Prof. Roch Lefebvre from Université de Sherbrooke (Canada) is the inventor of ACELP technology commercialized by VoiceAge inc. used by 6 billions mobile phones in the world and has generated over $180M in revenue to Université de Sherbrooke and its inventors. Photo Credits La Tribune René Marquis.

Let's start with a definition from Wikipedia:

"Deep tech, or deep technology startup companies are startup companies with the objective to provide technology based on substantial scientific advances and high tech engineering innovation. They require lengthy R&D, may take a long time to reach commercial application, and often require large investments to achieve commercial success. The underlying intellectual property of deep tech innovations is usually well-protected and hard to reproduce, making it a strong competitive advantage or barrier to entry."

Hence, deep tech is a sort of technology that comes from research (typically academia research). It is not the famous garage/shallow technology made by geeks having a good business idea and developed at home with basic tools (which has been very successful, e.g. Microsoft and Apple have started this way). It is technology that comes from the real state-of-the-art of human mind/technique and done by people that have invested years to master a specific area of science or engineering (professional researchers or professors found in lab and universities). One good example here in Canada is the ACELP technology developped by Prof. Roch Lefebvre at Université de Sherbooke that is now used by more than 6 billions mobile phones in the world to increase sound quality.

While it sounds amazing and fulfilled with great potential, the deep tech journey has many pitfalls and challenges (well explained in this excellent 15 minutes TED presentation by David Allen from University of Arizona, USA).

The Potential of Technology Transfer | David Allen | TEDxTucsonSalon - From YouTube.com.

Deep tech is typically split in two segments (with social innovation as a new and fast emerging segment):

Life sciences (stuff related molecules needed to build new drugs)
Engineering (basically everything else: lasers, software, etc.)

The process of taking inventions to market (a.k.a. technology transfer) from life sciences and engineering is basically the same (invention disclosure, IP protection, maturation, product development, commercialization) but the business parameters are very different:

Life science market is a very large market, where product form factors (pills, vaccines, etc.) are well standardized but the regulation process is very long (tests to make sure the pill is safe) and capital needed to reach the market is huge (can be in the billions).
Engineering market has smaller opportunities and product form factor is not well standardized (can be anything from software to lasers and robots) but the time to market is smaller and capital needed is small compared to life science. For those reasons, those segments are not very well connected (life science and engineerng are two different worlds). My expertise is in the engineering technology transfer.

When speaking about technology in general, what is called 'technology' is often confused with the product, especially in IT where websites and software applications are called 'technologies'. In deep tech, there is a profound difference between the technology (the technical features that enables some sort of magic experience) and the product (what is built around the technology and what the customer will pay for). This is often a problem because most people developing deep tech do not have a 'product mindset' which can increase the gap (time, capital, efforts) in getting their inventions to market (effective invention disclosure analysis are needed to avoid this problem as early as possible). For this reason, I have co-founded (with my colleague Dietmar Bruckner from Austria) a few years ago a new IEEE publication on technology transfer to make researchers more aware of the basics of technology commercialization so they can have those important guidelines in minds while doing research and increase the odds to get their inventions protected, productified and commercialized.

Regarding intellectual property protection and management (patents, secrets, etc.), this is something core to deep tech (even more in life science then engineering) because research is largely funded by public funding (government) and the outcome of research has typically very high reach (requiring venture capital to finance product development & marketing activities while being a mechanism to secure investor's money). The culture of intellectual property is something existing in general tech but less deeply connected (lots of successful general-tech based products have no real intellectual property behind).

On the commercialization perspective, deep tech requires a lot more 'pre-sales' activities than general tech. The goal of any startup is to reach a repeatable sales process where new paying customer will deterministically be acquired after some level of marketing activity (e.g. if I reach out for 10 customers, I know I will have 3 paying customers) and where Customer Lifetime Value (CLTV) is large enough to sustain Customer Acquisition Cost (CAC) and grow the business. If you check the TRL image above, you may achieve this stage only after TRL9 and the deep tech journey will typically begin at TRL3-4. While those TRL stages are related to tech/product maturation, it involves two important 'sales' activities before the first real sale:

At TRL3-4: you will start with the inventors technology prototype to convince a company (new or existing) to invest in the development of a product prototype. The company investing at this stage has normally confirmed the existence of a business case either from its current business activities (already selling products in this market) and/or from a customer survey (having some kind of validation for the new product at a proposed price) and the number of customers who might be interested in the new product. Hence, at this stage you do not sell a product, you sell to potential of developing a successful product prototype.
At TRL6: you now have a prototype that has the desired performance and form factor. At this stage, you will put the prototype in the hands of customers and ask for feedback. The company will decide to finalize the product development (up to TRL9) based on this feedback. Hence, at this stage you begin to offer/sell the new product to limited potential customers (early adopters).
At TRL9: the company has now a full product (not a prototype) that has been done at typical sale conditions (price, support, delays, etc.). This is the first real sale and this is where you want to ramp up your marketing, quickly growing leads and begin to shorten your sales cycles (better qualification process, optimized value proposition and sales conditions). We take for granted that your manufacturing can support the sales volume (that part is easier for pure software products).

Some will argue that the commercialization part begins as early as the invention disclosure analysis and I agree. At that time, you should be able to roughly see the final product form factor and who is the customer. Also, it is rare to see B2C sales from deep tech: most of the time, you are dealing with B2B/complex sales. In any case, failure to have a 'sales mindset' at TRL3-4 and TRL6 will lead to numerous lost opportunities. This is why at this stage it is important to switch from inventors to entrepreneurs, i.e. people having the market in mind first (not the technology).

That being said, the best case is when you can build a product with 'shallow tech' (for example a mobile application or website) that relies on deep tech (for example an algorithm or data that has been developed by research and backed by science) to solve an important problem.

You then have the best of the two worlds and Google is one great example.

For further reading here are some other articles on deep tech by Boston Consulting Group, Forbes and Canadian venture capital firm RISC Capital.

Do you want to discuss more about deep tech and how it can benefit you and your organization?

Whether you are a researcher, a TTO officer, a product owner or an investor, I will be pleased to share my expertise with you and check how we can work together. Book a meeting now!

Meanwhile, you can always DM me on Twitter or LinkedIn.