Product Management and Cognitive Bias

In product management, understanding customers' needs and pain points is pivotal for success. However, unravelling these complexities requires more than just surface-level user-research. This is where the power of Behavioral Science comes into play. Behavioral Science is a discipline that explores human decision-making patterns, and it can offer invaluable insights to product managers. If you understand your user well, you can design products that truly resonate with them. Beyond the interaction with users, it is important to take note of how your decision-making as a product manager can be influenced by your own biases.

Behavioral science studies human behavior through systematic research and scientific methods, drawing from fields such as psychology, sociology, and cognitive neuroscience. One important aspect of behavioral science is the study of cognitive biases which are defined as systematic errors in thinking that occur when people process and interpret information in the world around them. They are shaped by experiences, emotions, and cognitive processes, affecting our judgment and decision-making abilities. They are essentially our mind's way of taking a shortcut to deal with an overload of information and complexity.

In Product Management, understanding how cognitive bias can impact our judgement is essential to course-correct our behavior/judgement and calibrate the data collected during user-research! When applied correctly, it allows for more effective crafting of strategies that align with the way people naturally think and behave.

This article will delve into the intersection of product management and cognitive bias, highlighting how the latter can significantly influence successful product management. I will try my best to get my show how these biases had influenced me throughout my career.

Let's go!

Cognitive Biases

The list of cognitive bias is extensive – here is a Wikipedia article with many biases. For this article, we will focus on three cognitive bias:

1. Confirmation Bias: Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms one's pre-existing beliefs or hypotheses. This bias is powerful because it can lead people to overvalue information that supports their views and ignore information that challenges them, leading to flawed decision-making.
2. Anchoring Bias: Anchoring bias is the tendency to rely too heavily on the first piece of information encountered (the "anchor") when making decisions. Any decisions made after are done in comparison to the initial anchor, even if the anchor is unimportant or irrelevant.
3. Availability Heuristic: This is a mental shortcut that relies on immediate examples that come to a person's mind when evaluating a specific topic, concept, method, or decision. In other words, people heavily base decisions and actions on their most recent or vivid experiences rather than considering the full scope of relevant data or potential outcomes. This can lead to overstating the importance of recent information and making inaccurate judgments or forecasts.

Let’s dive into more details for each bias!

Confirmation bias

When product managers succumb to confirmation bias, they might ignore or misinterpret customer feedback (or usage data) that contradicts their hypotheses about the product. This could result in bad decision-making, like adding unnecessary features or failing to address key shortcomings, ultimately leading to a product that doesn't fully meet users' needs.

In my experience, product managers experiencing confirmation bias may ignore negative feedback from users or team members, focusing mainly on the positive aspects that validate their beliefs, thus missing opportunities for crucial improvements. I mean, we all love the products that we are designing but we need to be pragmatic about its problems and rely on data to improve products.

In the same line, we love people that love our products ?? However, clearly, considering only positive feedback can compromise the objectivity of user research. We might subconsciously select participants that are more inclined to provide positive feedback or might overlook critical points in user research data that contradict our preconceived notions about the product.

In a team setting, confirmation bias might cause product managers to overlook good ideas that contradict their own, creating an atmosphere where dissenting or different views are not encouraged, stifling innovation and growth ?

Ultimately, consequences can be big here. If, for example, you are favoring market data or trends that align with your expectations, you may be overlooking potential risks or challenges. This could result in launching a product in a non-viable market or incorrect target audience segmentation.

How do I correct for “Confirmation bias”?

Here are a few tips to help dealing with confirmation bias:

1. Make a conscious effort to seek out and genuinely consider information contrary to your existing beliefs. Inviting critique and regularly challenging your assumptions can help to offset the effects of confirmation bias.
2. Cultivate a culture where different opinions are not only tolerated but encouraged. Having a wide range of perspectives in the team can help to challenge existing biases and bring to light any unconscious agreement with preconceived notions.
3. Lean into data and analytics as much as possible when making significant decisions. This approach promotes impartiality and bases your decisions on factual evidence rather than mere beliefs and assumptions, which can be influenced by confirmation bias.

Anchoring

Anchoring can present significant challenges for product managers. This bias is very common if you have been working in a specific field for many years and you’ve been asked to take on a product management role. Take myself as an example, my background is Chemical Engineering and I worked for a few years in Integrity, Reliability and Risk engineering before taking on the role of a product manager. My experience in delivering projects in these areas has been essential to help me understanding the user pain points. However, I believe some of the features I prioritized back in the day were probably more important to me (anchoring to my experience) than to the wider user community. So, anchoring can hinder understanding of a product's actual value or potential.

And this issue happens both ways – as the product manager uses its own experience to guide the product roadmap or when running user research. For example, early feedback about a product's price, usability, or feature set may anchor a product manager's perceptions and influence future decisions about product improvements, possibly ignoring subsequent information that contradicts these initial impressions.

Another important point to consider here is how anchoring can negatively influence user research. If the initial questions set an anchor that biases the rest of the conversation, it can even lead to skewed prioritization if decisions are influenced by early set priorities. I believe some of us have certainly experienced this before – you are a product manager and you hate a feature. When running some user research, you are asking questions that pretty much biased to get it rid of it ??

How do I correct for “anchoring”?

Here are a few tips to help dealing with anchoring:

1. Consider multiple scenarios based on different anchors. By objectively examining a range of possibilities anchored at various points, you can overcome a single, potentially misguided, anchor's influence. It supports the idea of making data-driven decisions that yield more accurate outcomes.
2. When discussing features or user-stories with your team, leverage the diverse perspectives to prevent individual anchoring biases. Encourage team members to independently generate estimates, product ideas, and problem solutions before sharing them, to avoid early ideas anchoring the group's thinking.
3. Leveraging A/B Testing is useful for testing two different assumptions to minimize the risk of anchoring bias. It allows the team to make informed decisions based on actual user behavior, rather than relying solely on their preconceptions.

Availability Heuristic

The Availability Heuristic is a cognitive bias where people make judgments about the probability of events by how easy it is to think of examples. Decisions are influenced by what is most recent or emotionally charged in one's memory, and people tend to overestimate the importance of this information.

In product management, this is the old “putting our fires” behaviour – every time we might be asked to prioritize a user story or feature, we are likely to overestimate the importance of the most recent conversation we had with a user. We are likely to overreact to immediate problems, even if they have minimal impact on the overall product, taking resources away from dealing with larger, more significant challenges that are not as immediately apparent.

Or, even worse, decision-making around feature prioritization might be influenced by a few vocal users, leading to imbalances that fail to consider the silent majority's needs (a clear stakeholder map might help with this one)! It is clearly very dangerous to base our understanding of users on a few notable customer interactions or feedback sessions - they may not have the most accurate or representative view of user needs and preferences. Also, considering our users’ biases is essential – remember, people are likely to remember what happened to them more recently but not necessarily what has consistently happened throughout a certain period.

How do I correct for “Availability Heuristic”?

Here are a few tips to help dealing with anchoring:

1. Engage with a broad range of users regularly to get a holistic understanding of the user base. This will help in avoiding decisions based on feedback from a vocal minority.
2. Timing is very important here – one advice is to resist making decisions based on recent events or information. Look at trends over time to ensure your decisions align with long-term objectives and outcomes. It is very important to take time to pause and reflect before making important decisions. This enables processing of all available information and reduces reliance on readily available or recent experience.
3. Analytical models or frameworks can help structure thinking and decision-making, mitigating the risks of the availability heuristic.

Conclusion

This article is just a short overview of how cognitive biases can influence product management.

My advice?

Now that you understand what Cognitive bias is and how it can influence you, go through the list of cognitive biases and come up with strategy to dealing with it.