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Understanding Employees’ Experiences through Data with Eve Mannix, DEIAB Client Executive

DEIAB (Diversity, Equity, Inclusion, Accessibility, Belonging) Client Executive Eve Mannix shares how your organization can get started with its data journey.

In part one of “Understanding Employees’ Experiences through Data,” our DEIAB (Diversity, Equity, Inclusion, Accessibility, Belonging) Client Executive Eve Mannix shares how your organization can start the DEIAB journey by using data.

Tell us about why DEIAB data is important to organizations.

Data really helps pinpoint where to put your efforts, your resources, and focus, stepping forward—it's all about helping the organization know what is really going on.

An employee’s experience directly impacts performance, innovation, and ultimately trust. DEIAB (Diversity, Equity, Inclusion, Accessibility, Belonging) data is about getting all the facts and a more comprehensive picture, meaning hard data and soft data to better understand how to support employees.

Hard data can mean gathering facts and figures from employee surveys or from representation data. Soft data is qualitative, meaning conversations, quotes, and anecdotal information. Both hard and soft data tell a story about organizational culture to help organizations put together relevant, data-driven strategies.

It is not as easy as a lot of people might think. Data collection takes a lot of forethought, tools and strategies to put in place. Once you have those in place, it is so much easier, you can rinse and repeat with a similar survey year to year to measure progress.

How does data help organizations gain insights about employee experience? What are some of the questions that data can help answer?

The insights we get from the Inclusion Climate Survey tool are incredible. The survey measures to what extent the employee feels like they belong. When we analyze questions about belonging, we ask, “Is everyone having the same experience? or are there meaningful differences based on identities?”

Data replaces the need for assumptions. When you ask employees to tell you about their experiences, their feedback is always enlightening – and often surprising. The positive elements that we often see in data are just as important as the deep-rooted issues employees are talking about.

In analyzing data, trends emerge in areas like experience with inclusion and belonging, employee development and advancement, how well conflict is managed, and the relationship with supervisors and teams. The data helps leaders understand what to prioritize, where resources are needed in the short term, and areas that need focus over the long-term.

What advances have been made in collecting data on employee experiences with inclusion and belonging?

The most crucial advance has been in the analysis of employee engagement and inclusion climate surveys. Before, using a one-factor tool like Excel, we could look at data one variable at a time, such as race and ethnicity or gender or disability. Now, we are able to take an intersectional, or multi-dimensional, approach to data collection and analysis.

We realized that when we are talking about Diversity, Equity, Inclusion, Accessibility, and Belonging (DEIAB), we need to actually bring in more variables. For example, I am an Asian American to identify my race ethnicity, but I also identify as a woman and as bisexual. So all of these elements create an intersectional identity that is important to understand employee experiences. Without the fuller picture, we may not be getting the whole story.

CST moved to analysis through Tableau, a data visualization software that allows us to analyze data through multiple aspects of identity. Basically, you can bring more parts of someone's identity into the picture to see what their experience is like. Clients are able to more precisely define where challenges exist. Better data makes for better strategies to create solutions that better support employees.

Stay tuned for Part II of “Understanding Employees' Experiences through Data” where Eve will discuss the challenges she faces as a DEIAB Data Analyst and Consultant.


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