This week on the startup to scaleup journey:
First-time founders losing ground in the downturn
We now know that 2021 was a clear outlier year in VC, with investment volumes and valuations now returning to long-term averages. But what is less well known is that the number of new startups is also reducing sharply, as Dealroom's latest market assessment confirms. This puts first-time founders at a disadvantage versus their serial-founder peers who are seen as a safer bet for investors. This is reinforced when we hear investors talking euphemistically about a "clearer focus on quality" with the new winners coming from "a strong foundation of senior talent". So, what are the big insights of recent months and what actions can first-time founders take to level the field? Dealroom firstly states that the 'adjusted market reality', which began in 2022, is here to stay. "This trend has continued into the first half of 2023, as total investment volumes in Europe are set to reach around $50B+ for 2023 as a whole, based on activity to date. This represents around a 50% drop compared to the record highs of 2021, and around 38% down on 2022. The report then confirms that the market downturn is reflected in fewer new tech startups being created: "Based on analysis of over 500 million LinkedIn profiles, about 15-20% fewer companies have been created year-on-year, and we’re even further off the Covid-fuelled peak of 2020."
The share of companies being started today by repeat founders and by experienced operators, are at all-time highs for the European ecosystem. 37% of new founders in the most recent quarter were repeat founders, up materially in just a few years. Similarly, the share of founders that have prior work experience as senior operators has also increased by 8 percentage points from 2018 to 2022 and now stands at 19%. We know that all founders must possess a set of essential capabilities and that in certain cases, first-timers may even possess some advantages. But when it comes to fundraising, our own insights from working closely with dozens of founders over the past decade reveals that serial founders are able to hit the ground running faster. This is due to 3 key factors: 1. Timing: They start thinking about funding a lot earlier. Experienced founders know that the business strategy and the funding strategy are intimately interwoven from day one. One does not follow the other. 2. Stages: They align funding rounds with distinct milestones of company progress and they think at least 2 stages ahead on this. i.e. Will this next round of funding get me to the round after that? 3. Investor motivation: They develop an appreciation of the investor mindset that is just as deep as their understanding of their target customers. They understand the investor's problems and how they can provide a solution.
Another way of putting all this is that experienced founders develop a funding strategy from the outset and they keep it regularly refreshed. In our bid to help founders hit the ground running, we have developed a framework that the captures the essential elements in a proven methodology: Investment Analysis. This enables founders to think immediately about timing, the stages of company evolution, investor types and motivations, and how these fit together in a funding strategy built around clear investor targets. First-time founders - and for that matter any founder that has been out of the funding market for 2 years or more - need some extra help as the players on the field boast ever higher levels of experience. Even if you just look at unicorn alumni, the figures are remarkable. Dealroom has calculated the number of new founders spun out of European unicorns 10 years after founding; the 1990s cohort started 5 new startups; the 2000s unicorns generated 75 new startups; and the 2010s cohort created 801. It's too early to know what the cohort of the 2020's will produce, but those from 2021 alone will likely blow earlier numbers away. But first-time founders have everything to play for: Even though investment levels have dropped alarmingly, they are still 35-40% ahead of what we saw in 2020 and 2019. Despite the market downturn, Europe is on track to have its third largest year in terms of funding raised. It’s just that fewer startups will now capture the spoils.
Sam Altman says his early startup advice was wrong
OpenAI's Sam Altman, co-founder of the famous startup accelerator, Y Combinator, made some remarkable comments this week about the advice he gave founders whilst at YC. Interviewed at IIT Delhi, he admitted:“Honestly, I feel so bad about the advice that I gave while running YC that I’m thinking about deleting my entire blog ... There were a lot of things that we really held dear ... you got to launch right away, you’ve got to launch a first version you’re embarrassed about, raise very little capital upfront, you don’t take big R&D risk, you’ve got to immediately find product-market fit with something. OpenAI raised a billion dollars of capital before we had any product at all. It took us 4.5 years after we started to release something, and when we released it we didn’t talk to users at all for a while…We just didn’t do it the same way and it still worked." Many jumped on these comments in the tweetstorm that followed, criticising Altman for providing years of bogus advice. But much of this angst seemed misplaced. Whilst Altman didn't do himself any favours, many founders will have taken Altman's reflections as a partly tongue in cheek summary of what early stage investors really understand as being a much more nuanced topic.
What Altman recounted here was no doubt an overly simplistic view of how to start a software company. We'd like to think that an experienced founder would never have interpreted this as a prescriptive playbook. Perhaps some first-time founders might have taken it too literally. But many will have seen it as more of a framework. A framework where lean startup principles - such as those captured so effectively by Steve Blank in 'The Startup Owner's Manual' and Peter Thiel in 'Zero to One' - could reside. Blank, using the same vehicle of the MVP, more eloquently talks about the principal of 'customer development' being the early driving force rather than just 'product development'. The idea being that you are searching for the business model that will find real resonance in the beachhead market. This is 'customer pull', the first real sign of product/market fit (PMF). Thousands of software startups have successfully used this framework, each creating their own customised method for iterating on the journey to product/market fit. If you want to delve into some excellent examples, a great resource is the First Round Review. The reality is of course that startups don't "immediately find product/market fit." The great software success stories have nearly always been iterative, multi-year journeys to discover a truly scalable business model, often after a pivot (or two!)....and most VCs do get this.
The subject of not taking R&D risk is trickier. The OpenAI experience has certainly opened Altman's eyes here. But founders undertaking pioneering work in any DeepTech field - from Biotech to Quantum - know that R&D is the essential bedrock. But they also know that broadcasting the fact to investors that there is a big R&D challenge ahead is likely to turn many off. VCs, certainly those that pursue mainstream SaaS for example, are only happy taking market risk and typically veer away from any technical risk. The shortage of true DeepTech VCs, especially across Europe, too often drives founders slavishly towards government grants and corporate funding for research capital - which can only take a company so far. If Altman's advice helped convince the venture industry that it needn't participate in R&D driven businesses then yes, he probably did many founders a disservice. The lesson here is to be cautious about adopting 'how to' advice too literally. The judicious use of a proven framework housing widely-endorsed startup principals is a better pathway. Within that, a founder can (and must) develop their own approach to finding PMF and eventual scaling.