Lydia Harlan, Kristin Buxton, & Gabriele Hayden University of Oregon Libraries Automating for success: Making invisible work visible 1 Kristin's intro Subject Librarian Former Software Engineer Science Fund Manager No Cost per Use? 2 Gabriele's intro Data Services Librarian Former English Professor Love to share knowledge Always seeking projects to build technical skill set 3 Lydia's intro Worked in Acquisitions Now Budget Analyst for my division  including collections Fun with Excel, Alma Analytics, and learn a little new-to-me tech thing every day. 4 How we made our invisible work visible. It's literally about visualization Show supervisors, colleagues, groups with an expanding scope. Collections Budget Group Collection Managers Subject Specialists This presentation! Article to come 5 Reflection point What kind of invisible labor do you do?  What barriers make your work invisible? What would you need to do to get people to see your invisible labor?  Who could you get to see your work? 6 Reflection point What kind of invisible labor do you do?  What barriers make your work invisible? What would you need to do to get people to  see your invisible labor?  Who could you get to see your work? 7 DESCRIBE PROJECT IN BAREST OF TERMS Get cost Get use Join, transform data into Cost Per Use Turn static data loads into APIs Make it look pretty Share it Use it 8 The why of the project Context: someone was manually doing all this work, on a long delay, with new analysis each time, and not as comprehensive as we would like Breaking down silos. Automating saves the work of several colleagues Allows it to be much more up to date In making invisible work visible, it’s not just visible it’s visualizations (taking it literally) 😊 9 Reflection point Is there a project you think would be solved by a cross functional team?  Is there a successful cross functional project you’ve worked on?  What made it successful?  10 Reflection point Is there a project you think would be solved by a cross functional team?  Is there a successful cross functional project you’ve worked on?  What made it successful?  11 The why of the team Bring different backgrounds and skills together to propel the library forward We wanted to invest in ourselves and our skill set Project became a catalyst to motivate and direct professional growth The team became a cohort of people learning the same tools at the same time Taught ourselves (loosely) about project management and productivity Able to apply skills developed in this project to other projects Contribute to a culture of growth, which in itself strengthens the organization 12 How did we work together? Recognize differing levels of  excitement  engagement  motivation  prioritization  and time over time  Communicate what you need  Celebrate small victories Please and Thank You Meme / GIF economy 13 Process Weekly (ish) Zoom meetings Standing meetings Working meetings Occasional meeting clusters Tag-team challenging bits: no one is stuck all alone.  Break the project into tiny parts Independent work Alma Analytics importing data into Power BI Python coding.  Find help:  Campus Power BI Teams group  Power BI course Lydia joined API working group 14 the project IN a BIT MORE DETAIL 15 the project IN a BIT MORE DETAIL 16 Defining our success What does "done" look like? Value of the skills we learned Value of the final project Value of opportunities to come 17 What did we learn? - Lydia Lots of technical tools I already used Power BI on another project about APC fees and impact metrics.  Not the fastest. Could have hired a consultant, but then we wouldn't have learned anything. Cross-departmental friendships/relationships helpful for getting other things done.  18 What did we learn?  - Gabriele Iterative  Reusable technical skills:  Python API skills  Power BI Kept having to recommit to the project in order to move past barriers or when we lost momentum.   More understanding of how things work in our various departments.  19 What did we learn? - Kristin Will be using Power BI for another project looking at use of a physical library space. Kept having to recommit to the project in order to move past barriers or when we lost momentum.   Power BI campus community – provided training. There are more resources out there than you think.  None of us could not have done this project alone. We needed all three of us to bring different knowledge, skills, and approaches.  Since we started the project all three of us have been promoted. Recognized for initiative? 20 Questions? Lydia Harlan, lharlan@uoregon.edu Gabriele Hayden, ghayden@uoregon.edu Kristin Buxton, kbuxton@uoregon.edu 21 Nitty Gritty what power bi looks like Nitty Gritty power bi m code Nitty Gritty power bi dax Nitty Gritty python meme references - chronological Surprised Pikachu [Digital image]. (2001). Retrieved from https://www.reddit.com/r/MemeEconomy/comments/9upm7x/alternate_to_popular_meme_hot_off_the_press/ Cats being weird little guys [Digital image]. 2022. Retrieved from: https://twitter.com/weirdlilguys/status/1565870440890806272 Pepe Silvia [Digital image]. (2008). Retrieved from https://knowyourmeme.com/memes/pepe-silvia I look amazin in a mirror [Digital image]. Retrieved from https://cheezburger.com/5332046848/i-look-amazin One does not simply make the dream work – without the teamwork [Digital image]. Retrieved from https://makeameme.org/meme/one-does-not-5c172f Shia LeBouf magic [Digital image]. (2008). Retrieved from https://doughenningproject.com/2020/05/20/shia-lebouf-snl-sketch/ Programmer's credo [Digital image]. (2021). Retrieved from https://www.reddit.com/r/ProgrammerHumor/comments/nu3d5t/i_thought_same_somehow/ Day 4,321 [Digital image]. (2023) Retrieved from https://gregdeckler.com/2023/05/01/day-4312/ Code lifespan [Digital image]. Retrieved from https://imgs.xkcd.com/comics/code_lifespan.png image1.jpeg image2.png image3.jpeg image4.jpeg image5.png image6.png media1.mp4 image7.png image8.jpeg image9.png image10.jpeg image11.jpeg image12.png image13.png image14.jpeg image15.jpeg image16.png image17.png image18.png image19.png