~ Benjamin Heet

1. Managing a Miasma of Statistics
Benjamin Heet
University of Notre Dame
http://www.binary-finary.com/wp-content/uploads/2010/01/Binary-Finary-1998-The-2010-Remixes.jpg

2.  What stats should we collect?
 How do we manage what we collect?
 How do we use and interpret the data?
 What are best practices going forward?

3. What should we collect?
http://zforza.typepad.com/.a/6a00d8341d0eae53ef010535cdba6d970c-800wi
Impact factor
Eigenfactor
SFX
JR1 – Full Text Downloads
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4. Can we make questionable numbers more meaningful by
adding other questionable numbers?
http://www.buzzinn.net/img/fun/confused-animals-are-funny/confused-animals-are-funny15.jpg

5. What does it all mean?
 HTML vs PDF
 Outlier – Use Spikes

6. HTML vs PDF

7. OMG…Where did that come from????
Outlier / Use Spikes

8. Speedy Delivery? Not quite!

9. Keeping Busy
 Download new stats each
month for every provider
 Merge new month onto prior
report
 Using Excel v-lookup function
Why are we doing this?

10. Building a better mousetrap
There must be a better way!

11. http://erm.library.nd.edu

12.  Upload statstics as .txt files
 System parses, verifies and imports data
 Log files of all activity

13.  Account logins stored in single location, easily accessible
 System does the work, takes significantly less time

14.  Manage statistics, option to delete problematic months
 System automatically flags outlier data / use spikes

15.  Separate reporting page
 Collection managers can run and obtain their own reports

16.  Report output, option to export to excel

17. Questions?
Benjamin Heet, heet.2@nd.edu
Find out more at http://erm.library.nd.edu
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