Using Network Science to Better Understand Inclusion

By Tatem Burns and Aaron Sorensen 


Why is inclusion placed after diversity and equity in the DE&I moniker that has become a top priority for so many organizations almost overnight? When we hear the acronym “DE&I”, Diversity comes first, Equity comes second, and Inclusion comes third. The order of these concepts is misleading – in reality, inclusion comes first. Without a culture of inclusion at your workplace, diversity and equity cannot be maintained. 

An organization can exhaust resources to onboard diverse individuals and create more equitable pay structures. Frankly, these efforts are moot if diverse individuals feel like outcasts in their workplace place. An organizational focus on improving inclusion is paramount to fostering an effective DE&I effort. 

Diversity and equity in the workplace have observable properties. Data is available to quantify the demographic diversity in your company. Data is available to quantify any pay disparities due to race or gender for individuals doing the same work.  Measuring and assessing individual feelings of belonging, access to development and mentorship, involvement in critical work events and discussions, however, are another matter. 

Typical measurement techniques for these aspects of inclusion fall short. For example, surveys embed significant bias when it comes to measuring complex phenomena like inclusion. This is particularly true for organizations with little diversity, where survey anonymity is not guaranteed and fear of scrutiny for being honest about a non-inclusive workplace can lead to unreliable survey responses. 

Instead, more sophisticated, and less intrusive assessment methods are available for organizations to measure, track and improve inclusion, leveraging the field of network science.  Network science is the study of complex linkages among phenomena. It helps us understand connections, like those between the neurons firing in our brains, the interactions of different species in the wild, and, in service of the quest to observe and define how best-practice inclusiveness really works in organizations, the communications between people and groups. 

Network science surpasses the limitations of surveys. It does not require any time to complete, it is less biased in measurement, and it physically demonstrates the day-to-day workplace communication signals between employees. It does so by tapping into data that underlies typical communications in the workplace, like email and instant messaging and calendar invitation patterns, instant messaging receipts and calendar invitations, to reveal how inclusive your organization truly is. Leveraging network science unveils the patterns of inclusion that exist in your organization, creating visibility into the ways in which underrepresented segments of the workforce experience inclusion, where teams foster inclusion, and where to pinpoint intervention and investment to create a more inclusive culture. 

Network science now enables the advancement of true inclusion through noninvasive methods that yield rich insights. 

Behavioral Science
Data Analytics
Data Science