How to make complex multi-factor apples to oranges decisions (for example about investments)

The title reminds me of an old science fiction movie - something about "The Effect of Gamma Rays on Man-in-the-Moon Marigolds" (1972). Today it would probably be retitled "Invasion!!!" or some such thing. The complication of the title would seem to indicate the complication of the issue. But on to the decisions.

Investors have to choose between investment options. There are many of those options. So how do they (we) decide? There are lots of ways folks do this. There are quantitative types (it's all in the numbers) and qualitative types (this feels good to me) and types that combine them (the numbers are good, but it doesn't feel that good to me). I like the old trick of tossing a coin in the air and as it comes down, identify which one you are rooting for. Heads or tails? Don't bother to look at the actual outcome. Then there is the sleep on it and see how you feel in the morning.

But there is a lot more to decision-making than just this dimension. Different folks use different approaches. Many investment groups I know of keep narrowly focused with experts in their fields, and they make choices between outstanding candidates that meet all of their minimal criteria. They spend months in due diligence and make decisions to invest only a few times a year. Other groups I know make multiple decisions each month, a few hundred investors choosing perhaps once a week (after a few months of due diligence). Some groups today are strictly followers - they will put $50,000 into any investment where someone else they know has put in a similar amount under the same terms very recently. Some groups have investment goals of so many investments a year, while many individual investors may make one decision a year.

The investment thesis

I'm unaware of who came up with the term, but the idea is that investors have a notion behind what they do instead of just picking at random. They formalize this to some extent into an investment thesis. Something like "We hypothesize that companies with positive cash flow and high growth in a huge emerging market and at a price point far better than the average we see is worth investing in." Then they go after seeking out companies who meet the criteria, ignore the applicants who do not meet it, and perhaps end up investing in... well... I think you are unlikely to find any of these.

Different investors go after different things. For example, since the price tends to go up (per percentage ownership) as the quality goes up, early stage investors are looking for high risk, high reward opportunities, many of which will fail. That's their investment thesis, at its heart. 70% or higher failure rates, but the top 10% generate 30x in 5 years average, and the other 20% generate perhaps 5x in 5 years. So if I invest in 100 companies at $10K each ($1M total), that yields $700K (70 failures) lost, $1M gained (from the 20 yielding 5x), and another $3M gained (from the 10 companies averaging 30x). So $1M turns to $4M in 5 years. That's a statistical investment approach to high risk high reward early stage companies.

Different folks have different strokes, and all of them can work, assuming one thing. You need to be able to get the right risk/reward profile out of your investments to meet your approach. And there's the rub. How do you tell which opportunities meet your criteria for risk and reward?

Measure it?

I was educated as an engineer/scientist, and as such, I tend to view the world from that perspective. That's one of the reasons I try to work with folks who have other backgrounds. Because I don't want to make mistakes that engineers and scientists make about investments when left on their own. Of course I have also started and run companies since the 1970s, so I have some business experience, including operations, management, sales, marketing, etc. Which is why I imagine I can tell when someone in these fields is better at it than I am. Which is how I choose who to work with. If they aren't better than me at it, they cannot be very good at it - my thesis for collaboration (as opposed to task workers, individual contributors who just have to be good enough to do what they do, not better or worse than somebody else at doing it).

So I like to measure things. I measure things using a set of metrics based on many years of experience and looking at decision processed from from lots of other folks. So I measure and measure, and then what? Somehow, you need to make decisions after you measure, and if the measurement was worth the effort, it has to effect the decisions. I have some rules for myself on measuring things:

I have created a measurement framework for Angel to Exit, and we use it for all presenting companies. These metrics are then available to use for decision-making. While they are not the end all of the decision-making process, they are a good beginning to see if we are on the same page. If you look at the quarterly update (top right hand corner of the a2e.co Web page) you can click through to the actual metrics on presenting companies and see just what we measure today, and how the presenting companies claim to measure up to those metrics.

Higher scores make for better investments - right?

Nope. It turns out this is completely wrong. For several reasons. Here are some of them:

So how do I use such metrics?

It turns out, you have to weight each of the things we measure according to your investment thesis and according to the industry and situation in order to have the metrics make sense. And how do we determine these weights? There are a few ways... some of which I have listed here, each with their own problems.

We believe in choosing your own approaches. We provide the ratings, ways to look at them, and mechanisms for you to apply them in the ways you like. You of course make your own decisions.

Are you better off?

I don't know. I feel better off, and I can certainly use the information to make decisions and justify them. But at the end of the day, we don't get to repeat our experiments, and I don't have enough money or time to do the job on my own. But perhaps you do? My metrics - your money?

Metrics can bring you things regardless of the outcome of the final decision regarding an investment. Here's an example. Suppose I am looking at 2 companies and they seem pretty similar. How do I tell the difference? Of course I compare them, but on what basis? If I don't have anything to measure, how do I decide?

I hear folks say things like "I like the CEO" or "I like the market size", but at the end of the day, these have to be balanced against one another in order to make decisions. So I prefer to use tools so I can see how I am shading things and avoid cognitive errors associated with ordering, etc. I can decide to favor one over another, change my weightings for one company vs. another, and see the results. And then I can find ways to explain it and justify it to others.

A call to action

Am I better off? I think so. Do you? You will only know if you try. Want to try? Start by presenting at one of our upcoming sessions and use the metrics to measure your company.

Go To Angel

Then use Decider to look at how decision-makers such as investors will view your company. Then...

In summary

Making better decisions doesn't mean having a computer tell you what to do. It means using tools to help you understand and justify what you do.

Copyright(c) Fred Cohen, 2021 - All Rights Reserved