Reducing Bias as a Product Manager

Thinking, Fast and Slow

Cognitive Bias Codec
John Manoogian III, licensed under CC BY-SA 4.0.
  1. Employ System 2 deliberately
  2. Be aware of specific biases
  3. Counteract your biases

Particularly relevant biases for PMs

IKEA effect

The IKEA effect means that we ascribe relatively higher value to products we partially created. This bias is extremely relevant in product management. We are much less likely to stop a project or remove a feature that we have put effort into building than if that same project or feature was someone else’s.

Confirmation bias

Confirmation bias means that we seek out evidence that supports our view, and disregard evidence that doesn’t. Especially in conjunction with the IKEA effect, this means that we are not nearly skeptical enough about the features that we build and the ideas we have. It also means that we might latch onto views about the product, the market, or our customers that are not true.

Sunk cost fallacy

Somewhat related, the sunk cost fallacy means the tendency to take into account already incurred (”sunk”) costs when making forward-looking decisions — often described as “throwing good money after bad money”. This happens all the time in product management. Consider, for example, a big project that was supposed to take 6 months. 4 months into the project, the biggest customer that was going to use the feature churns, or some new difficulty is discovered that will delay the project by another 6 months. The natural tendency is to say “we’ve already spent 4 months on this project, we can’t stop now!” That is the sunk cost fallacy at work. Instead, you should reevaluate the decision as if you were making it from scratch. Is the return on investment still there after these changes in circumstances?

Availability heuristic / recency effect

Availability heuristic and recency effect mean that we tend to think that examples that come easily to mind, for example, because we recently encountered them, are more representative of the whole than they actually are. As an example, because we recently sat in on a sales call or read a couple of support tickets where a particular feature was requested, we believe that feature to be in high demand, even though it might not be.

Anecdotal fallacy

The anecdotal fallacy is closely related to availability heuristic and recency effect. Human beings have a natural affinity for stories (anecdotes). Stories affect us differently, more deeply than sheer numbers do, because they tap into our empathy for other people. For this reason, we put a great deal of emphasis on ideas and perspectives that are supported by anecdotes. We also more easily remember anecdotes than other facts, playing into the availability heuristic. Therefore, if someone tells us a story about how they had a particular problem with our product, we will likely want to fix that problem even if the data tells us that this is a rare occurrence.

Hindsight bias

Hindsight bias is well known: “Hindsight is always 20/20”. It is our tendency to think that past events were more predictable than they actually were. As a product manager, this can prevent you from properly assessing risks and learning from wrong assumptions. To address this, you should turn “we should have known” into “how could we have known”.

Self-serving bias and fundamental attribution error

Self-serving bias and fundamental attribution error mean that we are more likely to attribute our own failures to circumstances, and others’ failings to their character (or abilities). These biases matter in a lot of situations for product managers: if we have issues using someone else’s product, that’s because of poor UX, if someone has issues using our product then they’re stupid. If we forgot to respond to a stakeholder’s email it’s because we had too many things on our plate, if someone else does it to us they are deliberately ghosting us. If we didn’t deliver the spec in time it’s because we got pulled into some emergency, if an engineer is late with their feature it must be because they are lazy.

Curse of knowledge

The curse of knowledge refers to the fact that once you know something or have learned something, it is impossible to see things from the perspective of someone who doesn’t. This is very challenging for product managers: we are experts in our own products and know all the flows, interactions and idiosyncrasies. It can be really hard to understand the challenges that a more novice user might have with the product, because everything seems obvious from our perspective. The same thing is true for the tools and processes that we use — they can sometimes be hard to understand or inefficient, but because we’ve learned to live with them, we don’t see the flaws anymore.


Biases are natural, and all human beings are biased. They stem from constantly needing to handle more information than we can consciously process. Some of them, like the ones outlined in this article, can easily lead to making suboptimal decisions in terms of the products we build and how we work. Thankfully, many of these biases can be counteracted by being aware of them and taking deliberate steps to address the biases.



Head of Product at RevenueCat; previously at 8fit, Yammer, BCG.

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