Do you remember Kodak, the brand who produced cameras and films in the 80s and 90s? Have you ever wondered why Kodak didn’t make it in the digital age? Well, it failed to believe that digital was the next big thing in photography and stuck to film and photographic chemicals, as that was its primary business.
When Sony had already released its first digital camera, employees started to ask themselves whether they should be worried about the rise of digital photography. Kodak’s CEO researched to understand the core technologies and likely adoption curves for Halide film versus digital photography. The results showed that digital photography could replace film-based cameras, within the next ten years.
What did Kodak do? It chose to improve the quality of film using digital technology. So it still had film in a digital camera and needless to say, the product didn’t last long. Aside from poor strategy and decision-making, the Kodak CEO was blindsided by confirmation bias.
In this article, you’ll learn what confirmation bias is, how it impacts your role as a product manager, and how to overcome it within your product team.
Confirmation bias occurs when an individual makes decisions that are consistent with their existing beliefs by only looking at data that confirms what they want.
With confirmation bias you choose data that strengthens your beliefs rather than looking more objectively at all the data and considering it in your decision-making. This happens unconsciously and is common in all areas of our lives, personal or professional.
Confirmation bias can appear in multiple situations in your day-to-day life as PM, but here are the most common situations.
Confirmation bias can greatly influence decision-making. When faced with choices or making tradeoffs, product managers may lean towards options that align with their existing beliefs or preferences, even if evidence suggests alternative paths may be more beneficial. This can lead to missed opportunities and poor decision-making.
To minimize the impact of confirmation bias, you can seek advice from the other two members of the product trio, the product designer and the technical lead. Additionally, you can use your opportunity solution tree to trace everything back to your goals and the product principles that align with the overall product strategy.
User research is the area where confirmation bias may appear the most. You may unconsciously look for data or interpret the feedback that confirms your beliefs about the product or a specific feature.
For example, if you believe that users prefer a specific design, you may focus more on the positive comments that support that belief and downplay the negative or constructive comments.
To prevent this, you should involve multiple team members in analyzing user research and only dismiss feedback once it has been critically reviewed.
Your unconscious biases can also appear when using GenAI tools such as Chat GPT. AI offers powerful tools, but they can reinforce your beliefs rather than provide an unbiased response. Depending on your prompt, the answers you get may be the ones you expect rather than the more objective ones.
PMs should approach GenAI results critically and be open to the possibility that their initial assumptions may be incorrect. Regularly validating AI-generated insights with real-world data and external experts can help reduce the impact of confirmation bias in this context.
While confirmation bias often occurs unconsciously, there are strategies you can use to prevent, or mitigate its impact.
One effective way to counter confirmation bias is actively seeking diverse perspectives and opinions. Encourage team members to challenge assumptions and provide alternative viewpoints during discussions and decision-making. Embrace constructive feedback and debates to uncover potential biases and blind spots.
You can even play devil’s advocate with one of your colleagues. If you want to take it even further, why not add another hat to the mix — the data seeker. In this scenario, you focus on data analysis and objective assessment when it comes to decision-making and then present your findings only leaning on that.
Whenever you research, try to have multiple data sources and don’t just rely on small amounts of data or unreliable information. Seek out more context for the data and consider the sample size. In some situations, you may want to use more than one single research method to back you up.
This approach helps mitigate the risk of confirmation bias by promoting a holistic view of the situation.
Formulate questions that encourage participants to provide candid and unbiased feedback during interviews or user research sessions. Avoid leading questions that predispose respondents to specific answers. Instead, ask open-ended questions that elicit genuine insights and perspectives.
For example, whenever you want to find out your user’s opinion about a feature, don’t ask them:
“What did you like about this?” or “Did you like this feature?” You should instead focus on more objective questions such as, “What did you think about this feature?”
Confirmation bias may lead to poor decision-making, biased research results, or missed opportunities. The first step is to acknowledge this and make use of tools that help you minimize the effects, such as running your ideas through the other two members of the product trio and triangulating your research. These will help you make more objective decisions that help to benefit the strength of the product.
Featured image source: IconScout
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