In psychology, there is a phenomenon called Outcome Bias, which basically means that we tend to judge the efficacy of a decision based primarily on how things turn out. After a decision is made, we rarely examine the conditions that existed at the time of the decision, choosing instead to evaluate performance based solely (or mostly) on whether the end result was positive or not.
But what happens as luck plays a role in outcomes? Did we actually make the best decision? Or was the result really a product of conditions outside of our control?
Understanding Outcome Bias
A relatively strong example of Outcome Bias can be found in the gambling world. Take poker, for instance. Many players will overplay the cards they are dealt. Imagine that you have four cards to a straight. There are two remaining cards to play. You might make bets that are statistically weak, but if the card you were looking for shows up, you will evaluate your own performance as strong for the hand. After all, you did win, right?
The challenge with Outcome Bias is that the fortuitous turn of events leads you play other hands in a similar way. Despite the fact that you were lucky in getting one of the few cards that would help you, you feel as if you played the hand optimally. If you continue this type of play over the course of many other poker hands, the odds will eventually come back to haunt you.
Outcome Bias isn’t just about positive outcomes
While it is easy to point to examples where luck played a role in things working out, the same dynamics can happen on the negative side. Using the same poker analogy, imagine that you are on the other side of the same hand. You make a series of bets only to have your opponent improbably draw one of the few cards necessary to make her hand.
In these moments, it is easy to second guess your play. When similar situations occur in the future, you might be more hesitant to play aggressively, which actually weakens your decision making. Over time, if you adjust your play to be weaker, you end up putting yourself in increasingly difficult positions.
Applying Outcome Bias to technology
These same dynamics play out again and again in our professional lives. We have probably all been part of companies that have made decisions that led to historically good or historically bad outcomes. A common example in business school case studies is the early PC days that saw Microsoft and Intel do battle with Apple.
What most people take away from the PC wars is that the market favored an open ecosystem of disaggregated components. They talk about the role of Intel in opening up the PC and laptop markets so that multiple vendors could participate. This allowed more Wintel (Windows and Intel) solutions to hit the market. With a larger install base, Microsoft was able to flood the market with an operating system and supporting applications that resulted in a dominant incumbent position. Microsoft and Intel rode this wave to billions of dollars of revenue over the next several decades.
Evaluating Apple’s decisions during these early days, it is easy to conclude that a tightly integrated hardware and software platform with proprietary interfaces simply could not succeed in the high tech arena.
Flash forward to today’s mobile handsets. Apple’s various mobile devices (iPod, iPhone, and iPad) are clearly thriving. But these devices are tightly integrated hardware and software platforms with Apple-specific APIs. How can it be that the same decision made decades apart can have such different outcomes?
Obviously the conditions under which each decision was made are different. The point is that you cannot take a decision and then evaluate whether it is right or wrong based solely on the outcome. While decisions might be informed by previous outcomes, each one is actually different. The conditions that exist around the decision must be evaluated separately, and then an answer has to be independently reached each time.
The process of getting to a good answer
Similarly, we have probably all worked with someone who worked at a competitor in a previous life. The fear in hiring people from other companies is that they will naturally bias to running the same plays that worked with them at their previous employer. If the previous employer was a dominant incumbent who made some dicey engineering decisions, will they replicate the same behavior in the new role?
If the person suffers from Outcome Bias, the answer is that they might at least try. But of course the conditions that surround a challenger are different than those that exist at an incumbent. Accordingly, the plays that need to be run are going to be different. Success is rarely as simple as just replicating wins from the past.
The right behavior is to understand the process to get to a good decision.
Make it repeatable
For anyone who works in a technology company, know this: success at a corporate level is rarely dictated by a single decision. Rather success is dependent on stringing together a series of good decisions. If you want to make success repeatable, you have to understand how to arrive at the same decision not once but over and over again.
When something goes right, you simply cannot stop executing the process. As the market changes, executing against the same basic decisions might not lead to continued success (Blackberry, anyone?). And similarly, just because a decision did not work out does not mean that the process was not sound. If you execute a solid process and arrive at a similar decision, it very well could be that the same decision made years later returns a very different result (as with Apple).
The bottom line
Ultimately, anyone in the tech space is going to have to make a number of product and market decisions. During discussions around these decisions, it is tempting to pull out plays that have worked for other companies at other times. But latching onto a decision and trying to re-create lightning in a bottle without doing the due diligence required to predictably arrive at a positive outcome is essentially relying on luck. Companies can survive on this type of decision making… but only for a time. Eventually, as with odds in poker, luck runs out on most people.
But make sure you apply the same logic to your personal career decisions as well. It is easy to celebrate or lament a particular decision based on the outcome. But understand that the best you can ever do is make the best possible decision based on the information you have at the time. If something works out or doesn’t work out unexpectedly, the right answer might not be to abandon the decision-making process but rather to double down on your information gathering efforts. Fooling yourself into thinking you are extraordinarily good or exceedingly bad at making decisions only clouds the next set of choices in front of you.