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Influences on Real Estate Benchmarking Practice
Understanding the challenges and opportunities in the real state
benchmarking process
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Name: Bart Bisschops
TU Delft mentors: D.J.M. van der Voordt
M. Prins
External Examiner: R. Rocco
Graduation company: Johnson Controls International
Company mentors: L. Jansen
J. Suyker
Create insight into the variables that influence current benchmarking practices by
corporate real estate departments in large multinationals.
Goal
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• Problem description
• Main research question
• Methodology
• Theoretical exploration
• Explorative interviews
• Theoretical model & hypotheses
• Semi-structured interviews
• Conclusions & Discussion
Contents
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Corporate Real Estate Management
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Benchmarking
Benchmarking is the process of comparing one's business
processes and performance metrics to industry bests or best
practices from other industries.
Internal benchmarking:
• The comparison of different elements or entities within an
organization.
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Key performance indicators
Performance Indicators
Not an exhaustive list; anything that can be measured could potentially serve as an
indicator.
Key Performance Indicators (KPI’s)
• Indicators that are ‘key’ to the
organizations performance and
success.
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“If firms want to effectively align their real estate to support their strategic goals,
proper indicators are needed that reflect how property is being utilized in the
business”.
“Organizations should choose a limited set of personalized Key Performance Indicators
that are based on their own strategy and context”.
“Organizations often lack an objective assessment and rationale for the selection of
these KPI’s”.
What’s the problem?
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What’s the problem?
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Research Questions
How do the context variables and hurdles influence the choice of KPI’s that are
benchmarked by the Corporate Real Estate Management departments?
• What is current best practice performance measurement and benchmarking for
Corporate Real Estate Departments as presented in the current theory?
• What are the current benchmarking practices of real estate departments?
• What are the main characteristics of the CREM Departments that are studied and
the organizations and context that they operate in?
• What are the main hurdles they face during the benchmarking of their real estate
and how do they attempt to solve these?
• What is the relationship between the characteristics of an organization and its real
estate benchmarking practices?
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Methodology
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Research Design
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Introduction
Literature review Explorative interviews
Conceptual Framework
Semi-Structured interviews
Conclusions and Reflection
Methodology
• Qualitative research
• Explorative research
• Interpretevist paradigm
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Demarkation
Real estate portfolio benchmarks
Information about real estate objects collected for the entire portfolio or a subsection
of the portfolio that serves to make comparisons between these objects or other sets
of real estate objects
As opposed to
• Project information
• General management information
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Theoretical exploration
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Literature survey
Scientific papers
• 160 papers
• 50 cited
Keyword searches
• Google Scholar
• Databases like Emerald
Journals
• Journal of corporate real estate
• Journal of real estate management
• …
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Performance measurement theory
• Organizations should choose a limited set of personalized indicators that are
based on their own strategy and context
• Firms should develop a performance measurement system of valid and reliable
measures that match their objectives and are reasonable considering available
data and resources (Lindholm & Levainen, 2006)
• Proper measurement system should include both financial and non-financial
indicators and both lagging and leading indicators that consider both internal and
external performance and both long term and short term gains
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Status of RE performance measurement
• “Real estate organizations often still lack an objective assessment and rationale for
the selection of these KPI’s” (Varcoe, 2005).
• The common understanding between the core business and corporate real estate
still lacks both the quantity of relevant data and the common understanding of
how to prove the value-adding elements (Lindholm & Nenonen, 2006).
• Many companies are still focused mainly on cost reductions and financial
indicators. In this sense, the development of real estate performance
measurement has thus lagged behind the general developments.
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Explorative interviews
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Interviewees
Explorative interviews:
• Selection various experts and practitioners
• Open topic interviews
• Face to face
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Nr Company Interviewee Position
1 Twijnstra Gudde Klaas Bosma Corporate Real Estate advisor
2 AT Osborne Stef Weekers Consultant Corporate Real Estate
3 Stork Technical Services Carel Fritsche Manager Corporate Real Estate
3 Johnson Controls Louis Jansen Real Estate Account Director
4 Johnson Controls John Suyker Corporate Real Estate Executive
5 Johnson Controls Gemma van Kessel Real Estate Consultant
6 Johnson Controls Alex Koenig Real Estate Director
7 Johnson Controls Vincent verheijdt Account Manager Real Estate
Model & Hypotheses
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Theoretical model
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Theoretical model
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Hypotheses
The type of KPI’s that will be used will be influenced according to the characteristics
of the organization and overall context in which it takes place. The main influencing
variables are expected to be:
• Economic conditions
• Strategic focus of the organization and its sector
• Type of CREM department
• Tasks and strategies of the CREM department
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Semi-Structured Interviews
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Semi-structured interviews
14 Semi-structured interviews
Case selection
• Large multinationals
• Varied set of companies in multiple sectors
Procedure
• Face to face interviews
• Questionnaire sent in advance
Analysis
• Full transcriptions
• Excel
• Atlas TI
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Interviewees
Semi – Structured interviews:
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Nr Company Interviewee Position
8 Akzo-Nobel Hans Cijs Real Estate Manager
9 Philips Ronald Blanken Real Estate Director
R. vd Burgt Ac Manager Cons lifestyle / Global program manager
10 Microsoft Ed Folge Real Estate Manager (Regional integration manager)
11 IBM Paul Wittebrood Real Estate Manager
Albert de Vries Facility Manager
12 Canon Tamar Bos Real Estate Director
13 Wolters Kluwer Martijn Westerink Global Vice President Corporate Real Estate
14 OCE Jacques Brulot Real Estate Director
15 KPN Victor Huijboom Real Estate Manager
16 JCI Louis Jansen Real Estate Director
17 BP Tom van Duijn European program manager
18 Ericsson Jan vd Broek Real Estate Manager
19 Hewlet-Packard Marjolein Schotte Global real estate country delivery manager
20 Ericsson Willem Koning Facility Manager
21 MSD Jos Barnhoorn Facility Manager
Companies
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Company Revenue (2012) (Millions) # of countries located in Employees
Akzo-Nobel 15.390 80+ 50.600
BP 370.870 80+ 85.700
Canon 29.635 50+ 196.968
Ericsson 26.478 180+ 110.000
Hewlet Packard 89.201 170+ 331.800
IBM 77.510 170+ 434.246
JCI 31.083 150+ 170.000
KPN 12.409 3+ 27.165
Microsoft 54.619 100+ 94.000
OCE 2.648 30+ 21.635
Philips 24.788 100+ 118.087
Wolters Kluwer 3.603 25+ 19.112
Average 78.577 109 166.720
CREM departments
Size
• Average of 4 people with a range of 1-6 (n = 11).
Reporting
• Almost all the real estate departments report to Finance.
• Some directly to the CFO
Position
• 6 departments report directly to the board of directors
• 4 had only 1 level in between them and the board.
• 2 were three or more levels of reporting away from the board
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CREM departments
Task priorities
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CREM departments
Most important strategies
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Composition of real estate portfolios
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m2 (n = 10) Objects (n = 11) Countries (n = 8)
Average 796.873 288 31
Range 20.000 - 6.000.000 4 - 1300 1 - 80
Composition of real estate portfolios
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m2 (n = 10) Objects (n = 11) Countries (n = 8)
Average 796.873 288 31
Range 20.000 - 6.000.000 4 - 1300 1 - 80
Overall status of benchmarking practice
A more complex activity then initially suspected
While some data might be easily collected, extracting meaningful information from
even the most basic benchmarks is often wrought with difficulties
• Some which have built considerable benchmarking competency
• Overall, most are still in the beginning stages
• Very few express full confidence in completeness and validity of data
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Current benchmarking practice
Key Performance Indicators
• Basic indicators
• Ratios
• Other indicators
• No qualitative indicators
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Named KPI's Count
Basic indicators
Cost 12 12
m2 12 12
FTE 10 10
Workplaces 9 9
Ratios
Cost / m2 9 9
m2 / FTE 9 9
m2 / workst 9 9
Cost / FTE 7 7
FTE / workst 4 4
Cost / workst 3 3
Other indicators
Occupancy rate 4 4
Cost / revenue 3 3
Space utilization 2 2
Leased / Owned per country 1 1
Average contr lengh /counry 1 1
Rolling / Fixed leases 1 1
Qualitative
Workplace satisfaction 1 1
Current benchmarking practice
Upward reporting
• Mainly financial and quantitative data
• Often just a single cost or savings metric as most important KPI
External Benchmarking
• Widespread skepticism about quality of external benchmarking information
• Desire for better benchmarks
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Hurdles
Before the benchmarking process
• Identifying a clear use beforehand
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Hurdles
During the benchmarking process
• Availability
• Different Databases
• Measurability
• Costly to gather
• Resistance, low priority
• Validity
• Human errors
• Multiple databases
• Comparability (consistent definitions used)
• Internal
• International
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Hurdles
During the analysis and use of the benchmark
‘For internal benchmarking, the biggest challenge is to make correct divisions in the
data and compare only comparable groups’.
Heterogeneity of the portfolio
• Functional Heterogeneity
• Regional, National factors
• Cultural factors
• Unique, special objects
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Benchmarking Use
• Aid portfolio optimization
• Enhance management reporting
• Raise support among business units
• As feedback on own management practice
• To improve the quality of the benchmark itself
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Conclusions & Reflection
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Overall Conclusion
Because companies focus on basic benchmarks, and the sets are very similar, definite
relationships between the benchmarking and influencing variables are hard to prove.
Influencing factors:
• Pressure from above
• Economic crisis
The other hypothesized relationships like strategic focus, type of CREM departments
and their tasks and strategies could not definitively be proven.
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Influences on benchmarking practice
Different kind of influence
Cause
• Complexity of benchmarking?
• low benchmarking competency of CREM?
Most importance influences
• Perceived use / importance of benchmarking results
• Willingness / opportunity to invest time and resources to this end
• Experience with and competence in benchmarking
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Prescriptive models
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Increasing complexity
- m2
- Derivatives Other quantitative Qualitative indicators
- Cost - Basic ratios strategic benchmarks e.g.
- FTE - Affordability
- Workstations
Regional National International
Internal External
Relatively Mix of functions Different functions,
homogeneous in portfolio often in the
portfolio same objects
Are
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Benchmarking competency
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Early stages
Only basic benchmarks and ratios are used.
Collection of information that is readily available.
Definitions will most likely differ through out the portfolio but are neglected in analysis.
Completeness of the data is low for most benchmarks.
Validity of the data is relatively low and no structured validation process is in place.
Intermediate
More integral definitions used basic KPI's like total cost of occupancy instead of simple contract rents.
Move towards uniform and enforced definitions for the KPI's.
Structural collection process of desired data is in place.
Start of a structured validation process.
Current top performers
Additional KPI's chosen according to own strategy and context.
Own set of enforced definitions for the benchmarks that are used .
Reasonably complete and valid databases for basic KPI's.
Department is actively trying to fix the remaining errors and outliers in the data.
Organizational knowledge has been built over time causing less errors in the data.
Benchmarking succes factors
Selection of KPI’s
• KPI’s that appropriate for your own strategy and
context,that are derived from organizaional drivers and
are appropriate for your level of benchmarking
competence and experience.
• When starting out, avoid being too ambitious too early
on and start with a limited set of basic KPI’s.
• Contemplate ahead of time on the ways in which the
management information resulting from these
benchmarks will be put to use later on in order to avoid
wasting time and resources.
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Benchmarking succes factors
Collection and validation of the data
• Specify precise definitions for each KPI and communicate
this clearly to the parties that will supply the
information.
• Possibly use the 80/20 rule to signal out the most
important objects and make sure the KPI’s are correctly
defined here.
• Establish a clear process for validating the data that is
obtained.
• Either have the business units supply the data
themselves, or have them sign off on the correctness of
the data before they are confronted with the results.
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Benchmarking succes factors
Analysis of the data
• The main challenge here is to make sure that you make
correct divisions in the data and compare only
comparable groups.
• Consider the possible heterogeneity of the dataset
accross different dimensions, namely
• Ownership,
• Function,
• Area.
• Identify and remove possible outliers from the data or
special or unique objects that should be analyzed
seperately.
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Benchmarking succes factors
Possible uses for the results
• Communicate the performance of the CREM department
more succesfully and to raise support for CREM
interventions amongst various stakeholders,
• To raise the efficiency of the portfolio, for example by
helping to identify possible outliers in performance, both
positive and negative
• To reflect on an sharpen the strategic priorities of the
department
• And to inform decisions in possible projects and business
cases.
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Benchmarking succes factors
Feedback
• Use every iteration of the benchmarking process to
reflect on and improve the data collection, and validation
processes.
• Strengthen organizational knowledge, for example by
using misunderstood questions in a survey to signal
areas or departments where more knowledge is needed.
• Continuously work to get the entire portfolio measured
by a uniform set of definitions.
• Reflect on the KPI’s that are used and consider
expanding the set of benchmarks if this is deemed
appropriate.
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Relevance
Scientific relevance
• Results have been compared to current relevant theory
• Discrepancies between theoretical model and reality were explored
• Interesting further research has been identified
Societal relevance
• Help making real estate portfolios more efficient
• Help shift benchmarking towards a more integral measurement of value
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Practical application
• Still a lot of room for improvement
• Inventory of most common benchmarks, hurdles and uses can provide a roadmap
for CREM departments on how to set up or improve their benchmarks
• Companies can get a clear view of where they stand compared to other real estate
departments with respect to their benchmarking competency.
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Recommendations for further research
• Larger scale quantitative study
• Definitions and analysis of benchmarking information
• Influence of the new ways of working on indicator use
• External benchmarking
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