A few months ago I shared a story and post on Facebook about survivorship bias and was amazed how often it was liked and shared. It also highlights the risk of survivorship bias in the gaming and gambling space. The image and blurb told the story how the navy analyzed aircraft that had been damaged and based future armament decisions on where they had received battle damage, thus they were going to increase the armor on the wingtips, central body and elevators. These were the areas that showed the most bullet holes.

One statistician, Abraham Wald, the founder of statistical sequential analysis, however fortuitously stopped this misguided effort. According to Wikipedia, “ Wald made the assumption that damage must be more uniformly distributed and that the aircraft that did return or show up in the samples were hit in the less vulnerable parts. Wald noted that the study only considered the aircraft that had survived their missions—the bombers that had been shot down were not present for the damage assessment. The holes in the returning aircraft, then, represented areas where a bomber could take damage and still return home safely. Wald proposed that the Navy instead reinforce the areas where the returning aircraft were unscathed, since those were the areas that, if hit, would cause the plane to be lost.”

Survivorship bias is universal

Survivorship bias occurs everywhere. If you are a poker player, you may have a hand of three of clubs, eight of clubs, eight of diamonds, queen of hearts and ace of spades. The odds of that particular configuration are about three million to one, but as economist Gary Smith writes in Standard Deviations, “after I look at the cards, the probability of having these five cards is 1, not 1 in 3 million.”

Another example would be professional basketball. If you look at the best professional basketball players, a high percentage never went to university for more than one year. From this information, you (or your teen son) may infer the best path to the NBA is going to university for one year or less. The reality is that there are millions (if not billions) of people who went to university for less than a year and never played in the NBA (or even the G League). The LeBron Jameses and DeAndre Aytons are likely in the NBA despite playing less than a year in college due to their great skill, not because they did not go to university for more than a year.

As an investor, survivorship bias is the tendency to view the fund performance of existing funds in the market as a representative comprehensive sample. Survivorship bias can result in the overestimation of historical performance and general attributes of a fund.

In the business world, you may go to a Crossfit gym that is packed with the owner making a great living. You decide to leave your day job and replicate his success. What you did not see is the hundreds of Crossfit gyms that are not profitable and have closed.

The problem exists in gaming

You often see survivorship bias in the gaming and gambling space. People will look at a successful product and select a couple of features or mechanics they believe have driven the success. They then try to replicate it and fail miserably, only to then wonder why the strategy did not work for them. What they fail to analyze is the many failed games (for every success there are at least 8-10 failures) because they do not even know they exist. The failed games may have had more of the feature you are replicating. Getting a star like Kim Kardashian is a great idea if you only look at Kim Kardashian: Hollywood, but if you look at the hundreds of other IPs that have failed your course of action might be very different.

Survivorship bias can also lend its ugly head when building a VIP program. You talk to your VIPs and analyze their behavior, thus building a program that reinforces what they like about the game. What you neglect, however, is that other non-existent features might have created even more VIPs.

In the gambling space, you may look at a new blackjack variant that is doing great and build a strategy around creating new variants of classic games. What you did not see is all the games based on new variants that have failed.

Avoiding survivorship bias

Looking simply at successes, or even failures, leads to bad decision making. When looking at examples in your industry or other industries, you need to seek out both the successes and failures. With the failures, you need to make sure they are the failures (not the airplanes that returned shot up but the ones that were destroyed). You also should not use others successes or failures as a short cut to robust strategy decisions. You need to analyze the market, understand your strengths-weaknesses-opportunities-threats (SWOT) and do a blue ocean analysis. Only then will you build a strategy that optimizes your likelihood for success.

Key takeaways

• In WW2, by analyzing surviving aircraft the US navy almost made a critical mistake in adding armor to future airplanes. The planes that returned were actually survivors, while it was the planes that were destroyed that showed where on the plane was the greatest need for new armor. This phenomenon is called survivorship bias.
• This bias extends into the gaming and gambling space, as companies analyze what has worked in successful games but do not know if it also failed (perhaps to a greater degree) in products that no longer exist.
• Rather than just looking at survivors or winners to drive your strategy, you should do a full SWOT and Blue Ocean analysis, that is the strongest long-term recipe to optimize your odds of success.