Solving innovation challenges through the power of cognitive diversity - Part 1: Surface vs deep-level diversity


What does diversity in the workplace mean to you? Is it a good mix of people with different racial or ethnic backgrounds? Gender? Or maybe you work in a multidisciplinary team? The key point is that there are different types of diversity but they can be broadly placed into two buckets - surface-level diversity and deep-level diversity. In this first part of a multi-part blog series, we’ll start by looking at diversity in its different forms. So what are the differences?

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It’s harder to observe deep-level diversity.

Traditionally, diversity has focused on easily observable, surface-level demographic traits like gender and ethnicity. In contrast, deep-level diversity focuses on traits that are psychological (e.g., personality, cognitive, or decision-making styles). Since it inherently involves the “inner workings” of people’s minds, it’s naturally less obvious than the visual characteristics of someone’s skin colour or gender.

It’s possible to measure deep-level diversity with reliability and validity.

Although not easily observed compared to surface-level traits, many different types of tools have been developed to measure deep-level traits so that they can be studied with rigour. These include tools measuring cognitive and decision-making styles, perceptions of cognitive diversity in established teams, and the range of academic and commercial tools designed to measure personality dimensions.

The links between surface-level diversity and group performance in a range of tasks are weak or non-existent.

Different studies have found support for the role of deep-level attributes that drive performance in tasks such as problem-solving and decision-making. In contrast, these studies have found little support for the effect of demographic variables on group performance in these tasks. That’s not to say that ethnic or gender diversity isn’t important for a just and representative workforce, given the times we live in, but that deep-level diversity plays a much larger role in driving performance outcomes regardless of demographic variables.

It’s important to distinguish between surface and deep-level diversity because the two types aren’t necessarily intertwined. When we tease apart the impact of the types of diversity that are important for key outcomes, we can start to see a more nuanced picture of diversity as a whole. Stay tuned for the next update when we talk about when diversity is useful and when it might not be so useful.

Zisheng Chen