Interview with Mike Molinari
I am thrilled that my first interview in this newsletter is with Mike Molinari, Managing Director of IP Group Australia. Thanks Mike for sharing your wisdom. If you haven’t come across IP Group before, here is how they describe themselves:
IP Group accelerates the impact of science for a better future, developing and supporting some of the world’s most exciting businesses in deeptech, life sciences and cleantech. Our specialist investment team combines sector expertise with an international approach. In Australia and New Zealand, IP Group works in close partnership with the Go8 Universities and the University of Auckland to identify ground-breaking technologies rooted in hard science, which have the most promising commercial potential.
How have you ended up involved in deep tech?
It has actually been quite a straight path for me, although it didn’t feel that way at the time! All throughout school and university I was fascinated with science and technology - understanding how the world works and how we can shape it. Early in my career I explored a range of roles - management consulting, Cricket Australia - that helped me to understand what I enjoy. I realised quite early that for me it really comes down to the intellectual challenge of science and the daily experience of working with people. I then went back to university to complete a PhD with the goal of coming out of it to work at the intersection of science, impact and business that is deep tech. I was fortunate enough to end up at IP Group in London, a global leader in developing and investing in deep tech companies, which has ultimately led to the opportunity to lead the team building IP Group in Australia.
What do you think needs to be considered when investing in deep tech, compared with other types of startups?
The fundamental difference is technology risk and how that relates to impact. A deep tech startup is typically developing a first-in-world product or capability - by definition no-one has done it before and there is a real risk that you might not be successful. Deeply understanding the technology and the risks involved is fundamental - I like to say that you can’t build a car while driving it, you need to understand the risks and challenges before you get started. This is also critical to tracking progress - for the first few years the milestones are likely to be scientific in nature rather than revenue and users, which creates a challenge. And at the same time you need to balance this to be sure that you are not falling into the trap of chasing a perpetual motion machine - a new product where there would be massive demand if you could make it, but it is never actually going to be possible.
You also need to be cognisant that once you have solved that initial technology challenge you still need to launch a product, scale a business and reach an exit for investors and it is important to start planning for this early in parallel to technology development.
In contrast, in a more ‘typical’ software startup you can generally be confident that you can write the code and the main risks are on the market side - user acceptance and ability to scale. Progress metrics are simple to define - users and revenue. You get to those challenges earlier because there is lower risk in developing your product, but because of that lower barrier to entry it is also a much more competitive environment and you always need to be looking over your shoulder and focusing on generating network effects.
So why would anyone do a deep tech startup? For me it comes down to impact. If you are successful you can bring to the world a whole new capability that can create whole new industries. Deep tech will be central to solving climate change, extending healthy lifespans, and how we relate to the digital world in a way that a new HR platform or talk management software just can’t deliver. And from a financial point of view, the moats that are inherent in deep tech products provide long-term defensibility and margins in a way that allows for tremendous value creation.
Can you give an example (or two) of a deep tech company you’ve been impressed by?
I’ve been hugely impressed by working closely with Paul Barrett and the Hysata team for the past three years.
Hysata is developing technology originally developed at the University of Wollongong that enables a huge step change in the efficiency of electrolysers for producing green hydrogen. Today’s electrolysers operate with an overall system efficiency of ~70-75%, while Hysata can deliver >95% efficiency - a 20% improvement in efficiency, or put differently an 80% reduction in inefficiency.
The technology has given the team a strong starting point, but it is the way that the team are making the most of the opportunity that is most impressive. From day one they have been focussed on attracting global talent and creating a workplace environment that gets the most out of them, on deep engagement with customers, and on crafting a public narrative that resonates. In each of these areas they have been truly world-class and we’ve seen that reflected in the progress and results to date.
Why do you think Australia doesn’t (yet) have deep tech startup successes mentioned in the same breath as Atlassian, Canva or Airwallex?
We do. We have Cochlear and Resmed, both of which are now mature companies and global leaders in their markets that are textbook deep tech companies - world-first technology that was nurtured for years before product launch that has redefined lives around the world. What we have had is a period of 30 years where we haven’t had the next generation of companies come through, and where the ecosystem has not had that lifeblood of major success stories to sustain it.
I’m absolutely confident that we will see truly world-class companies come through over the next decade that will be the cornerstones of a thriving deep tech sector in Australia - our challenge then is to ensure that we can build on this success.
How do you advise people working within Universities to transition their research into a successful venture?
I often struggle when I hear people talking about research and translation as separate endeavours - the reality in most fields is that for your research to have a positive impact on the world it needs to get out into the ‘real’ world in the form of new products and capabilities. For example if you identify a new target for a cancer therapy, it doesn’t benefit a single patient until it gets turned into a new drug, which involves patents, hundreds of people and hundreds of millions of dollars - none of which will happen without at least an awareness of what is required. Or in the example of Hysata, a technology breakthrough doesn’t reduce emissions until it is turned into a product and manufactured and deployed at scale.
The most important thing that I would advise researchers within a university to do is to get out of the university environment and speak to customers to understand their problems. Without knowing what customers want there is a real risk that you will be solving a problem that no one cares about, or that has been addressed by industry in a different way.
Secondly, engage with the various support structures in the university. No one is expecting you to know everything, and the major Australian universities that we work with have made a significant investment over the past decade to create resources and teams that can help.
And third, give us a call at IP Group Australia!
What podcasts/books/people have influenced your perspective on investing in deep tech?
Great question. I listen regularly to Acquired which is a great podcast with a number of deep tech stories - their episodes on Microsoft and nVIDIA have been particularly interesting recently. Obviously the traditional startup ‘bibles’ are required reading - Lean Startup, Zero to One, Hard Thing about Hard Things. For deep tech in particular, I highly recommend Clayton Christiansen’s Innovator’s Dilemma, and Bill Janeway’s Doing Capitalism in the Innovation Economy, together with Marianna Mazzucato’s various books on innovation and the role of the public sector. A final one is Bulletproof Problem Solving which has valuable approaches for breaking down complex problems like those we encounter in deep tech.
Perhaps most importantly, you should read as broadly as possible across different news sources and genres - you never know where a valuable insight or new perspective might come from.