How Bad Is Your Management Bias?

How bad is your management bias? And I don’t mean discrimination. I mean data. Specifically, I mean the bias you give your information sources when making important management decisions. When was the last time you thought about where you get your most critical data from and the credibility of those sources over time? Listen, it’s normal to favor some sources over others. It’s also important to be aware of the built-in limits of your sources.

Why? Because it’s very easy to accept or discard information at face value without examining its credibility or usefulness. Take, for example, the articles you read in a magazine like TIME or a newspaper like The Washington Post – when was the last time you examined the author’s perspective in a piece? Or what about a billboard that says “97% agree that Widget Company is the best” – 97% of what group? How many people are included in that 97%? You see, humans are notoriously ineffective at assessing data quality.

With training, you can improve the ability to think critically. It’s enormously valuable to be able to distinguish trustworthy from untrustworthy, logically sound from logically flawed, and perception from reality. In the meantime, here’s an overview some common pitfalls to be aware of when it comes to trusting your data. Remember: your organization’s performance depends on your ability to make sound leadership decisions.


When taking the pulse of your organization, notice who you gravitate to most naturally. Who are you more likely to trust? Who are you less likely to trust? Do you have favorites? How might your perceptions of people’s nature influence how you interpret the data they give you?

Here’s an example. Say you’ve got a team of 30 people – you’ve got a few high performers, a lot of average workers, and a few low performers. Now, say want to get a picture of employee engagement. Who do you speak to? Who’s going to give you the most valuable feedback? Who’s will have the most credibility? You might not like the low performers, the content of their criticism, or even its delivery, but when you discount their feedback entirely you may have missed a valuable learning opportunity.


It’s frightening how many ways there are to misuse statistics. It’s even scarier how so many of us accept statistics as the final word in decision-making, as if they always give you a clear picture of what’s going on. While that’s true some of the time, it doesn’t let you off the hook all the time. Be careful!

The Bottom Line…

At some point, the process of data gathering and decision-making becomes a matter of trust. And this is an open question…

How do you know what sources to trust and when to trust them?