Measuring the value of public libraries
New year, new idea! Something to ponder in 2021. How do we measure the value of public libraries? Not that I and others haven’t been wondering about this for ages, but maybe it’s time to really put the thinking cap on. And this is the idea that’s forming.
Step 1: Start by describing common types of library use.
Margaret is an older retired lady who comes in to the library every fortnight to get 6 new books to read. We probably all know a Margaret.
Yan and Mei come to the library every week with their Mum for Story Time, and always leave with a bag of books to read at home.
Wasim is a tertiary student who goes to the library on Tuesdays and Sundays. He spends 4 to 5 hours each time, quietly studying up the back.
Ezra comes in after school on Wednesdays for Lego Club. He is a regular at school holiday programs.
Geoff and Lorenzo are at the front doors every weekday morning, waiting for the library to open so they can read the newspapers and catch up on what’s happening in the world.
Jane comes to the craft activities in the afternoon. Sometimes she borrows a book, but mostly she is there for the company.
…
And so on. The middle-aged reader and the teen reader. The person referred from Centrelink for help with their papers. The jobseeker printing their resume. The family on a Saturday morning changing over their borrowings. The quick in and out to collect some holds. Georgina downloading ebooks. The between school and home kids. Michelle accessing Ancestry.com and the local studies collection.
I’m up to fifteen already and I’ve only just started. But what I’d like to do is come up with about twenty different archetypes of library user that might represent, say, 80% of library users. Not perfectly! But enough to say that each categorisation is a reasonable and recognisable description of people who are often found in libraries.
Step 2: Estimate a value for each archetype. That is, calculate a $ value for each type of user and each use. This might involve a mix of hard $ and soft $. So, for example, every visit Margaret makes to the library might be worth $25 (at this stage I’m just making it up). That value might combine:
a saving on buying books for entertainment (which is a direct benefit to Margaret)
a health and wellbeing component because she is keeping her mind active and her imagination firing (which is a net saving to our health system)
a social benefit as every visit is an active trip out of the house (although this benefit might be greater for a Jane).
You could get really scientific here, but in the first instance I’d be taking an educated guess.
Step 3: Do some research at a library to see how many of each type of user there are every day or week. I’d start at my local library – which is not too big to make the task overwhelming – and watch the people come and go for an hour here and there. Different times of the day, different days of the week. Observing or, with the approval of the library, doing a 30 second survey as people left the library. Something along the lines of:
i) Who are you (life stage)?
ii) What did you do (type of library use)?
iii) How long were you here (depth of use.)?
In the first instance that information would enable me to test my categorisations from Step 1, and as needed revise the calculations from Step 2. Then I’d want to test this in some other libraries, further refine Steps 1 and 2, and check that the method of finding the distribution of use by user type is sound.
Step 4: And now it starts to get interesting – analyse the results. To begin with there is the following table (which once again is entirely made up).
So what could we do with this sort of data? Well, we could …
calculate total community value delivered by the library per year
calculate a Return on investment (ROI)
calculate an average cost per visit or use
find out which library services deliver the greatest net benefit, and what sort of benefit that might be – literacy, social, resource efficiency, etc.
characterise libraries and communities (e.g. reading, activity , place) to assist in service planning
advocate for more or targeted funding to enhance benefits for specific user groups.
Ultimately, this sort of information is not just entertaining for data nerds like me. It is the sort of information that is needed if the community and its representatives are to have an informed debate about how we best support communities and how we all pay for it.
Of course there are risks in having this sort of information. It might show that public libraries aren’t as valuable as we think they are. People might want to use the data to argue to stop delivering ‘lower value’ services. People might use it to argue for user contributions to library services. And so on.
But there are also risks in not expanding our understanding of the economic and social benefits of libraries to individuals and communities. There are reasons that military organisations invest heavily in intelligence. You might not always need it, but it might just win you the war.
In 2021 I am going to start working on this idea. If you’d like to join me, you know where I am.