Using adaptable organization network analysis to reveal patterns that drive inclusion

Posted by Tiffany McDowell, Maya Bodan, India Mullady, and Devon Dickau on April 21, 2020

CX516P_loAmid efforts to emphasize inclusion in addition to diversity, many corporations have struggled to accurately track and measure the sometimes-ambiguous concept of “inclusion.” Diversity—often measured via individuals’ self-reported identities and shared via pie charts and bar graphs—has for decades served as a straightforward metric for companies to assess what they have called “D&I” (or diversity and inclusion) efforts. In reality, point-in-time or longitudinal demographic data are largely only indications of diversity, not inclusion—not to mention that such data typically only includes percentages of a workforce who identify as a specific gender identity (male, female, or nonbinary) and race or ethnicity (for example, Latinx or Black/African American), let alone everyone else. However, assessing progress around inclusion has shown to be more difficult.

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Enhancing new talent pools in the future of work

Posted by David Leathers, Tej Mehta, Devon Dickau and Sendhil Govindarajan on June 6, 2019.

As we think about the future of work, a key question is “who can do the work?” Talent models are changing, and while some work will likely be done by robots and other forms of artificial intelligence, organizations must think more creatively around how humans with different, diverse backgrounds will continue to help build and grow the organizations of tomorrow. How well is your organization tapping into multiple talent pools for your future workforce? And how does your workforce reflect your organization’s role and goals as a social enterprise?

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