This week on the startup to scaleup journey:
VCs now have an Exit Predictor tool
Investors have a powerful new tool that helps them in the investment selection process. The PitchBook VC Exit Predictor leverages machine learning and the company's vast database of information on VC-backed companies, financing rounds, and investors to provide objective insights into startups’ prospects of a successful exit. Output from the tool can be used to improve the efficiency and effectiveness of VC investment selection workflows, which have become increasingly time-consuming as the universe of startups has grown rapidly over the past 10 years. During this time the total number of active VC-backed companies in the Pitchbook database has tripled to nearly 120,000. Even after filtering this list for an investor’s preferred industry, geography, and stage, there will often be thousands of companies left. The Exit Predictor tool helps filter this list to help zero in on specific 'high-return' targets. In a backtest with active VC-backed companies as of February 2018, startups ranked in the top decile based on output from the VC Exit Predictor were found to be 3.1x more likely to exit successfully (via M&A or public listing) than those in the bottom 90%.
The primary component underpinning the tool is a classification model that predicts the probability a VC-backed startup will ultimately be acquired, go public, or not exit due to failing or becoming self-sustaining. This model has so far been trained on over 64,000 observations of startups with a known outcome where each observation includes hundreds of individual data points, on average. The exit probabilities that are generated from the model are then used to calculate a 'naïve expected return' of an investment in the startup’s next financing round using historical returns by series derived from cap table data. This allows Pitchbook to produce a single stage-agnostic Opportunity Score that can be used to rank and filter a list of companies when screening for potential investments. It is not intended to be used as a standalone quantitative investment strategy or replace the due diligence process. This is primarily because many important factors in a startup’s success - both quantifiable and not - are not available to include in the model, such as detailed company financials, the business model, and founder intangibles, to name but a few.
Predicting exit outcomes is a task undertaken by every institutional investor when weighing up an investment. But it's also a key consideration for founders when building that same investment proposition. As part of investment preparation, a conventional peer group analysis can be used to seek insights into the funding 'journeys' and outcomes for a cohort of comparable companies. This identifies the cadence and key attributes of prior funding rounds, revealing deal size, valuation, investors and other key metrics. The Exit Predictor takes this analysis to the next level by not only identifying how the company is expected to perform relative to its peers, but if an exit is likely to materialise at all and, if so, whether this will be via an IPO or M&A event Quantitative ML methods like this can only ever provide part of any predictive analysis but if combined with a qualitative assessment of investment readiness, they should significantly aid funding preparation for founders (who have access to the platform). Being aware of how your startup is rated against its peer group will provide powerful, fly-on-the-wall intelligence about how the investment proposition is likely to be received by investors. Heady stuff.
The formula for funding success hasn't changed
As founders confront an ever more challenging funding environment, everyone is asking the same question: What can be done to increase the chances of funding success? The first thing to grasp is that the two fundamental ingredients of successful capital-raising haven't changed, they have just become even more critical: Founders must present a compelling investment proposition to well-qualified investors. Sounds simple. But what makes a proposition 'compelling' and an investor 'well-qualified' has changed dramatically over the past 18 months. Since the valuation bubble burst in 2021, when even 'average' propositions could get funded by the most obscure of investors, we have witnessed a total market reset. In terms of what is now 'compelling', founders could be forgiven for thinking that investors have simply become more risk averse: To have a compelling proposition now surely means to have made greater commercial progress, be generating more revenues, have more customers, and a financial outlook that is trending quickly towards profitability. Whilst sound economics are always desirable - and even more so at the moment - this simple characterisation obscures a bigger realisation.
What Tech investors truly crave are propositions that are compelling because they are genuinely disruptive. That means they are bold, innovative, category-creating outliers that will deliver outsized returns. For an edge-case sense of what this means, the manifesto of Peter Thiel's Founders Fund provides a galvanising reference point for the industry. Thiel shares a critical perspective that looks back over the history of Venture Capital - right back to the 1960s. "We believe that the shift away from backing transformational technologies and toward more cynical, incrementalist investments broke venture capital." Then adds "...the most promising companies (at least from our perspective as investors) tend to share a few characteristics: 1. They are not popular (popular investments tend to be pricey); 2. They are difficult to assess (this contributes to their lack of popularity); 3. They have technology risk, but not insurmountable technology risk; and 4. If they succeed, their technology will be extraordinarily valuable." In summary, Thiel concludes; "The best companies create their own sectors". Far from seeking 'better mousetrap' opportunities that might currently exhibit lower risk profiles, what leading institutional investors are looking for are real industry game-changers.
So now we have a better appreciation of what "compelling" means, we can turn to what counts as a "well-qualified investor". We must get back to the basics of selecting investors whose investment thesis and track record is well-matched with the proposition on offer. They must be a clear and proven fit in terms of stage, sector, geography and business model profile. This requires some serious, up-front research to ensure you are picking the right funds and, just as importantly, the right individual investors to approach. Taking shortcuts here will only result in the pursuit of investors that don't meet ALL of the basic criteria: In other words, a wild goose chase with lots of wasted time and effort that will almost certainly result in a 'No'. And given the more cautious investment climate, with many investors still recalibrating their investment strategies, founders must plan to talk to many more investors than they did just two short years ago. If you had a shortlist then of say 40 to 50 targets, today you need to think 2x that number to find that elusive investor match. Finally, and above all, there must be real chemistry in the relationship. There are now too many startups that took easy money over the past 2 years from questionable investors that now look like horrific, long-term liabilities. Be just as cautious as investors themselves have now become and choose wisely. That will increase the chances of real funding success.
SVB's demise is like 'a death in the family'
One week since the SVB crisis and startups are still coming to terms with the impact. The headline news that deposits were safe both in the US and UK calmed everyone's worst fears, but there is still a huge sense of loss. Over the course of nearly 40 years, SVB solidified itself as the leading lender and banking partner for many successful venture startups as well as VCs themselves. This brand recognition and trust resulted in SVB amassing more than $175 billion in total deposits by the end of 2022. But it was the depth of the connections and relationships within the VC ecosystem that made SVB truly different. This enabled SVB to understand the market and the real level of risk as they made credit available to startups. Mike Moritz of Sequoia, in a wonderful homage to this unique institution in his recent FT article, compared the bank's collapse to "a death in the family". "Before SVB sprang to life [in 1983]...it was difficult, if not impossible, for a start-up to secure a relationship with a large, established bank...Small west coast technology companies were incomprehensible or insignificant to the large east coast banks whose customers included international airlines, heavy industry and nationwide retailers. Our companies, often started by people in their twenties, were bypassed or ignored.”
The same can be said here in the UK. SVB UK is now part of HSBC, and the jury is out on how Europe's largest bank will manage this apparent culture clash. The concern is that any potential new owner, particularly a large, established bank, may not have the skill set, the inclination or even the risk appetite to cater to the specific needs of SVB's startup clientele. And it's not just startups that are feeling anxiety about future access to credit, but VCs themselves. As reported by Crunchbase, the largest proportion of SVB’s loan business — around 56% — catered to PE and VC firms to support their capital commitments to startups, a business that was very low risk for the bank, but played a role in facilitating capital deployment for funds. Venture firms could deploy capital quickly once they made investments in startups by using loan financing from SVB. Firms would then follow up to get that capital from their limited partners over time. That helped to streamline the funding process. As VC Miriam Rivera of Ulu Ventures explained: “We don’t necessarily have to make sure that dozens of LP checks have come in the door before we can actually wire money to a startup company." In the US, the FDIC is still looking for a buyer, so there is still great uncertainty about how this aspect of SVBs business will play out there.
The broader concern now, both in the US and the UK, is how a more constrained funding environment will further impact valuations and startup failures. The latest survey from Startup Snapshot shows that founders believe they will immediately face much greater investor caution. In the post-SVB world, venture debt will be much harder to secure and this could have significant implications. As CB Insights reports, plentiful and cheap venture debt has been helping companies delay taking the medicine of a lower valuation and dilution. In some cases, it also helped companies avoid (or perhaps delay) layoffs or even failure because of an inability to raise equity capital. Dealmaking was already slowing down through 2022. In 1Q22, for example, the median time from Seed to Series A was 16 months. By 4Q22 it had extended out to 21 months. So we have the combination of more discerning investors, a slower financing market and less debt available. Founders that were carefully crafting funding plans for later this year suddenly have a lot more to factor in.