Supplementary dataset

Below is the suggested supplementary data for collection by NHS libraries. It can be used as you see fit. Please feel free to add data collection that is helpful to your library and your situation. Data can be collected over what every period you feel is most useful to your situation. Some data you may want to collect regularly so that you can build up trends; other data can be collected as and when it is needed. You need to think about what data would be most useful to you and your service, what you want to use it for and remember that data is only of any issue if there is a story that goes with it.

Excel spreadsheet for supplementary dataset.

Within this suggestion for supplementary data collection OpenAthens hasn’t been included. This is because this data can be found from the admin side of OpenAthens. It can be download in several different ways into excel and data can them be analysed as needed for the library service.

A number of librarians and library services already collect supplementary data and use them in a number of different ways. Alan Fricker, Head of NHS Partnership & Liaison for the Library Services at King’s College London is one and he share his story about why he collects supplementary data.

In preparing the action plan style annual report I am really keen to have statistics that help tell a story and engage.  As far as possible I do not want to include any numbers where I do not have some qualitative explanation to accompany them.  Without the story most numbers are a so what moment waiting to happen.

In line with the principles for good metrics I want stats that are

  • Meaningful – to my audience not just to the library service – things that important to them. A good example was GMC data which is significant for people who hold our funds. In our satisfaction data some topics draw a lot more answers than others – I would suggest this is a guide to what people actually care about in our service.
  • Actionable – I want to be able to talk to people about things we might do that will affect the figures we have.  In the report I am always looking to explain potential reasons for change or to propose ways that we might address negative trends / unsatisfactory levels of use.  Our recurring user surveys in South London have been great for showing how changes to the service over time (increased ejournals / opening hours for example) have lead to shifts in satisfaction
  • Reproducible – I tend to look for figures that I can readily access and refresh the data if I need different time periods.  I prefer not to use things that involve human input (enquiry stats for example) as these can be somewhat unreliable and hard to validate).  So active OpenAthens users is a great favourite – I record this figure each month but it is the annual figure I would use in my annual report as this reflects the overall shift over the past year rather than picking out a good or a bad month
  • Comparable – I tend to stick to comparing against our own performance through time as this is the area where I have most control over what has been happening and strong data.  GMC was another area where I might pull out some comparator data as this is very appealing to stakeholders who want know where they stand against their peers. I would not be worried about whether we look the best in these as we want to engender a joint stake in making progress.

The action plan style report has had a much greater impact than the previous text heavy document.  It has helped guide conversations with key stakeholders and support discussion at meetings.  It has been a way to reach out to people I have not had enough contact with and to secure meetings with others.  It has been circulated to places and meetings I was not able to go to.  Some of that is undoubtedly down to using it in a different way than I would have tried with the old style report.  Some of it is also because people opening it are quickly presented with numbers and stories that speak to their interests. Presentation about the Annual Report.

Downloads: 

additional data set