So some craaazy hippie was telling me that, apparently, corporations these days have much more power than the government to effect society.
I think we’ve all come across this notion at some point. There’s no doubt in my mind that it is, at least in some respects, true. And, oh, how people are in an uproar.
But I think people miss a huge strategic notion in this debate. The notion revolves around where these company’s power originates. They have power because they make so much money. They have so much money because the mass population decides, on a transaction by transaction basis, to give them their money (in exchange for goods and services).
Now people in the past have tried boycotts. And that’s fine. But boycotts have an off-putting notion because the boycotters main goal is to get other people to not buy from the company. Which is fine.
My suggestion is that consumers simply accept the fact that government is broken, weak and largely un-fixable. Not that we should abandon it, but we should also do what we can in lieu of our government votes being so non-consequential. We should instead realize that every single dollar we spend is a vote in favor of that company’s practices. Just as we have responsibility to know what the governments for whom we vote will do with the power we give them, so should we be aware of what the corporations will do with the power (through dollars) that we choose to give to them.
And just as those government parties whose policies are not liked wither and die, so will such corporations. Use your dollars to vote.
Back to bid-niz. As I was having dinner with some start-up folk a few weeks back, I got to thinking about where talent flocks. Typically talent doesn’t always flock to just where the money is. Talent will flock to what’s sexy and has money. This means that markets, where there is currently money to be made, are very likely to be under-served.
There is disproportionate value in unsexy markets.
Think about all the badly run mid market businesses out there in unsexy markets that haven’t changed much in the past 15 years. No talent wants to work in the plastic injection molding bath tub industry. But that means there’s some guy with a facility in China pumping out these walk-in tubs for old people out at $65 bucks a pop and selling them at $800 and making 25mm per year with no competition. Not bad.
Think about all the talent flocking to tech startups trying to vie for all the VC money and all those consumers. They don’t call tech a competitive scene for nothing.
So maybe you should think about a less sexy market, where, for some reason you have an in, a leg up, an odd connection or a random talent to start your next venture.
New idea generation is riddled with failure. And it has to be this way. Not from our choice, but simply because of how the world works:
Ideas have to be thought of in terms of risk and reward. If an idea has many great attributes and is not risky than it will be very likely that someone has already identified this and tried it. And so that leaves only the risky ideas that also have many great attributes.
This logic leads one to understand that testing in business is of the utmost importance. It means that the only way you will find out if these risky, good ideas will work, is through testing their main components. It therefore increases, exponentially, the importance of testing ideas in the least capital intensive fashion possible.
And if you’re playing in a risky space with high payoffs, it also means many of your ideas will fail. Not because they were bad ideas, but because you could not inherently know that the idea would not work.
And so it also means that you must have to confidence to expect failure, be ready for it and be ready to have the confidence to move immediately forward with your next ideas afterwards.
Note: Inspiration from this post was gleaned from the authors of “Black Swan”, “A Drunkards Walk”, “A Random Walk Down Wall Street” and “Fooled by Randomness”.
When it comes to prediction in anything. It is usually the most simple algorithm with the fewest moving parts that can stand the test of time.
But there’s an aspect of this axiom that is even more fun. Experts often tout their ability to predict the future in various fields. Recent research concerning experts versus simple algorithms has shown that this is often not the case.
The best example in my reading is a wine connoisseur who buys and sells wine of a particular region in France each year. Not only does the algorithm (which simply uses rain fall and temperature to achieve a forecast price with 90% accuracy) beat the expert, even when the expert has the ANSWER from the algorithm and is told the algorithm’s ACCURACY, he still forecasts worse than the algorithm.
It is mostly due to humans natural tendency to overweight minor details. The expert tries to think outside the box and be smarter.
So what’s the big deal? Well if you’re a wine connoiseur, shut up and trust the algorithm and if you’re in business, look for ways to use simple algorithms where your judgement might be clouded by several small confounding factors whose weight you’re likely to overvalue.
More interesting things to come from Kahneman’s new book, I’m sure.
There are two irrational human tendencies about which I’ll write today. They are the Possibility Effect and the Certainty Effect.
It has been proven that humans will consistently overestimate the importance (or “weight”) of low probability events. We will also overvalue the importance of 100% certainty compared to 95% certainty for example.
This concept is a little hard to grasp, but let’s consider the idea below. If there were a 1% probability or chance of something happening in your life, you might expect that you weight that chance at 1%. In fact, meta analysis shows the that weight people usually give something with a 1% chance of happening as being more like 5.5%. Conversely, if there was a something in your life with a 99% chance of happening, you’d like to think you would weight it’s value at 99%, but you don’t. It’s far from perfectly certain in your mind and so you weight it around 91.2%
As an example, what would you rather?
A) A sure gain of $300, or
B) An 80% to win $450 (20% chance to win $0)
If you’re like most people, you’ve chosen option A, a sure gain. However, if you do the math, an 80% probability of winning $450 carries an expected value of $360 (.8 x 450). So, most people would give up an expected $60 of value just for certainty.
If we were perfectly rational people (or Homo-economicus or Econs as some refer), we would select the risky option. But we are not. This is the certainty effect: the irrational draw we have to the 100% certain.
We do a similar thing with low probability environments. As soon as something is remotely possible, we weight or value that possibility to a greater degree than we should. This Possibility Effect as Kahneman explains in his new book “Thinking, Fast and Slow” is the reason why lotteries are so popular. If we have a ticket; “… you’re sayin’ there’s a chance.” I guess Dumb and Dumber wasn’t so dumb after all.
There is an increasingly significant economic reasoning for doing what you like in this world as a career.
It involves two axioms.
Firstly: that the competition for particular jobs is ever-increasing. As the population grows, so also does the amount of jobs (that’s why the unemployment rate stays a +/-3% range usually), however the amount of different jobs does not grow as much.
Secondly: that you are generally better at a particular job if you like it.
Therefore, there will be (and are) increasingly more people who will apply for a particular job who are also likely to literally LOVE that job. This means that if you don’t LOVE that job, others will be able to be better at that job than you. You will either have to work harder or be smarter than the competition. And that’s tough. Because if they love the job more than you, they’ll likely want to work even harder than you. And especially harder if they see you beating them out for the job (when either applying or while working there).
So, if you want to be amazing at your job. Just like yo momma said, do what you love. As time goes on, it is increasingly more efficient and beneficial to choose something you love.
In the 1980’s North American brewers began to do something very interesting. They started advertising the fact that they used 100% malt in their beers and zero adjunct. Now that sounds well and fine, expect for the fact that the had been doing this for a very long time. And also, that adjunct didn’t actually mean anything bad at all.
The term adjunct in brewing in simply a term for other types or substitutions of malt that have been used for centuries. Rice, wheat and corn are all adjuncts. It coincided with the explosion of micro breweries onto the brewing scene.
The marketers are a tricky bunch. Because of the simple way they phrased these new ad campaigns, the wording makes you think that adjuncts (a term previously unknown to consumers) are bad. What were adjunct using beer companies to do? Start advertising that adjuncts are ‘okay’? That’s almost an admission of guilt.
It’s a very interesting nuance about the way consumers interpret new information. The marketers are explicitly advertising that they use “100% Malt”. That’s what, as consumers, we think they’re trying to convey. It’s hard to argue with, “I’m sure they can’t advertise ‘100%’ without actually using 100% malt”.
But we gloss over the implicit message; that 100% malt is good and that adjuncts are bad. If the marketers had explicitly said “adjuncts in beer are bad and we don’t use them”, you as a consumer would question the ad more.
It marketing slight of hand – just like my blog was knocked off the #1 blog charts for being too real and edgy.