The Hard Truth Behind Investing as a VC
I joined the rank of investors not that long ago. Before that I used to talk to a lot of people about the VC industry (mostly entrepreneurs) and it wasn’t clear for most people how the investment decisions were made.
Some of the VCs had a very narrow investment thesis, and seemed to have a hard time at finding very good projects in their field, especially if they invest only in Europe.
Most of them talked about the current hype (sharing economy, marketplace, SaaS, apps at that time). It could be seen as a lack of vision, but basically it means that they were betting on people, which is not a bad strategy on itself. However good this strategy was, most of the VCs wasn’t communicating it clearly for the outside world.
What is surprising for most outsiders are the due diligences in the VC industry, especially for early-stage companies (it is much more easy to have analytical procedures when a company has traction and its market already well drawn).
And to be fair, there is a kind of schizophrenia from the outsiders, especially from entrepreneurs: they want VCs not to rely too much on data (the “xls-kind of guys) and to make quick decisions, but they complain that the due diligences are “too light”, that “VCs don’t get the value proposition and/or the way the startup is disrupting the market”.
The recurring complaints about due diligences are the following:
- There is no user research.
- There is no in-depth market analysis (they are mostly based on very few calls with players in the industry and centered around competition, not around usages, consumer behaviour & psychology).
- There is a big reliance on VCs own tastes and habits.
- There is a strong role of intuition: how “they felt“ the entrepreneurs, the market, the product.
- Many people are denouncing a herd mentality.
- For what I could see, I was especially concerned about correlated errors (see below). The resort to the same sources (successful entrepreneurs locally) and the structure of governance (managing partners being very influential internally).
To give you an example of correlated errors, think of the wisdom of the crowd. You might have already heard that if you ask many people how many coins are in a jar, you end up with an answer pretty close to the reality, almost always better than the answer of a single expert. What we often forget to say is that if people hear each other, the estimate ends up totally incorrect because we tend to conform, hence getting a… correlated error.
- There is no procedures to minimize biases such as overconfidence or anchoring effect (and if you know the industry, you know these kind of biases are not exceptions).
So when I entered the industry, I was eager not to be the target of these critics. I wanted to build a damn good due diligence methodology.
Toward The Damn Good Methodology
My first due diligences was far from perfect comparing to my expectations. I hadn’t yet developed the research methodology I was dreaming of (with the right database, sources, frameworks, network, tools, etc.), nor did I had developed the checklists and processes to end up to the optimal decision.
However, I made my best to do what I thought I should do. I made an in-depth market study. I talked to many sources, that couldn’t influence each other and that didn’t share the same perspective. Eventually, I wrote a (very) long report that I shared with the team. I was proud. I was heading in the right direction to develop the research methodology and decision-making processes I longed for.
Before I realize I was wrong. Entirely wrong.
The Hard Truth of VC
I knew we needed to accept complexity in the realm of digital innovation.Therefore I hadn’t the ambition to predict outcomes, only to assert strengths, opportunities and to get a dynamic pictures of particular ecosystems.
However, my dream of the perfect methodology was built on foundation that didn’t go along very well with complexity. Especially, I forgot something crucial in the field. S-P-E-E-D. The time I took to make these due diligences was time I didn’t spend to meet new people or scan other opportunities.
VC is not about making the best analysis. VC is a job where trade-offs are kings. You always act under time constraints:
- the dealflow is endless (there is not a single day when good entrepreneurs are not tackling a big problem with talent, all the time you spend in one deal is time you don’t spend with others),
- deals are competitive (if you don’t decide, other will ; and the more time you spend,
- entrepreneurs’ time is a key asset: the more time you put them on hold, the more you waste their time and energy. This is not a good way to be chosen and recommended.
- and your resources (=time) are scarce.
So did I gave up improving how things are done? No. But I have the right information to play with the variables and work toward what I find optimal. And it’s certainly not the biggest report possible.
The Road Toward Optimality
Let’s remind something: I believe there are many local maxima, all depending on resources and strategic choices of VC (depending on vision, investment thesis, maturity of the investments, geographical scope, size of the fund managed, internal organization, associated stakeholders, etc.). Here, I only talk about choosing to do an investment or not (= “sending a termsheet”), which is only one component of the VC job (you also need to source the best companies, being chosen by the best entrepreneurs, help your companies grow, help your company raise and exit, fundraise, etc.).
After having said that, how to improve the way to make an investment as I see it now?
1. Develop methodologies to gather valid and diverse informations as fast as possible.
At daphni, we built a community (200+ people, most of whom have invested in the fund) to make sure we can access information easily. We made sure to have people with many backgrounds, age, geographies and profile, not only to have the broader knowledge base possible, but also to decorrelate errors.
We are also working on knowledge base to be able to have fiable comparables and capture know-how overtime. This is not an easy job when you are a generalist, in a fast moving industry (sometimes I wish we only looked at b2b SaaS companies).
2. Build a culture of trust, goodwill, curiosity and humility.
A December 2009 survey of 463 readers of mckinseyquarterly.com, asked “Does management admit mistakes and kill unsuccessful initiatives in a timely manner?” 80 percent of C-level executives said yes. In contrast, only 49 percent of non-C-level executives agreed with the same statement. Our society reward over-confidence. We associate leadership with decisiveness. We like John Waynes. And let’s be clear: there is a cost of not being John Waynes. But there are many more upsides in the long run in my opinion. Philip E. Tetlock, University Professor of Psychology and Political Science, showed in his work (and in his wonderful book Superforcasting) that overconfidence always lead to worst capacity to forecast.
I’ve talked about how to keep on having a great culture. I recently read something very witty from Gary Klein on that matter:
“What concerns me is the tendency to marginalize people who disagree with you at meetings. There’s too much intolerance for challenge. As a leader, you can say the right things — for instance, everybody should share their opinions. But people are too smart to do that, because it’s risky. So when people raise an idea that doesn’t make sense to you as a leader, rather than ask what’s wrong with them, you should be curious about why they’re taking the position. Curiosity is a counterforce for contempt when people are making unpopular statements.”
3. Set up processes and a governance able to make the right decisions
One of the key question around decision, besides minimizing biases, is around the confidence we should put into intuition. My partner, Mathieu Daix talked about it in our last discussion and shared great insights about intuition and decision-making when you are a VC.
Here is an extract from a conversation that took place between Gary Klein and Daniel Kahneman, two of the most recognised thinkers on the subject:
McKinsey Quarterly: In your recent American Psychology article, you asked a question that should be interesting to just about all executives: “Under what conditions are the intuitions of professionals worthy of trust?” What’s your answer? When can executives trust their guts?
Gary Klein: It depends on what you mean by “trust.” If you mean, “My gut feeling is telling me this; therefore I can act on it and I don’t have to worry,” we say you should never trust your gut. You need to take your gut feeling as an important data point, but then you have to consciously and deliberately evaluate it, to see if it makes sense in this context. You need strategies that help rule things out. That’s the opposite of saying, “This is what my gut is telling me; let me gather information to confirm it.”
Daniel Kahneman: There are some conditions where you have to trust your intuition. When you are under time pressure for a decision, you need to follow intuition. My general view, though, would be that you should not take your intuitions at face value. Overconfidence is a powerful source of illusions, primarily determined by the quality and coherence of the story that you can construct, not by its validity. If people can construct a simple and coherent story, they will feel confident regardless of how well grounded it is in reality.
The Quarterly: Is intuition more reliable under certain conditions?
Gary Klein: We identified two. First, there needs to be a certain structure to a situation, a certain predictability that allows you to have a basis for the intuition. If a situation is very, very turbulent, we say it has low validity, and there’s no basis for intuition. For example, you shouldn’t trust the judgments of stock brokers picking individual stocks. The second factor is whether decision makers have a chance to get feedback on their judgments, so that they can strengthen them and gain expertise. If those criteria aren’t met, then intuitions aren’t going to be trustworthy.
Most corporate decisions aren’t going to meet the test of high validity. But they’re going to be way above the low-validity situations that we worry about. Many business intuitions and expertise are going to be valuable; they are telling you something useful, and you want to take advantage of them.
Daniel Kahneman: This is an area of difference between Gary and me. I would be wary of experts’ intuition, except when they deal with something that they have dealt with a lot in the past. Surgeons, for example, do many operations of a given kind, and they learn what problems they’re going to encounter. But when problems are unique, or fairly unique, then I would be less trusting of intuition than Gary is. One of the problems with expertise is that people have it in some domains and not in others. So experts don’t know exactly where the boundaries of their expertise are.
Bottom line: the key issue for Kahneman and Klein is the validity of the environment, which is a function of (1) the stability of the relationship between objectively identifiable cues and subsequent events (predictability) (2) the capacity to learn from the regularities (feedback-loops).
For those who wants to dig deeper, in low-valid environment (such as VC?) (1) you should acknowledge uncertainty, and the best strategies to improve decisions are (2) heuristics and algorithms (cf Kahneman, Klein, Gigerenzer).
4. Stay up-to-date with current technologies, business models & usages
You can choose not to be specialized (in an industry, a specific go-to-market or a technology) but you cannot make the economy of staying up-to-date with big trends (blockchain, deep learning, etc.) and you need to know when to do an in-depth market study that will be helpful in the long run.
As you can see, I discovered an unexpected behind the scene when I entered the VC job. And as Albany says in King Lear (I, 4):
“How far your eyes may pierce I cannot tell. Striving to better, oft we mar what’s well.“.
I’ve first forgotten the key role of speed which is the biggest constraint, alongside complexity in the VC industry. That doesn’t mean you can’t step up your game and aim at improving your research & decision processes. You just need to remember that sailing a ship in an unexplored road is different from driving a sport car in well-designed roads. This is the hard truth behind investing as a VC.