> Experimentation is contrasted with another mode of learning that I term Analysis. Classical competitive strategy emphasizes learning through analysis (Porter, 1980) whereby, instead of generating real options, entrepreneurs generate option sets and arrive at a decision through optimization (see Delmar and Shane, 2003, for an example). In my study, analysis includes gathering market, product, and regulatory data or developing business plans. Gans et al. (2019) distinguish analysis from experimentation in two important ways. Analysis is “commitment-free” whereas in experiments some irreversible investment in the ideas being tested is inescapable. In turn, the commitment-free nature of analysis implies that it can only yield noisy information, whereas experiments produce high-fidelity signals. I add a third difference, which is that analysis, in and of itself, conforms to standard and routinized practices,⁶ whereas experiments are, by definition, innovative and require counterfactual thinking (Camuffo et al., 2020). This delineation between the two modes of learning described above is also present in the practitioner literature (Bhidé, 2000; Blank, 2013; Ries, 2011).
I've been in the software business for a long time. I've been in startups and big companies, and worked with angels and VCs. But I have no idea what any of this means!
What is the market for a paper like this? And why can't it be written in plain English?
(1) "classical competitive analysis" (Porter) would be basing business decisions on market trends.
(2) "experimentation" is what many of today's startups call "MVP minimum viable product" + "iteration", or "lean startup" popularized by Eric Ries.
The (2) experimentation is emphasized lately because cloud infrastructure like AWS makes software experiments very cheap and fast to test business ideas.
But (1) classical analysis is often the only choice especially for building physical products requiring upfront heavy capital investment. You can't "cheaply iterate" to build airplanes or launch a constellation of commercial communications satellites. You have to commit billions to build them first based on theoretical market projections and hope customers will buy it. E.g. both Airbus A380 and Boeing 787 were designed by working backwards from market data analysis. Neither had the money to iterate by having the factory build 10 different airplanes.
>What is the market for a paper like this? And why can't it be written in plain English?
Based on the author's bio, the primary "market" appears to be his PhD thesis advisors:
The secondary market might be HN readers who have no impact on his academic career.
But this is exactly what SpaceX is doing? Ditto with Starlink.
No, not the same.
For SpaceX, Elon spent almost all of of his $160 million PayPal wealth on 3 failed rockets before the 4th finally worked. And that 4th successful rocket test only demonstrated a proof-of-concept and didn't have a real payload from paying customers. That's an example of R&D in physical materials not iterating cheaply like the software world.
For Starlink, some google search finds this:
"Despite the heavy investment needed to build Starlink, the company's leadership estimates Starlink will cost about $10 billion or more to build"
$10 billion is not cheap to build/iterate.
Compare to the software world... Kevin Systrom building an iOS app for location check in (Burbn) and then pivoting to a different idea of photo filters (Instagram) is way cheaper than spending millions/billions on destroying rockets and launching satellites.
Ditto with Starship.
Yes, they are all more expensive than software, often much more so to iterate over, but fundamentally what SpaceX do is iterative development.
Yes, SpaceX and many other companies (aircraft companies, car companies, etc) also "iterate" ... but you're losing sight of the original question that was ask by gp (Stratoscope) and the context of "iterative development" for this thread.
The author of the paper was trying to explain the difference between "classical analysis" vs "experimentation" to drive new business strategy.
Yes the companies forced to do "classical analysis" _also_ do product "experimentation/iteration". However, when the author breaks out "experimentation/iteration" as a separate type of "business learning", he's talking about Eric Ries' version of "fast & cheap iteration" and not SpaceX's slower more expensive iteration.
>It is ten billion dollars to build the old system, [...] Yes, they are all more expensive than software,
And these are the real-world financial constraints that bias "classical analysis" over cheap iteration of the author's two learning styles.
I’m thinking of the space IoT startup Swarm (of radio space piracy infamy).
Two ways to learn about the market.
1 - Analysis
He's defining as using data from existing companies, economic trends, etc. Much of this data is relatively low cost and can be fine quickly.
Analysis tends to provide insight into existing supply and demand. E.g. How many companies are selling electric cars? How much did the sales increase/decrease this year?
Based on analysis, a startup might want to create a new charging station.
2 - Experiments
This is where someone puts an offer into the market and sees if there are buyers.
Usually these are for unique features, or possibly new products.
Example: clubhouse was an experiment
He's saying experiments usually cost more, because in theory you are at least prototyping + spending money on marketing/sales + support of early buyers.
Analysis looks to identify useful patterns in what is already happening, so factual.
Experiments try to find gaps that look for needs that aren't being met, so no behavior yet... So "counter factual".
Possibly he's also saying that deeper innovation happens based on experimentation.
And he's further asking: Do angel investors support experimentation more than other types of investors.
VCs are quite risk averse in my opinion, at least at the seed stage.
If you are a founder—any industry—hit me up and hopefully I'll fund you! Email firstname.lastname@example.org
I don't care if I don't know an industry. I look mostly for qualities and unique characteristics in the founders themselves.
Dude you asked for it :)
The earliest investors (mostly angels, usually not VCs) are taking the risk of "can you ship?"
The next round (some angles, but mostly VCs) are taking the risks of "is there any market for this?" and "can you sell to a few customers in that market?"
The next round (almost entirely VCs) are taking the triple risks of "is this a real market?", "can you sell to LOTS of customers?" and "can you scale a business quickly?"
And every round (exclusively VCs) are taking the dual risk of "can you expand your customer base into adjacent segments?" and "do your economies of scale eventually work?"
Unfortunately, no stage proves the next one, sometimes what looked like market early on turns out not to be one (many of the dotcoms), sometimes the math never works out (MoviePass, 98% of the dotcoms), sometimes the people who got you there can't get you to the next level and can't admit it, and there's the occasional frauds that slip through (Theranos).
There are hundreds of other, more nuanced reasons investments fail but those are the big ones.
Avoiding category-creation risk is true of most investors most of the times
For VCs, it's understandable given investors see so many co's pitch and it's one less risk to worry about. The later the stage and bigger the check, even more pressure.
Earlier stage is always more welcoming than later stage. Risk is lower for angels b/c betting on team means the startup can pivot (harder later) and can always exit for lower amounts ($20-30M exit for a $50K check is more of a 5X return than the goal of 10-100X return-the-fund, but a few of these still works and is more doable)
Angels, on the other hand, are more likely to have a wider range of internal motivations and less constraints.
Some of them might be open to real innovation instead of hedging against it.
I see what you are trying to say but misworded it. Their goal is to generate high returns instead of innovation. If innovation will generate returns then they will invest. Their role is the riskier are the higher percentage earning investments in a portfolio for an endowment (historically).
That said angels can only do the front end very high risk of the investment curve. They can’t carry the company to fruition.
> VCs are thus disincentivized from disrupting those companies, even if it makes a good return for the new company.
How do you think Uber, AirBnb, etc. were all funded?
Huh? VCs clients are pension funds, fund of funds, etc. Their main job is to return those LPs a return on investment. Nothing more. Very few of those LPs have deliberate plans to avoid disruption. Unless you're talking about CVC specifically.
Unless I'm mistaken about your use the word "client", this is just plain wrong.
The observation is that disruptive innovation is inevitable.
The role of VCs is to protect against this risk.
You can't protect money by letting it in the bank, investing and hedging is the only viable option.
Makes sense, agreed.
> The role of VCs is to protect against this risk.
Protect who though?
Are you just saying that a LP has to allocate funds to a VC asset class in order to hedge against worse returns in other asset classes? In other words, if I'm a pension fund, I don't put all of my capital into Marriott because I need to allocate some of it into AirBnb, since Marriott's market cap will likely go down as a result of ABNB's success? Hence - the hedge.
The goal is not to create value or even to make money, but to not lose it.
But for who? You keep saying "from their clients", but I don't think you understand how the VC model works or care to explain what you mean by "protect".
Here's an example:
The California State Teacher's Retirement System, or CalSTRS (called an LP) committed money into Shashta Ventures. Shasta ventures then invested in several Series A and Series B startups (presumably "disruptive innovation"). Sashta then profits from selling those companies and takes a part of that profit for themselves and gives another part to CalSTRS.
So. No, they're not "protecting it from their clients". VCs clients are their LPs and their goal is purely to profit from M&A/IPO activity and return that for themselves and their LPs.
There isn't any dirty little secret about the industry - its that simple.
VCs (and their clients) are aligned against innovation, contrary to what we might read naïvely.
They are investing in "innovative" companies to protect their money against the innovation and also to control them.
For the record, I'm an angel investor and work with VCs. What you're saying makes no sense to me.
To use concrete examples, while I know there are always internal believers, perhaps decision makers at Visa invested in Stripe and at USAA invested in Coinbase to hedge downside of disruption, not because they want to encourage those technologies.
PS - Those are examples of CVC. Which IMHO have very different goals than traditional VCs.
If you have your own idea it's believed that you love the idea a little too much unfortunately.
Making a return is protecting money, and in this case this is done by hedging against innovation.
VCs are not the friends of innovation.
I would have guessed it's the other way around.
Since VCs have usually more money on their hand, they can diversify more and take bets.
Yes they take far more than I do.
I take more risky bets in the sense that I would fund pre-revenue companies (higher % lets say).
Having said that recently there has been explosion on seed stage VCs trying to grab angel money directly and deploy to startups through funds with tax incentives.
Not my thing, prefer to go direct, they have resulted in more inflated valuations and competition though but good for the startup not necessary your average joe angel like me.
I am currently negotiating a buy-in for my SaaS, so for validation purposes I contacted a few VCs in our domain, and received a few replies stating they required at least 500k to 1 million ARR.
It would be my assumption that - in Europe - you don't really need VC money if you're making this amount of ARR, unless your margin is so low, or you are growing so fast that there is a huge risk involved.
To me getting VC money at 500k/1 million ARR sounds like a very expensive loan where the VC has limited risk (the investment) and unlimited upside. If I would be at that amount of ARR and in the need for some credit, I'd rather go to the bank and pay for a credit line for a couple of million that we can use when/if we need it, especially at the current cheap interest rates...
Update - addendum: Just to clarify: I am a big fan of external capital if it also includes proper engagement, preferably an org that has a huge network and/or proper domain knowledge.
It's likely the business you're pitching has an offering, but the revenues are pretty flat or growing slowly. You're in that weird in between zone that isn't interesting to VCs. You need to keep iterating on the offering until you find something with the right growth potential, otherwise you're stuck just staying a small business.
Your own money you only need to justify to yourself. Someone else's needs justifications that are socially viable.
Don’t get programmed by what they are promoting. The most successful companies don’t discover markets, they create them.
If you need the venture $, find the 1%.
That makes them sound like something out of a Jeff Minter game.
(FWIW, I have started and been part of the founding team for several companies, both angel and VC-backed. VCs are not nearly as interested in innovation or building a good company as they are in establishing control to set up a successful exit. That's not necessarily bad, it's just that they're more mercenary by nature.
Many more angels are willing to put up with early losses to develop the tech/company, then the VCs come in to fund growth and they get washed out after taking the lion's share of the risk. Sad, but true.)
consider silicon valley. government allocates funding for long-term high risk research programs toward various defence objectives. this funds fundamental research in universities.
some researchers then spin off startups to develop products for defence applications -- so the government takes the risk to fund any long-term blue-sky research and then is also willing to as the first customer and provider of contracts for any startups that figure out how to industrialise/commercialise the research for defence applications (electronic warfare...).
see e.g. https://steveblank.com/secret-history/
similarly, consider the development of tcp/ip. pretty handy thing. no startup managed to capture the rights to tcp/ip and change rent to all users of the internet, so arguably from the perspective of commercial startups tcp/ip is a failure.
My understanding is that the quality varies greatly from investor to investor regardless of being a VC versus an angel, and their reputation is the greatest indicator of how helpful they'll be. I'm sure an investor from Sequoia is going to be much more helpful than Random Joe Angel.
So I feel like this is a field where individual characteristics are key, and this paper turning to statistics, generalizing over many angels and many VCs, makes little sense. What am I missing?