From his perspective as an investor, Mr. Wen Hsieh defines five characteristics of hard tech startups that he likes to invest in. Coming across Mr. Hsieh’s list of defining characteristics, I really liked it because of the clear structure and it’s something I can connect with as the CEO of a deep tech company:
In summary, the 5 items that define powerful HardTech companies are:
hardcore science and engineering,
a combination of hardware and software,
hard to do,
hard to copy, and
being ventureable / hard to find.
I think these are good topics for fostering discussions about deep tech startups in general.
Here, I will focus and explain NanoScent in the context of these characteristics, as well as provide some tips about managing these ‘hard’ items based on our experience as a deep tech company over the past few years.
1. Hardcore science / engineering
A deeptech company should have some kind of scientific background, this could be like deep algorithms. This can’t come off the shelf. You need to be able to connect some things, synthesize, and there is a lot of trial and error. These are things that are maybe on the quasi-research side or maybe going from research towards development and really have a lot of depth into them.
So, when you are talking about HardTech, which is essentially hardcore science and engineering, by definition you need multiple disciplines because if it was not a multiple discipline combination, it would probably not be a hardtech startup but rather a more specialized startup.
One of the easy ways to spot such a company is by the number of PhDs or people with high engineering degrees that are employed relative to the rest of the company. In this context, when we are looking at NanoScent, we have 4 PhDs coming from multiple disciplines, like material sciences, organic chemistry, algorithmics and physics, and biochemistry coupled together with a strong software engineering team.
One of the hard things about having such a team is having them come and work together as a harmonized unit and lead the science forward. So, it’s very important to keep the scientists happy and in harmony with each other because that usually means that good creativity can occur, allowing the team to evolve together. Each scientist has a different KPI for being happy, so it’s important to balance the different ways and needs. From one side, you want to allow them to stray a little and be innovative but on the other you want to pull them together and back to the company focus.
In order to manage this aspect, we found three main things that helped us:
We set sprints which are 6 weeks long. We found that if they are 2 weeks, it’s not long enough and 3 months is too long. Thus, we have 6-week long sprints which divide into 8 per year and we call them ‘bits.’
We try to split the different engineers and chemists and staff into small teams where a lead engineer or PhD is leading a team of 2-3 people. This allows us for a good working relationship and creates pockets of small teams cultivating scientific creativity.
We also hold our patents as a KPI and make it a point to have the patent attorneys talk directly to the engineering teams in order to see if there are opportunities or if maybe something was missed.
In summary, the tips for this aspect are to hold sprints but try to see the time duration that works for you, try out different time periods and iterate. Also, breaking down into smaller teams fosters intimacy and creative energy while focusing on patents, and supporting your multi-disciplinary team by keeping balanced and happy.
2. Hardware is involved, in addition to software
Hardware in itself is a hard challenge to do, especially if you are innovating. But, managing both hardware and software together is even more challenging because they both have different physics and different time scales. We go a step beyond this complexity and add chemistry into the mix. So we have hardware, chemistry, and software all involved together. Sometimes it feels like coordinating an orchestra between an elephant, an owl, and a dolphin. All from different worlds, all unique, yet working to make them sound harmonic in sync.
We have made this coordination between hardware, chemistry, software a way of life at our labs. The following processes define this multi-disciplinary interplay and explain how our development efforts and choices are guided:
Synthesizing: Advanced capabilities centered on producing nanoparticle solutions in a creative, quick way from synthesizing ligands to printing (ie., sensor-based chemistry).
Sample conditioning: Know-how and discipline to work in accurate simulations of the environment given that the gas environment of which the sensor operates is as important as understanding the signals.
Algorithmics: Involves signal analysis of the sensor readings but also calibrating the sensors in order to take into account the environmental effects such as temperature and pressure.
3. Hard to do
When you are talking about a startup, there is no small job. Hardware has a specific hardness to do and you need a specific set of expertise and also people who have this desire to do it in order to accomplish it.
The answer to this is (like anything) is focus and this is challenging because it is hard to do. On a startup level, it is hard to do and focus on, especially when it comes to product fit challenges and wanting to be more on the customer side which is challenging when your technology hasn’t reached maturity and you can’t test or validate it with the customer.
This has been an ongoing process for NanoScent over the years, in a way like walking in a dark forest: you don’t know where you are headed most of the time as you are discovering new paths or unsure if something will jump out at you and surprise you. This is something that as a team you learn how to work on together, to get to the other side by establishing two things: a sense of direction and defenses.
The key is to focus, more specifically, the key is to focus on the customer. NanoScent, from early on, had a customer-focused philosophy even while developing the technology by being project-oriented through long-term projects for a product that was more R&D. This was good from a funding perspective because it did not dilute us much but focusing from a technology perspective only made it harder because it became a longer process to accomplish.
One example of this was our COVID-19 project which had a lot of customers requesting a quick non-invasive breath test. There was a lot of momentum and people interested in funding and investing. Having this focus allowed us to advance the technology quickly and in less then 10 months we advanced much more quickly than we did in the previous 2-3 years. So by having a focus through a customer and understanding who the customer is, it really helps the startup focus and develop. In the COVID situation we also had this luxury of funding to last through the advancements.
So what is the hard thing to do? For a company to decide, take a risk, decide on something, as we decided on COVID. Although we advanced, now it is hard to shift back into the climate tech industry. But the lesson from the pandemic taught us that the decision to pick a focus and focus on that customer has the potential to help us so much. Because you go into the customer mindset regardless of the technology, you can zoom in and focus on the customer and everytime you zoom in you find more depth and more challenges and you need to decide again how to narrow it. That is exactly what we did when we pivoted back into climate tech, focusing on hydrogen, after the pandemic.
Through discussions with over 100s of customers we were able to create a product roadmap that as the technology develops, it addresses more and more customer needs in parallel. For the first launch of VOCID® H2Confirm, we are targeting humidity and oxygen detection:
By definition, this shows focus
But also, this is hard to do because the focus at this point is so specific it can disappoint someone (who may want other gases or VOCs to be included in the first product version) or even yourself
In summary, the actionable tip here is to make a decision, focus on the customer, and walk directly towards the lion and hope it doesn’t eat you and pray, it doesn’t hurt anyone. The respective KPI is to see if the customer is happy or not. Go out and talk with them and be smart enough to get the insights back to your science and engineering team.
4. Hard to copy
To be honest, our technology is so complex and hard to do that it’s hard for me to imagine how it can be copied. Our partner scientists and consultants need a year or two just to understand it, which is a good gauge of its complexity.
When you are looking at what NanoScent is offering, a complicated process with regards to the chemistry and synthesis, the raw materials, ingredients and everything, how it is deposited, a lot of steps have been developed over multiple iterations to get to where we are today. We have had over 1000 synthesis during the past few years, using different chemistries, ligands, and this is hard to mimic. There is a lot of secret sauce within the ingredients that provide us safety and security in the know-how. Also, algorithms play an important role. So every part of the process alone is hard to copy, along with the integration of the system, along with the mechanics.
5. Venturable
Here, I will spin the table a little bit and say that it's also hard for us to find a venture or funds that are truly interested in playing with hard tech. Currently, a lot of ventures are looking for software because they understand software, the business, and the return on investment, along with the competition, and they are also comfortable with having 2-3 companies competing in the same space and all jump in it together and see who will succeed or fail. That’s the classic venture capital approach.
To find people with the level of expertise in physics or engineering alongside a business understanding of these business cycles, when the returns could come, and the duration required, is challenging. We’ve talked with many deep tech funds and found that they are not really into deep tech but into software or are looking for early-early on high-risk which, for a company like us, that is past this stage. So this is challenging. We found it better to have strategic partners who have a patient approach (which has its pluses and minuses). On the other side, government funding is more available for science and engineering companies. We recently received a grant from the IAI.
So the KPI here is to look for strategic partners and government grants in your area, to have a lot of patience and perseverance. Take one step at a time and make sure you are gagging the process and the team size properly by always trying to keep a lean team. A lot of time, you might get the urge to expand into sales, but R&D always needs more infrastructure and capital, so it's okay to hold back on expanding and keep a slower pace.
Commenti