Content uploaded by Christoph Maria Ravesloot
Author content
All content in this area was uploaded by Christoph Maria Ravesloot on Apr 29, 2020
Content may be subject to copyright.
Available via license: CC BY 3.0
Content may be subject to copyright.
Modern Applied Science; Vol. 14, No. 5; 2020
ISSN 1913-1844 E-ISSN 1913-1852
Published by Canadian Center of Science and Education
63
Strategically Measuring Quality of Existing Building Stock
Arie Stapper1 & Christoph Maria Ravesloot1,2
1 Business School Netherlands, Buren, The Netherlands
2 Rotterdam University of Applied Sciences, Rotterdam, The Netherlands
Correspondence: Arie Stapper, Stapper Advies BV, Dorpsstraat 32, 2902BD Capelle aan den IJssel, Netherlands.
E-mail: mail@stapper.eu
Received: December 10, 2019 Accepted: April 24, 2020 Online Published: April 28, 2020
doi:10.5539/mas.v14n5p63 URL: https://doi.org/10.5539/mas.v14n5p63
Abstract
Dutch housing corporations generally have two methods of assessing the strategic value of existing housing
stock. The first is by calculating the financial return on investments with a life expectancy of fifty to sixty years.
The second method is to balance the technical quality against maintenance and renovation planning. A Dutch
housing corporation needed a integrated method, so in a single case study, a new method was developed based
on research on how to monitor the technical and financial assets better.
Four problems were detected: (1) the existing strategy did not seem to be resilient to future changes, (2) there
was no instrument for measuring progress, (3) there was no way to translate strategic data to individual estates
and (4) there was no instrument for monitoring the results of improvements set off against the strategic goals.
With one integrated tool to fix these four problems, an integrated approach to a closed asset management
strategy and policy would be available. Such a tool would make it possible to make adjustments to the strategy
based on facts gained by measuring the results of former adjustments to the strategy. The goal of this paper is to
present the research supporting the design of a new model.
The result, the so called Return Matrix, is a fully elaborated model. It supports the management team in decision
making about strategy (five years) and vision (twenty years) development. It creates insight into and support for
the outcome of the strategy among policy professionals, staff and colleagues. And finally, it creates
understanding among the tenants, it s understood and supported by the civil servants and gets approval and
agreement of cooperation from the municipal executives.
With the knowledge gained by this study, it will not be difficult to compose the instrument for other cases too.
Keywords: asset management, dutch social housing corporation, Netherlands, return matrix, financial return,
social return, strategy measurement model, woningcorporatie
1. Introduction
Dutch housing corporations generally have two methods of assessing the strategic value of existing housing
stock. The first is by calculating the financial return on investments with a life expectancy of fifty to sixty years.
The second method is to balance the technical quality against maintenance and renovation planning, mostly
based on past experience and personal estimation by maintenance officials. However, a combination of both
methods is needed for strategically planning sustainable renovation of existing building stock. After all, the
budget can only be spent once.
1.1 Introduction of the Problem
A Dutch housing corporation in Velsen recognised this strategic problem because of expected, rapidly emerging,
technical and financial changes as well as changing governmental and municipality policies. Therefore, housing
corporations in general, and this housing corporation in particular, needed a more accurate method of monitoring
technical and financial performance indicators for the renovation of existing building stock within strategic asset
management for social housing. In an exploring single case study for the housing corporation Velsen, research
was carried out to gain the knowledge necessary to develop and test a new method to better monitor the technical
and financial assets. This method also had to reflect on possibilities to communicate the results more directly
amongst professionals from the housing corporation and to private and public partners.
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
64
1.2 The Importance of the Problem
Four strategic problems were detected in the daily routine of asset management: (a) the existing strategy did not
seem to be resilient to future changes, (b) there was no instrument for measuring progress, (c) strategic data
could not be translated to individual estates; and, finally, (d) there was no instrument for monitoring the results
of improvements set off against the strategic goals.
Dutch housing corporations in general, and Velsen housing corporation in particular, could solve these four
strategic problems, if they had one integrated tool. An integrated approach to a closed asset management strategy
and policy would allow them to make adjustments to the strategy based on facts gained by measuring the results
of former adjustments to the strategy. A majority of the Dutch social housing stock is old and out of date. The
quality is poor, which means tenants pay little rent. This is true for Velsen too.
Policy makers have little idea of what is the best strategy of improvement. Even if they had, there would be no
instrument to test an improved strategy. Besides, changes in Dutch public policies and changing financial
conditions have to be anticipated.
1.3 The Question Central to the Purpose
As said before, housing corporations generally have two methods of assessing the strategic value of existing
housing stock: the financial return on investments and the technical quality. Both methods were insufficient to
determine what strategy would be best. Therefore, this housing corporation needed a more accurate method of
monitoring technical and financial performance indicators for existing building stock within strategic portfolio
management for social housing. So it was a problem the Housing Company can not measure the strategy.
2. Method
The main question of the research focusses on the single case study of the Velsen housing corporation: In what
way can housing corporation Velsen develop a tool for strategic asset management policy with good technical
and financial detail?
The aim of the research is to gain knowledge about key performance indicators and other ingredients necessary
for a strategic asset management tool. This knowledge will be used to develop a visual monitoring instrument
that will make proper discussion and decision making, based on shared facts about the real technical and
financial performance of existing building stock, possible. A serious strategic challenge like this asks for a very
reliable result. For this reason, an applied scientific approach has been adopted. An extra step in the verification
of the process and in the validation of the results has been added to increase accountability and reliability.
2.1 Literature Research
Firstly, literature research was executed to get more knowledge about the known fail and success factors of
strategic asset management for housing corporations and in social housing. What would be the conditions for
making a strategic asset management policy work properly and for making it resilient? Also, performance
indicators in strategic asset management and in housing policies were looked for, both with private parties and
with public authorities.
Table 1. keywords and sources
Concern Keywords, sources
Single search
BIM, Big Data, added value, collaboration, support, result, vision,
mission, strategy, social housing, NOM, renewable, circular,
renew, renovate, rejuvenate, aging, sustainability, energy,
Composed search social housing estate planning
social housing Dutch quality measurement
critical evaluation Dutch social housing
literature sources scholar.google.nl
Library of ASRE
The literature research ought to show the fail and success factors of strategic asset management for housing
corporations and in social housing. What would be conditions to make a strategic asset management policy work
properly and make it resilient? Also was looked for performance indicators in strategic asset management and in
housing policies, both from private parties as from public authorities. In order to increase reliability, experts were
interviewed on the subject matter.
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
65
2.2 Interviews
Secondly, involved professionals from the housing corporation and stakeholders were interviewed about strategic
policy making in the case of Velsen. What strategic policy is used at the housing corporation and what kinds of
strategic policy are known in literature and amongst professionals? An overview of policies and their
opportunities and risks was made. Special attention was given to the question of how to discuss and how to
decide on the norms for a future resilient strategic asset management policy. The external interviews with the
most important stakeholders should give criteria for a detailed financial and technical evaluation of existing
building stock. To get this information and leave room for unexpected information, semi structured interviews
with partly fixed and partly open questions were designed. The DESTEP analysis method was adopted for the
SWOT diagram. In the case study of Velsen, this matches the quality and results of the previous asset
management tool.
2.3 Compare the Options
Thirdly, literature provided some models of which the information could be compared and combined into some
alternate options. A morphological mapping method with the above mentioned and prioritised criteria was used
to compare the options, leading to the model which was best fit for its purpose and combining technical and
financial perspectives in a strategic asset management tool.
2.4 Tthe Factors and the KPI’s
Fourthly, comparing the factors found in literature as well as in the interviews and the analyses, gave insight into
the possibly useful ingredients of a tool. Comparing the factors and assessing them to decide which were useful
in general and in the specific situation of the case Velsen, a selection was made. For each factor, as many KPIs as
possible were selected, with criteria for each KPI. This was done to increase reliability. For the Velsen case, a
proposal for decision making was made, based on proportional distribution. The final KPIs and their weight were
chosen and by the management team of Velsen.
To improve communication with the users, the result was simplified by presenting it as a linearly scaled scored
number between zero and ten. For each KPI, the score number of six is determined to mean ‘sufficient’, as in
“just good enough’ and the score number of ten is set to be ‘the highest score possibly wished for’. This means a
score higher than ten will be ten, and lower than zero will be zero.
2.5 Implementation
The fifth step was the first implementation of the model at Velsen. All data were collected on the level of the
6.500 separate housing units. To minimize the effect of outliers, each KPI was calculated on the lowest level
(6.500 separate units) before determining the average. To establish that the instrument and the outcomes would
be robust, a data expert was asked to check the data, the data processing and the outcomes.
2.6 Reliability Check
As a final step, the reliability of the model was checked. At the Velsen organization, little identified and
classified information was available. To increase the reliability of the model, new information was gathered for
validation of the outcome of the model and validation of the model itself. The organization consists of separate
teams dealing with four elements (technics, rentability, livability and finance). Each team has its own specific
knowledge of the housing stock. So, for validation, these four knowledge groups were defined in four factors.
Because the knowledge was unclassified and unidentified in this case, the traffic light method was used to
identify the information and to classify the information for each factor. A meeting was organised for each factor
and people with relevant knowledge and experiential experts were invited. In preparation of the group meetings,
maps of the neighborhoods of the city of Velsen were made. In these maps, the four elements of housing stock of
the corporation was visualized by color. During the meeting, the experiential experts were asked to give each
stock of houses a green (= good), yellow (= moderate) or red (= bad) sticker. Subsequently, they were asked for
their top ten of red and their top ten of green. In this way, a five-point-scale for each factor was found, revealing
knowledge from experts and sharing it. To validate these data and to increase reliability, a discussion was
organised at the end of the meeting. After this discussion, minor changes were allowed for.
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
66
3. Results
Literature research was carried out to find out about the known fail and success factors of strategic asset
management for social housing corporations. What would be conditions for making a strategic asset management
policy work properly and for making it resilient? Additional literature research was done on the performance
indicators (KPIs) in strategic asset management, in housing policies, with private parties and public authorities.
3.1 Recent Scientific Literature
The search for scientific literature has yielded a broad spectrum of articles, such as those on the effect of the
development of social real estate to be seen as an investment on our government (Loon, 2017), on the effect on
housing associations, not regarding the value of real estate, but regarding the development of the values of the
organization (Nieboer & Gruis, 2016), on making homes sustainable for the elderly and how to involve them
(Boerenfijn, 2018), on the effect of financial crisis on new construction and land policy and on renovations and
real estate strategy (Buitelaar, 2016), on the relationship between government policy and rent policy (Tu, 2015),
on the financial problems of Vestia and an explanation of the "economization" of the social housing sector
(Aalbers, 2017), and on the development of an evaluation model to support the decisions of public authorities,
which influence urban renewal and social housing, and which were implemented with the involvement of private
investors (Tajani, 2015).
3.2 Older Scientific Literature
This search for information led to an additional amount of (indirectly) useful literature. Firstly, a publication
about the potential applications of performance measurement as well as the indicators that can be used to
measure financial and social returns. “The Net Present Value is the Most Relevant Indicator” (Gruis, 2005). Also,
26 social return indicators in 4 categories are described in this article.
Secondly, a report by the Sheffield housing department, which stated: “Social theory is all very well, but the
opinions of the people who live there should be the criterion by which the success or failure of Park Hill must be
measured” (Hollow, 2010). Nieboer (2005) stated that real estate investors in the Netherlands decide about
physical and technical development only partly by using their reasoning: the decisions are also partly based on
intuition. The periodic evaluations for strategic stock management would only be based on financial calculations
to weigh competing signals and interests. Some stated that a systematic weighing of other relevant aspects is
unnecessary or even unrealistic. Despite the periodic evaluations of all estates, landlords would not have a
systematic approach to weigh the relative importance of the different aspects. Consequently, this part of the
process remains a ‘black box’.
According to Mossel (2010), the maintenance of heating and water systems and maintenance of hinges and locks
of windows and external doors are the very important maintenance services of housing associations to customers.
The exterior paintwork has a high importance when obtained with the regression analysis method, but not when
directly asked. Veenhoven (2002) states that social policy makers need both objective and subjective indicators.
Though subjective indicators have their limitations, objective indicators also labor under serious shortcomings.
For some purposes objective indicators are best suited, for other uses subjective indicators are preferable. The
challenge of social reporting is to combine the strengths of these indicators and to make sense of the
discrepancies they show.
Figure 1. Beleids8baan (Conijn, 2013)
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
67
Relevance
Although these are all fascinating and some (indirectly) helpful articles, I have not come across any actual
scientific literature that can directly help to come up with a good instrument to test a portfolio plan of
Woningbedrijf Velsen.
Figure 2. Real Estate pyramid (Conijn, 2013)
3.3 Professional Literature
Some professional literature about models for the Dutch social housing corporations exists only in Dutch
language. It describes the process of making a real estate strategy. The model connects the strategic process with
de tactical and operational process. This model is called the ‘Beleids8baan’ (figure 1) and is widely used by
Dutch housing corporations (Os, 2013).
Ortec Finance has integrated the activities, output and process on the levels Strategy, Tactics and Operations in
one picture (figure 2: The Real Estate Pyramid). The output of the Real Estate Strategy is defined as the
‘Portefeuilleplan’ and this covers five years in the future of the housing corporation (Conijn, 2013).
The BCG matrix is an instrument for strategic decision making. Two of the largest Dutch housing corporations
use a similar model (Conijn, 2017). These corporations are Havensteder and Vestia. This model is called the
‘Rendementsmatrix’. This model looks useful, although there is no description of the model or how it has been
composed.
3.4 Interviews with Experts
A model like the BCG matrix can also be found in literature. In Dutch it is called the ‘Rendementsmatrix’
(Conijn, 2013), the English translation would be ‘Return Matrix’. This model is described by Ortec-finance as an
instrument for strategic decision making for Dutch social housing corporations. This model looks like the BCG
matrix. Both have two axes and four squares. The BCG matrix uses the axes ‘marked share’ and ‘growth rate’.
The Return Matrix uses the axes ‘financial return’ and ‘social return’.
mas.ccsene
t
The Retu
r
formulas,
corporatio
Vestia (wi
t
to collect
a
and the ne
These int
e
worked o
u
3.5 Criter
i
The outco
m
it clearly
a
energy qu
a
disordere
d
demograp
h
quality of
p
oints. T
h
are weak
f
Risks are
d
Tab l e 2 . s
c
t
.org
r
n Matrix loo
k
for example
t
ns. So, two i
n
t
h Paul Tazel
a
a
dditional inf
o
eded informat
e
rviews show
e
u
t in factors,
K
i
a for a Mode
l
m
e of the int
e
a
nd stick to it
f
a
lity, diversity
d
people sho
w
h
ic, economi
c
the service, r
e
h
e old houses,
f
actors. Oppor
t
d
isappearing s
u
c
ore table
k
s useful. Th
t
he factors or
n
terviews wer
e
a
ar). The inter
v
o
rmation abou
t
ion and data.
e
d that the e
x
K
PIs, norms, s
c
l
e
rviews with t
h
f
or long. Valu
e
and affordab
i
w
ed up. Besi
d
c
, social, tech
n
e
ntability, fina
n
technical qua
l
t
unities are th
e
u
bsidies, decr
e
Moder
n
Figure
3
ere is no inf
o
the KPIs, in
e
planned, one
v
iews with m
e
t
the model its
x
isting model
c
ales etc. Flori
s
h
e stakeholde
r
e
s which were
i
lity. In additi
o
d
es, the local
n
ological, eco
n
cial position
a
l
ity, energy q
u
e
strong mark
e
e
asing cash fl
o
Score
1
2
3
4
5
n
Applied Scien
c
68
3
. Return Mat
r
o
rmation abo
u
literature. It
for each cor
p
e
mbers of the
p
elf, and to dis
c
is mainly ab
o
s
Ledder advi
s
r
s was the assi
considered i
m
o
n, a preferenc
counsel offer
e
logical and a
a
nd the collab
o
u
ality, afforda
b
e
t demand, col
l
o
ws through a
d
Valuatio
n
Ver y b a
d
Bad
Sufficien
t
Good
Very goo
d
c
e
r
ix
u
t the theory
is used by t
w
p
oration: Hav
e
p
olicy staff o
f
c
uss the norm
s
o
ut how to th
i
s
ed to use the
t
gnment to ma
k
m
portant for th
e
e for smaller
h
e
d help. The
political ana
l
o
ration with s
t
b
ility, slow de
c
l
abora
t
ion an
d
d
ditional taxe
s
n
d
t
d
behind this
m
w
o of the lar
g
e
nsteder (with
f
these corpor
a
s
, the key per
f
i
nk. The Ret
u
t
actical KPIs
fo
k
e a clear str
a
e
property we
r
h
ouses and att
e
DESTEP an
a
l
ysis, resultin
g
t
akeholders ar
e
c
ision making
d
the use of ne
w
s
, financeabilit
y
Vol. 14, No. 5;
m
odel or abo
u
g
est Dutch ho
u
Floris Ledder
a
tions was des
i
f
ormance indi
c
u
rn Matrix wa
fo
r this model.
a
tegy, commu
n
r
e technical q
u
e
ntion for lon
e
a
lysis consists
g
in a SWOT
.
e
considered s
t
and quality
o
w
energy solu
t
y
and rentabil
i
2020
u
t the
u
sing
)
and
i
gned
c
ators
s
not
n
icate
u
ality,
e
ly or
of a
The
t
rong
f life
t
ions.
i
ty.
mas.ccsene
t
Tab l e 3 . C
C
C
R
e
Me
a
R
The inter
v
according
clear ther
e
followed
b
for the ho
u
for the m
o
are techni
c
3.6 Choic
e
The BCG
the price,
process o
f
and not m
u
reliability,
showed th
3.7 Choic
e
The mode
l
3.7.1 Fina
n
To realiz
e
regarding
WSW use
s
In practic
e
LtV (Loa
n
useful. Th
WSW for
financial
K
The loan
a
t
.org
riteria for mo
d
Cr
iteria
C
la
r
ity
e
liability
a
surability
R
apidity
Price
v
iews with st
a
to them. The
e
was only on
b
y technical q
u
u
sing corpora
t
o
del are clarit
y
c
al quality, en
e
e
of Model
matrix is a w
e
rapidity and r
f
decision ma
k
u
ch unambig
u
measurabilit
y
at this instru
m
e
of Factors
l
uses two di
m
n
cial Return
D
e
a new strat
e
loans for this
s
an instrume
n
e
, two KPIs ar
e
n
to Value) is
m
e norms of th
e
the long ter
m
K
PI fo
r
makin
g
a
nd the value
c
d
el
Ae
a
keholders ga
v
first thing th
e
e chance to
m
u
ality and div
e
t
ion was the s
u
y
or unambigu
i
e
rgy quality, fi
e
ll-known ins
t
eliability. The
k
ing, while it
d
u
ity. The inter
v
y
, rapidity and
m
ent meets all
t
Figure 4.
m
ensions: fina
n
D
imension
e
gy, a housi
n
sector in the
N
n
t to measure t
h
e
most import
a
m
ost importa
n
e
WSW limit
t
m
is LtV. Th
e
g
strategic ass
e
c
an be influen
c
Aedex
model
subjec
t
model
Integra
t
model
Moder
n
e
dex model
2
4
5
2
3
v
e insight into
e
y asked for
w
m
ake a good
p
e
rsity of stoc
k
.
u
ggestion that
i
ty, reliability,
i
nance, old ho
u
t
rument for st
r
downside fo
r
d
oes not meas
u
v
iews with ex
p
a low price.
T
t
he c
r
iteria we
Morphologic
a
n
cial return an
d
n
g corporatio
n
N
etherlands is
h
e financial si
t
a
nt. ICR (Inte
r
n
t for the long
t
he financial
p
e
case study
e
e
t manageme
n
c
ed by strateg
y
t
ive
t
ed
n
Applied Scien
c
69
Su
bj
the most im
p
w
as clarity a
n
p
lan. Their se
c
.
The last pri
m
the houses c
o
measurability
,
u
ses, affordab
i
r
ategic decisi
o
r
social housi
n
u
re the right t
h
p
erts showed t
h
T
hese intervie
w
should meet.
a
l map for the
d
social return
.
n
has to borr
o
the WSW. Th
e
t
uation of eac
h
r
est Coverage
term. ICR a
n
p
ossibilities of
e
stablishes th
e
n
t policy.
y
. The loan is
t
c
e
bj
ective model
4
2
2
5
5
p
ortant standa
r
n
d honoring e
x
c
ond priority
w
m
e factor was
a
o
uld be smalle
,
rapidity and
p
i
lity and the q
u
o
n making. Th
n
g corporation
h
ings either, s
o
h
at the Return
w
s were a gre
a
alternate solu
t
.
o
w money. T
h
e
y provide ba
n
h
housing cor
p
Ratio) is mos
t
n
d LtV are wi
d
a Dutch hous
i
e
LtV of the
W
t
he outcome o
f
I
nt
e
r
ds a good st
r
x
isting comm
i
w
as the envir
o
a
ffordability.
A
r. So, the mo
s
p
rice. The mo
s
u
ality of life.
e upsides of t
h
s is that it do
e
o
it does not p
r
Matrix can pr
o
a
t inspiration t
o
t
ions
h
e most imp
o
n
ks with finan
p
oration.
t
important fo
r
d
ely accepted
i
ng corporatio
W
SW to be
t
f
the policy. T
h
Vol. 14, No. 5;
e
grated mode
l
5
4
4
5
5
r
ategy should
i
tments. This
m
o
nment and e
n
A
n interesting
s
t important c
r
s
t important f
a
h
e BCG matri
e
s not facilita
t
r
ovide much c
l
o
vide much c
l
o
me, becaus
e
o
rtant organi
z
cial guarantee
r
the short ter
m
and used, and
n. The norm
o
t
he most imp
o
h
is makes the
v
2020
l
meet
m
ade
n
ergy,
a
side
i
teria
a
ctors
x
are
e the
l
arity
arity,
they
ation
.
The
m
and
very
o
f the
o
rtant
v
alue
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
70
the part to be actively influenced. So, a good method to measure the success of the strategic asset management
policy should measure the value. According to the policy of WSW, the value is defined as the NPV (Net Present
Value, in Dutch the ‘Bedrijfswaarde’). This dimension is composed of income (rent) and expenses (maintenance,
management and interest costs). The NPV is widely accepted, used and useful too. So, the value is the factor and
the NPV is the KPI.
Table 4. Financial Return KPI’s
Instruments Values
* KPI's weight value 0 value 6 value 10
Financial value 100%
* NPV (Net Present Value) in € 100% - 30.000 50.000
Table 5. Social Return KPI’s
Instruments Values
* KPI's weight value 0 value 6 value 10
Energetic quality 20%
* Energy index 20% 2,50 2 1,00
Affordability 20%
* Net rent in € 10% 710 524 400
* rent class 10% 5 1
Living pleasure 20%
* WWS points 5% 80 134 170
* accessibility 5% 0 6 10
* WOZ (registered) value in € 5% 70.000 178.000 250.000
* M2 5% 40 58 70
Real Estate Quality 20%
* Condition 'score' 3% 1 6 10
* condition ROG (Red-Orange-Green) 3% 0 10
* Lifespan in years 3% 0 20 33
* Age in years 3% 75 30 0
* complaints maintenance (€/vhe) 2% 1.000 400 0
* complaints per house 2% 3 1 0
* mutation maintenance 2% 1.000 400 0
* technical ROG (Red-Orange-Green) 2% red orange green
Livability 10%
* WOZ / M2 5% 1.500 2.000
* Livable ROG (Red-Orange-Green) 5% 0 2,4 4
Rentability 10%
* reaction rate 3% 0 100
* refusals 3% 10 0
* Rentable ROG (Red-Orange-Green) 4% red orange green
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
71
3.7.2 Social Return Dimension
Loosbroek (2005) describes the factors and KPIs needed to measure the success of tactical plans and realization.
These factors are primarily affordability, availability and technical quality. Next are popularity and the quality of
living and life. The new factor is sustainability, added due to current events. Because of missing information
about which factor is more important, all these factors were selected and used with the same weight in our model.
After consulting the management team, the Social Return Dimension was composed of energy quality (20%),
affordability (20%), residential quality (20%), technical quality (20%), quality of life (10%) and rentability
(10%).
Figure 5. Final result of the research (optimized for the colors)
3.8 Choice of KPIs
Conijn (2017) presents a Dutch study about the use of tactical KPIs. This was helpful. Because of missing
information about which KPI is more or most important, all these KPIs were selected and used with the same
weight. For this case, 23 KPIs were used.
3.9 Addition of Data
All necessary data was available. So, a data model was made, the data were added and the ‘Return Matrix’ (in
Dutch ‘Rendementsmatrix’) was composed. The next step was checking and validating the outcome on both axes
with experiential experts from Finance and ICT. Except for a few small details, no adjustments were needed.
3.10 Increase of Reliability
To identify the unidentified information, we interviewed professionals from the housing corporation. To classify
the unclassified information, we used the ‘traffic light method’. By combining these two methods, the color red,
orange or green was assigned to every group of houses for its technical quality, its quality of life and its
rentability. Up-to-date financial information was used for determining the financial return of each group of
houses. Using the Likert-scale, this information was transformed into a rating for each group of houses.
The outcome visualized that there is a ‘top 10’ of groups of houses which need more attention because of the low
financial and strategic scores (dark red+ on the chart). In addition to the scoring and ranking sessions, the
arguments for the rankings were discussed. These discussions showed that the professionals know a lot about the
property and if the right question is asked, they provide essential information. The answers were very helpful in
finding out how to realize a lot of quality improvement with little money.
Comparing the chart ‘Final result of the research’ (figure 9) with the ‘Chart on base of the internal interviews’
(figure 11), it can be concluded that the same objects appear in the top 10 results (= red) of both charts. This fact
was very helpful in creating support for the implementation stage, because that the message internal
professionals picked up, was: “You already knew it. The only thing the management had to do, was to ask the
mas.ccsene
t
right ques
t
4. Discus
s
The case
s
measurin
g
financial
s
also impo
r
sustainabi
l
DESTEP
a
The finan
c
there is a
f
available
f
WSW bac
LtV one o
Value can
(Net Pres
e
t
.org
t
ions.”
Figu
r
s
ion
s
tudy was carr
i
g
the success
o
s
trength of th
e
r
tant. The ca
s
l
ity is low an
d
a
nalysis.
c
ial case stud
y
f
ree monthly
c
f
or investment
king is neces
s
f the borders
o
be influenced
e
nt Value, ‘Be
d
Fi
g
r
e 7. Result o
f
i
ed out accord
i
o
f the strategy
e
corporation.
s
e study of th
e
d
the rent is l
o
y
was about t
h
c
ash income o
f
. To invest m
o
s
ary, and the
m
o
f a new strat
e
by strategy.
T
d
rijfswaarde’
i
Moder
n
g
ure 6. Out
p
u
t
f
the ‘traffic-li
g
i
ng to the DE
S
: technical, e
n
Local presen
c
e
property in
f
o
w. So, there
i
h
e possibilitie
s
f
1 million eu
r
o
re money, the
m
ost importan
t
e
gic plan. LtV
T
he Financial
V
i
n Dutch). Th
e
n
Applied Scien
c
72
t
of ‘traffic-lig
g
h
t
-method’ (
n
S
TEP analysis
.
n
ergy and livi
n
c
e and visibili
t
f
ormation sho
w
i
s a serious g
a
s
to invest in
r
os. So, for th
e
housing corp
o
t
KPI for this
h
has two parts:
V
alue of the R
e
e
second outc
o
c
e
h
t
-method’
n
ot optimized
f
.
This analysi
s
n
g quality of
t
t
y of local in
v
w
s the house
s
a
p between th
e
the realizatio
n
e
next five ye
a
o
ration has to
r
h
ousing corpo
r
loan and val
u
e
al Estate for
a
o
me of the fi
n
f
or the colors)
s
determined o
b
t
he houses, va
l
v
olvement of
t
s
are old, the
e
se results an
d
n
of a strategi
c
a
rs there will
b
r
ent money. T
o
r
ation is the
L
u
e. Loan is the
a
housing cor
p
n
ancial case st
u
Vol. 14, No. 5;
b
jective criter
i
l
ue for mone
y
t
he corporatio
n
quality is lo
w
d
the criteria
o
c
plan. First
o
b
e 60 million
e
o
increase the
L
tV. This mak
e
output of
t
he
p
oration is the
u
dy is that th
e
2020
i
a for
y
, and
n
are
w
, the
o
f the
o
f all,
e
uros
loan,
e
s the
plan.
NPV
loan
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
73
can increase with a maximum of 100 million euros. This totals 160 million euros as the maximum for investment.
This is not enough to do what is needed for all the houses. The situation is urgent too, because of the expected,
rapidly emerging technical and financial changes as well as changing public policies. So, the corporation has to
make a plan and they need an instrument to measure the quality of the plan. The Return Matrix does it all.
4.1 Discussion of the Norms for Resilient Strategic Asset Management Policy
A good strategic management policy is well-balanced between what is needed and what is possible. Besides, a
good strategy should allow for its quality to be measured. A resilient strategy should have the option of being
monitored, preferably each year and at least once in five years. It is also important the strategy can be translated
to the tactical level. And, last but not least, to increase reliability, it is important to integrate as much information
as available. The Return Matrix does it all.
4.2 Discussion of Conditions for An Improved Method
The need for this model is found in asset management, which fits the model of the “Beleids8baan” as described
in Os (2013). And the opportunity necessary is found in financial policy, which fits one of the norms of the WSW.
The translation into practical terms is new and not found in existing literature. The possibility to compare the
known to the unknown data (to the data with the opinions) is new and makes it possible to get additional
information and increase reliability.
With the Return Matrix as an integrated tool, it is possible to fix the strategic problem of decision making. It
integrates technical data, environmental data, financial data and the expert opinions of the professionals involved.
The integrated approach to a closed asset management strategy and policy (between strategy and tactics) has
now become available. This model for creating strategy and policy will make it possible to decide about
adjustments to the strategy based on facts gained from measuring the results of former adjustments to the
strategy.
4.3 Discussion of the Decision-Making Result
The internal application of this model was meant to facilitate decision making regarding strategy (five years) and
vision (twenty years) for the management team. It generated a lot of support from and understanding among the
experts, the staff and the other colleagues.
The external application of this model resulted in agreement from and cooperation with the municipal executive,
support and understanding from the civil servants and acceptance from the tenants.
The (very satisfied) CEO found this model very helpful because of the unambiguous visual representation, the
combination of the different sources of information and the widely supported outcome, internally ánd externally.
They have not changed anything after the model was finished.
4.4 Conclusions and Recommendations
Taking everything discussed above into consideration, it will not be difficult to compose the instrument for other
cases too. The clarity of the instrument gives direction to and understanding of the necessary decisions. This was
very helpful while gaining support from the many stakeholders, such as the board, the management team, the
professionals and the policy staff of the housing company; but also from the local tenants, civil servants and the
municipal executive. This support was very helpful in the process of planning and taking a final decision. It also
helped decrease the time and effort this process took. The factors and the KPIs of the instrument were helpful in
clarifying the reasons behind the decisions.
Another conclusion is that strategic questions can be answered by asking the right people the right questions in
the right way without using specific data, because the internal professionals have the information in their minds.
This information can be used by an instrument as a quick scan and as a check to increase its reliability.
It is recommended:
1. To be aware of any low-hanging fruit, because this is valuable and good value for money.
2. Also, it is important to document the steps taken while composing the instrument for any specific case and to
remember what information was necessary for this process. Now all this information and knowledge is available,
but this might not be so at the time an update of the instrument will be necessary in five years’ time. To prevent
wasting time in the future, make sure to store this information carefully!
3. Making a new policy is time consuming, so it is recommended to start making the update a year before
finishing the actual policy. Objective information is valuable for performance improvement, so participating and
using a benchmark is recommended.
mas.ccsenet.org Modern Applied Science Vol. 14, No. 5; 2020
74
4. Finally, a house is much more than just KPIs, so go out and have a look to check the plan with reality to
prevent making an expensive, wrong decision.
WSW is planning to change the content of ‘value’ in the near future. This can influence the outcome of the
instrument. It is WSW’s expectation there will only be a small effect.
It was a surprise this elementary instrument (and its detailed elaboration) had not been available in scientific
literature before: this provided a good reason to write this Journal Paper. It would be interesting to further
investigate any possibilities to improve the ‘Return Matrix’ by reducing the amount of KPIs of the instrument,
maybe to 5 or 6 KPIs.
References
Aalbers, Manuel B. (2017). The Financialization of a Social Housing Provider. International Journal of Urban
Regional Research, 41(4), 572–587, conference paper, https://doi.org/10.1111/1468-2427.12520
Boerenfijn P. (2018). A multi-case study of innovations in energy performance of social housing for older adults
in the Netherlands. Energy and Buildings, 158(1), January 2018, Pages 1762-1769.
https://doi.org/10.1016/j.enbuild.2017.10.101
Buitelaar, Edwin & Arjan Bregman. (2016). Dutch land development institutions in the face of crisis: trembling
pillars in the planners’ paradise. European Planning Studies, 24, Theme issue: Crisis and renewal of
contemporary urban planning, Pages 1281-1294. https://doi.org/10.1080/09654313.2016.1168785
Conijn, Johan. (2013). Portefeuille sturing bij Woningcorporaties. Rotterdam: Ortec-Finance
Conijn, Johan. (2017). Handreiking performance analyse. http://insights.ortec-finance.com/nl-nl/
2017/10/16/handreiking-performance-analyse, 19-03-2018.
Gruis, Vincent. (2005). Financial and Social Returns in Housing Asset Management: Theory and Dutch Housing
Associations’ Practice. Urban Studies, 42(10), 1771–1794, September 2005.
https://doi.org/10.1080%2F00420980500231696
Hollow, Matthew. (2010). Governmentality on the Park Hill estate: The rationality of public housing. Urban
History, 37(1), 117 – 135. 1 april 2010. https://doi.org/10.1017/S096392681000009X
Loon, Jannes van. (2017). How real estate became ‘just another asset class. European Planning Studies, 25(2),
Pages 221-240. https://doi.org/10.1080/09654313.2016.1277693
Loosbroek. (2005). Strategische Voorraadbeleid van Woningcorporaties,
http://docplayer.nl/12752427-Strategisch-voorraadbeleid-van-woningcorporaties.html , 19-03-2018.
Mossel, Henk-Jan van & Sylvia J.T. Jansen. (2010). Maintenance services in social housing: what do residents
find important? Structural Survey, 28(3), 215-229. https://doi.org/10.1108/02630801011058942
Nieboer, Nico. (2005). How strategic is housing asset management of institutional real estate investors?
Property Management, 23(1), 22-32. https://doi.org/10.1108/02637470510580561
Nieboer, Nico & Vincent Gruis. (2016). The continued retreat of non-profit housing providers in the Netherlands.
Journal of Housing and the Built Environment, 31(2), 277–295. https://doi.org/10.1007/s10901-015-9458-1
Os, P. Van (2013). Mensen, stenen, geld – Het beleidsproces bij woningcorporaties. Rigo Research & Advies BV.
Tajani, Francesco & Pierluigi Morano. (2015). An evaluation model of the financial feasibility of social housing
in urban redevelopment. Property Management, 33(2), 133-151.
https://doi.org/10.1108/PM-02-2014-0007
Tu, Qi. (2017). House prices and long-term equilibrium in the regulated market of the Netherlands. Housing
Studies, 1-25, Received 09 Jul 2015, Accepted 21 Jun 2017, Published online: 18 Jul 2017.
https://doi.org/10.1080/02673037.2017.1346786
Veenhoven, Ruut (2002). Why social policy needs subjective indicators. Social Indicators Research, 58, 33-45,
ISSN 0303-8300. https://doi.org/10.1023/A:1015723614574
Copyrights
Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution
license (http://creativecommons.org/licenses/by/3.0/).
