I have written about the advantages of having good data when lifting weights. I recently started wearing a smart shirt that tells me exactly how much each muscle works in real time during my workouts. Since doing so, I have exceeded my maximum bench press by 40 pounds. And I set that record 12 years ago when I was in my 30's. This should not happen.
The difference is that I finally have data that tells me exactly how well each lift works and what muscles it works. And what works is not the same as the conventional wisdom of personal trainers and muscle mag gurus. If fact, they are mostly wrong.
If you hook electromyogram (EMG) sensors to a muscle, they tell you how much it is firing. Now whether an expert weightlifter believes that the muscle is firing is of remarkably little importance. And it turns out that conventional wisdom about which exercises do what, while widely agreed upon, is often wrong.
Often, experts are relying on flawed perceptions and groupthink. Similarly, one can see this happening in the robot-advisor space - in fact, in most advisory services. All base recommendations on age, time to retirement and a 5-10 point risk appetite scale. You can talk to a person, go to a website, or use an app. The approach is the same. After all, everyone know that this is how you do it.
Of course, when they all do it the same way, one has to wonder what their value proposition is. they seem to be saying, "well we ask you age in a more insightful way." Right.
With all of the investor data these investment companies have, you would think they would have built a better sensor to read this. I have personally done the work on this and it turns out that while there are groups of people who behave the same way over time, these groups are not necessarily clustered around age, time to retirement and risk scale. So the measurements used don't necessarily correlate with a persons investment style nor what is best for their goals.
In other words, the company is saying, "we want to build our advisor muscle, so we are going to do squats." And it then turns out that the advisor muscle responds best to pull ups. Everyone knows that squats are what work. Everyone does squats. And everyone has the same lame advisor muscles that aren't improving. But because they already have the answer, why build a sensor to understand what is really happening.
So the sensor of analytics that could be used rarely is, and when it is, the senior experts disregard anything that contradicts what they know: everyone gets more risk averse as they age. All poor people need larger returns, all women are more conservative than men, etc. Only, what they know is opinion, not fact.
Someone could easily use the data that already exists, find the patterns of behavior, and build a true automated advisory system that beat the face to face assessments, and at lower cost. It does not even take sophisticated math (but you'll have to hire me to tell you what it does take.)
Any day now, someone will develop this insight and start offering services that do to the industry what Amazon did to online retail. And everyone will be doing face palms because it is so simple. But by then, the battle will have been lost.
For what it is worth, friends who ask me how to build muscle often find my penchant for data interesting, but they still prefer to just sort of guess at what works in the gym. Being guided by fiction is much easier than the discipline required to drive by numbers. And this is very fortunate for anyone competing. There is nothing better than your competition refusing to challenge their dearly held, and erroneous beliefs.