Last week I learned a lesson about making mistakes, and it was both humbling and helpful. Just one day before the deadline for locking the University’s numbers into the IPEDS system (Statistics for the U.S. Dept of Education) for FY18-19, I was contacted by the University’s director of data analysis and reporting. “Where are the libraries’ numbers? “After a brief email exchange, password in hand, I was quickly able to input those numbers – prepared months ago for other purposes – ARL, ACRL, AASHL.
Annoying, each agency asks for data sliced and diced in different ways. Sometimes we separate out physical and digital titles, sometimes we separate articles and books in reporting interlibrary loan transactions. Reference can be most complicated, with data coming from multiple systems and channels (SMS, Chat, Analytics. LibAnswers), Excel spreadsheets, manual reports).
But I felt confident in my IPEDS numbers, and the data input was easily completed. I reported back to Institutional Research and Assessment, and pointed them to the required backup documentation – multiple spreadsheets, reports from Alma, Read-Me files. From year to year, if numbers seem out of line with previous years’ reports, those anomalies need explanation. For instance, I noted that physical circulation declined due to the closing of Paley library. All good. Next step, the data is AGAIN verified by the University Data Verification Unit. DVU provides another thorough audit, also requiring documentation to back up each number.
At 4:45 the day the numbers are due, DVU discovers an error. In calculating the total monographic expenditures for Law, HSL and Main libraries, I double counted two figures. I felt stupid, of course. But the error was easily fixed, verified by the Unit, and at 5:07 pm, the University’s data was locked. Yeh!
A long story, but I learned a couple of things. While the University-mandated data verification process is sometimes annoying, especially when time is tight, there is real value in having an external reader to double-check formulas, data input, and logic. No one is perfect. Internally here in the libraries, I’ve begun the practice of my own verification – so I will double-check numbers provided to me. I want to understand so I can explain to others.
It is equally important for those “on the ground” to help me understand the numbers. Why did circulation go down? Why did interlibrary loan go up? What happened on March 19 that caused our gate count to plummet? What was the impact of making our webchat more visible?
When we ask for documentation, it is not to be mistrustful or to create extra work. It ensures that the data we report for surveys, to accrediting bodies, for funding agencies and to our professional associations is as accurate and reliable as we can make it.
I don’t believe that mistakes are a good thing. But I learn more from my mistakes than pretending I don’t make them. I’m much better off when I am willing to ask for help, allow time for others to check my work, and consider the perspectives (and expertise) of my colleagues. And next time, maybe I’ll remember to keep my thumb off the camera lens.