With the first semester coming to an end and with most institutions having completed this semesters space utilisation survey by now, this article looks at 8 tips for analysing teaching space utilisation data in order uncover areas for improvement, providing thoughts on why these methods are useful as well as a “how to” section for each, outlining how to carry out each data analysis technique yourself.
To accompany this article, I will be making a series of space utilisation analysis templates available to all subscribers of the Education Space Consultancy newsletter, that cover the majority of the techniques included in this article. Therefore if you would like to receive this for free, remember to sign-up!
In order to write this article, I have presumed that you have actual space utilisation data for all of your teaching rooms over the same length of time (i.e. a week), I do not advise using all of these methods if using timetable utilisation data as the results and conclusions may well be misleading. In fact I strongly advise that if you don’t collect actual space utilisation data that you certainly consider doing so as it this data is an incredibly valuable source of information for getting the most out of your space and saving money. The following methods will help to explain this reasoning further as will a lot of the other posts that have been added to this blog so check these out if you want to see the incredible value of actual space utilisation data.
‘Space, like time, is money” National Audit Office
1) Teaching Rooms With Low Frequency Rates
Why? A straight forward measure is to pinpoint the rooms with the lowest and highest frequency rates and investigate why, in doing so solutions can be found that will help to improve the institutions utilisation rate i.e. change of room booking procedures, increasing timetable demand for the space or perhaps removing the space from the timetable and creating a different type of space that is in high demand within the institution. For those that have high frequency rates, the reasons for this should also be investigated to determine whether there is nay best practice that can be shared throughout the institution promoting space utilisation improvements.
How? Sort the space utilisation survey data by the teaching rooms’ frequency rate and investigate those that have the lowest and highest frequency rates. The SMG suggests a target frequency rate of 75% for general teaching space, however I would recommend selecting those rooms with the lowest frequency rate to begin with and working up the list from there. I have a excel template for calculating the frequency rate by room that I am happy to send to those that are interested (for free), just get in contact or subscribe to the Education Space Consultancy this week to receive it in the upcoming newsletter (w/c 15/12/14). Also, I have posted a video tutorial going through this process that is definitely worth a look- Video Tutorial Space Utilisation Survey Data Calculations – Part 1
2) Teaching Rooms With Low And High Occupancy Rates
Why? The aim in this case, is to find which teaching spaces have the lowest and highest occupancy rates and investigate the reasons for this. In investigating the rooms with low occupancy rates, solutions can be found that will enable the institutions utilisation rate to increase – for example the there may be insufficient demand for this size of space, therefore this space could be divided or a smaller space reconfigured to provide the same teaching resource, releasing this room for other uses. As with point 1) it is also worth investigating the rooms with the high occupancy rates as there may be booking practices that can be used as best practice and shared throughout the institution.
How? Similarly to point 1), sort you space utilisation room data by occupancy rate and then select the rooms with the lowest and highest occupancy rates to investigate. Again, I have an excel template for calculating the frequency rate by room that I am happy to send to those that are interested (for free), just get in contact or subscribe to the Education Space Consultancy this week to receive it in the upcoming newsletter (w/c 15/12/14). Also, as with point1) I have posted a video tutorial going through this process that is definitely worth a look- Video Tutorial Space Utilisation Survey Data Calculations – Part 1
3) Space Type Analysis
Why? I find this is a very useful tool for uncovering patterns of poor utilisation within an institutions teaching space. By comparing rooms of the same space type, performance can be ranked and those with low utilisation investigated. High utilisation should also be investigated, as there me particular booking practices that promote this excellent utilisation of space that can be shared throughout the institution.
How? Ensure you know the space types for each of your teaching rooms. Then split your space utilisation room data by space type and calculate the average frequency, occupancy and utilisation rates for each.
Its worth remembering at this point that the availability and access to teaching spaces will certainly effect the demand. Therefore if you have teaching rooms that are only accessible by certain departments, it is also worth further splitting the space type data by department access and comparing the results. This is important, as for example one department may very effectively utilise their seminar spaces whilst another may not – without splitting the data by department, this intricacy may well have been missed.
I have a excel template for calculating space type utilisation that will be made available to all Education Space Consultancy newsletter subscribers, with a link supplied in next weeks newsletter so remember to subscribe to receive this and the other templates mentioned in this article for free!
4) Timetable vs Actual Frequency
Why? I personally believe this can be one of the most effective methods for improving space utilisation and teaching room availability. The aim here is to understand if there are any differences between what is being timetabled and what is actually being used as there is often a considerable difference. This difference represents a big opportunity as by solving these inaccuracies you can increase teaching room availability within the timetable. This then enables more activities to be booked within the same amount of teaching space – improving space utilisation, conversely the reduction in timetable demand could allow for teaching space to be reconfigured to reflect the demand, as highlighted in 8) Room Requirement Analysis.
The reasons behind why these inaccuracies occur are often very varied, surprising and interesting! I have posted a further article on the Education Space Consultancy blog looking at this data analysis technique in further detail and its well worth a look – How to Improve Your Teaching Space, Without Damaging The Student Experience
How? To carry out this comparison you will need to compare the timetabled activities for the survey week 9 i.e. via timetable export for the survey week) against the corresponding timeslots within the space utilisation data, highlighting and creating a list of all the activities for each department that were timetabled, but didn’t take place. There typically isn’t a “one size fits all” template for this, as it requires the comparison of two data sets from different sources however I am very happy to carry out this comparison for you at a very affordable price, so please don’t hesitate to get in contact if you are interested in carrying out this comparison but are unsure how.
5) Timetable vs Actual Occupancy
Why? This data analysis method, compares the timetabled class sizes against the actual number of students that attended each activity. This comparison can then be used to highlight any activities where there are large disparages between the number of students that attended and the class size timetabled. There are typically two reasons for a difference, 1) Incorrect class size 2) Low student attendance – both of which are of interest to an institution and in resolving can improve space utilisation and/or student engagement.
How? As touched on already, the aim with this data analysis method is to compare the timetabled class sizes against the actual number of students attended. This can therefore be done by simply taking an export from the timetable that includes the same parameters as the survey week (i.e. Monday-Friday 09-17:00, in the same rooms), plus ensure that this includes class sizes.
Then compare this timetable export’s activity sizes against that of the survey data occupancy numbers, this can be done quickly and easily with excel formula’s. If you need help doing this, I can set up an easy to use template that you can use for this and all future comparisons that will provide you with these results in an easy to digest format at a very affordable price, just get in contact. This does take me some time as it often has been custom designed per institution, hence the small charge.
6) Day and Timeslot Analysis
Why? The spread of teaching activities across the teaching week, is critical to ensuring an institution can get the most out of its available space. If teaching is bunched at certain certain times or on certain days, space may appear very well utilised at these times however during the periods where little teaching is taking place space will appear very underutilised. These peaks and troughs, more specifically the peaks, result in teaching rooms having to be provided to cope with these peak demand periods. If the demand was spread out throughout the week, the peak demand would be reduced, meaning that space could be reconfigured to match the average demand enabling an institution to get more out of its space.
I would typically carry this data analysis method for both frequency and occupancy. The frequency will show you the spread of demand and the occupancy will show you the affect days/timeslots has on room occupancy, the latter is particularly useful when measuring at institutional and space type level.
The frequency rate analysis can be used to highlight and solve, demand and occupancy peaks and troughs. In doing so, this will address the issues associated with peaks and troughs in demand and enable an institution to get more out of its space. The occupancy rate analysis, similarly can be used to highlight peaks and troughs, this is very useful for determining the usage (and popularity) of open access study/teaching rooms throughout the survey week.
How? All you require is the same space utilisation data, the frequency and occupancy rates fore each timeslot/day can then be calculated using the data you have available. I have a excel template for calculating both frequency and occupancy rate by timeslot that will be made available to all Education Space Consultancy newsletter subscribers, with a link supplied in next weeks newsletter so remember to subscribe to receive this and the other templates mentioned in this article for free!
7) Department vs Central Teaching Space Analysis
Why? The nature of department only teaching space, means that they are typically only available for that department’s teaching, This therefore reduces the potential timetable demand for these teaching spaces, which can impact on the space utilisation.
This analysis method is best used in combination with space type analysis method, as this ensures similar central and department teaching spaces are compared against each other. This creates a fair comparison and any noticeable differences can then be highlighted and discussed with the central and departmental teams responsible for the management and booking of the teaching rooms.
I have posted two articles looking at the use of department only teaching space further and these are definitely worth a read – The Pros and Cons of Department Only Teaching Space and 6 Factors Institutions Should Consider For Maximising The Benefits of Department Only Teaching Space.
How? Ensure all of the rooms surveyed have been labelled in the data as central or department (with the corresponding department name) rooms. Then sort and separate by space type and then sort and split again by central/department name, finally run in the space utilisation calculations against each of the central/department splits, for each space type. I have an excel example of calculated department and central teaching space utilisation rates that will be made available to all Education Space Consultancy newsletter subscribers, with a link supplied in next weeks newsletter so remember to subscribe to receive this and the other templates mentioned in this article for free!
8) Room Requirement Analysis
Why? Another one of my favourite space utilisation data analysis techniques and again I typically look to use this analysis in combination with other other techniques, such at institution level, space types and department vs central teaching spaces. The aim of this technique, is to understand how much space is actually required in order to accommodate the the number and size of activities recorded during the survey week thereby creating an ideal space provision scenario.
This can be used to highlight any over or under supply of teaching space, providing evidence for adjusting the estate to match the recorded demand ensuring the institution is getting the most out of its space.
How? To start with sort and separate the data into suitable categories. i.e. if you would like to find out the room requirement by space type, follow the How? section of 3) Space Type Analysis. Then decide what capacity bands you want to record demand within, for example 0-10, 11-20, 21-30, 21-50, 51-75, 76-100 etc. Finally count the number of activities that occur during the week within each capacity band.
This will provide you with the number of hours required for each capacity band, to find out the total rooms required to accommodate this demand simply divide the the number of hours the space was surveyed i.e. 40 hours if Monday-Friday, 09-17:00. I have an excel example of room requirement analysis that will be made available to all Education Space Consultancy newsletter subscribers, with a link supplied in next weeks newsletter so remember to subscribe to receive this and the other templates mentioned in this article for free!
That concludes my 8 tips for getting the most out of your teaching space utilisation data. As mentioned at the start of this article I will be posting an additional article on this topic later next week investigating some examples of underutilisation and the possible solutions. The article will follow the same structure, including at least 1 example for each technique mentioned. Subscribe to the Education Space Consultancy newsletter and you will not only receive an information packed newsletter, including new posts and sector news you will also receive a link to access all the templates referred to in this article for free!
If you have found this article interesting and want to get the most out the teaching space at your institution but feel you may need assistance, I am very happy to provide free advice whether this be by email, over the phone or in person, so please don’t hesitate to get in contact.
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All the best,