Colin Wilkins, Supervisor of Collection Development, The Public Library of Brookline
He started by asking why we are here?
He showed us a bunch of web management reports.
What do we want?
Three big ones:
Innovative Interfaces product
It’s more of a macro-level tool
Bad things: no natural language, steep learning curve, report loading time, it’s ugly.
He showed a screenshot of Decision Center. There is a popular authors tab. It’s also a great way to generate weeding reports to determine low and high circ. “Dusty” items can be caught when running high circ. You can also look at age of collection and supply and demand.
Reports have a lot of numbers. He showed us one of owning location by item type. He is working on a case study with turnover.
Turnover = circulation/collection size
Higher the turnover, the healthier the collection
Think of turnover like your GPA
Ways to increase turnover: increase circulation or decrease collection size
Good things: Micro-level tool, Ingram integration, retail data, much better UX than Decision Center
The bad: Manual process for data transfer, time consuming to build data volume, pool of peer library data ia relatively limited.
Analytics Case Study: DC tells us that circ for hardcover and paperback science fiction is lagging behind. When you marry the strengths of DC with Edelweiss, it becomes a powerful thing.
He then showed us the Edelweiss site. Things like missing titles are shown, peer suggestions, market suggestions, holds, etc. We looked at the top 50 books that his library does not own. It came up as a pie chart.
Questions to ask:
What soures of data exist? Who will use it?
How will we track and celebrate progress?
How will it affect integration and workflow issues?
Can anyone show me these tools in more depth?
We harvest this data, but what do we do now?
What is the next step? He thinks this should be built into the process.
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