I’m Busy and I Can Prove It: CMS Data Mining to Track Staff Activity

I know I’m busy, but does everyone else at my museum know it? Sometimes it can be useful to have quantifiable data that confirms empirically what you already know to be the case: that you’re working with superhuman energy on many projects simultaneously and your efforts are helping the museum stay afloat. It can also be useful to be able to apply some quantification to the work of others on your team.

While not expressly designed to support this sort of quantification, your collection management system can be used to generate statistics on staff activity. Your CMS exists at the core of much of your museum operations, and every use of the CMS leaves some sort of digital fingerprint, whether it’s a new record created by a user or an audit trail indicating the edit of an existing record.

How deep you’re willing to go in your CMS forensic analysis partly depends on what your information requirements are. For example, you may only be interested in reporting on who among the staff logs on to the CMS each day and how long they remain logged on. True, this statistic can be misleading: if a staff member logs on to the CMS, takes a long nap and then logs off, they would generate the same stats as the person who logs on, works like a demon, and then logs off. Nevertheless, this is a simple metric that has some merit particularly if your motive is to shine a light on who among the staff rarely logs on to the CMS at all (you know who you are, Mr. Star Curator). The report could look something like this:

Logon Time Screenshot

What You Did and When You Did It

Logon records are a crude tool, though, because they don’t give any indication of how much work a user did between logging on and logging off. It would be nice to have a metric that’s an aggregate of the number of changes made within your CMS throughout the day by each user. The Audit Trail feature of your CMS is designed to track changes to each object record, but can also be leveraged to create aggregates of changes made per user or per day. There are many valid reasons to consult your CMS without making any data changes; the Audit Trail can’t tell when you’re simply pondering an object record and thinking deep thoughts. Still, by mining data in the Audit Trail you could create the following report:

Data Updates Screenshot

This report, in turn, cries out for a companion report that would show the detail for each row, listing the specific changes in the CMS made by each person each day. And you can combine both reports into a dashboard to provide a high level overview of user activity every time you connect to your CMS. I’ll cover dashboards in another post.

It’s always good to be able to quantify the hard work you and your staff are performing; you never know when you’ll be asked to give an accounting, and it helps to have numbers in hand when that day comes.

About the Author:

Danielle Uchitelle
Danielle has worked for over 25 years in academic and non-profit administration and has over 15 years of museum experience, including 7 years at the Solomon R. Guggenheim Museum. At Gallery Systems, in her role as Chief Operating Officer, Danielle is responsible for managing client support, training, documentation, and custom services. In addition to her professional background in museum administration, Danielle holds an MBA degree from New York University and an MLIS degree from Columbia University,


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