Messy Problems
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Messy Problems

The Talent Arbitrage basis for Tech Valuations

A few years ago, as I was early in angel investing, I was offered angel allocation into a deep-tech computer vision company. One of the arguments given for investing was that the founders and team were highly technically competent and that there was at least a downside valuation floor of an acqui-hire at the going rate of 1–2M USD/engineer. Given that the company already had 4 engineers, at a 10M valuation, I was basically investing in the liquidating price of the company.

This was a very interesting argument because it was basically an arbitrage on tech talent hiring, and can provide a partial explanation to the current state of tech startup valuation.

Essentially, if you believe that new and old talent is fundamentally flowing from incumbents into startups (for a variety of non-financial reasons), and that startups are increasingly given enough capital to challenge incumbent payscales, then the disconnect between VC valuations and fundamentals is fundamentally an accurate reflection of startups as an index-able bet on the future of talent.

5 years ago, culture and Tier 1 entrepreneurial talent attracting great talent would have been enough to defend this thesis adequately.

Now, this is supplemented with the increasingly massive influx of venture capital into the startup scene, it is almost undeniable that the fastest way for smart people to get outsized financial returns is to work in the startup/tech sector — whether you are a driven, hungry undergrad or a seasoned industry executive with 15 years of experience.

This means that the brain drain from traditional industries and incumbents is happening at an increasingly ferocious pace, and growth through M&A/acqui-hires will continue increasing exponentially, especially coupled with the inability of traditional hiring teams in incumbent companies to recognize the value of increasingly messier CVs of the younger generation.

This is not a new concept — Management Consulting has long been noted as a talent arbitrage that channels top talent to work for traditional incumbents that might not have been able to hire such talent.

“Of the ~15 clients I served while at McKinsey, I realistically would only have taken a job at 1 or 2 of them.” — Ex-Consultant

If we believe that tech startups will soak up the next generation of talent over top management consulting firms, the interesting question is not whether talent arbitrage exists, but rather the form in which it takes place, and what new forms of talent arbitrage will emerge.

Already, companies like Palantir have been recognized by Harvard Business School as engineering talent arbitrage for the military.

Compared to companies like Google, Apple, Facebook, Amazon or the latest startups funded by Sequoia Capital or A16Z which are all desperate for engineering talent, the last place a top software engineer wants to work is in an old government building. Palantir takes advantage of this arbitrage opportunity by creating a top tier employer tech brand in Silicon Valley that attracts the best talent.

This has the obvious conclusion that we should invest in founders that can hire well. As those who have hired know, hiring is not just about building lead generation funnels or efficient pipeline tracking processes. It is about the proper construction of narratives, company branding and vision, and optimizing for Talent Density Potential [Tier 1 talent only want to work with other Tier 1 talent, creating a talent moat which is hard to build, hard to assail, easy to break].

However, it also provides support for what could be inputs for successful venture-backed businesses — for example, Capital Moats.

Technology is great, but if this Talent Arbitrage exists (especially in Emerging markets or traditional industries), an investment strategy exists that posits that we can just focus on investing in the top 10% of Talent and those who can recruit a team of associated talent — defined by raw intelligence and execution ability, regardless of the business model. Technology merely serves as the potential medium for incumbents to be disrupted through the top 10% of Talent.

Further, one reason capital follows capital is that by and large, talent also follows capital — Capital as a moat may not make sense for sustainable long-term business models, but may do so for sustainable long-term talent arbitraging.

If we imagine a situation where the cost of an incumbent to hire Tier 1 Talent to accomplish X complicated project is $100 (including salary, but more importantly including all-in acquisition cost), but the cost of a startup/challenger to hire Tier 1 Talent is $80 (even if assuming salary cost is higher, balanced by lower all-in acquisition cost, which includes the cost of convincing talent to take the offer).

The idea that it may be cheaper for a startup to hire Tier 1 Talent than incumbents sounds counter-intuitive, but makes sense in the context of equity offerings, culture, and mission/vision. Arguably, it is easier to hire ambitious talented people into a vision-aligned startup that is looking to disrupt X, than it is to hire the same people into a traditional conglomerate.

Interestingly, I have been told anecdotally that certain large conglomerates in Indonesia, for example, have payscales for executives and high potential overseas graduates that even FAANG companies sometimes struggle to compete against — a reflection of what I infer to be forward thinking on brain drain in a talent-scarce ecosystem.

If all of this is true, then instead of waiting for talent and startup ecosystems (particularly in emerging markets) to develop organically, one could create talent moats via capital moats.

The implication is that the combination of capital moats, startup culture and startup upside to fund Tier 1 Talent Hirers in talent-scarce startup ecosystem (typically emerging markets) will lead to market dominance, regardless of the starting business strategy/model. The company can be trusted to hire talent to progress/pivot accordingly, and at the necessary speed.

VC investments (and its associated valuations) can thus be seen to be a broad index on talent — not necessarily an endorsement of specific business models. Spotting founders who understand the power of leveraging capital and talent arbitrage will create outsized returns in traditional and emerging markets.

Chia Jeng Yang, Principal at Saison Capital, dives into consumer, SaaS, and fintech investment trends across the U.S. and Asia, builds projects in the venture capital and public policy space, works closely with early-stage founders (Pre-Idea/Launch) and can be contacted at jengyang.chia@gmail.com. Previous work here: http://chiajy.com

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Chia Jeng Yang

Chia Jeng Yang

Principal @ Saison Capital | Consumer/fintech investing | Angel/Operator | work with smart people on projects: http://chiajy.com