Is your Spin-Off a startup?
Understanding what determines what kind or project you are working on
Creating Spin-Offs (or Spin-Outs) from universities and research centers is quite easy. You fill some forms, you get the formal approval from your department, and then you create the limited liability company. That’s it.
Many governments are nowadays focused on promoting startup creation among scientists and then (tentatively) support them with different tools.
In terms of University mission (that can be summarized in “create and diffuse knowledge”), creating businesses with startups potential is without any doubt the modality that can maximize the potential of knowledge diffusion and impact on society.
The reality, however, is that most of Spin-Off for different reasons are never going to be startups.
To better comprehend why, let’s start from the definition of Startup:
A startup is a (temporary) organization designed to search for a repeatable and scalable business mode - Steve Blank
The most important part of the definition is the part related to the scalability of the business model. Scalability refers to the ability of a business to grown and expand in a cost effective and efficient way (read the cost/revenue relationship is not linear)
Nowadays, however the term Startup is misused: it is in fact frequently associated with any kind of company in the first stages of operations. Here comes the catch:
All startups are companies “in the first stages of operations”, but not all “companies in the first stages of operations” are startups.
Understanding whether the idea of the company that you have in mind has a startup potential is therefore the first step in the your entrepreneurial journey, and will avoid making you look unprofessional in front of investors (as suggested in this post on I Want Product-Market Fit by Jeroen Coelen)
Before continuing the post, I need to make a clarification. As you might have noticed from the header meme and other posts, I’m trying to be a little bit critical regarding the startup culture. Since I feel that there is still a lot of confusion, the goal of this post (and of this newsletter) is to raise awareness of people involved in science regarding different typologies of entrepreneurial activities, limitations of each model and relative trade-offs to provide them better tools to evaluate whether to engage in entrepreneurial activities. Now that I warned you, we can go on.
What determines what kind of project you are working on
Even if entrepreneurs can be defined as “people who solve other people’s problems”, the way in which problems are solved and the typology of problem to solve will determine the typology of your venture.
Three strictly interrelated elements must be taken into account to evaluate what kind of company you can launch (and potentially save you from stomach ache):
Your entrepreneurial attitude
Technology & Market characteristics
Project characteristics
Let’s break down all the elements before exploring how they map into different typologies of ventures.
Entrepreneurial attitude
Not everyone want to be the front man of the new company and try to sell as hell their solution.
Not everyone wants to change their daily routines and their activities.
Not everyone wants (or have time) to share their knowledge, grow other people and let go part of control and ego.
Not everyone wants to share ownership of the company they are creating (neither with friends nor with investors)
The typology of company better suited for different personal attitudes depends strongly on how you feel regarding these four points.
Technology & market characteristics
Many technologies have the potential to address huge markets. These technologies are usually referred to as platform or key enabling technologies. At the same time, many other technologies are strictly focused on solving very specific niche problems.
On top of market dimensioning, whether you can launch a startup or not depend also on how it is structured the value chain in which you would like to operate.
Is the solution based on your technology a component of a larger system? likely never be a startup, irrespective from market size.
Does your solution sell as a stand alone product? likely be a startup if market is big enough
Does your solution needs to build up the value chain from scratch? likely be a startup if market is big enough.
Another element to consider is the transferability (or tacitness) of the knowledge developed. Is the knowledge easy to embed in a product or a service that can be delivered “at scale”, or your intervention is always required to deliver what you are offering?
Understanding what kind of knowledge and technology you have in your hands and how the market surround you is structured are other fundamental elements to take into considerations while thinking about the optimal type of venture you can set-up.
Project characteristics
This third elements is the element that most depends on the previous two. Depending on how you set up the project, you are automatically closing up some doors.
Want to do consulting? You will never be a startup.
Your total market is worth 500K€ and there are other 35 companies doing something similar? Likely not what is required to a startup.
Will take 6 years to finish developing the technology? Unlikely that you will get funded as a startup due to VC functioning.
Here comes into play the development plan of your startup. The time and resources required to market the technology, and the financials of the solutions you would like to provide once it is fully developed, determine what kind of project you can aim for.
Three Spin-Off archetypes
Considering the previous elements, 3 main different type of entrepreneurial endeavors might be generated by spinning-out from universities:
1 - Consultancy firm
Consultancy firms work on a project-related base, and researchers directly provide the services. Many universities (rightfully) regulate consultancy projects carried out by professors due to potentially conflict of interest with the university mission (which is the institutions that is paying your salary and equipment). If the knowledge is totally embedded in the people and not easily repeatable at scale, the model that best suits your entrepreneurial attitude is consultancy. This type of entrepreneurial endeavor does not require investment of any type, because what you are selling is your (or your university) know-how. Moreover this model does not require you to change dramatically your routines, and most of the time does not even require you to share ownership of your activity (even because you already have the opportunity to do it through the university!) In this case, it is useless to talk with Venture Capital and investors if you want to consult for other companies. Investors invest exclusively on projects that have the potential to become startups. No (sane of mind) investor will ever finance something that does not have the possibility to scale. If the service you are supplying is exclusively linked with the know-how embedded in few persons that are directly involved in providing the service, Investors are not the right interlocutors. Better interlocutors might be companies which are already paying you research contracts, and to manage these relationship most of universities’ are already well equipped in supporting sponsored research (which does not even require you to set up your own company, because probably there is a big conflict of interest!)
2 - Small enterprise
Different from consultancy, small enterprises are companies that do produce a service or a good that is not linked with personal capability to deliver that product. These products/services are based on technologies that can embed the innovation and be sold without requiring the direct involvement of inventors. What differentiate a small enterprise from a startup is the possibility and the willingness of the owners to scale the solution provided.
Ability: Many technologies have the potential to disrupt big market, but many are so specific that their potential (and therefore their market) is inherently limited and not big enough to receive VC investment. These “small market” technologies are not attractive for Venture Capital investors due to their investment model (which with each investment need to potentially recover all the fund), but might be very attractive for specific corporations willing to buy product and or services that you can supply with in a repeatable and reliable way.
Willingness: If it is not in your plans to give up the control over your company, then you should not look for investors money. Their model is entirely based on selling (sooner or later) their stake in your activity and (hopefully) make a profit from it.
This typology of venture might require you to change a little bit your daily routines to a more market oriented technological development, and entails that sooner or later you will need to fins someone available to set up industrial processes and carry on with the administrative and operational activities (like logistics, customer relationship, etc etc).
3 - Startup
To work on something that can be considered a startup, few characteristics must be met:
You must be willing to give up ownership of your baby. Venture capital industry works just like that, and people that will be added to your team/board will help you in generating value for your customers and for your stakeholders. If you want to remain king of your castle, investors money is not there for you.
You must be willing to change radically your work, or let someone else do the salesmen for you. Startups with researchers in CEO positions are well seen, but only when the researchers detach from the university. If you have a full tenure track and no idea of leaving the academia, you must assign the operative roles to someone else. Investors will appreciate this move, recognizing that you were able to see the limitations of your knowledge and time availability.
Your business model must be scalable. Before starting talking with venture capitals, think twice about the ability of your business model to return venture-capital like investment. Is your project capable to return ALL the fund of the VC, if everything goes right? Projects targeting small markets are simply not fitting with VC models, and recognizing this can avoid you useless rejections from them.
A fourth path
In reality, there is also a fourth path, one that few researchers choose nowadays amid the current innovation circus: keep doing research in the lab while quietly preparing the technology for a spin-out when the conditions are right.
This approach is often the most challenging, especially in an environment where there are “opportunities for entrepreneurship” are way easier to access than opportunities for research funding (even though the value of the former often is close to 0, if not negative altogether for the progress of your project). Yet, for many projects, it can be the most effective way to reach real investability. It allows teams to continue developing a solid business case while maturing the technology safely within the lab, away from premature market pressures, and most of all preventing people from burning their bottoms with unproven and uninvestable projects. From the outside, such technologies may still appear too risky or too far from any tangible commercial application, but I think that this patient groundwork is precisely what makes future success possible.
Conclusion
Beside these differences, all entrepreneurial endeavors share some basic common points:
every type of activity must have an economically sustainable business model (even non-profits have business models)
every type of activity need to understand who their customers are and which are their needs
every type of activity needs some salesmen and project management capabilities.
Startup creation is only part of entrepreneurship, but entrepreneurship is needed for any kind of technology transfer endeavor. If you are thinking about setting up something, then start with understanding what entrepreneurship is about, since it is scientifically demonstrated that scientists with an entrepreneurial mindset are better scientists under andy aspects (better science, more funding, more success). Only after that start think about startups.
Brilliant. This distinction is so important, especially with all the buzz around AI spin-offs. How do we truely better equip researchers to build scalable models from the start? Your insights are incredibly valuable.