Is More Information the Answer?
In 1973, Paul Slovic ran a study to find out the effect more information has on our decision-making ability.
He used professional horse racing gamblers, also known as handicappers, as his subjects. It’s important to note that each of these handicappers made a full-time living from betting on horse races. In other words: these were experts, rather than casual gamblers looking for some fun.
I remind myself of the results from this study more often than I care to admit. Whenever I’m faced with a challenging decision, my default move is to gather more information.
Allow me to elaborate why more information isn’t the right answer.
?Stress Caused by Information Overload
To begin the study, each handicapper was allowed to ask for 5 data points before ranking 40 races with 5 horses in each race. Each handicapper chose a unique set of 5 variables.
Here’s an example of one handicapper’s set of 5 data points:
There was a list of 88 variables of past-performance for each horse to choose from. Some of the variables include what you see in the image above plus the following:
- Percentage of races horse finished 1st, 2nd, or 3rd
- Number of days since horses last race
- Number of lengths horse finished behind the leader in last race
After predicting the finishing order (First, Second, Third, Fourth, Fifth) for 40 races with 5 data points, each handicapper was allowed to ask for 10 variables, then 20 variables, and finally 40 variables. They predicted the finishing order at each stage of the information available.
Finally, the handicappers were asked to report their confidence levels alongside their race rank submission.
?The Findings Were Incredible:
- Accuracy was as good with 5 variables as it was with 10, 20, & 40 variables!
- 3 of the 8 handicappers became LESS accurate with MORE information
- Only 2 of the 8 handicappers improved with more information while 3 stayed the same
- All of the handicappers became more confident with more information.
The relationship between information and accuracy is only a portion of the findings.
What’s equally important is the effect more information had on the handicapper’s confidence level as well as their judgment.
Equipped with more information, and therefore more confidence, you can imagine the handicappers making larger sized bets or taking on “riskier” positions.
?Why Does This Study Matter?
This isn’t about being able to predict the outcome of horse races. This study is about understanding the stress caused by information overload.
There are so many areas in life where large sets of data are available to us before making a judgment decision. Investing is one such example.
Let’s say you decide to invest in the stock market or real estate. Will you use 5 critical data points to choose which asset to acquire or will you search for 40 data points that ultimately boost your confidence, but do nothing for your accuracy?
The main problem with gathering more data is confirmation bias.
Confirmation Bias is the tendency to interpret new evidence as confirmation of one's existing beliefs or theories.
Let’s say you are looking into a company or house to invest in. The first 5 data points you gather are going to likely lean you one way or another. All the following data points gathered will likely solidify your anchored position.
“Beyond a certain minimal amount of information, additional information only feeds confirmation bias, leaving aside the considerable cost and delay occasioned in acquiring that information. The additional information we gain that conflicts with our original assessment or conclusion we conveniently ignore or dismiss, while the information that confirms our original decision makes us increasingly certain that our conclusion was correct.” (Excerpt from Tim Ferriss Show Episode #322
5️⃣5 Data Points for Real Estate Investing
If I could boil down the variables I consider when evaluating a particular real estate investment, they would be (in no particular order):
Demographics (Location, Location, Location):
- Affordability - I’m looking for the median household income of the immediate area (3 miles) to be 3x higher than the target market rent. A Starbucks, Target, or Trader Joe’s in the immediate area makes it a no-brainer.
- Not a “data point” per se, but employers should be diverse and violent crime should be close to non-existent.
Sidenote: I’m typically buying 2-bed units or smaller. I’m not super focused on school systems. If I started buying 3-bed units or larger, I’d care more about schools.
- All-in costs (purchase price + closing costs + rehab + carrying costs) need to be 80% of comparable asset values or less.
- Monthly rents need to be 1.25%+ of All-in costs.
- Projected Net Operating Income needs to be 125%+ of the monthly mortgage payment.
⚖Less is More
Next time you're faced with a decision in a field that has so many variables it’s far too complex to grasp, settle for less information.
The more you try to make sense of what’s going on, the more anchored you become to your initial assumption. You start to believe your own story. This vicious cycle blinds you to what’s actually going on in the real world.
If your results are not favorable, don’t add more data. Instead, identify which data point(s) is most likely the cause of your unfavorable outcome and replace it with what you would have added.
Then, retest. Hopefully, you can continue retesting. The only thing preventing you from unlimited retesting is running out of resources (capital, or otherwise).
Don’t test the depth of the river with both feet. Don’t become so confident in your position you bet it all on one race. Live to fight another day.
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