Biggest Challenges for a Membership Experience Manager at University of Michigan
Annalee's role as Membership Experience Manager at the University of Michigan presents significant challenges, primarily juggling "so many different needs across the organization" simultaneously, from technical issues to academic data analysis and financial tasks. A key challenge involves persuading stakeholders to utilize raw data for research, a hurdle overcome when assisting students with impactful social issue research, making the demanding work "all worth it".
Project Management, Data Analysis, Communication, Problem-Solving, Overcoming Challenges
Advizer Information
Name
Job Title
Company
Undergrad
Grad Programs
Majors
Industries
Job Functions
Traits
Annalee Shelton
Membership Experience Manager
University of Michigan
California State University Northridge, 2006
Pepperdine University, MA Social Entrepreneurship and Change
English
Education
Sales and Client Management
Pell Grant Recipient, Took Out Loans, Worked 20+ Hours in School
Video Highlights
1. Managing multiple projects simultaneously and prioritizing tasks effectively.
2. Bridging the gap between raw data and user needs by promoting data literacy and analysis.
3. The rewarding experience of using data analysis to help students address important social issues.
Transcript
What are some of the biggest challenges in your current role?
Some of the biggest challenges in this job are the sheer amount of moving parts. There are so many different needs across the organization, and many different types of work go into addressing them. It's like spinning plates.
On any given day, I might be working with IPS, proxies, and internet services. On the other side, I might be working with instructors and data analysis in an academic setting. I might also be working with journalists or making sure invoices go out accurately.
All of these things need to happen simultaneously. I need to be able to sense what the most important thing to do next is. Where is this project? Has it reached the goal needed for the next person to take it? It can be very challenging to keep all of those things in line at the same time.
A major challenge is that people don't necessarily look for data first. You might look for an article or ask someone you know a question, but you don't necessarily look for raw data or know how to analyze it.
So, getting through the hurdle of helping people understand that raw data is available to them and how to look under the hood to find the answers they need can be tough. But it is exciting when you meet with a student trying to answer a deep question about a social issue they care about.
Then you've found a dataset for them that gives them the data they were looking for to help a person in need. That is a remarkable feeling, and it makes it all worth it.