This post and project is managed by Kirsten Wyatt and Stacy Schweikhart. If you’re interested in getting involved with this project, or want to connect us with MPA program contacts send us an email and we’ll loop you in to our efforts.
It should come as no surprise that we’re passionate about the #13Percent conversation. Last year’s conference schedule had ELGL members talking, thinking, and presenting about the issue around the country throughout the year. And together we authored a short series about the 2015 women in leadership data from ICMA and our perspectives about why that data is insufficient when we talk about women in leadership. We’re proud of the conversations that ELGL has started on this topic.
But now, we’re ready to get aggressive. The past two years of ELGL work on #13Percent have been effective and emotional. We’ve learned a lot. And we’ve heard countless stories about how the issue impacts people across the country.
And yet, good data on the number of women and people of color in CAO and assistant CAO roles is missing. There’s not a group out there that’s collecting and sharing this information. Groups like ICMA are reporting out from their membership about gender in leadership, but their membership comprises a very small segment of the local government population.
For example, currently, 3,406 ICMA members serve as CAOs (unsure of the breakdown between city and county managers). And so ICMA data is a good starting point, but there are roughly 39,000 general local governments in the US. What’s happening in the 90% of communities not represented by ICMA? What might we learn if we had data from cities of all types, and not just council-manager forms of government?We’ve asked NLC repeatedly to partner on this, and we’ve also asked ICMA to leverage their relationship with NLC. So far we haven’t had luck getting NLC to engage in these efforts.
So we’re taking matters into our own hands. In 2017, ELGL will begin a nationwide data collection effort to compile race and gender data on CAO and Assistant CAOs in all forms of local government on a state by state basis. Sounds easy, right? It won’t be – but we’re sick and tired of waiting around for someone else to do it, and we’ve all heard the quote “what gets measured, gets improved.”
We believe that it is imperative that the leadership of our local governments reflect the communities we serve. ELGL will continue to stress about the importance of diversity in leadership, and now we’re also going to get data to help us tell the story.
Here’s our approach:
- We’ve partnered with the MPA program at the University of North Carolina at Chapel Hill, and the League of Wisconsin Municipalities and the MPA program at the University of Wisconsin at Oshkosh to do data collection and analysis.
- We’ve pitched the project to several other MPA programs and anticipate more universities coming on board to collect data for their states.
- UNC and UW-O students will build a replicable data collection model and will collect the race and gender data for for the states of North Carolina and Wisconsin.
- We’re excited to give students the opportunity to do original data collection, analysis, and sharing. This is consistent with ELGL’s mission to connect, communicate, and educate.
- While working on this project, students will maintain a weekly guest blog on ELGL.org about their work, experiences, methods, and final products.
- The data collection model and data sets will be open source and shared via a new site we’ll launch later this year called DiversityDashboard.org.
- This means that you can review the data on a state by state basis, or in aggregate for local government as a whole.
We’ll also develop a model where interested volunteers can compile data for their state (if there’s not an MPA program willing to take on this project in your area).
We’re jumping in to data collection, and we welcome your support and assistance if you’re ready to help us gather important data about in the percentage of women and people of color in local government leadership.
Actions speak louder than words.