for more investments, is a central question in commercialization.

The purpose of Proof-of-Concept (POC) programs is to reduce uncertainty by testing key assumptions of novel ideas. These can include team’s capability of building a working prototype or customer’s willingness to use a demo version of the invention. POC stage takes place after initial analyses on the validity of the business case are done. In higher education, POC programs often bridge the funding gap between traditional R&D activities and private funding. A business case that survives the POC stage becomes much more attractive to the private investors, as the associated uncertainty is lessened (Munari et al, 2016). POC programs often focus on IP owned by the university, but some program operate more like grant programs supporting university-born entrepreneurship regardless of the status of the IP ownership

Picture 1. Role of POC programs in the commercialization pipeline

To illustrate how POCs work, let’s look at NASA’s technology readiness level (TRL) classification (Kapurch, 2010). According to TRL an idea is ready for physical tests and prototyping when it passes the first two levels. Passing the first level requires gathering and reporting most relevant scientific findings about the technological challenge. To put it in other words, TRL 1 is about becoming familiar with what is already known. In some cases basic research type activities are needed, if the phenomenon is not well studied. At the second level actual concepts are being developed and analysed for feasibility and benefits. No experimental data or detailed analyses are required to pass this stage. Thus, given what we already know from TRL 1, TRL 2 can be said to be about creating good concepts that solve the challenge. The POC stage begins at TRL 3. This is when developers start to do small experiments to validate their models and assumptions.

NASA’s TRL classification assumes that the technological challenge at hand is important and a solution is required. In business setting however, the existence of a customer need is often the most important uncertainty. In a more business oriented POC toolbox, the lean start up methodology, validation of customer need is the first step. In lean start up, techniques such as use of google ads for testing for customer interest can be used. In the next stage of the process a minimum-viable-product (MVP) is created (Ries, 2011).  Anthony (2014) introduces a process with an initial definition stage and then two steps of so-called desktop research. During these steps basic assumptions of the business case are evaluated by searching for evidence using various sources of information such as online sources and expert interviews. According to Anthony these steps should take only from few hours to few days to do. For Anthony, the POC stage can be seen to begin with building a simple demo to be used by the potential customer.

POC programs that operate in higher education can face unique problems. All students, researchers and faculty in higher education setting are not necessarily fully up to date with business case evaluation and commercialization methods. POC programs or idea grants that only cover some expenses and don’t pay inventor salaries, also have the uncertainty regarding the would-be entrepreneur’s continued motivation (Immonen, 2017). This puts a lot of burden to the selection process, as program should be able pick good ideas and teams from poor ones. Pitching to a panel of experts is a method used by many POC program, but selection based on pitching alone can be heavily biased (Pentland, 2008). One option is to comb through every business case in detail, but this easily increases the relative cost of the selection process itself. Robust and quick ways to deal with selection process would be much needed. This very topic I hope to address in future writings.


Anthony, S. D. (2014). The first mile: a launch manual for getting great ideas into the market. Harvard Business Review Press.

Kapurch, S. J. (Ed.). (2010). NASA systems engineering handbook. Diane Publishing.

Munari, F., Rasmussen, E., Toschi, L., & Villani, E. (2016). Determinants of the university technology transfer policy-mix: A cross-national analysis of gap-funding instruments. The Journal of Technology Transfer41(6), 1377-1405.

Team Engagement – Exercises for Improved Team Communication

Team Engagement – Exercises for Improved Team Communication

Heiki Immonen

Principal Lecture of Entrepreneurship at Karelia University of Applied Sciences

Since 2008 I have worked with hundreds of student product development teams and very early-stage startup teams. Typically, there is a standout individual in every team who acts as a team spokesperson and a team manager. If there is a pitching event, this extroverted individual takes care of business. When you go and follow team meetings, the roles often remain the same. When measured in terms of how much each individual in the meeting speaks, the spokesperson often dominates the conversation. Of course, this is a common feature of meetings in professional teams and organisations as well. We all know the problem. What if a silent person has something valuable to contribute? What if the ideas of the spokesperson are not actually that good, but nobody criticizes them?

Engagement is a term referring to a pattern of internal interaction in a team or an organisation. Engagement and its effect on team effectiveness has been one of the major discoveries of Alex Pentland (2015) and his research group from MIT. A meeting where everybody spends equal time talking, the duration of individual comments is short, and where people take turns talking in no specific order has a high level of engagement. The opposite, i.e. low engagement, is when one person uses most of the shared time in long monologues. The reasons for low engagement are not really significant, they could be personality driven (introverts vs. extroverts) or due to some formal hierarchy or cultural difference. The thing that matters is the actual level of engagement. If the team fails to utilize the knowledge of all of its members, the team will not use all of its potential.

In their paper published in the highly acclaimed Science magazine Wooley et al. (2010) found a so-called “collective intelligence factor,” which surprisingly didn’t correlate with either the average team intelligence or the maximum individual intelligence of the team members. Instead, this factor depended on the social sensitivity of team members and equality of conversational turn-taking. Teams with higher collective intelligence were able to perform better in complex problem-solving tasks. In another study of engagement in companies, Pentland and his colleagues (2015) discovered that the amount of communication and idea flow between co-workers directly influenced the profitability of a call-center. When workers had the opportunity to talk about their tasks during coffee or lunch breaks, efficiency rose.

Obviously, engagement matters. How can you teach students the skill? In the past couple of years, I’ve been experimenting with my fellow teachers e.g. Dr. Ana Gebejes from the University of Eastern Finland, with different methods that help teams of students to become more engaged in their meetings and interactions. One of the exercises that allows students to have an analytical viewpoint of their team’s communication patterns is to have the team record their meeting and then ask each student to analyze a certain part of the recording, e.g. a ten-minute segment. Analysis is done by counting the number of times each person spoke and the total time each person spends talking. After that, you can ask participants to provide suggestions for how the team could improve their communication pattern.

Another exercise, directly integrated in the meeting, has an immediate effect on communication patterns. This exercise creates a so-called token economy. In the first version of the exercise, each team member gets an equal amount of tokens, e.g. small pieces of paper. Every time a person talks she takes one token from her personal pile and tosses it in the middle of the table. As everyone’s token pile is visible, team members can adjust their participation. If person A has very few tokens left, he should start listening more, and if person B has a big pile, then she should start getting more involved. In the words of Elon Musk: “You haven’t said anything. Why are you in here?” The second version of this exercise has one big pile of tokens in the middle of the table. Every time a student talks, he or she takes a token from the pile. If a personal pile gets too big, it’s time to give more room for others. Of course, there isn’t much difference, but the first version might require less reaching out to the middle of the table.

The question is: what if you really don’t have anything new to contribute? Isn’t the smart choice to stay quiet? Not really, you can significantly advance the dialogue by using one of two powerful conversational techniques. First, you can paraphrase what the other person just said: “So you’re saying X?” This allows the whole team to see if everybody is on the same page and even improve the thinking of the person with the original contribution (Kaner, 2007). Second, you can simply ask a clarifying question: “What do you mean by Y?” This is especially good in situations where the previous speaker used words or terms that are unfamiliar for the listener. You cannot really appreciate the value of an idea if you don’t understand the words being used.

Because of blended learning, IoT and AI, there is an opportunity to integrate technologies into meetings that automatically produce an engagement report for the whole team to learn from. Dynamic applications could nudge individual members to interact in a more balanced manner even during the meeting. As it is, these technologies already exist. Pentland’s group have used electronic automated measurements. Their techniques are based on the use of sociometric badges, i.e. small multi-sensor devices people wear on their necks. However, it is likely that voice recognition and directional microphones can replace such wearable devices. With such powerful tools, team working skills would become a more concrete objectively measurable ability.


Kaner, S. (2007). Facilitator’s Guide to Participatory Decision-making. John Wiley & Sons.

Pentland, A. (2015). Social Physics: How Social Networks Can Make Us Smarter. Penguin.

Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a Collective Intelligence Factor in the Performance of Human Groups. Science, 330 (6004), 686-688.