© Stellae 1 Space modelling: the key to a successful property strategy AoC Estates Regional Meeting, 13th July 2011 Richmond upon Thames College, Twickenham, Middlesex, TW2 7SJ Stellae, Corpus Christi House, 12 West Walk, Leicester, LE1 7NA , George Edwards Consulting, Huntersdale, Knoll Hill, Sneyd Park, Bristol, BS9 1QY, ,

© Stellae 2 Identify major factors affecting the changing pattern of course delivery. Demonstrate a quick method for the assessment of required college floorspace. Calculate the financial costs of keeping excess floorspace. Describe opportunities for the more effective management of floorspace and the use of teaching and learning facilities. Purpose of workshop

© Stellae 3 review the adequacy of existing floorspace assessment systems; examine how information about learner use of college facilities may be assessed; recommend the best option for assessing floorspace requirements. A fresh look at floorspace In 2009 the Learning and Skills Council contracted Stellae to:

© Stellae 4 a higher level of non-attendance on college courses; increases in learner directed learning. The current situation It appears that learner absence is higher, sometimes much higher, now than it was in the 1990s. This might be partly due to: It is not possible to establish the proportions relating to each factor but this does not matter. It is the outcomes that are of primary importance.

© Stellae 5 it can support effective learning strategies; it reduces course costs; the technology to deliver it is now available; surveys indicate that particularly the more able learners prefer it as part of course delivery. New developments The introduction and spread of Learner Directed Learning (LDL) is of increasing significance. The benefits are:

© Stellae 6 Space assessment The revised assessment system must establish space needs under all conceivable circumstances and for the entire range of learners. Because colleges are now responsible for assessing space requirements the system must be useable by colleges. The ILR is no longer a reliable basis for estimating floorspace requirements due to higher absence levels and the newer learners not on the ILR, such as for example, year olds, higher education students and franchised in WBL.

© Stellae 7 Assessing the floorspace envelope There is now only one realistic option. Assess floorspace requirements on the basis of actual attendance multiplied by an appropriate factor Count actual learner attendance in a two week period when there is a heavy demand for space. Convert observed hours into annual equivalent MNWs by dividing annual hours by Total maximum floorspace requirement = observed and adjusted MNW * 14.5 m 2. Less floorspace will be required in future due to increasing LDL and a possible reduction in growth levels.

© Stellae 8 Space modelling The new method of establishing space needs gives an estimate of the total floorspace requirement. It does not provide detailed timetables required to evaluate estate plans. For this reason: Stellae has developed software to use the most reliable available data for the modelling of future space requirements; an assessment of space needs provides useful additional data if it is planned to make significant changes in student enrolments. Timetabling by academic staff is a predictive activity and generally provides the least reliable data for space modelling.

© Stellae 9 A strategic curriculum plan and preferred estate scenario should be prepared prior to the modelling of space requirements. (Hilary Hale, Hale Consulting, , Space utilisation data provides the most reliable data for the modelling of future space requirements. An assessment of space needs provides useful additional data if it is planned to make significant changes in student enrolments. General planning strategies

© Stellae 10 Student attendance by timetable slot The peak period of attendance is Tuesday at am when space utilisation reaches 37%. In just over a quarter of the teaching slots space utilisation is less than half this peak level. The uneven demand for accommodation across the teaching day, the teaching week and the teaching year provides opportunities for improvements in space utilisation. Slot 1Slot 2Slot 3Slot 4Slot 5Slot 6Slot 7Slot 8Total% Monday % Tuesday % Wednesday % Thursday % Friday % Total %14%15%17%9%15%14%11%5%100%

© Stellae 11 Room use by timetable slot On Wednesday at am 253 rooms are occupied or 71% of the total teaching room stock. The periods of relatively low demand for accommodation provides clear opportunities for more efficient timetabling. Slot 1Slot 2Slot 3Slot 4Slot 5Slot 6Slot 7Slot 8Total% Monday % Tuesday % Wednesday % Thursday % Friday % Total %14% 16%10%14% 11%7%100%

© Stellae 12 current uneven distribution of demand for teaching space; adjustment of base data to reflect estimated absences; adjustment of data to reflect a growth or decline in staff or student numbers; incorporation of curriculum changes reflecting strategic planning priorities and new delivery systems; all existing timetabling constraints or any set of new constraints. The following case study demonstrates an adjustment of room sets based on a single timetable slot. Fully modelled timetables can take into account any defined timetabling constraints for all rooms and courses. Factors supporting the modelling process The modelling process takes into account the:

© Stellae 13 Current college estate The coloured rooms identify the current location of classes in different buildings.

© Stellae 14 Sample room timetable prior to building removal

© Stellae 15 Building E has been removed and classes have been redistributed to the retained buildings. Possible estate scenario

© Stellae 16 Sample timetable after building removal

© Stellae 17 Financial savings On the basis of a space charge of £70 per m 2 the required income per used workplace, at 24% space utilisation, is £2043 per year. The equivalent figure at 38% space utilisation is £1289 per year. This is a reduction in required income per used workplace of £754 per year. The calculation does not take into account any income from the sale of property or any reduction in operating costs.

© Stellae 18 Campus removed from estate Any set of rooms based on, for example, room types, departments or buildings, can be used as a basis for modelling.

© Stellae 19 Do space costs impact on course viability? The relationship of space utilisation levels to the required income per used workplace can be readily illustrated. 1.Average unaudited annual space costs in the sample college are estimated to be £70 per square metre. Given an average workplace area of 3.5 square metres the average income per used workplace is £245 at a space utilisation level of 100%. 2.Assuming teaching space forms half the gross internal area of the college, loading total space costs onto revenue generating teaching space raises the cost per workplace to £ As space utilisation falls the income required to meet the cost per used workplace increases. At 40% space utilisation the income required per used workplace is £1,225 per year. At 16% space utilisation this figure has rises to £3,062.

© Stellae 20 Required income per used workplace

© Stellae 21 Space modelling reduces capital and operating costs whilst maintaining the provision of high quality courses. Appropriate facilities used efficiently have a major impact in the financial viability of courses. The effective use of teaching and learning facilities helps to maintain well qualified and experienced course teams working in financially viable colleges. Space modelling, which takes into account established timetabling procedures, is a vital part of the strategic planning process in colleges. Successful space modelling

© Stellae 22 Space modelling: the key to a successful property strategy AoC Estates Regional Meeting, 13th July 2011 Richmond upon Thames College, Twickenham, Middlesex, TW2 7SJ Stellae, Corpus Christi House, 12 West Walk, Leicester, LE1 7NA , George Edwards Consulting, Huntersdale, Knoll Hill, Sneyd Park, Bristol, BS9 1QY, ,