Our FOPL members have access to the 2001-2015 analysis and rankings of public library systems in Ontario report here: FOPL_Data_Report_2017_rev (1)
Over the past years FOPL has been leading a pilot study of new measurements for Ontario’s libraries based on the data we have from the Ministry of Tourism, Culture, and Sport. We have held webinars and symposia on statistics in libraries and offered this white paper for discussion: discussionpaper_2-2-1
Now we are pleased to offer customized reports to our members for their research, advocacy, and strategic planning needs.
About the FOPL Custom Reports Service
The Federation of Ontario Public Libraries has continued working on data compiled by the Ministry of Tourism, Culture, and Sport on those libraries. With the publication and distribution of FOPL’s recompilation of these data, there is now a large, rich dataset about Ontario’s public libraries. The data span the years from 2000 through 2015 so that one can analyze data on all libraries or any subset of libraries and also analyze trends by following the data over a set of years.
The dataset is quite rich and the Ministry has done a wonderful job in structuring the data. What can be done with this resource? Of course, various groups will be interested in different uses of these data. FOPL has already issued survey reports exploring these data with an eye to using them to assess the state of Ontario’s public libraries for assessing our health as a community and driving the communication of the value and impact of public libraries in our advocacy role. As that work is fleshed out, these assessments can be used to inform policy decisions affecting Ontario and the nation. But the history of library data shows the primary use of such data has been to analyze individual libraries or groups of libraries and to compare them. Typically, it is to examine libraries “like mine,” and the results of these data analyses are often seen in the stories that are teased out of the data.
How does my library compare with others? Which libraries are like mine by this or that criterion? What are they doing better than us—or not as well? What good stories—and bad stories—are in the data about my library and how can I use them to tell a compelling story to our library’s funding agencies? The data can be a directory to libraries “like mine” and suggest investigating those similar libraries to see how they dealt with problems your library has.
There are many ways to choose which libraries are alike. Normally, libraries are grouped by size but there are other ways to choose libraries to compare to yours. They can be analyzed by region, county, similarities in budget or collection, and so on. Often, too, what is of interest to a librarian is to examine with data what is of interest to those involved in funding that librarian’s library.
In other words, the data can be looked at in many ways and to address many questions. The dataset is available to FOPL members but it is a large and complex dataset and good, flexible analysis will require skill and experience. Those skills involve manipulating the data, sensing unexpected surprises in the data, and knowing how to present the data in a compelling way. After all, with our audience, pages of tables with number upon number is not as useful as seeing the story the data tell and saying it in clear language. To this end our initial offering is to provide simple reports that tease out specific measurements that our research tells us are of interest to you – as planners, management, CEO’s or board members. Our tradition in Ontario has been on volumes of data and not as much on common analyses and measurements. With the successful introduction of open data for the Ministry’s public library data, we now have this opportunity to learn from our data in a more accessible way.
What is available?
We offer an array of reports on common variables with your library compared to similar libraries or we can compare on a broad-based set of data variables based on the experimental FOPL Index which uses 16 variables and ranks libraries by those ratios.
We offer a number of measures and their components in the fashion of an index with libraries ranked with their peers (your choice of peers) as well as a few select ‘influencer’ libraries that serve as major comparables. (Consider: How does my system compare on key measurements to TPL? You may be surprised!)
Here are the five major measurements derived from the Ontario Public Library Datasets:
Peer Comparison Notes
The peer comparisons presented are based on data from the Ontario Ministry of Culture, Tourism and Sport’s published 2015 Ontario library data.
The comparisons take these data and sort them into 17 separate variables and organizes them in five “dimensions:” Service, Usage, Community Engagement, Efficiency, and Development. This design is discussed in some detail elsewhere but, simply, it is based on a study of four well-known public library assessment efforts: the BIX, HAPLR, the IMLS US state ranking tables, and the LJIndex. These all use ratios of different reported variables—rather than the raw data—and then assign ranks to the calculated ratios. Those ranks are in order by which numbers are “better.” Lower number ranks are better because 1 is the top rank.
The Ministry’s data series are very rich and offer more opportunities for exploring variables within this design. We have largely followed the example of the current literature for now.
The most common use of these data is to use them to analyze “peer” libraries. What is a “peer” library? It is a library you wish to compare to yours. The comparisons will be based on data.
Data do many things well but not everything. They give you a measure and it is up to you to weigh the evidence from the data in order to learn how your library compares with your peers. They do not measure everything, however, and are weak in analyzing qualitative aspects of a library.
How to pick your peers depends on your interests and objectives. You may wish to compare to libraries in your area, or to libraries with similar users, or to libraries you wish to emulate. These data will not give you one big number but 17 and those must be considered and weighed in light of your library and its peers in the context of your strategic plan priorities, vision, mission and goals. Efficiency is something we all want but it can work at cross purposes to Service. So: balance. Weigh the evidence and it will often be one step in a process.
As mentioned, the data are calculated and then ranked. The comparisons are simple unweighted ranks. Yes, ranks are often weighted but the first presentation are unweighted. Weighting recognizes that some variables are more important than others and handles that reality. There are ties in the ranks when libraries have the same raw scores. In those cases, the ties get the same rank while the next library is ranked where it would be if there were no tie. That is, if two libraries had the best rank, they would be 1 and 1 and the third library would have a rank of 3.
The data presented here are in several forms and with varying levels of detail depending on the detail needed for different views.
Variable and Dimensions
Now we will outline the variables and dimensions. This discussion of variables is brief and the reader is cautioned to realize that in each case where the variable is described as a higher ratio or lower ratio is ranked better that what is left unsaid is: “all other things being equal.” They are not and that is why we have more than one variable to give you the context to understand your library and its peers as the data describe them.
The first dimension is SERVICE and it has four variables:
Collection units per capita. “Units” is defined broadly. This is a measure of how big the collections are for the size of the libraries’ resident populations. Higher is better.
Employees per capita times 1,000. This measure tells us how big the staff is to service the population. Higher is better. The calculation gives a small number and to make it easier to understand, we multiplied by 1,000. It can be thought of as so many people for each 1,000 in the resident population.
Population per workstation. This measure tells us how many workstations the library has. By dividing the population by the count of workstations, we have a number which indicates, how likely a library user is to find an empty workstation. Here, a lower ratio is better. Consider: is it better to have 10,000 people per workstation or 100?
Population per service point. Service points are broadly defined to include places where people will have physical access to the library. They can include bookmobiles, branches, and deposit stations. Again, a lower ratio is better. Is it better to have 10,000 users per service point or 100?
This dimension has three variables related to the actual use of the library.
Stock turnover is a traditional measure: how many times is each item (on average) checked out? Here total annual circulations are divided by a count of circulating items held. Higher is generally better.
Circulations per capita is another well-known calculation. Annual circulations divided by resident population. Higher is better.
Program attendance per registered borrower. How many of the libraries’ cardholders attend the libraries’ programs. The reported number in the detailed tables is 100 times the raw calculation. Total annual program attendance divided by the reported number of library cardholders. Higher is better.
This dimension is new to the world of library assessment and it was created to get a handle on an important set of changes occurring in the library world: the modern library is not a passive organization waiting patiently for people to appear but one increasingly looking for opportunities to meet its public wherever they are and wherever they have information needs. The four measures in this dimension are an attempt to measure how libraries are adapting.
Programs offered per capita. The higher ratio is better.
Registered borrowers per capita. What percentage of the libraries’ resident populations have library cards? Higher is better but we have documented how this percentage has been declining in Ontario’s libraries. Caledon Public Library is low to their peer group which is an opportunity and correlates to facilities readiness.
Hours open per capita times 100. Hours open includes not just buildings but bookmobile and deposit station hours. More hours open per person although as we know, a library’s electronic presence is open for business at all hours. Higher is better.
Estimated Annual Visits per capita. This ratio is the result of a complex calculation. Visits are tracked as “Typical Week” data so the data presumably re for one week. The population is an annual figure so the visits were summed and then multiplied by 52 and that product divided by the resident population. Visits are of three types: In person, electronic (to the libraries’ Websites,) and electronic (to the libraries’ social media sites.)
This dimension occasionally works against the others. Service is better with more staff, money, and service points but more economical if these are balanced by care in allocating resources. It is always a matter of balance and by looking at your peer libraries, you can see how they made the same kinds of balancing decisions that your library must make.
Collection expenditures per circulation. Lower is better. That is, more circulations per dollar spent is better than spending many dollars per circulation.
Estimated Visits per open hour. Visits, again, come from “Typical Week” data and given that these figures and the open hour figure are both weekly figures, there is no need to do more than sum the number of visits and divide by the number of open hours. Higher is better: more people visiting is better than fewer people. Note that electronic visits are included and that these can occur when the library’s buildings are not open.
Total Expenditures per estimated annual visit. Total operating expenditures of the libraries divided by the annualized visit figure to give an imputed cost per visit. Lower is better. It is better to have more visits per dollar spent.
The attempt here is future oriented.
Staff Training as a % of Total Operating Expenditures. This number is times 100 so these are the percentage figures. Staff training in this day and time is important but with library budgets being stretched, helping staff keep up with new developments by training or conference attendance is a difficult thing. But: higher is better.
Total Operating Expenditures per capita. This is an important number and one that affects the whole operation of the library including what it does and can do to prepare for the future. Higher is better.
So, there you have it – a little background.
FOPL has been working with esteemed statistician, Robert Molyneux, MLIS, Ph.D. Bob is a global expert in library statistics and is available for consultation on demand. He will be creating your custom reports.
2 reports have been done so far for select Ontario public library systems.
Basic foundations report:
2014 data (latest available) – all measures. $500.00 CDN ($1000 for non-members)
2012-2014 Data (latest available) – all measures. $750.00 CDN (includes basic report) ($1500 for non-members)
In addition we have the capacity to compare your system to a few other jurisdictions in Canadian provinces as well as all libraries in US states.
Confidential Sample Reports can be viewed on request.
So there you have it.
We can help you choosing peer and influencer libraries and feel free to use the main report FOPL_Data_Report_2017_rev (1) to select them.
Stephen Abram, MLS, FSLA
Executive Director, Federation of Ontario Public Libraries