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Modelling and the
Building Information Modelling and the
2 © RICS Research 2015
Report for Royal Institution
School of the Built Environment, University of Technology,
Associate Professor Julie Jupp BA BSc PhD
RICS Research team
Dr. Clare Eriksson FRICS
ceriksson@rics.org
Global Research and Policy Manager
ajohal@rics.org
Global Research & Policy Officer
pchatterjee@rics.org
The views expressed by the authors are not necessarily those of RICS nor any body
connected with RICS. Neither the authors, nor RICS accept any liability arising from
the use of this publication.
Copyright RICS 2015
© RICS Research 2015 3
Building Information Modelling and the Value Dimension
Glossary of Terms .................................................................................................... 6
Executive Summary ............................................................................................... 7
1.0	Introduction and scope of research ...............................................10
1.1	Rationale for the research ...............................................................10
1.2	Research question, aims and objectives.......................................10
1.3	Limitations...........................................................................................11
1.4	Structure of the report......................................................................11
2.0	BIM and the Value Dimension...............................................................12
2.1	Property Life Cycle ............................................................................13
2.2	Data Types and Needs........................................................................14
2.2.1	Property Information Requirements .............................................14
2.3	Education Issues ................................................................................16
2.3.1	BIM within AEC Education (project-level lifecycle).....................16
2.3.2	BIM within Property Education (property-level lifecycle).........17
2.3.3	Developing New Knowledge Competencies in RICS....................17
3.0	Research design and methodology..................................................19
3.1	Stage 1 Workshops ............................................................................19
3.2	Stage 2 Online Questionnaire Survey ............................................21
4.0	Workshop Analysis and Discussion ................................................22
4.1	Workshop 1 Identifying Data Types and Needs............................22
4.2	Workshop 2 Identifying the Challenges ........................................25
4.2.1	Technology-based Challenges.........................................................27
4.2.2	Socio-technical Challenges..............................................................27
4.3	Workshop 2 and 3 Identifying Timelines & Mapping
Data Needs Through Life ..................................................................29
5.0	Survey Data Analysis and Discussion.............................................31
5.1	Part 1 – Respondent Profiles, Current Awareness and
Usage of BIM........................................................................................31
5.2 Part 2 – Experience Working with Information Technologies...33
5.3	Part 3 – Information Frequency and Need of Use........................35
5.4	Part 4 – Challenges & Benefits of BIM............................................40
6.0	Overall conclusions and further research ..................................43
6.1	Data through-life................................................................................43
6.2	Challenges & Benefits of BIM...........................................................43
6.3	Integration of BIM in Property Education......................................44
6.4	Recommendations and further research......................................44
7.0	References.....................................................................................................45
Appendices ................................................................................................................47
Appendix 1 – Property professionals data types and needs....................48
Appendix 2 – Key to symbols used in figures 5 and 6 and Appendix 3......49
Appendix 3 – Managing data through the property lifecycle
(Workshop 2 output). .......................................................................................50
Special Thanks .........................................................................................................52
4 © RICS Research 2015
Table 1	Information Categories Developed for Workshops and Survey......15
Table 2	Descending relative importance of data types for
Stakeholder Groups (highest to lowest)..............................................23
Table 3	Relative Importance of Five Main Information Types
& Stakeholder Groups...............................................................................23
Table 4	Challenges to through-life information management and
corresponding RII......................................................................................25
Table 5	Comparison between Australian and UK participants’ perspectives
regarding the key drivers and challenges when sourcing,
integrating and generating data through-life....................................28
Table 6	Frequency of use of data types by area of practice / discipline.....36
Table 7	Data need score by data type / area of practice................................37
Table 8	Tests of Professional Differences in Information Importance.......39
Figure 1	Property Development and Management processes compared
with Single Facility Project Processes (Source: Authors) ...............13
Figure 2	Selection of sort cards showing data types adapted from
Lutzendorf & Lorenz, 2011 ....................................................................20
Figure 3	Importance of Main Information Types according to
Stakeholders and Activities across CPDM/ Project
Lifecycle Phases........................................................................................24
Figure 4	Relative Importance of Challenges to Through-life
Information Management .......................................................................26
Figure 5	Data needs for a Buildings Surveyor Technical Due
Diligence survey ........................................................................................29
Figure 6	Data needs for Portfolio Management Surveyors through
the lifecycle ................................................................................................30
Figure 7	RICS region respondent work in ............................................................31
Figure 8	Respondents’ area of current practice ...............................................32
Figure 9	Land use types and sectors of property respondents work on ......32
Figure 10	Use of Information Technologies in the workplace ...........................33
Figure 11	Understanding of BIM ..............................................................................34
Figure 12	Experience of BIM .....................................................................................34
Figure 13	Source of BIM training .............................................................................34
Figure 14	Information Type Need versus Frequency ..........................................38
Figure 15	Key Challenges in information management through life ...............41
Figure 16	Key benefits of digital information through life ................................42
© RICS Research 2015 5
4D Fourth Dimension in BIM – the time perspective 5D	Fifth Dimension in BIM – the cost perspective 6 © RICS Research 2015 . engineering. construction AECO Architecture. construction and operation BIM Building Information Modelling BMS	Building Management Systems PDM Property Development and Management O&FM Operations and Facilities Management PLM Product Lifecycle Management RICS Royal Institution of Chartered Surveyors ROI Return on investment VBM Virtual Building Model TM	Transaction Management 3D	Third Dimension in BIM – 3D geometry. engineering. Building Information Modelling and the Value Dimension Glossary of Terms AEC Architecture.
to property professionals. the opinions of a panel of experts through successive This report outlines the findings from a research project rounds of questionnaires and interviews. Two groups of diverse and experienced survey was conducted. and a global online further comment. by providing better characteristics. in that it sought to investigate the potential were originally developed by the architecture. From these. However. quality and accessibility. needs. currently. the associated challenges of through-life information management. it was necessary to ascertain and gain a deeper design and construction data. c)	how information requirements compare with those of AEC project level processes and the extent to which 1. skills and competency of BIM within the professional practice. data types and needs property professionals were invited to share their were identified and then mapped across the property knowledge and experiences in real time. d)	to explore the potential to expand education about BIM 2. could BIM downstream data requirements relative to data help increase property income yields. The scope Following on from this. over the course of three workshops. so too does the opportunity type of data required. For example. Following analysis of the data generated by the increasing capital growth. The survey allowed us to. this project aimed. and. such as. four parts to ascertain members’ knowledge and understanding and discover how best BIM data can be b)	to evaluate the importance or need for these data types used most effectively within the property professions.org/research Executive Summary Building Information Modelling (BIM) offers rich opportunities for RICS property professionals to use Methods information throughout the property lifecycle. Workshops were carried out in Sydney and anonymously and then the panel was asked to provide London with property professionals. This stage of the research adopted a a)	to identify the specific types of data that various quantitative approach to validate the earlier qualitative property professionals use throughout the property data collected in the workshops. To do and construction (AEC) sector to assist in managing this. quality data on: minimising risk on investment returns.	Map the property information/data that members use this data is generated in AEC focused BIM deliverables. potential benefits of BIM for property professionals have The research had the characteristics of qualitative been largely untapped to-date. The results investigating the potential for RICS property professionals to from each round were collated and fed back to the panel utilise BIM data.	Reveal what opportunities exist within BIM to enhance knowledge. engineering for property professionals to use BIM data. rics. BIM tools and processes research. an online survey of RICS members globally deprecation? As a scoping study. BIM models. or linked to. and. in Sydney and lifecycle. Alignment with BIM data was undertaken. Research question and aims Workshop 2 Objective: Identify upstream and downstream data requirements related to professional The research question investigated was: what is the role property service tasks. was undertaken. membership of the property disciplines. As these technologies and understanding of their information / data needs and the processes mature and evolve. which seeks to aggregate contained within. © RICS Research 2015 7 . The first stage of the research for other professional groups to utilise various types of data employed a Delphi approach.	Understand the value and significance of those data into property education. London. the This research adopted a two-stage research design. and managing and optimising workshops. and. of the value dimension in BIM? This question is examined relative to the activities and professional services performed Workshop 3 Objective: Analyse upstream and by RICS property professionals. The survey comprised lifecycle. education for existing and future members were reviewed Workshop 1 Objectives: Identify the types of data that along with the ways in which BIM can be integrated into each of the professional groups use in daily activities property education on RICS accredited courses. e)	to identify steps that RICS can take to increase 3. issues around training and of each workshop was as follows.
19)	Environmental Quality 5)	There are several steps identified that RICS can take 20)	Micro-Location to increase knowledge. in their professional practice. whereas others. Property management students and subjects will initially benefit most from increased 15)	Design Process Quality awareness and knowledge of BIM and Building 16)	Site Features Management Systems (BMS) technology. respect of the five research objectives this research finds. had a need for a were identified in the workshops. this may change over time. The number 7)	Land Features of existing buildings with BIM. Property professionals more limited range of data types at specific points in the undertake a very diverse range of professional tasks lifecycle. as a proportion of the 8)	FM Quality total stock is small. Valuation 17)	Planning Quality subjects can also start the process of awareness raising though most of their data needs currently lie 18)	Macro-Location outside of BIM. 2)	Health & User Comfort we found the AEC projects focus on design and construction phases. though this is being extended 3)	Tenant & occupier Situation into the operational phase and this falls within the 4)	Functional Quality field of Facilities Management. Different data types were Value Dimension. such property professionals through the property lifecycle as Building Surveyors (see figure 5). through the building lifecycle and participants use a total of 24 data types listed below (see table 2 also). 10)	Technical Quality 4)	It was found that there is great potential to expand 11)	National Market education about BIM into property education at 12)	Design/Aesthetic Quality undergraduate and post-graduate level across all RICS regions. 23)	Environmental Context 24)	Urban Design Quality 8 © RICS Research 2015 . In required at different stages of the property lifecycle. Property professionals 5)	Payments In who require data relating to building performance and maintenance costs will find BIM data useful. such as Portfolio Management Surveyors (see figure 6) have repeated data needs over 1)	The specific data types that are used by a number of longer periods of the lifecycle. Some professionals. This potential will increase over time as 13)	Payments Out the rate of uptake of BIM technology increases in the 14)	Market & Letting Vacancy Situation built environment. however BIM enabled stock is more highly represented in higher quality new 9)	Surrounding Characteristics commercial property. 3)	When information requirements are compared with those of AEC project level processes and the extent 1)	Building Description this data is generated in AEC focused BIM deliverables. Building Information Modelling and the Value Dimension Key findings 2)	When different property professionals ranked the importance or need for these data types for property The key findings are that there is potential for BIM in the different profiles emerged. These measures are outlined in the 22)	Operational Quality recommendations below. that is for the property profession. where 6)	Construction Quality it is available. skills and competency of BIM 21)	Cultural/Image Value within the existing membership base of the property disciplines.
resources for members to raise awareness and knowledge There is great potential to expand the current use of BIM in respect of BIM and how property professionals could data for property professionals. Develop RICS training courses for existing members of the property disciplines in BIM 1. After all BIM is about 2. In particular details on data source. to expand the range of data linked to BIM for use by property professionals. Develop a set of CPD events to raise awareness among property professionals recommendations of BIM This research has shown that there is a place for BIM As a priority RICS should develop some online education and the value dimension and that this will grow over time. format. for members in the construction sector. RICS BIM & Property Education Task Force in databases outside of BIM that could be easily made compatible to BIM. There is also potential use data within the models. It is acknowledged that RICS have established the first BIM certification BIM Managers. and (b) data needs and types currently in a digital format but found 5. 4. into RICS APC for property professionals The RICS APC group should develop appropriate property discipline BIM competencies with the APC structure so that property professionals can obtain recognition for knowledge. Introduce BIM professional competency collaboration between various stakeholders to share information for optimum outcomes.org/research Conclusions and 3. Map data needs and types across all Concurrent with the roll out of CPD events for members RICS disciplines and the development of online education resources. ‘the value dimension’. RICS should form an Education Task Force could be digitised and incorporated due to the extent to champion the roll out of BIM across RICS accredited of potential usage within the property profession. other professional bodies are also establishing education quality (with respect to reliability and accuracy) are needed. and benefits in collaboration. © RICS Research 2015 9 . could be used by property professionals. RICS One of the key priorities is to undertake a comprehensive should develop a series of training courses for existing mapping of data needs and types across all RICS members globally to realise the potential of using BIM data disciplines to identify (a) what is currently within BIM that in their professional practices. and the requisite awareness. rics. skill and capability with the application of this knowledge in their professional practice. property courses globally to ensure new members have The full list should be categorised and prioritised. task forces and there may be some opportunities for. Some be initiated. There may be some aspects that may be transferable to a property focussed certification. knowledge and skill with respect where necessary negotiations with third parties should to BIM and property or. Additionally this review would identify With regards to the integration of BIM into property those data needs and types that are outside of BIM that education.
multi-residential. Each iteration of BIM is On this basis. It is written in a style to avoid the overuse of jargon membership of the property disciplines. BIM can be viewed 1. 3D models allow data to be shared. skills and competency of BIM within the jargon. and professionals use throughout the property lifecycle. 2008). these studies have generated in AEC focused BIM deliverables. by providing better quality data on: minimising risk required during the assessment of the risk. Building Information Modelling and the Value Dimension 1. the research question posed is: what is referred to as a ‘D’.2 Research question. scheduling) 5D (cost) data. This research is predicated on the premise that various sectors of property encompasses the sourcing. Commercial property professionals Gerber et al. growth and services performed by RICS property professionals. engineering. the technology and its associated knowledge. To date. Sourcing data from BIM technologies and that architecture. or workflow. and valuers has been largely efficient through-life information management (Becerik- overlooked to date. increasing capital growth. Whilst value has been 2)	to evaluate the importance or need for these data types addressed partly in the research literature relative to for property professionals. it is ‘the next major evolution buildings. this research has been typically at the level of the AEC project and has sought 3)	how information requirements compare with those of to understand value relative to participating project AEC project level processes and the extent this data is stakeholder organisations. namely risk. could BIM help increase property income of BIM is therefore defined by the information or data yields. This research explores BIM is defined as ‘a modelling technology and associated the potential to expand BIM beyond the AECO disciplines set of processes to produce. and and depreciation status of a property and provides managing and optimising deprecation? As a scoping a description of its performance through life. stakeholders can serve property professionals and add value to their professional services. environment data sources for more effective and property managers. investors. This study. The use of semantic web numerous client-side benefits such as quicker approvals technologies for operations and facilities management due to clearer design intent. Over time the 3D model has developed to incorporate 4D (time. largely neglected the broader processes of client-side 4)	to explore the potential to expand education about BIM stakeholders and the activities that lie upstream and into property education and. 2014). ‘through life’. communicate and analyse and project stages. a dimension. and education disciplines within RICS. some of the same information management capabilities organisation and reuse of a variety of built environment derived from a BIM-enabled approach that benefit AECO data and data sources. As such. depreciation (Millington. the broader scope for (O&FM) offers a means of structuring different built client-side stakeholders such as property developers. Effective information management across 2015). 10 © RICS Research 2015 .1 Rationale for the research Today. in connecting information. 2011). as well as beyond current approaches building models’ (Eastman et al. who are 5)	to identify steps that RICS can take to increase less familiar with BIM. Whilst advocates for BIM claim buildings (McGraw Hill 2014). where intelligent to project and organisational notions of the value of BIM. The value dimension For example. health. downstream of design and construction. BIM’s return on investment (ROI). For those who are unfamiliar with require good quality through-life information about the term ‘semantic web’. this project aimed. construction and operation building management systems (BMS) is becoming (AECO) professionals will work in the future (Macdonald. growth on investment returns. hence the value dimension. aims and as a series of interlinked databases (typically represented graphically using models) that can be shared and updated objectives for design and construction tasks. recommissioning / disposal. This report is aimed primarily at property professionals. operations and maintenance. to make it accessible to this new audience within the RICS professional membership. the surrounding environment and the market. more common in the delivery and operational stages 2012) and is integral to real-time coordination across the of commercial.0 Introduction and scope of research 1. information technology is readily employed across different lifecycle stages of building and infrastructure Building Information Modelling (BIM) is shaping the way facilities. the role of the value dimension in BIM? This question Value can be characterised by three principal is examined relative to the activities and professional characteristics of property. 1)	to identify the specific data types various property project execution. lifecycle perspective includes its original commissioning. It enables data to be linked Professional property activities require robust and reliable from a source to any other source and to be understood data from many sources to deliver a complete view of by computers so that they can perform increasingly performance and value during the building lifecycle or sophisticated tasks on our behalf’ (Cambridge Semantics.
the researchers encountered some difficulties in obtaining equal representation across those dealing with commercial. Whilst the research study and methodology sought representation across these different property professionals. 1. The research design and methods are outlined in section three. the data analysis and findings of the online survey are presented.3 Limitations The research is limited to the investigation of these considerations from a property development. This perspective encompasses a large range of professional property service tasks surrounding property development. and education properties. through an examination of the property lifecycle and data types and needs. where commercial property interests were more widely represented. This research limitation surrounding stakeholder representation was encountered in the workshops.org/research 1. property transactions and real estate. multi-residential. growth and depreciation variables as well as outlining areas for further research. retail. The report closes with a discussion of the main findings and BIM’s ability to support client-side decision-making relative to risk. Section four reports on the data analysis and findings of focus groups held in Sydney and London. property investment. property and facilities management. It reviews the educational aspect of BIM in respect of the project and property lifecycles and discusses the integration of BIM into property education. © RICS Research 2015 11 . and building surveying. management and valuation perspective. In section five.4 Structure of the report Section two analyses the literature around BIM and the value dimension. property valuation. health. property and portfolio management. rics.
long-lived buildings mean that that 50% of the industry was using BIM.K. In the US in 2009. that 49% of contractors. in sustainable commercial property in the UK. buildings and estates. Germany and U. representing it is important for property professionals to have robust a 75% increase in a two year period. 2015). have been and asset managers. industry surveys undertaken in Australia. architects and engineers reported BIM usage. titled. et al. 2014). 2009. investment and valuation surveyors.K. these studies most often centre on the using BIM. Property professionals considered in Europe’ (McGraw-Hill 2010).. Research studies on the value of BIM relative to client-side and wider El-Gohary (2010) argued that potentially. sustainability rating levels say. A McGraw-Hill and reliable through-life information about a building’s Construction report. there is no clear In the past five years more than 250 articles have and consistent demand for adoption by clients. Building Information Modelling and the Value Dimension 2. Europe. However it is not known that BIM uptake has in recent years been accelerating and whether the information specified in AEC BIM models is likely to accelerate over the next few years (McGraw Hill. which focuses on many years before a majority of stock has BIM. whilst the value of BIM has North America. US and and consider only single facility project processes Australia. Most studies include client when assessing sustainability in a property development perspectives on the perceived benefits. project and/or an AEC business level outcomes. Currently investigated the impacts of BIM relative to project BIM adoption is largely in the larger AEC companies and performance and its impact on business value (e. Carroll within larger construction projects. using BIM longer. where the costs and the potential of new technological. under BREEAM or Green the UK and US (McGraw Hill 2014) have shown that most Star. currently meets the needs of the property professionals. advised of the social. different options can be assessed in respect of likely For example. 2009) 12 © RICS Research 2015 .g. where in a previous report McGraw-Hill found project lifecycle and define value relative to AECO interests. but overall BIM adoption is greater in building surveyors. Rowlinson et al. However they are total stock of buildings annually (Wilkinson. Studies by Fuerst and McAllister (2012) and Newell clients perceive a positive ROI when BIM is adopted. Using BIM data and simulations. Becerik-Gerber & Kensek 2010. shows construction here include property and facilities managers. development professionals in France. (2011) have indicated that there is a value premium However. process and organisational change. Furthermore given that typically only 1-2% is added to the 2010. BIM can add value property interests are lacking. costs and risks of feasibility study. However. Sebastian & van Berlo 2010).. (McGraw-Hill 2009). or at least consider the US and Australian/New Zealand AEC industries show the impact on property value. However.0 BIM and the Value Dimension The lifecycles of complex. it was reported (Young et al. ‘The Business Value of BIM performance and value. clients can be neglecting the broader property perspective. it will be limited in terms of their definition of value. The study shows that a little over a third been addressed in the research literature relative to its return (36%) of Western European construction professionals are on investment (ROI). environmental and economic costs and benefits of various options allowing them to make A number of studies undertaken across the U. these studies are limited to the project lifecycle. more informed decisions that optimise.
1)	Conception. a BIM model is apparent. The established role for BIM in managing information within AEC professions can Only the client is involved in the entire process and be extended to property professionals. where 5)	Construction (CO). but relevant property data. When taking the wider property development during the lifecycle is information needed and. Property Development and Management processes compared with Single Facility Figure 1 Project Processes Single Facility Project Lifecycle Phases (PD) (SD) (DD) (CD&CO) (OM) Commercial Property Development Conception Planning & Preparation Execution Operation Recommissioning & Management (C) Feasibility (P) (E) Maintenance (R) Lifecycle Phases (SD) (OM) Source: Authors © RICS Research 2015 13 .org/research 2. at what periods required. and information must be able to be accessed and used by 6)	Operation/Maintenance (OM). be managed over and complexities surrounding the different consumers and generators of information. rics. This property perspective of lifecycle step was to identify and then make an assessment of includes not only the AEC phases described above. what is and management activities that surround the AEC project the frequency of which such information is required? In into consideration. is defined as: The recent increase in digital information generated 1)	Pre-design (PD) in which the decision maker from the during AEC projects and throughout a property’s client side evaluates project feasibility. property. 5)	Operation and Maintenance (O&M) and 6)	Recommissioning (see figure 1). multiple AEC projects and the application of BIM in this However there is a lack of literature reporting studies wider scope of property services is not well understood.1 Property life cycle When the two different levels of lifecycle are compared. operation and maintenance creates potential for a new approach to information management within 2)	Schematic Design (SD). numerous property professionals. 4)	Execution. Questions arise other professionals join and depart from the project as such as. at the level of an AEC project. a more extensive lifecycle process seeking to provide answers to these questions the first becomes evident. the requirements of information management is more complex Property development and management activities and the opportunities to maintain and leverage the data encompass more than the combination of single or contained within. 2)	Planning and Feasibility. 3)	Preparation. also activities that encompass property such as. the general surrounding the business case for deploying BIM – either lifecycle process of the design and construction project on single facility projects or relative to property portfolios. The development of new approaches must 3)	Detailed Design (DD). consider the lengthy time periods that information must 4)	Construction Documentation (CD). or linked to. what are the information needs. of well-defined property based or client-side strategy Typically.
consisting of five main types of property. These studies were approach to benefit AECO stakeholders can be extended examined to ascertain whether BIM might offer for the to serve property professionals and thereby add value to broader scope of property development and management their services. and variety of professional AECO and property activities valuers. and also re-worded into property valuation and related professions. The authors developed a method for identifying and developed an information requirements framework and determining the importance of information types. property activities and were re-structured according to Lützendorf and Lorenz (2011) identified a comprehensive information and data formats that are readily available list of descriptors to represent information types used by throughout the property lifecycle. Each information type was identified 2. consultants reports. 25 sub-types and 90 individual need for the information. duration of reacquisition. building surveyors that span the building lifecycle. building inspections. A list of 22 language more familiar to property professionals. project. extensive. The five main categories of information include of reacquisition. the main categories and generated the information or who may consume it). used to access property. and the capabilities that are being derived from a BIM-enabled Green Property Alliance (GPA 2010). building. in other words. and. it is necessary to The researchers analysed each information requirement evaluate the relevance and importance of each data relative to the scope and processes identified in Figure 1 type. The data collected and in property transactions.2. a combinations and at different lifecycle stages. the value dimension. workshop and survey findings.2 Data Types & Needs These information types are shown in the second column of Table 1. and correspond to the type and portfolio managers. completeness and accuracy of this information of workshop discussions. 5)	Process Qualities. Their sources management systems (BMS) is becoming more common included The European Group of Valuers Associations in the delivery and operational stages of commercial (TEGoVA 2003). With the volume of data generated. property are disparate. Based on outcomes and is often unknown and sometimes unchecked (by those who learning from the workshops. the effort attributes. The classification developed in Table 1 was The data sources that are required to provide a description compiled on the basis of information traditionally sourced. development and management information. Distinct data types may coexist in isolation and These attributes and characteristics formed the basis the quality. 3)	Property Data describing Economic information. 14 © RICS Research 2015 . making sub-categories were modified to cover a wider range of information management in property disciplines complex. property investment surveyors. Together in various databases. This data can be sourced encompasses market. and documentation of the is reused by a variety of property professionals to inform design and planning process typically created during the performance and valuation tasks. the frequency of use. industry operations and maintenance data. environmental or social indicator of value. descriptors relevant to property development and Modifications of this method were used to analyse the management of. information traditionally gathered and used for property Sourcing data from BIM technologies and building valuation and risk assessment purposes. activities. financial. This research is based of sustainability assessment schemes such as the United on the premise that the same information management Nations Environment Programme (UNEP 2009). property and facility manager. and finally.1 Property Information Requirements based on its mapping with property development and management activities and its classification as either an Currently a range of separate and distinct sources are economic. property. design and planning stage for verification of conformity with regulations. from building documentation. 2)	Property Data describing Plot of Land. and assessment of a property’s performance and value organised and (re)used by property developers. The final descriptor categories shown in the first column of Table categories developed for the survey are shown in the third 1. development and The first step was to prioritise information based on the management descriptors. facility managers. RICS (2009) as well as a cross-section buildings (McGraw Hill 2014). 1)	Market and Location Data. this data variety of building reports. identified by Lützendorf and Lorenz (2011) according to column of Table 1. Building Information Modelling and the Value Dimension 2. 4)	Building Information.
Real Estate Data (Added to incorporate – User comfort & Post-occupancy Descriptors data typically collected that describes evaluation information 16.	 Mechanisms / Instruments 3. Process Information Types. Alteration and Repair.	Building – Brand Value Descriptors – Property Insurance Attributes – Property Insurance Rate Variables 20. 21. Regional and Neighbourhood – Micro Location Data Market Data – Listings. including: 5. Recent Sales.	Operations and Maintenance Data.	Economic Quality – Payments Out – Payments Out.	 1.	Process Quality – Management 8. including: – Property Lot Attributes 5. – Building Documentation and Images Descriptors – Environmental design information.	Location Information Types.	 L ocation – Micro Location Descriptors – Macro Location Data – Micro Location Data 4.	Building – Urban Quality Descriptors intangible value descriptors).	 Plot of land – characteristics and 2.	Project Data. – National Market Data – National Market Data – Macro Location Data – S tate.	Process Quality – Construction – Design process information – Design Management Data Descriptors – Construction process information – Construction Process and – Operations and Facilities – Management Data Management information 22. including: Descriptors – Planning process information – Planning and Feasibility Data. – Maintenance. – Asset Monitoring and Tracking. and Auctions Data – Property Transfers Data – Property Marketing Statistics 2.	Property Information Types. 14.	Building Information Types. Economic and Financial Data.	Building – Basic Building Quality 4.	Building Data.	Building – User Health / Comfort – Image and reputation value Quality Descriptors – Property Imagery information 18. – Payments Out.	Property Information Types. including:: – Payments In.	Process Quality – Planning 5.	Building – Cultural Value Descriptors – Property Activity 19. – Utilities Descriptors – Surrounding Contextual Data) – Environmental Attributes – Surrounding Building Context – Property Development Details 6. 3. 7.	Property Location Data.org/research Table 1 Information Categories Developed for Workshops and Survey Information types identified for Categories of data defined for Property descriptor types workshops (Adapted from RICS survey (Based on Workshop (Lutzendorf & Lorenz 2011) Lutzendorf & Lorenz 2011) Outcomes & Learning) L ocation – National Market Descriptors 1.	Economic Quality – Payments In Descriptors – Payments In.	Building – Environmental Quality – Design/ Aesthetics information Descriptors – Contribution to urban quality 15.	Building – Design / Aesthetics Quality 6.	Building – Functional Quality – Functional information. including: 1. Descriptors including. including: Descriptors – Building design information – Spatial attributes 12.	Economic Quality / Cash Flow – Tenancy/Occupier Descriptors 11. – Vacancy / Letting and Descriptors – Vacancy/Letting and – Tenancy Occupier Data 9. including: 7. 8. – Space Management © RICS Research 2015 15 .	 Plot of Land – Surrounding Context – Characteristics and Configuration.	Financial Data including.	 L ocation – Macro Location Descriptors 2. including: – Cultural value information – Property Value Attributes 17. describing 3	Property Site Data including.	Market Data including.	Building – Technical Quality – Technical and building systems – 3D model objects (elements) and Descriptors information properties (parameters) 13.	Economic Quality – Vacancy / – Tenancy/Occupier Information Letting Descriptors 10. configuration descriptors Plot of Land. describing 4. rics.
digital product data can be exploited for downstream Macdonald. 6. construction and operational information can be utilised 3)	Digital methodologies to improve product and in Facility Management subjects. universities. the simulation professional development (CPD) and short courses. design. firstly.	BIM and preconstruction – planning a BIM project. With the property lifecycle extending and virtual reality techniques can be used in the visualisation far beyond the project lifecycle. 2012).	Cost and lifecycle analysis – target cost modelling.	BIM and design management – design coordination. Building Information Modelling and the Value Dimension 2. process quality. Secondly it considers. utilising virtual building Broadly.g. that translate into productivity gains. departments or schools have Quantity Surveying. 2)	Digital methodologies for time and costs savings simulated construction timelines.	BIM and updates – pre-bid. management than the (AEC-based) project lifecycle. property maintenance and property management purposes. information exchange. Project Management and Property undergraduate trade coordination. including – the incorporation of valuable property related data that is used through the property lifecycle for property investment. models as a visual tool for learning. value-added and re-purposed according generated to meet AEC deliverables for property education to subject content and requirements. 2012). moving AEC students from abstract (VBMs) as an integrated source of information for teaching concepts to applied knowledge.	Production quality – documentation output is flexible 4)	Sustainability for the built environment. there is the potential for 4. 1. component relationships.	BIM and construction – scheduling. enabling students to quickly and more easily analyse building solutions and propose 5)	Greater transparency and accountability in alternate construction technologies and methods. clash detection updates. and and exploits automation. has the potential to increase student This section examines some key issues around understanding. Construction and 3. BIM provides an appropriate and potentially models within AEC and property programmes provides a beneficial suite of technologies for the development of vehicle to introduce principles of teamwork. not only of design and construction the education of property students and existing processes. inter-disciplinarity. of integrated planning. within the AEC disciplines is provided and the potential Macdonald & Granroth 2013). the property lifecycle forces of typical and be-spoke AEC methods. decision-making 8. but also (perhaps most importantly) of how to property professionals with respect to BIM knowledge collaborate and share information with other professionals competencies.g. information transfer standards. An overview of the integration of BIM across the property lifecycle (e. 2012. budget management. inter-operability. of particular the needs of existing practitioners and the role of continuing import to property focused subjects. clash The adoption of BIM technologies and processes offers detection and reporting.3 Education Issues Teaching with virtual building models. This section rigorously. 16 © RICS Research 2015 . 7. integration.g. finally products and process via simulation and. collaboration new teaching and learning approaches that can enable and continuity across multiple lifecycle stages. constructability. Geometric modelling Property education. sharing between disciplines. students can engage with (automated) the AEC disciplines that BIM offers include increases assembly and manufacturing problems. feasibility and implementation processes. the next section explores design and construction details. virtual building models can allow students to a client’s perspective. requirements. model 1)	More effective workflows for improved information updates. level lifecycle) 2. model coordination planning. Macdonald & Mills. Other educational purposes. The benefits to students studying processes. Macdonald. a potential roadmap for advantages are the engagement and exploration of building the adoption of BIM for teaching and learning. In particular where faculties.	Customer focus – often the customer or client is A key benefit of BIM in education is the virtual building left out of the equation in the teaching environment. digital 2. and. in knowledge and understandings of: 5.1 BIM within AEC Education (project. and related BIM technologies. estimate updates. simulations performed and design performance considers. and post-graduate provision. Given the benefits highlighted by researchers in AEC provide AEC subjects with a means of visually simulating education (e. Virtual building models. Buildings can be analysed to leverage off this experience is discussed.3. students are able to gain environment.	BIM and Assembly and Manufacture – because cross-disciplinary and inter-disciplinary projects (e. From this perspective. understand design and construction technology with ease and speed. as visual teaching aids. BIM models or virtual building models benchmarked. allowing students to a broader more enterprise level view of BIM for information access information in the classroom (Jupp and Awad 2012). the potential and issues for the integration of BIM within construction materials and activities. Model-based building data and learning and the re-usability of building information can be shared. model coordination and many benefits to educational programmes offered by management. defining responsibility and ownership. Due to its geometrical As virtual building models can be understood through representation of the parts of a building in an integrated data accurate visualisation.
sales and marketing. and many 2011). competencies. and education. Over time it is governance and information management (Ford et al. some property professionals. introduction of Product Lifecycle Management (PLM) data. people from Product Lifecycle Management in engineering systems purchasing. Hewitt’s study (2009) showed that the shift of perspective and object-based visualisation activities. The changes to targeted areas of property education and professional are predicated on the development of new technical skills. associated with through-life requirements and activities. is to set up introductory BIM subjects to provide and cultural change. Competencies in RICS organisation of teams around deliverables and timelines. assessments and sectors. order management. These challenges stem from various new accreditation relative to PLM and manufacturing. Issues surrounding RICS can learn from this by adopting a proactive lead in changes to professional practice and cultural change the implementation of BIM in property education. protocols and jargon. some inventory management (Hewitt.2 BIM within Property Education The experiences of the BIM and Product Lifecycle (property-level lifecycle) Management communities can be used to understand the practice-based issues. To some degree. share similarities such as 2. a broader lifecycle 2014). challenges and opportunities prompted by the would be a requirement for close integration of products. Moreover property professionals initial understanding of the concepts of BIM. With the increasing uptake of BIM. where possible. between professionals. leading to differences in approach to data background) and project engineers. for example. in the automotive and aerospace industries during the and equipment from across the supply chain. possible new responsibilities and roles will emerge within 2013). which development of CPD courses that focus on the changes could. and relationships was required.3. but a whole organisation. such as valuation. PLM 1990s. rics. work methods. roles/responsibilities. © RICS Research 2015 17 . 2014). 2009). a BIM-enabled approach to information management which are underpinned by vastly different BIM/ Product through the life of property assets. which may be experienced in due course by approach to information management is desirable. able to perform new professional services also for property professionals. as described in the framework requires greater levels of collaboration and communication proposed by Macdonald (2012). project management. Product Lifecycle AEC professionals are experiencing significant changes Management implementation requirements dictate that to their professional working practices (Jupp & Nepal. applications. and activities that change the nature of professional roles and RICS should consider starting this process with respect responsibilities at practice and project level.3 Developing New Knowledge the approach to data sharing. At a those subjects. The construction industry is in the One approach to deliver education that could be adopted early phases of BIM adoption and stands to benefit most in undergraduate and fast track post-graduate conversion in learning from PLM experiences of professional practice courses.org/research 2. this would be the case technologies. property funds investment would lifecycle of a product and is not the responsibility of see BIM-enabled teaching and learning embedded within one unit or department. people. Hewitt affect the practical deployment of BIM and Product (2009) found educational establishments and professional Lifecycle Management concepts within their respective bodies needed to align curriculums. competencies. knowledge and responsibilities are determined at the outset (Stark. possibly be co-taught with AEC to roles and responsibilities. Thereafter the specialised application of BIM in the various property knowledge fields.3. 2014) and may be identified a number of new responsibilities within existing applicable to the expansion of BIM into property. BIM reflects many of the Similarly across some property service tasks there changes. RICS members need to be versatile. cross- new knowledge fields and stakeholder relationships (Jupp functional professionals who are up-to-date with emerging & Nepal. including within RICS can benefit from this experience also in the its processes. The key differences lie in the information system some of the RICS property professions as a result of and tools utilised by their different application domains. 2009). Likewise responsibilities in relation to partnering characteristics reported on the adoption and deployment companies and their role in the process must be carefully of BIM and Product Lifecycle Management information considered (Hewitt. This approach to information management requires the implementation team works RICS may be able to learn from the integration of closely with business teams. grounds for sharing lessons learned. traditional roles in the Product Lifecycle Management BIM and Product Lifecycle Management differ mostly literature as well as how these roles are shared between around the capacity for technical and organisational administration executives (typically with an engineering integration. Lifecycle Management platform specifications and data requirements. students. changes to professional practices relating to roles and responsibilities and it is vital that the roles to new activities. technologies. in manufacturing based industries. The challenges from product delivery to a lifecycle approach represented that follow from these shared characteristics provide fertile a knowledge gap for many manufacturing companies. Jupp and Nepal (2014) systems are shared (Jupp & Nepal. Further opportunities lie in multi and general level Product Lifecycle Management deployment cross-disciplinary subjects. processes. Product Lifecycle Management focuses on the whole property management. BIM and PLM. During the implementation of Product Lifecycle deployment in supply chains raises significant changes Management.
knowledge and skills in BIM. academia responded to the needs of the changing workforce from one that was task oriented to one that is competency based through the development of innovative curricula. 18 © RICS Research 2015 . RICS should consider a series of BIM & the Value Dimension training programmes that will provide members with an understanding of BIM technology and applications in respect of their professional practice and services. and appropriate level. 2015) route to membership and some aspects may be transferable to the property disciplines. existing members are equipped with the necessary. For existing members. RICS could constitute an Education Task Force to champion the rollout of a global initiative to develop a BIM literate property profession. RICS needs to ensure new entrants to the property profession. Building Information Modelling and the Value Dimension Hutchins (2004) noted that US manufacturing professionals were asked to perform tasks not traditionally included in their professional scope of works and that they lacked the capability to undertake the tasks successfully. as well as. 2010). such as Purdue University’s initiative to develop a PLM-literate workforce (Fillman et al. RICS has taken the lead in developing the BIM Managers Certification (RICS. 2010) and RICS could consider a similar approach in respect of BIM and property. Likewise. The Society of Manufacturing Engineers researched “competency gaps” and developed a ‘Manufacturing Education Plan’ (Fillman et al.
1 Stage 1 Workshops Workshop one objectives were to: a)	Identify the types of data that each of the professional To identify the main information types used by the different groups use in their daily activities. The first exercise (1A) comprised a clustered were invited to participate. In London six participants attended the workshops facilitated by a Chartered Building Surveyor and academic. Design and Construction.org/research 3. and. ‘nice to know’ or ‘irrelevant’ to their work tasks (see and Transactions Management. property stakeholders the research design was based on the Delphi method (Dalkey and Helmer 1963). data requirements. 1975). rics. and finally a full workshop discussion. Results analysis (Silverman. with each session including a presentation by the employed a series of workshops with industry experts facilitators to frame and introduce the exercises. followed followed by feedback reporting and surveys. were reported to participants via email for feedback and To address the objectives. 2013). The research design groups. interdisciplinary and technology based issues Workshop one was convened over a half-day period. Management and Valuation. In Sydney 13 participants attended the workshop and researchers. on complex. The value b)	The associated challenges of through-life information of Delphi is demonstrated in a wide range of applications management. facilitated. The participants were figure 2). The information requirements were presented on 24 The company types of invited participants included: cards and participants asked to sort them on the basis Development and Asset Management. Sydney (UTS). The aim was to establish the main information industry experts who were content matter experts on their types and identify correlations between stakeholder respective fields and regularly engaged in the sourcing.0 Research Design and methodology 3. Practitioners had a minimum list of 24 relevant information requirements elicited from five years post qualification experience as the findings the literature as being important to property professions. group break-out research used an inductive approach to qualitative data sessions. using a method for structuring group communication The workshop was divided into two sessions with four processes (Linstone and Turoff. organisation and reuse of disparate data sources during their work tasks. © RICS Research 2015 19 . representing the property and construction disciplines from the University of Technology. Property of the information types they perceived as ‘essential’. As such the by individual brainstorming tasks. The same participants attended each of the three workshops to ensure consistency. property and AEC professionals this data was then used as the basis for the subsequent working for different companies in Australia and the UK workshops. should reflect business practice as closely as possible.
Building Information Modelling and the Value Dimension Figure 2 Selection of sort cards showing data types adapted from Lutzendorf & Lorenz. 2011 20 © RICS Research 2015 .
whereas others had data needs at a single point BIM enabled data according to respondents. a by participants were used as the basis for identifying questionnaire was designed to allow the researchers challenges to the sourcing. Finally part only during the life cycle. This part of the research cards so as to pinpoint individually problems in relation embodied the characteristics of quantitative research to a BIM-enabled approach to information management. © RICS Research 2015 21 .org/research Workshop two had the objective to: 3. Participants needs identified by the participants matched those of were asked to identify challenges on the basis of their the profession more broadly. accessibility. and asked respondents about quality. As a result of the second An online survey was designed adopting best practice workshop a timeline for managing data through the in survey design (Silverman. (Silverman. cards classified as ‘essential’ and ‘nice to know’ property professionals in the Stage 1 workshops. knowledge and usage of BIM in their a)	Analyse upstream and downstream data requirements professional services. typical examples). their level The objective of workshop three was to: of expertise. The survey was designed for completion within a 10-minute period. rics. the stage of the property lifecycle during which their expertise was required. Part two focussed on the value relative to data characteristics. 2013) whereby a statistical analysis of data before then discussing their findings within each group. reveals the characteristics and needs of a larger group Participants were then asked to rank challenges deemed of practitioners. and remained open for a four-week period. their area of expertise. of data contained in BIM. respondents were asked to rank the significance of different challenges be they technical challenges or data quality and fidelity challenges and so on. The survey was distributed through RICS channels and reminder emails were sent weekly to encourage as good a response rate as possible. source. The next section of the survey In this workshop. 2013) comprising four parts property lifecycle was produced for each participant to and launched in April 2015. Part one asked respondents explore in the final workshop (see Appendix 2 and 3 for about their area of practice across the RICS regions. Having identified the key challenges from Workshops 2 and 3 in respect of data. participants reviewed their timeline chart asked questions about non BIM enabled data and for managing data through the property lifecycle and respondents data needs in order to prioritise the data commented on any changes that were required. most to least significant. Part three focussed on the status of various points in the property lifecycle for a task and had information technologies in professional property tasks complex data needs (see figure 5 and 6 and Appendices and which land use types had the most requirements for 2 and 3). organisation and reusing of to determine whether the workshop data types and information throughout the building lifecycle.2 Stage 2 Online Questionnaire a)	Identify upstream and downstream data requirements related to professional property service tasks Survey The same respondents participated in the second Having ascertained the data types and data needs of exercise. In some type property professionals would find most useful to cases property practitioners required identical data at access in a BIM. the importance of different types of BIM data to their professional services. such as format. four examined the value of data sources and potential BIM enabled information.
Functional Quality (RII 0. All data captured from group selected Site Features. and then and involvement throughout CPDM and Project timelines. where each stakeholder group’s activities occurred within The highest ranked attributes that fall within the top 5 the CPDM and Project lifecycles as shown in Figure 3.0 Workshop Data Analysis and Discussion 4.85). 4. and Transaction Managers and are discussed below. i.e. with six RII = W of the nine information sub-types being important across A  N all stakeholder groups. calculated across four groups: Development and Asset Managers. 1. Technical Quality. and N = number of respondents. The All Response column (in Table 2) shows the five most important information types were. confirm agreement between workshop participants on the Functional Quality and Micro-Location as being of significance of the information types identified according most and equal importance. To Characteristics. Types and Needs as anticipated variation was identified. Building Description. the next indicating the next gaps relative to when and what information can be derived most important with rank 2 and so on. The importance of the five main each professional group were compared to the overall RII information categories was then compared according to rankings shown in Table 2. 22 © RICS Research 2015 .it notepads to Payments Out and Surrounding Characteristics as the record responses. The rankings of from the project lifecycle. Group discussions were recorded and two most important information types.1 Workshop 1 Identifying Data Examining the ranking of the importance of information sub-types according to the four stakeholder groups. a three-point Likert scale was in importance between stakeholder groups is shown used. A summary of the variation to each professional group.85). calculated according to each professional group. whereas the AEC facilitators and scribes took notes.85). The Using these insights together with a specification of BIM 22 information types were arranged in descending order deliverables (Succar et al. For example the ‘Development and Asset Management’ group returned Participants used workbooks and Post. AEC Professionals.	Building Description (RII 0. 2.87). where 1 equals least important (irrelevant) and 3 in Table 3. Land Features.	Payments Out (RII 0. The importance of these building descriptors to all stakeholders confirms the potential of where W = weight given to response. BIM’s application within the property profession. information types according to All Responses (in Table 2).92). 3.	Land Features (RII 0. A = highest weight. equals most important (essential) and were analysed by calculating the Relative Importance Index: The most consistent information types were those belonging to the ‘Building Descriptors’ category. Valuation and Cost Managers. Surrounding the workshop was analysed using thematic analysis. The mapping in Figure 3 reveals those significant The relative importance index (RII) for all 22 information information types relative to their stakeholder activities types were calculated for all participants. 2013) a framework is proposed of relative importance according to all participants and of the way in which client-side stakeholders can leverage ranked. and 5.	Technical Quality (RII 0.. The highest RII indicates the most important data to support the CPDM lifecycle and start to identify the information types with rank 1. Building Information Modelling and the Value Dimension 4.
92 3 1.00 1 0.00 1 1.63 23 0.33 12 0.92 3 1.00 15 0. to High High Significance Low Significance Managers Significance Significance Significance Transaction Medium Medium High Significance Low Significance High Significance Managers Significance Significance © RICS Research 2015 23 .74 14 0.67 12 0.83 12 1.00 1 20 Design/Aesthetic Quality 0.75 17 1.83 8 0. to High Med.00 1 0.75 17 1.92 3 1.88 8 1.00 1 3 Land Features 0.79 22 0.87 1 1.00 1 2 Functional Quality 0.79 8 0.83 8 0.92 3 0.75 18 0.89 15 0.00 1 13 Market & Letting Vacancy Situation 0.83 8 0.00 1 7 Environmental Quality 0.33 15 0. rics.83 8 0.83 8 0.62 14 0.75 17 0.75 20 21 Design Process Quality 0.78 22 0.75 20 4 Technical Quality 0. to High Low Significance High Significance Asset Managers Significance Significance Significance Med.63 23 0.75 18 0.83 12 0.89 6 0.83 12 0.00 1 19 Surrounding Characteristics 0.92 3 0. to High Med.77 19 0.51 14 0.75 17 0.00 1 17 Tenant & occupier Situation 0.00 1 11 FM Quality 0.72 22 0.75 17 1. to High AEC Stakeholders Low Significance High Significance Low Significance Significance Significance Valuation & Cost Medium Med.44 3 1.75 20 10 Payments In 0.78 19 0.00 1 6 Site Features 0.83 8 0.67 23 1.75 18 0.89 19 0.00 3 0.74 22 0.85 1 1.88 8 0.75 20 22 Macro-Location 0.00 1 18 Construction Quality 0.75 17 1.67 11 0.83 8 0.75 18 0.89 23 0.82 8 0.75 20 5 Payments Out 0.67 14 0.00 1 16 Environmental Context 0.00 1 9 Health & User Comfort 0.59 8 0.92 1 1.85 1 1.88 8 1.78 15 0.00 1 15 Micro-Location 0.00 1 12 National Market 0.92 3 0.85 21 0.83 8 0.89 8 0.00 19 1.00 6 0.75 20 Table 3 Relative Importance of Five Main Information Types & Stakeholder Groups RII According to Building Stakeholder Groups Location Plot of Land Descriptors Process Quality Economic Quality Development & Med.72 14 0.67 8 0.org/research Table 2 Descending relative importance of data types for Stakeholder Groups (highest to lowest) Development AEC & Asset Value & Cost Transaction All Responses Professionals Managers Managers Managers Information Types RII Rank RII Rank RII Rank RII Rank RII Rank 1 Building Description 0.00 1 8 Operational Quality 0. to High Med.92 3 0.72 8 0.33 8 0.83 12 1.75 18 1.92 3 1.00 1 14 Planning Quality 0.78 12 0.83 8 0.82 1 1.78 24 0.83 8 0.67 1 1.00 3 0.74 19 0.00 2 0.83 19 23 Cultural/Image Value 0.79 8 0. to High Med.88 8 1.63 24 0.00 1 0.89 8 0.72 1 1.75 20 24 Urban Design Quality 0.83 12 1.00 1 0.92 3 1.88 7 0.
Building Information Modelling and the Value Dimension Importance of Main Information Types according to Stakeholders and Activities across Figure 3 CPDM/Project Lifecycle Phases Single Facility Project Lifecycle Phases (PD) (SD) (DD) (CD&CO) (OM) Commercial Property Development Conception Planning & Preparation Execution Operation Recommissioning & Management (C) Feasibility (P) (E) Maintenance (R) Lifecycle Phases (SD) (OM) Location Descriptors Plot of land Descriptors Building Descriptors Process Quality Descriptors Economic Quality Descriptors Development Valuation AEC Transaction Mgmt. Stakeholders Stakeholders Stakeholders Stakeholders Low significance Low-Medium significance Medium significance Medium-High significance High significance Scope of professional practices 24 © RICS Research 2015 . & Asset Mgmt. & Cost Mgmt.
rics.	Ensuring data can be organised such that it can be discovered and exploited (RII 0.73) 23.74) Technical Challenges 14. life information management and then ranked them in Participants were then asked to rank the importance of the same way as exercise 1.85) 20.74) Context-based 10.90) 18. 4)	Security and privacy. Table 4 Challenges to through-life information management and corresponding RII Type Sub Type Challenges Identified 1. and.87) Issues 11. information overload and cognitive limitations (RII 0. sourcing and analysis (RII 0.81) 17. Figure 4 illustrates the results were identified. Far more socio-technical challenges (20 in total) Participants brainstormed the challenges relating to through were identified as being significant by participants.	Privacy preserving analytics and granular access control (RII 0. 2)	Data quality and fidelity.org/research 4.92) 4.56) Socio.90) Technology Inter- based operability & 2.81) Security & 15. socio-technology challenges as shown in Table 4.	Human error.85) 8.	Complexity of incorporating operational simulations (RII 0.	Conflict in interests relative to data transparency and business interests (RII 0.	Secure data storage and data provenance (RII 0.72) © RICS Research 2015 25 .82) Privacy 16.77) Data Quality 5.	Data verification and validation (GIGO – Garbage in.	Ensuring data can be sustained and updated over long timescales (RII 0.	Number of disparate data sources and disjointed nature of information flow (RII 0. accuracy and reliability (RII 0. the number and 1)	Inter-operability and data standards.85) Challenges Data Standards 3.	Intellectual property and information ownership (RII 0.85) 9.	Continual reporting and justification of business case for on-going data collection (RII 0.54) Competencies 22.92) & Fidelity 6. A total of 23 challenges each of the 23 challenges.	Degree of interpretation and human manipulation (RII 0.62) Digital Skills & Knowledge 21. Five categories (Table 4) identified by the over a building lifecycle. 5)	Digital skills and knowledge competencies.	Ensuring data to be compatible and interoperable over long timescales (RII 0. that are divided in technology based and of RII analysis. Whilst three technology-based facilitators and reported back to participants include challenges identified by workshop participants as having issues surrounding: a high level of agreed significance.	Perceived ‘black box’ and risk in loss of knowledge due to dynamic workforce (RII 0. Garbage out) (RII 0.	Need for cultural change amid feelings of fear & ‘loss of control’ (RII 0.	Data granularity and its consistent specification (RII 0.82) 19.	Lack of digital skill sets and domain knowledge (RII 0.	Confidence in IT infrastructure security in distributed networks & data stores (RII 0.	Data consistency. A number of issues will need addressing if the vast The challenges identified by each group were then amounts of property data are to be a useful resource discussed.81) 7.	Differences in levels of availability of data between stakeholders through-life (RII 0.	Compressed timeframes for data generation. significance of socio-technical challenges identified were greater overall.2 Workshop 2 Identifying Post workshop analysis further classified these five categories in terms of ‘Technology based Challenges’ the Challenges (category 1) and ‘Socio-technical Challenges’ (categories 2-5).54) 12.	Communication differences and difficulties between domain specific languages (RII 0.	End-point validation and filtering (RII 0. 3)	Context. 13.
0 Ensuring data to be compatible and interoperable over long timescales Interoperability Ensuring data can be sustained and and Data updated over long timescales Standards Ensuring data can be organised such that it can be discovered and exploited Human error. information overload and cognitive limitations Data consistency. Building Information Modelling and the Value Dimension Figure 4 Relative Importance of Challenges to Through-life Information Management Importance 0. accuracy and reliability Data quality and fidelity Data granularity and its consistent specification Data verification and validation (GIGO – Garbage in. Garbage out) Degree of interpretation and human manipulation Communication differences and difficulties between domain specific languages Number of disparate data sources Impact of and disjointed nature of current context information flow Differences in levels of availability of data between stakeholders through-life Compressed timeframes for data generation.2 0.4 0.8 1.0 0.6 0. sourcing and analysis Conflict in interests relative to data transparency and business interests Confidence in IT infrastructure security in distributed networks and data stores Privacy preserving analytics and granular access control Privacy and Security Secure data storage and data provenance Intellectual property and information ownership End-point validation and filtering Lack of domain knowledge and digital skill sets. lack of education and training programs Complexity of incorporating operational simulations Digital Skills Perceived ‘black box’ systems and loss and Knowledge of corporate knowledge due to dynamic Competencies workforce Need for cultural change amid feelings of fear & ‘loss of control’ Continual reporting and justification of business case for ongoing data collection 26 © RICS Research 2015 .
(2012) proposed professionals. and the changes at different levels. where one company constructs a high-rise commercial office. digital built environments and misspelling of words in service records. property in situations of dynamic relationships between but it is more difficult to address the deliberate falsification AECO companies involved in the lifecycle of a property of data/records. Participants noted that. 2012. in addition to primary data records. and compliance in the implementation of information systems.	Information generated over a property’s lifecycle nature of information flow. as were problems with data verification (PAS 1192-5: Specification for security-minded building and validation. a British Standard. rics. if the socio-technical challenges are not Security and privacy addressed then the benefits of BIM for information Six challenges were identified that relate to security and management for property professionals may not be privacy. the use of slang smart asset management) (BS 2015). Limited attention has been paid in the BIM literature Data quality and fidelity to these issues.2 Socio-technical Challenges context in which it was generated or collected. another owns it. to BIM adoption have discussed their impact. discussions. 2011). another maintains it and others lease it). © RICS Research 2015 27 . (for example.org/research 4. relationships between data types and lifecycle phases 3. are needed for updating. and strategies challenge because to understand and exploit the data.	Information needs to be organised so that it can need to be known and understood. no matter how good their IT systems are. the information generated or collected should include data describing the 4. that. However this is changing.2. Less attention is and abbreviations (Ball et al. Of these. Managing property related data potentially needs to be accessed over many is a challenge due to its’ diversity in terms of the number generations of computer hardware and software. of different aspects of the building. workshop participants mostly focused their attention on these ‘people’ issues. 2. challenge to make data consistent. in PAS An appropriate level of detail and consistent specification form. 5)	End-point validation. These are: interpretation and human manipulation of data. accurate and reliable.1 Technology-based Challenges Context based issues Workshop attendees identified three key technology. its’ development.2. Key challenges identified included the degree of based challenges. Ball et al. Previous studies observed accidental information modelling. reporting and merging these the context in which it has been generated. five were ranked highly. is up for consultation at the moment on this area was important. surrounding environment and market. and. Singh et al. 2011). It is a environment occurs over the lifecycle.	Multiple changes to the building and the local operations. These issues surround change management 1)	Confidence in IT infrastructure security. Modern information paid to issues of information ownership and intellectual systems can overcome these issues to some extent. the number of disparate data sources and the disjointed 1. Concerns about intellectual property rights were seen as limiting the possibilities to learn from the aggregation of property data. During 4)	Intellectual property and information ownership. including: delivered. 2)	Privacy preserving analytics. In research aimed be discovered and used by different property at supporting data re-use. and numerous AEC based case studies on the barriers 3)	Secure data storage and data provenance. security in data access and issues Participants felt there were many opportunities for the surrounding privacy of project data are most commonly accidental or deliberate entry of erroneous data with a discussed (Redman et al. Such barriers are documented in the literature.
property professional currently aggregates and interprets as well as the different areas of property represented in many sources of data when making an assessment of both groups of workshops. verification and ✓ ✓ information overload ✓ tags through-life ✓ Garbage out) validation Complexity of Continual reporting/ incorporating justification of operational business case for ✓ ✓ simulation data collection and upgrading 28 © RICS Research 2015 . Security of property and validation: protocols for data use. Participants highlighted the difficulty drivers and challenges faced with information needs and in making sense of large amounts of data without a data management through the property lifecycle. the lack of digital skill sets combined with an London workshop and table 5 shows the similarities inadequate level of domain knowledge was identified as and differences in perceptions of participants about the the most significant. information surrounding value of difficulties & and filtering &knowledge ✓ data & its ongoing use ✓ ✓ differences in domain ✓ ✓ through-life specific language Data verification Lack of standards & Human error. and what training would be required to use There is a need for education and training in new BIM effectively for this purpose. of A similar process was undertaken in respect of the these. integrating and generating data through-life Data Quality and Process and Aus Aus Aus Aus UK UK UK UK Fidelity Workflow Human Error Security and Privacy Data consistency.both security in distributed ✓ ✓ all users through-life ✓ ✓ institutional & ✓ networks & data stores ✓ organisational Data granularity & level Lack of automation & Black box systems Privacy preserving of details (LoD) integration between & loss of corporate analytic & granular ✓ ✓ information systems ✓ ✓ knowledge due to ✓ access control ✓ ✓ dynamic workforce Data quantity Vs Compressed Need for cultural Secure data storage & quality timeframes for data change admit feelings data provenance ✓ ✓ generation & analysis ✓ for fear & “loss of ✓ ✓ control” Objective Vs. participants stated that an experienced different cultures predominating within the two markets. Disjointed nature of Lack of combined Conflicts in interest accuracy & reliability information flow domain-specific relative to data across all lifecycle ✓ ✓ ✓ ✓ knowledge & digital ✓ transparency & ✓ ✓ phases skill sets business interest Data format and Differences in level of Lack of education IT infrastructure interoperability availability of data to and training. Five challenges were identified and. For issues than their UK counterparts and this may reflect the example. Participants expressed Comparison between Australian and UK participants’ perspectives regarding the key Table 5 drivers and challenges when sourcing. as an information Knowledge Competencies management “tool” could replicate this level of real-life experience. information systems and to develop new knowledge competencies. Overall good deal of intelligent processing and the knowledge/ Australia based practitioners perceived a greater range of experience to interpret and drive this processing. the state or value of an asset. cognitive limitations & and building metadata GIGO (Garbage in ✓ ✓ entry. subjective Uncertainty Communication End-point validation data. Building Information Modelling and the Value Dimension Need for New Digital Skill Sets and their concern as to whether BIM.
and involve different type of data. demolition optioneering however different sectors of the property and construction industry own and manage some of these databases and some negotiation is required to make these databases talk to each other for property professionals. © RICS Research 2015 29 . these participants did not complete the tasks for workshop Environmental Context 2 and 3. Having identified the extensive range of data types in Workshop 1. Quality (TDD) survey are shown. This task takes place during the lifecycle and typically requires relatively few data types. but are in other digital databases. rics. Use. It is clear that description some tasks are far more detailed and complex than others. Technical In some cases amendments were made. the second part of workshop 2 asked Visual Health Inspections and User participants to plot a timeline for managing data through Comfort the property lifecycle. there is potential to link these databases. Each participant focussed on a particular task they executed in their professional Basic capacity.org/research 4. a Chartered Building Surveyors’ data Discussion Environmental needs. it is apparent that some Discussion of their data needs are to be found within BIM. Workshop 3 involved a review of the timelines plotted in workshop 2 and a review of the data types and needs. Note that due to time restrictions for the London workshop. Discussions Quality between participants revealed the diverse nature of data types and needs required by the various property professionals for specific tasks. Data quality to Client Two further examples of the mapping of data needs and types over the property lifecycle is shown for a Transaction Manager and a Portfolio Management Surveyor in appendix Land features 2 and 3. In figure 5. Redevelopment. Although the data needs occur at different phases.3 Workshop 2 and 3 Identifying Figure 5 Data needs for a Building Surveyor Technical Due Diligence survey Timelines & Mapping Data Needs MAJOR COSTS MINOR COSTS Through Life.M. In comparison the Portfolio Management surveyor (figure Site 6) has requirements to access a far greater range of data features types over a much greater range of the building lifecycle from planning and feasibility through to the end of life cycle Access to Report Maintenance Functional when redevelopment or demolition is a consideration. Redevelopment/ strategic maintenance Technically. Figures 5 and 6 show two typical examples Building of the property data needs through life. such as BMS. when undertaking a Technical Due Diligence with F. Equally it is with Semas Operational apparent that other data needs / types are not yet included /Structural Quality Engineers within BIM. and repairs sale.
demolition optioneering establishment start-up and repairs . Redevelopment/ strategic Design Design and defects sale.30 Managing Property Data Through Life Mapping Property Professional Tasks with Information Inputs and Outputs MINOR COSTS MAJOR COSTS MINOR COSTS Figure 6 Planning Design Asset management Asset planning/Repositioning/H&BU © RICS Research 2015 Titles and Planning Design Building Tenancy Tenancy Maintenance Easements Report Report Audits Schedule Schedule Reports Environmental Quality Hazmat Land Concept Design Report Features Diagram Report GEO Indicative Tenancy Tenant and Tenant and Tenant and Basic Technical Occupier Occupier Occupier Building Report Costs Schedule Quality Situation Situation Situation Description Flooding Health Maps Design and User SSPECS Report Investment Maintenance Asset Building Comfort Model Schedule Documents Topography Facilities General Brief Management FM Score Ledger Quality Payments Agreements Site Plan Out Asset Plan Building Information Modelling and the Value Dimension Titles and Conceptual Easements ESD Report Facilities Investment Management Model Quality Conceptual Report Accountant Environmental Receivable Quality Payments BIM In Costs Asset Plan SPESC Technical Tenant Quality Survey Health and User Comfort Design OH&S Data needs for Portfolio Management Surveyors through the lifecycle Reports Audits Operational Quality Asset ESD Plans Modelling Conceptual Detailed Pre-construction Handover and Use. Planning and Feasibility and site Construction operations maintenance Redevelopment.
The respondents are employed by either very large organisations of more than 1000 employees (37%) or very small ones with less than 51 employees (42%). rics. target in respect of knowledge and awareness of BIM. involvement in stages of the property lifecycle. transport and infrastructure. The Health slightly biased to property professionals. which again is less likely to use BIM to construction. professional practice was primarily valuation and Less well represented are those working on industrial property development. The retail sector was also well represented though it is not clear the type of retail buildings covered. which is the group we wanted to buildings. © RICS Research 2015 31 . Those working in large organisations are likely to have access to latest innovations in technology including BIM. including region. Figure 8 shows that respondents’ areas of current Similar comments apply in respect of education buildings. Respondents were also asked to identify which sectors and land use types they worked on. Respondents working in construction and design were also well represented in the sample.1 Part 1 – Respondent Profiles.0 Survey Data Figure 7 RICS region respondents work in Analysis and Which region are you currently working in? Discussion Middle East and Africa 5 Latin America 0 5. property discipline and sector. Many worked in the professionals. with newer When the responses from the regions were analysed larger retail centres being likely to use BIM technology all North American responses were from property compared to smaller scale retail.org/research 5. most respondents (88%) are very experienced with 11 or more years working in the built environment sector. the Europe responses were slightly biased residential sector. Overall. design professionals within each region. care must be taken when drawing conclusions from the results. were collected in the first part of the survey Asia Pacific to provide context for the answers. Given the low response rate of the 14 membership base of RICS. Current Awareness and Usage Europe of BIM 19 The respondents’ profile information. years of experience and size of organisation. Areas of practice less represented were property portfolio management. property investment and FM. each of which completed the survey 21 North America to varying degrees. Survey comparisons by region were not possible sector. Figure 7 shows the distribution of respondents by RICS Figure 9 shows that most worked in the commercial office regions. The small group sector is reasonably well covered but again can range of respondents from the Middle East and Africa region were from small and simple buildings to very complex large- mostly construction professionals scale stock again with varying levels of BIM adoption. where larger new buildings are most likely to have due to under or over-representation of construction and some elements of BIM adopted in the construction phase. The survey had a total of 59 respondents. whilst the Asia Pacific respondents were unless the projects are large scale or high-rise.
0 Commercial Offices Retail buildings Residential buildings Health buildings Other commercial Education buildings Industrial Transport Infrastructure Other 32 © RICS Research 2015 .0 5.0 15.0 40.0 50.0 20.0 10.0 60.0 20. Building Information Modelling and the Value Dimension Figure 8 Respondents’ area of current practice Which area(s) of property do you currently practice in? (Select all that apply) Percentage (%) 0.0 25.0 10.0 90.0 80.0 30.0 Property Valuation Property Development Construction Design (AEC) Real Estate & Transactions Property and/or Portfolio Management Property Investment Other FM Figure 9 Land use types and sectors of property respondents work on What sectors of property do your work activities surround? (Select all that apply) Percentage (%) 0.0 70.0 30.
Conversely Likewise. high usage of intranets was reported When asked about their understanding of BIM. virtual data room (Figure 12) 67% record ‘no experience’ which confirms and BMS. which do you use in your current work activities? Percentage (%) 0.2 Part 2 – Experience Working be partly a result of the seniority and years of experience of the respondents. given the high numbers working have ‘no understanding’ and 48. valuation systems and extranets have fair levels just under a quarter (24.1% in the survey. Less well used are 3D modelling systems.0 50.0 40. technologies by the respondents were building simulation Having said this when asked about experience of BIM and analysis. the group is reasonably used to using the need to educate and up-skill RICS members. rics.org/research 5.0 30. understanding’ whilst just 15. 4D and 5D modelling. such as RP data in Australia.0 Intranets Online Property Databases Extranets Valuation Systems 3D Modelling Systems Finance Systems 2D CAD Systems Building Management Systems Virtual Data Rooms 4D or 5D Modelling Systems Building Simulation and Analysis Other © RICS Research 2015 33 . This may the 19 that had experience in BIM reported using it on a daily basis in their current work activities. however the advanced and newest iterations of BIM 12% have experience of BIM exceeding 5 years. Only IT.5% felt they have ‘excellent finance systems and 2D CAD systems. The lowest used understanding’ of BIM. Figure 10 Use of information technologies in the workplace Of the following information technologies.0 60.3% report having ‘limited in the property sector there is a high use of online understanding’.0 10. Also.0 20. Not surprisingly. skill over 60% of respondents (see Figure 11). Figure 10 summarises responses with Information Technologies in respect of use of technologies in the workplace. Nine of technologies are less familiar to the sample.1%) felt that they have a ‘good of usage. Overall. which shows a need to educate and up- property databases. 12.
Clearly where training is underlying the technologies and to be exposed to a greater delivered on the job. followed by is a greater potential in the education system for people. to be exposed to the theories and finally tertiary education. accredited global property education provision. Figure 13 shows where they received their up-skill existing members of a workforce.1% Less than 1 year Excellent understanding 9% 12. industry training courses. Most received training on the job. On this basis we strongly encourage individuals are exposed to a limited range of systems and RICS to promote the adoption of BIM education into its technologies already selected or adopted by their employers. in-house training programmes future RICS members. Figure 13 Source of BIM training Where did you receive your training in BIM? (select all that apply) Percentage (%) 0 10 20 30 40 50 60 70 Tertiary institution 3 Industry training courses 8 In-house training programs 7 On the job 11 34 © RICS Research 2015 .1% 12% 4–5 years 3% Of the 19 respondents that have had hands-on This approach is understandable where there is a need to experience.3% 67% Good understanding 5+ years 12. in house and via training courses range of systems.1% 1–3 years No experience 9% Limited understanding 48. However. there training. Building Information Modelling and the Value Dimension Figure 11 Understanding of BIM Figure 12 Experience of BIM What is your level of understanding of Do you have any practical hands-on Building Information Modelling (BIM)? experience with BIM? No understanding 12.
This is a long served traditional method of representing data in specifications and 2D drawings in the property and construction industry and this confirms the limited take-up and usage of BIM amongst many RICS members to date. The highest need for data falls SCORE = 3 in the area of maintenance where information needs are •	Necessary to carry out my business processes space management. This is closely followed by the most frequently used Property Location Data which is micro-location information •	Infrequently – one or only in certain scenarios. The next highest SCORE = 1 ranked need is for project data regarding feasibility and planning attributes. Given the low participation rate.org/research 5. © RICS Research 2015 35 . SCORE = 0 Information Need The options and scoring for need of use were: When looking at information or data need a different range •	Required by law of attributes score highly. quality of local facilities/amenities such as shops. the items within Real Estate Data are very highly information is needed in the context of their current work rated. Market Data is state. Conversely the 3D model objects given to higher frequency of use and to more urgent need and properties rated lowest in the frequency of use of of use. we Part 3 of the survey. with higher scores information frequently. an average score was calculated for the respondents. which has a high frequency use in Table 6. regional and neighbourhood market SCORE = 2 data. Similarly needs with regards to Documentation and Images (specifications and 2D drawings) ranked highly. The most frequently used •	Cyclically – used at regular intervals. Spatial (area data) and Project data (construction and SCORE = 3 planning/feasibility attributes). indicating survey respondents use this category of activities. entitled “Understanding Information will not look at individual information types. asset monitoring and tracking and SCORE = 2 information about alterations and repairs to buildings. •	Never schools and so on. Property •	Not needed by me Management and Building Surveyors. rics. This data is of use to Facilities Management. Other data types used most frequently were •	Frequently – used in daily business. such as transport connections or reputation/image of the SCORE = 1 area. data types. asked respondents to rank different types categories of information and their relative scores. of information on the frequency of use and why the In Table 6. The answers were scored.3 Part 3 – Information Frequency of Information Use Frequency and Need of Use For each information type. Documentation (specifications) and images The options and scoring for frequency of use were: (drawings) also rated highly and are used frequently by respondents. but rather the Value”.
Alteration and Repair 1. sections.55 Specifications 1.87 Planning & Feasibility Attributes 1.51 Macro-location 1.88 Payments In 0.46 Property Lot Attributes 1. etc.87 36 © RICS Research 2015 . Recent Sales and Auction 1. Ratings.67 Property Value Attributes 2.95 External fittings.27 Operations and Maintenance Manuals 1. Regional and Neighbourhood Market 1.32 Orientation 1.42 Surrounding Building Context 1.21 Structural components 1.61 Variables Affecting Property Insurance Rates 3.90 Area 1.92 Payments Out 0.36 Utilities 1.) 1.20 Heating.59 Design management attributes 1. elevations.) 1.45 Listings. furnishings & fixtures 0.44 Environmental Attributes 1.95 Hard & soft landscaping components 0.23 Architectural Components 1.45 Vacancy and Letting Situation 1.88 Construction Attributes 1.98 Internal fittings.00 Mechanical & plant components 0.73 Micro-location 1.75 State.53 Maintenance.38 Property transfers 1. Building Information Modelling and the Value Dimension Table 6 Frequency of use of data types Information Category Property Site Data Maintenance Data Property Location Spatial Attributes Documentation & 3D Model Objects Real Estate Data Financial Data & Properties Project Data Market Data Operation & Frequency Images of Use Data Average Survey item Score Property Insurance Claims 3.21 Space management 1.90 2D Documentation (plans.36 3D rendered perspectives 1.52 Property Imagery 2.54 National Market 1.63 Property development 1.34 Volume 1.55 2D geometry 1.74 Property Activity 2.59 Certifications (Permits.23 3D geometry 1. furnishings and fixtures 0.03 Electrical and lighting components 1. etc. ventilation & air conditioning components 1.40 Marketing Statistics 1.36 Asset Monitoring & Tracking 1.46 Tenant and Occupier Situation 1.
26 Planning & feasibility attributes 1.83 Utilities 1. Furnishings & Fixtures 1. regional and neighbourhood market 1.55 External Fittings.69 Macro-Location 1.38 Asset Monitoring & Tracking 2.73 2D geometry 1.55 Hard & Soft Landscaping Components 1.22 Property Insurance Claims 1. elevations.70 Operation and Maintenance Manuals 1.org/research Table 7 Data need score by data type / area of practice Information Category Property Site Data Maintenance Data Property Location Spatial Attributes Documentation & 3D Model Objects Real Estate Data Financial Data & Properties Project Data Market Data Operation & Images Need Data Average Survey item Score Space Management 2.78 Certifications (Permits.76 Micro-location 1.54 Electrical and lighting components 1.43 Payments Out 1.53 Payments In 1.85 Environmental Attributes 1.76 State.78 Property Lot Attributes 1.70 Architectural Components 1.84 National Market 1.64 Volume 1.90 2D Documentation (plans. ventilation & air conditioning components 1.55 Mechanical & Plant Components 1.60 Listings.63 Property Activity 1. etc.83 Design management attributes 1. rics.63 Structural Components 1.69 Property Value Attributes 1.69 3D Rendered Perspectives 1.55 Internal Fittings. etc.74 Surrounding Building Context 1.66 Tenant and Occupier Situation 1.57 Marketing Statistics 1. Ratings. sections.32 Maintenance.54 Heating.57 Property Imagery 1.58 Property Transfers 1.56 3D geometry 1.22 Construction Attributes 1.93 © RICS Research 2015 37 .40 Variables Affecting Property Insurance Rates 1.) 1. Recent Sales and Auction 1.97 Specifications 1.60 Vacancy and Letting Situation 1.76 Property development 1.) 1. alteration & repair 2. Furnishings & FIxtures 1.68 Orientation 1.83 Area 1.
etc. This suggests that •	Construction Attributes – Project Data these are used with great frequency by a small proportion •	Design Management Attributes – Project Data of the respondents for non-legal reasons. The •	Planning & Feasibility Attributes – Project Data specific information types that rank as highest in terms of •	Micro-Location – Property location Data frequency and need (top right quadrant) are: •	Property Development – Property Site Data •	2D Documentation (plans. Ratings.) – Documentation & Images •	Area – Spatial Attributes. they & Maintenance Data have relatively low rankings for need. Building Information Modelling and the Value Dimension Figure 14 shows information types plotted by their ranking •	Specifications – Documentation & Images on need and frequency of use. Of particular note. etc. Alteration & Repair – Operations were amongst the highest in ranking for frequency. Figure 14 Information Type Need Ranking versus Frequency Ranking Information Need Ranking Information Frequency Ranking 3D Model Objects & Properties Documentation & Images Market Data Operations & Maintenance Data Project Data Property Location Data Property Site Data Real Estate Data Spatial Attributes Financial Data 38 © RICS Research 2015 . is the •	Property Marketing Statistics – Market Data disparity between the frequency and need rankings of the real estate data. Although the real estate information types •	Maintenance.) – •	Property Lot Attributes – Property Site Data Documentation & Images •	2D geometry – Spatial Attributes •	Certifications (Permits. sections. elevations. but that a large proportion of the respondents do not use them.
Recent Sales Market Data Frequency 0.001 Important Important Financial Data Vacancy and Letting Situation Frequency 0. Ventilation & Air Need 0. Ventilation & Air Important Important Frequency 0.011 Less More Heating. The workshop “Location” These items might be indicative of a gap for property category was found to be less important to AEC professionals where these items have been relatively less stakeholders (refer to Table 3).002 and Auction Property Transfers Frequency 0.org/research Although the response rate to the survey was not professionals than to property professionals. including micro-location.004 Property Site Data Environmental Attributes Frequency 0.001 Surrounding Building Context Frequency 0.000 Real Estate Data Property Imagery Frequency 0. Regional and Neighbourhood Frequency 0. found in the workshops.004 Property Location Data Micro-Location Frequency 0.001 Property Lot Attributes Frequency 0.043 Conditioning Components Building Data – Operations and Maintenance Manuals Frequency 0.011 Heating.004 Property Value Attributes Frequency 0.003 Property Marketing Statistics Frequency 0.004 Property Development Frequency 0.002 Property Activity Frequency 0.000 Building Data – Spatial 3D geometry Frequency 0. which is equivalent important to AEC stakeholders but are of high frequency to the above result that “Market” and “Property and need for work activities. These survey results are consistent with the differences property lot attributes and property marketing statistics. found between the two groups when it came to ranking Several of the information types that were identified as information types.029 Documentation & Images © RICS Research 2015 39 . Financial data is of more A number of statistically significant differences were importance to property professionals. 14). the responses of the property professionals stakeholders (construction and design professionals) in were compared to those of the construction professionals.001 Utilities Frequency 0. both the workshops and survey. rics.011 More Less Tenant and Occupier Situation Frequency 0.002 Market Listings.027 Building Data – 3D Model Conditioning Components Objects & Properties Mechanical & Plant Components Frequency 0. property development. Building high enough to make a lot of cross-tabs or subgroup descriptors were found to be more important to AEC comparisons.046 Attributes Electrical & Lighting Components Frequency 0. Location” categories are less important to construction Table 8 Tests of Professional Differences in Information Importance Independent-Samples Median Test Frequency Statistical Property Construction Category of Data Information Type or Need Significance Professionals Professionals State. Table 8 shows the information types for being more important to property professionals also which there was a statistically significant difference in the ranked in the highest quadrant of information types (Figure median scores between the two professional groups.
4 Part 4 – Challenges are the industry benefits of potential for ‘performance improvements and increased transparency and open data & Benefits of BIM sharing across sectors’. The top completeness’ ranked the lowest of all whereas earlier three challenges. Second lowest ranked benefit is the ‘potential for participants. which aim to measure in-use •	Slightly significant performance. However when we examine the •	Very significant lowest ranked benefits. consistency and reliability issues (36%) (2) reliability was a concern. and (3) Secure data authorship and storage (32%). of an integrated approach to information management Other notable significant benefits are ‘improvements throughout the life of the property. Of note is that the top of property value’. including lack of training at an organisational investment management surveyors to assess the ongoing level and communication difficulties. which may be incomplete and thus unreliable and out of These responses echo the concerns of the workshop date. which again can save time and costs and rank how significant they saw challenges and benefits enable good design and construction to be replicated. are (1) Data in the survey respondents had said data accuracy and accuracy. 40 © RICS Research 2015 . More with several items of the lowest concern falling in this benefit may lie in the benefits to portfolio managers and category. there appear to be contradictions Figure 15 shows the percentage of respondents that evident as ‘improvements to information availability and ranked each challenge as “Very significant”. respondents were asked to re-purposed’. Human Factors seem to be less of a concern. Finally the significance of the perceived key benefits of an Building Surveyors and Facilities Managers will benefit from integrated approach to information management through access to data related to building performance in delivering the life of property are considered. which was the top challenge in lowest ranked item was ‘improvements to the assessment both the workshop and the survey. indicated by dark bars. Of highest significance some of their professional services. the valuation process from data contained in BIM. greater levels of innovation in industry practice’ and third consistency and reliability. Of equal highest significance is the benefit of ‘having data that can be re-used and In this part of the survey. Building Information Modelling and the Value Dimension 5. There seems to be little point in Lack of protocols to verify and validate data (33%) having an increased availability of data available to industry. Respondents also ranked ‘new abilities to •	Moderately significant provide value added services’ which reflects members’ •	Significant desires to maintain the highest standards possible in highly competitive markets. value of properties within their portfolios based on building performance and property maintenance costs over time. It appears that members currently two challenges fall within the category of Data Quality and do not perceive a great level of benefit to valuers and Protocols. Options were: to the assessment of building performance’ which is •	Not significant potentially very significant in terms of buildings rated under sustainability rating tools. particularly with respect to data accuracy.
consistency and reliability issues Scale and complexity issues surrounding large datasets Lack of industry standards to control Technical consistent data reuse Interoperability issues in structuring disparate data sources Security of property and building metadata Secure data authorship and storage Security Need for privacy preserving analytics and & Privacy granular access control Concerns Increased IT infrastructure security across distributed networks and data stores Conflicts in interest relative to data transparency & business interests Cost surrounding new information management infrastructures Justification of business case for sourcing.org/research Figure 15 Key challenges in information management through life Percentage (%) 0. rics. organising and maintaining data Increased and continued reporting Process & Uncertainty surrounding value of data and Workflow its ongoing relevance Compressed timeframes for sourcing.0 Lack of protocols to verify and validate data Trade offs between data quality and Data data quantity Quality & Protocols Data granularity Data accuracy.0 40.0 20.0 30. organising and reusing data Differences in level of availability of data to all users Disjointed nature of information flow between organisations / sectors Human error Communication difficulties and differences in domain specific “language” Need for cultural change amidst feelings of fear and “loss of control” Ineffective implementation due high staff Human turnover Factors Lack of education and training at organisational level Lack of education and training at institutional level Lack of interdisciplinary knowledge Lack of digital skill sets © RICS Research 2015 41 .0 10.
0 15. once captured.0 30. Building Information Modelling and the Value Dimension Figure 16 Key benefits of digital information through life Percentage (%) 0. can be reused and repurposed 42 © RICS Research 2015 .0 5 .0 20.0 40.0 25. Increased levels of transparency Based Benefits Increased decision support Greater accuracy and efficiency in property evaluations and assessments More effective control of resources and costs Improvements to the assessment of property value Improvements to the assessment of building performance Information Information can be checked and Quality validated Information.0 10.0 35.0 Improvements to industry performance Industry Increased transparency and open data Benefits sharing across industry sectors Potential for greater levels of innovation in industry practice Improvements to data quality and accuracy Potential for greater levels of innovation Faster assessment and reporting processes Organisational Reduction in data sourcing and Benefits co-ordination efforts New abilities to provide value added services Provision of a centralised point of control Improvements to organisational performance and operational efficiency Improvements to personal productivity Improvements to levels of acceptable risk Improvements to information availability & completeness Practice.
The workshops used in context. provide that data. This is a major challenge and the property over a whole of life timeframe (figure 6). The five main categories of fidelity and quality. increase the knowledge base and to develop access to data is provided. review and analysis of data types and needs in respect Furthermore understanding of BIM within the property group of professional property tasks and services. of property portfolio managers who will seek to rationalise properties within the portfolio based on performance amongst other variables. and: range of data needs and used 24 different types of data 3. which were largely endorsed in the require addressing. These needs were identified in the literature.2 Challenges & Benefits of BIM and should. survey. 2. FM and Property Management tasks.0 Overall conclusions The research question posed was: what is the role of The experience of property professionals using BIM was the value dimension in BIM? Through a comprehensive found in the workshops and the survey to be minimal. where data. The opportunities may not be realised in practice. professionals accessing BIM data widens. rics. as well as the mechanisms for incorporating such data.	Market and location data.	Compatible and interoperable over long timescales. as the key benefit Building Surveyors Technical Due Diligence reporting. tackles issues of security and privacy also revealed 23 challenges. also other buildings and that the majority of RICS members will be digitised building systems not initially considered within performing professional services on existing stock where the remit of this research. This potential role information is not available in BIM format.	Security & Privacy. and.	Digital Skills & Knowledge Competencies. 4. Protocols needs to established as the range of for example. such data is typically found in the BMS realised if data is not perceived to be reliable.	Organised such that it can be discovered and used. as many buildings may not have BIM but however it is considered that more benefit lies in the area may have a BMS. 1. property tasks. in Table 4. Socio-technical challenges summarised property information were. Overall the survey respondents felt there would be the opportunities within BMS technology to inform some little benefit at this point in time to valuers in using BIM data. Who would. We should bear in finds that there is potentially a significant role for the mind that currently BIM is largely restricted to larger newer adoption of property data into BIM and. simple at a single point in time. 5. construction Largely. 6. lead to poor decision making and professional very complex needs of Portfolio Management Surveyors judgements.	Property data (describing the plot of land) 2. Currently sources are often separate and often reflect those of professions whether using technology distinct and are at times unchecked with issues around systems or not and include aspects such as reliability. Technology based challenges were ensuring data can be. Other areas are identified skills within the profession. such as BMS. perceived by survey respondents of ‘improved performance’ and property portfolio management. There is a danger that in some cases there will be Building Information Models which are Data needs were also found to vary from relatively not well maintained and have inaccurate data entry that will. up to date and as much as the BIM. as well as the steps to As with all data needs. this research is also limited in breadth and depth. accuracy of some data.	Property data (describing economic information) 3. Property professionals were found to have a very broad 2. in their professional services.	Context-based Issues. Furthermore the opportunity lie largely in respect of the data on building performance to provide clients with ‘value added services’ may not be in use.org/research 6.	Sustained and updated over long timescales. This is likely to can be classified into those areas where data relevant to change over time. 3. were grouped as. it is critical that the data is reliable ensure such data is accurate and updated as necessary. However. providing awareness.1 Data through-life 1. is not within the BIM and further consideration of whether to incorporate such data is required. 4.	Process qualities (planning information.	Data Quality & Fidelity. Therefore RICS should investigate sound. ratified in the workshops and confirmed Not surprisingly the socio-technical challenges identified in the survey. The workshops profession need reassurance that the data they do access and survey revealed good potential to use some of the and use to base their professional judgements on is sound data already in BIM for property professional practices and reliable. © RICS Research 2015 43 .	Building information. the survey responses echoed concerns raised by information and FM information). 1. and accurate and as up to date as possible. however currently there is a need to raise property professionals exists and can be used. for example the Building if relied upon by those unable to interrogate and understand Surveyors Technical Due Diligence report (figure 5) to the data. 6. the workshop participants.
industry-wide approach may be 4. RICS 6. there is considerable scope for profession. or ‘the value dimension’. building surveying and facility management subjects as a potential 2. At this point an assessment of the demand for the data would determine whether it is desirable to implement such a change. Macdonald (2012) discipline BIM competencies with the APC structure so has proposed a framework to assist AEC academics in that property professionals can obtain recognition for implementing collaborative education programs with the knowledge. Furthermore RICS could form an all RICS disciplines Education Task Force to champion the roll out of BIM across property courses globally to ensure new members One of the key priorities is to undertake a comprehensive have the requisite awareness. it is apparent that great potential exists to enhance the quality and accuracy of many aspects of 5. rather than separate task forces being members of the property disciplines in BIM set up that essentially have the same aims. Such a program should encompass provision 3. and a unified. knowledge and skills with mapping of data needs and types across all RICS respect to BIM and property. In all cases issues identified in section 5. management. There are various initiatives in this use data within the models. area being undertaken by professional bodies and other groups. RICS could consider updating accreditation that arise out of this research. security and privacy RICS accredited property courses at undergraduate and should be considered. context. and this could be adapted this knowledge in their professional practice. skill and competency with the application of aid of BIM tools and processes. property investment. Develop a set of CPD events to raise of CPD for existing members. In particular details on data format post graduate level. under the As a priority RICS should develop some online education leadership of an Education Task Force. Introduce BIM professional competency source of information. Thirdly this review 44 © RICS Research 2015 . Mapping of data needs and types across data effectively. In this way property students will in RICS APC for property professionals start to see the potential for the use of BIM data across The RICS APC group should develop appropriate property a range of their professional tasks. Given the to incorporate property education. Develop RICS training courses for existing worth considering. Clearly property education is not restricted to the tertiary there may be some aspects which are transferable to the sector and this research concludes that a broad program property disciplines. This could build resources for members to raise awareness and knowledge on the work already carried out to develop the RICS BIM in respect of BIM and how property professionals could Manager certification.3 BIM in Property Education would identify those data needs and types that are outside of BIM that could be digitised and incorporated Given the low levels of understanding and practical due to the extent of potential usage within the property experience of using BIM. The full list should be categorised student to the concept would in construction technology and prioritised. From this research. disciplines to identify (a) what is currently within BIM that could be used by property professionals. Concurrent with the roll out of CPD courses for members and the development of online education resources. There are five key recommendations education. across all RICS disciplines at all levels of membership is desirable.4 incorporating some understanding of BIM technology into data quality and fidelity. and where necessary negotiations with subjects. RICS BIM & Property Education Task Force property professional practice with the adoption and use With regards to the integration of BIM into property of BIM in some tasks. training short courses and awareness among property professionals provision of Information Papers and Best Practice Guidance Notes. valuation. criteria for universities to include requirement for collaborative working with other disciplines/using BIM 1. Building Information Modelling and the Value Dimension 6. however it should also be referenced in property third parties should be initiated. Clearly the obvious place to introduce and source are needed. A comprehensive strategy should be established of BIM to deliver a roll out of resources to members. innovation in the RICS BIM Certified Manager qualification. (b) data needs and types currently in a digital format but found in databases outside of BIM that could be easily made compatible to BIM.4 Recommendations and should develop a series of training courses for existing further research members globally to realise the potential of BIM data in their professional practices.
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......................org/research 8....................49 Appendix 3	Managing data through the property lifecycle (Workshop 2 output)........48 Appendix 2 Key to symbols used in figures 5 and 6 and Appendix 3.................... rics............................0 Appendices Appendix 1	Property professionals data types and needs........50 © RICS Research 2015 47 .............
g. payments for modernisation. Local-context data. neighbourhood safety. degree of hard surface sealing Utilities E.g. Payments for construction.g. services. easements. median price. image of district. Property sales & transfers from Valuer General.g. car spaces. estate agent’s fee). population structure & development. political. bathrooms. suitability of location for property type. tenant fluctuation. and inflation Payments-In expectations. political. Distance to surrounding buildings. sunlight & shading levels. payments for operations 48 © RICS Research 2015 . Regional and E. water supplies. Energy supplies.g. Aerial. Environmental Attributes greenfield & brownfield conditions. communications services E. national auction results and clearance Auction rates. Vacancy rate.g. real estate industry data on annual Property Transfers transfers Property Marketing Statistics E. climate & geo data. social & medical facilities). Property listings. air. green areas & plantation. contribution to maintaining biodiversity. internal/external accessibility. rainwater Property Lot Attributes drainage. zoning.g. distance to amenities. existing Property Value Attributes owner. regional image. inclination.g. rental yield and rent demand) Listings.g. local Micro-Location transport connections. environmental conditions Property Site Data E. views & visual context. investment volume. location. rental growth potential.g. quality of public spaces and facilities (shopping. general Vacancy and Letting Situation letting prospects. noise & soil pollution E. legal and administrative conditions. Online. economic structure and situation.g. zoning. waste water supplies. Overall national economic situation. other payments-in (e. groundwater. Real Estate Data E.g. purchasing power E. development certificates. Insurance claims data such as residential property claims Variables affecting Property E. Regional transportation infrastructure & transport connections. details of the Property Development development. site selection/acquisition. size/area.g. Property attributes such as property type.g. facade advertising. tenant retention.g. duration of letting process. acquisition. Activity / interest in a property. street Surrounding Building Context layout. Number of tenants. expected rates of return E. disposal. security & crime Insurance Rate rates.g. Orientation. sale transactions and records. advance payments for utilities. Recent Sales and E. land use.marketing/letting (e. investment data (annual Neighbourhood Market growth.g. payments for operating costs. Economic situation. payments Payments Out attributable/non-attributable to tenants. lot/plan number. median rent. mapping images Property Activity E. layout. soil characteristics. internal and external property images. energy-feed-in) E. previous sales information Property Imagery E. mean area property price.g. rental listings and applications E. topography. building permission and planning regulations Financial Data Tenant and Occupier Situation E. duration and structure of rental contracts E.g.g. Building Information Modelling and the Value Dimension Appendix 1 – Property professionals data types and needs Market Data National Market E. socio-demographic Macro-Location development. tenants’ image and solvency.g. print and phone marketing data Property Location Data E. design & usage of open spaces. legal and administrative conditions State.g. Rental payments. Value and risk data surrounding absolute property value. evaluation of a property Property Insurance Claims data E.g. number of bedrooms. Environmental situation. traffic conditions E. Data surrounding development applications.
typically more deliverables. one or more output ‘scenarios’. © RICS Research 2015 49 . but can have be attempted.org/research Appendix 2 – Key to symbols used in figures 5 and 6 and Appendix 3 Node types Dependency The four types of node can be connected using two Deliverables types of dependency (line with arrows Represent packages of information or materials that are considered. but represent the possibility of generating a ‘backward branch’ (iteration). when The dependency indicates that the the task is complete. All the outputs of a simple task are created Data dependencies (or updated) at the same time. created Flow dependencies or modified by tasks. occurring between main project phases. Each scenario can represent a different Milestone ‘forward branch’ and contain one or Decision or stage gate. rics. Iteration constructs Similar to a compound task. The dependency contributes to the timing of the downstream task Simple tasks (eg. but Compound tasks doesn’t determine when the task can Similar to a simple task. the upstream deliverable must Represent tasks which take account be available to start the task) of inputs to create outputs. upstream information is used while executing the downstream task.
50 Managing Property Data Through Life Mapping Property Professional Tasks with Information Inputs and Outputs MINOR COSTS MAJOR COSTS MINOR COSTS Appendix 3A Asset Planning Design management Asset planning/Repositioning/H&BU © RICS Research 2015 Extra inputs Real Estate Micro National Agents Market location National Committee Programming Market Research Investment (Workshop 2 output) Reports Paper GEO Report Sales property lifecycle Micro Analysis Market location Rates Inspections Growth Rates Tenant and Occupier Situation Lefting up assumptions Marketing and Letting Capex Vacancy Tenant and Marketing Forecast Building Information Modelling and the Value Dimension Situation Occupier and Letting Situation Vacancy Situation Payments Development Out manager Tenancy Project DFC manager Schedule Assets Payments manager In Fund Payments Payments Concept manager out in forecast/ Tech. demolition Redevelopment/ strategic optioneering Design and defects operations Example of a Transactions Managers participant’s data needs at various stages of the establishment and repairs start-up . sale.due diligence report Outgoings  Other Appendix 3 – Managing data through the property lifecycle  Income Settlement Adjustments Handover Conceptual Pre-construction Construction and Use. Planning and Feasibility Design and site maintenance Redevelopment.
MINOR COSTS MAJOR COSTS MINOR COSTS Planning Design Asset management Asset planning/Repositioning/H&BU Appendix 3B Titles and Planning Design Building Tenancy Tenancy Maintenance Easements Report Report Audits Schedule Schedule Reports Environmental Quality Hazmat Land Concept Design Report Features Diagram Report (Workshop 2 output) GEO Indicative Tenancy Tenant and Tenant and Tenant and Basic Technical Occupier Occupier Occupier Building Report Costs Schedule Quality property lifecycle Situation Situation Situation Description Flooding Health Maps Design and User SSPECS Report Investment Maintenance Asset Building Comfort Model Schedule Documents Topography Facilities General Brief Management FM Score Ledger Quality Payments Agreements Site Plan Out Asset Plan Titles and Conceptual Easements ESD Report Facilities Investment Management Model Quality Conceptual Report Accountant Environmental Receivable Quality Payments BIM In Costs Asset Plan SPESC Technical Tenant Quality Survey Health and User Comfort Design OH&S Reports Appendix 3 – Managing data through the property lifecycle Audits Operational Quality Asset ESD Plans Modelling rics.org/research © RICS Research 2015 Example of a Portfolio Management Surveyors data needs at various stages of the Pre-construction Handover and Use. Redevelopment/ strategic Design Design operations maintenance sale. Managing Property Data Through Life Example of a Transactions Managers participant’s data needs at various stages of the property lifecycle. demolition establishment and defects optioneering start-up and repairs 51 . Planning and Feasibility Conceptual Detailed and site Construction Redevelopment.
Sydney. Australia Paul Zahara	Cranleigh. UK 52 © RICS Research 2015 . Sydney. Building Information Modelling and the Value Dimension Special Thanks Special thanks to the following people: Andrew Hannel Opus. London. London. Australia David Wagstaff	Pembroke. Sydney. Mid Anglia. London. Sydney. Sydney Jennifer Macdonald University of Technology. Australia Phil Boyne	Lend Lease. Sydney Ben Elder	RICS. UK Richard Stacey	Calibre Capital. London. Australia John Kavanagh	RICS. UK Christopher Stokes	ESurv. Sydney. London. UK Kath Fontana	BAM FM. Sydney. UK Clinton Ostwald	Urbis. Sydney. UK Leon Carroll	AMP. Australia Andrew Partridge	Eureka Funds Management. UK Richard Quartermaine	Hammerson Plc. Australia Sarah Sayce	University of Kingston. Australia Hernan Jerrez Guerrero Ridley and Co Sydney Australia Jack Moseley	Civic Valuations. London. UK Doug Rayment AECOM. Hemel Hempstead.
org/research © RICS Research 2015 53 .rics.
Building Information Modelling and the Value Dimension 54 © RICS Research 2015 .
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