Product Managers are responsible for making decisions that will ultimately determine the success or failure of our products. However, our personal biases can often cloud our judgment and lead to suboptimal results.
A recent study found that 63% of product managers have experienced at least one type of bias while making product decisions.
Here are five common biases that can impact product management, with simple examples and tips to avoid them:
- Confirmation bias
It is the tendency to seek out information that confirms our existing beliefs or opinions while ignoring or dismissing information that contradicts them.
Example:
If you believe that a specific feature is crucial to the success of your product, you might unconsciously discount user feedback that suggests otherwise.
To avoid confirmation bias, seek diverse perspectives and data sources, and challenge your assumptions and biases.
- Halo effect bias
It is the tendency to be influenced by a product’s reputation or brand rather than evaluating it based on its own merits.
Example
You might be more likely to approve a feature or design change simply because it comes from a well-respected team or designer, even if it doesn’t align with your product’s goals.
To avoid the halo effect, evaluate products and features based on their own merits rather than being swayed by branding or marketing.
- Availability bias
It is the tendency to rely too heavily on information, that is readily available or easily recalled rather than seeking out a diverse range of data sources.
Example
If you are considering a redesign of your product’s user interface, you might be influenced more by feedback from your most vocal users than by a more representative sample set of the user base.
To avoid availability bias, seek out a diverse range of data sources, and use data for your decision-making.
- Anchoring bias
It is the tendency to be influenced by the first piece of information we receive, even if it is not the most accurate or relevant.
Example
If you receive a cost estimate for a new feature that seems high, you might be more likely to reject it outright without considering other options or cost-saving measures.
To avoid anchoring bias, consider multiple options and information sources before making a decision.
- Overconfidence bias
It is the tendency to overestimate our abilities or knowledge and to be too confident in our decision-making.
Example
You might be convinced that a certain product feature will be a huge success, based solely on your intuition or experience, without seeking out feedback or input from others.
To avoid overconfidence bias, seek out feedback and input from others, and regularly reflect on your own biases and assumptions.
You can create better products and experiences for your users by becoming aware of these biases and actively working to mitigate their impact on decision-making.
This requires a commitment to ongoing self-reflection, learning, and collaboration, as well as an openness to feedback and a willingness to challenge your assumptions and biases.
Per a study by McKinsey, companies that address biases in decision-making are 22% more likely to achieve above-average profitability and 70% more likely to capture new markets.
So, it’s not just about creating better products; it is also about improving business outcomes.