PL 21/07: NTC - How to measure lending

It is common practice to report on lending – and on library activcities in general – once a year.

The reporting period is usually the chronological year (2006, 2007, 2008, …) – but it could also be the school year (05/06, 06/07, 07/08, ….) or, in some cases, the financial year (if it differs from the chronological year).

Since school years are separated by (summer) vacations, some libraries utilize the quiet period to organize their statistics amd write their annual reports.

One year’s lending

We may visualize each year’s lending as a table with books (or media) on the horizontal and lenders (or users) on the vertical axis.

Books and users in 2006

	Book A	Book B	…	Book ZZZ	H SUM
User 1	1	0	…	0	User 1 loans
User 2	1	1	…	…	User 2 loans
…	…	…	…	…	…
User nnn	0	0	…	1	User n loans
V SUM	# Loans of A	# Loans of B	…	# Loans of ZZZ	Total loans

In this way of thinking, all users (active as well as passive) and all books (with and without loans) should be included.

The most basic number is of course Total loans. This number must of course be related to

• The number of users: Loans per user = Total loans divided by the number nnn
• The size of the collection: Loans per book = Total loans divided by the number ZZZ

Some books are in great demand, some in moderate demand, and some do not circulate at all. The Vertical sums indicate the popularity of each book.

Some users are heavy readers, some are light readers, and some do not borrow books at all. The Horizontal sums show how users differ.

Both sets of numbers are interesting and can be analyzed with simple methods.

If your catalogue is automated, all the data you need should be available “inside the system”. To get them “out of the system” you must set up a program to generate the relevant reports. Each catalogue system has its own way of doing this – and you may need the help of data person. Here I consider what can be done manually.

Even a small community library will often provide many thousand loans during a year. To get a manageable set of numbers, we must take a representative sample.

The method for selecting days, which was outlined during the first session, will – roughly – cut the numbers (and the statistical work) by a factor of 25.

One year at Maktaba

Let us imagine a library called Maktaba – the word means library in Swahili. The head of the library, Mrs. Sabuni, has decided to define 12 days during the year as counting days. She has also asked one of her assistants to register all loans during these twelve days.

At the end of the year, she has a sample of approximately 750 loan transactions. The annual total must be around 750 * 24 = 18.000 loans. If Maktaba has 6.000 registered users and 9.000 books, we find:

• Loans per user = 18.000 / 6.000 = 3.0
• Loans per book = 18.000 / 9.000 = 2.0

We can further use this sample to study

• who our active users are – by age, gender, education, and so on…
• which books are being used – by age level, genre, subject, language, difficulty, and so on …. .

The simplest way is probably to

• write down the data for each loan on a 5 x 8 card
• sort the cards manually
• count the number of cards in each stack

This can be done repeatedly, for different variables (age, gender, age level, genre, ….)

Note that the sample reflects actual usage – not the total universe (population) of library users or books. Only active users and borrowed books are included – and the chance of being selected increases with the level of activity.

Who borrows what?

We can also use this sample to study “who borrows what” – in other words, the relationship between user characteristics, on the one hand, and book characteristics, on the other. We might for instance find:

	Books for children and youth	Adult fiction	Adult non-fiction	Sum
Children	200	50	50	300
Adult women	70	100	100	270
Adult men	30	50	100	180
Sum	300	200	250	750

Here, we may compare the three user groups by calculating the percentages within each group:

	Books for children and youth	Adult fiction	Adult non-fiction	Sum
Children	67 %	17 %	17 %	101 % (N = 300)
Adult women	26 %	37 %	37 %	100 % (N = 270)
Adult men	17 %	28 %	56 %	101 % (N = 180)
Sum	40%	27 %	33 %	100 % (N = 750)

In this particular case, it is also meaningful to compare the three catefgories of books, by calculating the percentages within each category:

	Juvenile loans	Adult fiction loans	Adult non-fiction loans	Sum
Children	67 %	25 %	20 %	40 %
Adult women	23 %	50 %	40 %	36 %
Adult men	10 %	25 %	40 %	24 %
Sum	100 % (N = 300)	100 % (N = 200)	100 % (N = 250)	N0 100 % (N = 750)

Since the sample of loans is taken “from inside the table”, it cannot be used to study the Vertical or the Horizontal sums.

• If we want to study the lending distribution of individual users, we could select – say – 120 users at random (every fiftieth user in the card register) and study how many books each of the had borrowed during the year.
• If we want to study the lending distribution of individual books, we could select – say – 180 users at random (every fiftieth book in the card catalogue) and study how many times teach had been borrowed during the year.

Resources

• PL 24/07: NTC – Listen to your public
• PL 23/07: NTC – What happens inside libraries?
• PL 22/07: NTC – Visitors and users
• PL 20/07: NTC – The idea of sampling
• PL 19/07: NTC – Program

Complete teaching materials for Numbers that count – as a single file (Google Docs). – 18 pp.

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