Tailoring the Business Modelling Method for R&D
L. O. Meertens, N. Sweet and M. E. Iacob
University of Twente, PO Box 217, Enschede, The Netherlands
{l.o.meertens, m.e.iacob}@utwente.nl
Keywords: Business modelling, modelling method, business models, research & development.
Abstract: While the benefits of innovation seem to be clear intuitively, Research and Development (R&D) organisations
are struggling to show the value they add. Especially in times of crisis, the result is that they get the first
budget cuts to reduce costs in the short term. This causes companies, industries, or even whole economies, to
lose competitive advantage in the long run. The field of business modelling deals with the creation and
capturing of value. However, it has not yet provided a method tailored to R&D previously. Building upon
earlier work on business modelling, we adapt the Business Modelling Method (BMM) to the field of R&D.
1 INTRODUCTION: CREATING
VALUE WITH R&D
For a company to grow, it must keep ahead of
competitors whenever possible. To do this,
companies must innovate, which often depends on
Research and Development (R&D). Following this
reasoning, investing in R&D would give competitive
advantage. However, it is not that simple. A higher
R&D spending does not automatically lead to more
or better innovation. R&D is difficult to manage,
while the success is not known in advance.
Because the direct effect is hard to measure, it is
interesting to see how R&D adds value. This question
remains unanswered since the beginning of research
on R&D.
The field of business modelling researches the
creation and capturing of value. A business model is
a simplified representation of reality which tries to
show how a company does business or creates value.
It is interesting to combine the fields of R&D and
business modelling to expose the business model
behind R&D. Translation of this interest to scientific
research leads to the main research question of this
paper:
How to build a business model for a research and
development organisation?
The research question combines two scientific areas,
the one of business model research and the one of
R&D research. R&D research is related closely to
innovation research and is intertwined with various
fields of expertise, such as knowledge management,
marketing, production, and so on.
Business modelling is a field with many changing
factors in the past two decades. The rise of
information technology, the introduction of a new
distribution channel ‘the internet’, and other new
forms of communication, together with the rise of
globalization, makes business model research an
interesting topic (Osterwalder, Pigneur, & Tucci,
2005).
Based on Vermolen (2010), Meertens, Iacob, &
Nieuwenhuis (2011) conclude that current literature
provides no methodological approach for the design
and specification of business models. In an attempt to
make business modelling a science instead of an art,
Meertens et al. (2011) propose a method that enables
the development of business models in a structured
and repeatable manner. They jump in one of the
research gaps defined by Vermolen (2010), as
‘Design’, and by Pateli and Giaglis (2004), as ‘Design
tools’. In this paper, we further advance this method
by demonstrating how it can be tailored. In this case,
we tailor it for the field of R&D.
The structure of the paper is as follows. Section 2
reviews current literature on business modelling and
identifies typical characteristics of research and
development. Section 3 provides a design science
method to tailor the BMM to R&D. By applying that
method, section 4 tailors BMM based on R&D
characteristics. In section 5, the first four steps of the
tailored BMM are demonstrated by means of a case
study. The last section consists of conclusions and
provides directions for further research.
96
Meertens L., Sweet N. and Iacob M.
Tailoring the Business Modelling Method for RD.
DOI: 10.5220/0005885900960106
In Proceedings of the Fifth International Symposium on Business Modeling and Software Design (BMSD 2015), pages 96-106
ISBN: 978-989-758-111-3
Copyright
c
2015 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
2 LITERATURE REVIEW:
BUSINESS MODELLING AND
R&D CHARACTERISTICS
This section is divided in two parts: business
modelling and R&D characteristics. First, in the
business model section (2.1), a business modelling
method is chosen and presented. Then, in the R&D
section (2.2), the characteristics of R&D are
discussed.
2.1 Business Modelling
The term ‘business model’ is often used, especially in
the entrepreneurial and management field, but also in
other areas. The combination of these two words is
used for multiple purposes with significant different
meanings. This is mostly due to the fact that the term
comes from different perspectives like e-business,
strategy, technology, and information systems (Zott
& Amit, 2010). In 2005, (Shafer, Smith, & Linder,
2005) found 12 definitions in literature with 42
different components. At the same time Osterwalder
et al. (2005) received 54 different definitions from
participants in the IS community. Nevertheless, no
consensus concerning the definition of a business
model (Pateli & Giaglis, 2004; Vermolen, 2010) from
an academic perspective has been reached. In this
research, the definition given by Meertens et al.
(2011) is followed: “A business model is a simplified
representation that accounts for the known and
inferred properties of the business or industry as a
whole, which may be used to study its characteristics
further...”.
We choose this definition, as it indicates the use
of a business model, not only as a design artefact, but
also from a business engineering perspective.
Besides the lack of a generally accepted
definition, no widely accepted methods for the design
of business models exists. To the best of our
knowledge, Meertens et al. (2011) propose the only
method to build a business model in a generic and
systematic way. Therefore, we focus on this Business
Modelling Method (BMM) in this paper. Application
of this method results in at least two business models.
One business model reflects the ‘as-is’ (current)
situation of the business, and the other reflects the ‘to-
be’ (target) business model(s). This represents the
potential impact on the business model after adoption
of innovative technologies or more efficient business
processes (Meertens et al., 2011).
The BMM describes six steps using specific
methods, techniques or tools. The first four steps
concern the creation of the ‘as-is’ business model:
1. Identify roles
2. Recognize relations
3. Specify activities
4. Quantify model
The remaining two steps concern developing the ‘to-
be’ model:
5. Design alternatives
6. Analyse alternatives
Meertens et al. (2011) provide the BMM only as a
baseline methodology, with a limited amount of
concepts. The methodology has to be extended and/or
tailored to specific situations. Each of the steps can de
detailed further by inserting applicable techniques.
The specific situation for this research is an R&D
organisation, which means that the known and
inferred properties of R&D are needed to tailor the
method.
2.2 R&D Characteristics
To discover the known and inferred properties of
R&D, we review the literature to investigate what the
Table 1: Concept matrix of selected R&D literature.
Projectmanagement
Managingactivities
Riskmanagement
Costmanagement
Value
Externallinkages
(Ali, 1994)

(Balachandra & Friar, 1997)
● ●
(Brockhoff, Koch, & Pearson,
1997)
● ● ●
(Chesbrough, 2003)

(Coombs, McMeekin, & Pybus,
1998)
●
(Sherman & Olsen, 1996)

(Healy, Myers, & Howe, 2002)

(Kleinschmidt & Cooper, 1991)

(Lev, Sarath, & Sougiannis, 2005)

(Liberatore & Titus, 1983)
●
(Morandi, 2011)
●
(Nobelius, 2004)

(Pinto & Covin, 1989)
●
Tailoring the Business Modelling Method for R&D
97
specific characteristics of R&D are. We follow an
explicit and systematic methodology to conduct the
literature review. Based on the literature review, we
selected the relevant and useful papers for this
research (Sweet, 2012).
By analysing the selected literature, we derive the
main concepts used to describe R&D. Table 1 shows
a concept matrix with the selected literature. Each of
the concepts is characteristic of R&D. In the
following sub-sections, we discuss each of the
characteristics.
2.2.1 Project-oriented
Liberatore and Titus (1983) notice that R&D
management research has an emphasis on project
management, which is in line with the conclusions of
Coombs, McMeekin, & Pybus (1998), and others
(Balachandra & Friar, 1997; Brockhoff, Koch, &
Pearson, 1997), that project management has an
important role in R&D.
R&D consists of projects. Pinto and Covin (1989)
state that projects usually have the following
attributes:
1. a specified limited budget
2. a specified time frame or duration
3. a preordained performance goal or set of goals
4. a series of complex, interrelated activities
These attributes lead to a set of characteristics and
issues, which are specific for R&D.
2.2.2 Risk Management
Pinto and Covin (1989) notice the overt risks, which
are familiar to R&D projects. Ali (1994) mentions a
lack or loss of project support and uncertain resource
requirements. The duration of an R&D project can be
very long (Brockhoff et al., 1997), especially for
radical innovation (McDermott & O’Connor, 2002;
Veryzer, 1998), which makes it harder and more risky
to determine the allocation of resources and set
reasonable goals. The same goes for project support,
which is important for R&D, because R&D benefits
are often only seen on the long term and success rates
are often low (Pinto & Covin, 1989; Sherman &
Olsen, 1996). The outcomes of R&D projects are
difficult to predict (Balachandra & Friar, 1997;
Brockhoff et al., 1997; Pinto & Covin, 1989), which,
together with the managerial aversion of taking risk,
makes risk management an important R&D
characteristic.
2.2.3 Managing Activities
R&D activities are often considered as a black box,
which is hard to systematically manage and control.
According to Brockhoff et al. (1997), R&D activities
are more often non-repetitive. Which is in line with
Pinto and Covin (1989), who state that activities
involved in R&D project execution are less amenable
to scheduling. A project is a series of complex
interrelated activities and the task uncertainty
(Morandi, 2013) involving R&D processes makes it
even more complex. However, because it is difficult
to manage and control R&D activities, this does not
mean it should be neglected. It is a common
understanding that the distinguished types of
innovation need to be managed differently.
Incremental innovation is more structured than
radical innovation, therefore the same management
and control techniques cannot always be used
interchangeable.
2.2.4 Value
Value is hard to determine because the success of the
outcome is not known. Even if the outcome definitely
leads to a patent, then the lifetime of that outcome or
product is not predictable. The expected returns from
incremental innovations are lower than from radical
innovations (Kleinschmidt & Cooper, 1991).
However, the risk associated with their development
and commercialisation is lower than from radical
innovations. Incremental innovations are important
for the firm’s overall profitability (Kleinschmidt &
Cooper, 1991).
2.2.5 Cost Management
Liberatore and Titus (1983) address the existence of
cost-effective techniques that can improve project
management for R&D. However, costing techniques
may not directly apply because of (lack of)
availability of information, which is in line with
earlier mentioned uncertainties. Uncertainty is why
financial accounting rules treat R&D as an expense
instead of the capitalisation of costs (Healy, Myers, &
Howe, 2002; Lev, Sarath, & Sougiannis, 2005).
Because the success of a R&D project is not known,
and neither is the eventual life time of the R&D
outcome, it is impossible to capitalise the R&D costs
without the big risk of manipulation of earnings
(Healy et al., 2002; Lev et al., 2005). The downside is
that intangible assets are often undervalued.
Fifth International Symposium on Business Modeling and Software Design
98
2.2.6 External Linkages
Rothwell (1994) mentions five generations of R&D.
Characteristic for the fifth generation is the emphasis
on external linkages, in other words R&D as a
network. The focus is on collaboration within a wider
system, involving competitors, suppliers, distributors,
etc.(Nobelius, 2004). This is in line with open
innovation that Chesborugh (2003) proposes. He
defines it as a paradigm that assumes that firms can
and should use external ideas as well as internal ideas,
and internal and external paths to market, as firms
look to advance their technology.
3 METHOD: DESIGN SCIENCE
APPROACH TO TAILOR THE
BMM TO R&D
Tailoring the BMM to R&D is a typical example of
design science. The result of this research consists of
artefacts at two levels according to the levels of
Gregor and Hevner (2013). We aim to contribute with
a second level (adapted method: the BMM4R&D)
and a first level (applied case: SBT) artefacts. We do
not have the intention to contribute to the third level
(grand design theory).
In the light of Gregor and Hevner (2013), we
position our research in the exaptation quadrant.
Exaptation in this context means that we attempt to
use the previously developed Business Modelling
Method (BMM) in another field: the field of Research
and Development (R&D). To achieve this, we tailor
the BMM for R&D by placing the right methods in
the slots/steps of the BMM, according to matching
with R&D characteristics.
In this paper, we attempt “to demonstrate that the
extension of known design knowledge into a new
field is nontrivial and interesting. The new field must
present some particular challenges that were not
present in the field in which the techniques have
already been applied" (Gregor & Hevner, 2013, p.
347).
The BMM contains prescriptive knowledge at the
second level (Nascent design theory—knowledge as
operational principles/architecture (Gregor &
Hevner, 2013, table 1)). Originally, it was developed
as a typical example of the improvement quadrant,
where a new solution was developed for a known
problem.
To adapt the existing BMM, we build on
methodology engineering as coined by Kumar and
Welke (1992) and further developed by Brinkkemper
(1996). More recently, Henderson-Sellers and Ralyté
(2010) captured the state-of-the-art on (situational)
methodology engineering. The methodology
engineering viewpoint has two aspects:
representational and procedural (Kumar & Welke,
1992). The representational aspect explains what
artefacts are looked at. The artefacts are the input and
deliverables of phases in the method. The procedural
aspect shows how these are created and used. This
includes the activities in each phase, tools or
techniques, and the sequence of phases.
In this research, we focus on the procedural
aspects, as the input and deliverables of each step are
quite well defined and suitable for almost any specific
situation where a business model has to be created.
Therefore, for each step (phase) in the BMM, we
reconsider the tools and techniques proposed in the
original method. For each step, we investigate the
literature for existing methods (tools/techniques)
possible in that step. Then, we compare those to the
R&D characteristics from the literature review in the
previous section. Based on this comparison, and
consideration of the originally proposed method, we
choose a method that best fits the particular
challenges of R&D. Thus, tailoring the BMM for
R&D. To demonstrate that the tailored method works,
we apply in two cases in an R&D organisation.
4 TAILORING THE BUSINESS
MODELLING METHOD FOR
R&D
In this section, the first four steps of the BMM are
assessed against the R&D characteristics from section
2.2. Step 5 and 6 are based on the first four steps or
use general techniques such as brainstorming. It is not
needed to assess them against the R&D
characteristics. Meertens et al. (2011) proposed
specific methods, techniques or tools that are suitable,
but they remark that other techniques may be useful
and applicable as well. Therefore, based on literature
reviews for every step, a possible set of suitable
techniques for BMM in an R&D setting is presented.
Before the tailored BMM is presented, it is
important to understand that this method is based on
the assumption that a R&D organisation is considered
as a portfolio of projects. This assumption is in line
with literature (Balachandra & Friar, 1997; Brockhoff
et al., 1997; Coombs et al., 1998; Liberatore & Titus,
1983; Pinto & Covin, 1989), but from the logic that
the projects create the value as well.
Tailoring the Business Modelling Method for R&D
99
4.1 Step 1: Identify Roles
One of the difficulties in ‘Risk management’ is the
often long time frame of R&D projects. While time
passes by, the interests of stakeholders change. The
stakeholder analysis (Elias, Cavana, & Jackson,
2002) focuses on the dynamics of stakeholders and
their changing interests. In this way, possible risks
can be foreseen and acted on.
Another focus of this stakeholder analysis is the
characteristic ‘External linkages’, which is implicitly
a part of every stakeholder analysis. This stakeholder
analysis distinguishes itself by conducting an analysis
on three levels, rational, process, and transactional.
This way, it gives a deeper insight in the management
of relations as well as the transactions that take place.
This information supports management of risks.
4.2 Step 2: Recognise Relations
The second step of the BMM aims to discover
relations among the roles. It may appear that relations
are already captured in the stakeholder analysis of the
first step and therefore this step is redundant.
However, several reasons exist why the recognition
of relations is a separate step in the BMM. First of all,
a stakeholder analysis often follows a hub-and-spoke
pattern, as the focus is on one of the roles (Meertens
et al., 2011). Meertens et al. (2011) suggest a role-
relation matrix as a deliverable, as this approach
forces to specify and rethink all possible relations
between the roles. Secondly, they note that relations
always involve some interaction between two roles.
Furthermore, they assume that this interaction
involves some kind of value exchange as well. This is
in line with Gordijn and Akkermans (2001) who state
that all roles in a business model can capture value
from the business model. From this perspective, the
proposed technique for this step, e3-value modelling,
is a valid one. The e3-value model models the
economic-value exchanges between actors
(Andersson, Johannesson, & Bergholtz, 2009;
Kartseva, Gordijn, & Tan, 2006). This economic-
value exchange can be tangible as well as intangible
(Allee, 2008; Andersson et al., 2009). The initiators,
Gordijn and Akkermans (2003), present the e3-value
model as being:
1. lightweight
2. a graphical, conceptual modelling approach
3. based on multiple viewpoints
4. exploits scenarios, both operational and
evolutionary
5. recognising the importance of economic value
creation and distribution
Properties 3 and 5 are in line with the choice of this
model in this step. The multiple viewpoint approach
is the missing link between the stakeholder analysis
and the role-relation matrix. Furthermore, the focus
on value exchange fits the property of a relation being
an interaction between roles with some kind of value
exchange. The remaining properties 1, 2, and 4 are
useful in step 5 of the BMM. The lightweight and
visual-oriented approach facilitates brainstorming
and generating scenarios, which are important aspects
of step 5.
Two R&D characteristics, which are relevant for
this step, are ‘Value’ and ‘External linkages’. The
value exchange of intangible assets is an exchange
that occurs often, as knowledge transfer goes hand in
hand with R&D. By exposing the tangible value
exchanges, as well as the intangible ones, the e3-
value model is suitable for R&D from a ‘Value
perspective. This automatically shows that this model
is suitable from the perspective of ‘External linkages
as well. External linkages are the relations between
different roles, for example a supplier, and the
exchange of for example knowledge. The strength of
the e3-value model lies in business network
environments and an organisation together with their
external linkages can be typed as a business network.
4.3 Step 3: Specify Activities
Meertens et al. (2011) propose techniques from
business process management to create the intended
output. However, in contrast to the example, R&D
activities are considered as a black box, which makes
them hard to specify. It is possible to cluster activities
in groups, but the number of techniques offered by
business process management is considerable, it is
necessary to look deeper into the field of business
processes in R&D.
4.4 Step 4: Quantify Model
For an organisation to assign costs, several systems
are available, which can be distinguished in
traditional systems and more refined systems, such as
Activity-Based Costing (ABC) (Drury, 2008).
Process costing, job costing, and a hybrid form of
these two are considered as traditional systems.
Process costing allocates costs to masses of identical
or similar units of a product or service, and job
costing allocates costs to an individual unit, batch, or
lot of a distinct product or service (Horngren et al.,
Fifth International Symposium on Business Modeling and Software Design
100
2010). Not only products or services can be cost
objects, also a customer, product category, period,
project (R&D / reorganisation), activity or a
department may qualify as a cost object. ABC refines
a costing system by assigning cost to individual
activities.
ABC is not a suitable technique for R&D as
activities are clustered and complex. Process costing
is used to cost masses of identical or similar units.
One of the characteristics of R&D is its non-repetitive
nature (Brockhoff et al., 1997), therefore process
costing is not suitable for R&D. Job costing, on the
other hand, allocates cost to an individual unit, batch,
or lot of a distinct product or service. As mentioned,
this research considers an R&D organisation as an
organisation that is built on projects. Although project
management techniques are used to create uniform
structures, such as New Product Development (NPD)
processes, this does not mean that process costing can
be used. These kinds of structures do not cluster
uniform activities but try to support the process of
delivering certain outputs. Each output is unique or
has its unique features and therefore job costing is a
suitable technique for R&D.
5 DEMONSTRATING THE
BUSINESS MODELLING
METHOD: THE SE BLADES
TECHNOLOGY CASE
Suzlon Energy Blades Technology (SBT) is an R&D
division of Suzlon Energy Limited and is specialised
in the design and development of rotor blades for
wind turbines. The division is spread out over four
locations: Hengelo (Netherlands), Århus (Denmark),
Pune, and Baroda (India). SBT is a project-oriented
organisation as most R&D organisations. Earlier, it is
stated that an R&D business model is a portfolio of
innovation processes. At SBT these innovation
processes are reflected in new product development
(NPD), design change management, and technology
projects. The NPD projects ‘directly’ create value for
the organisation, where the technology projects are
feeders for NPD projects. Finally, the design change
management projects are the continued development
of NPD projects. The innovation process for NPD
projects is already imbedded in the organisation in the
form of a Stage Gate System (see section 5.3).
In this case study, we examine two NPD projects
after the implementation of the stage gate system.
Both projects together should give a good perspective
on the innovation process of NPD’s at SBT and gives
us the opportunity to demonstrate the BMM4R&D.
5.1 Identify Roles
Suzlon is a multinational company with complex
relations. First of all, the business unit SBT itself is
internationally situated. It has to deal with various
cultures and different interests within the R&D
departments, and with the manufacturing in India as
well.
Furthermore, the interests of the wind turbine
division, overall Suzlon interests, and of course
market needs and market opportunities always play a
role. This reflects on current NPDs, future NPDs,
current and future technology projects. In this study,
the NPD is the unit of analysis, because an NPD can
be seen as an example of the generic NPD process
within SBT. The project teams consist of the
recurring roles. Although the location of these roles
may differ per project, the built up of a project team
is generic. Furthermore, internal stakeholders are not
taken into account, because research on roles within
projects is largely available.
For the sake of clarity, stakeholders in this paper
are combined and renamed. The stakeholders are
addressed per stage of the NPD (see section 5.3).
Suzlon Energy GmbH (SEG) and SBT manage
their organisations independently, which influences
an NPD on different levels. Not only do they interact
with each other, external factors as political change or
economic crises can have direct influence on each
project. The portfolio boards translate market needs
and opportunities into product strategies. NPD and
technology projects are derived from this strategy.
Table 2: Stakeholders per stage.
Stakeholder 1 2 3 4 5 6A 6B
SEG(SuzlonEnergyGmbH) ●● ●●
SBT(SuzlonBladeTechnology) ●●●●●
PBSEG(PortfolioBoardSEG) ●●●●●
PBSBT(PortfolioBoardSBT) ●●
NPDSEG(NPDonoveralllevel) ●●
Tailoring the Business Modelling Method for R&D
101
Most of the time the influence of the portfolio board
is long term, but some market changes need to be
reacted on quickly. Therefore, the potential influence
of such a stakeholder is always present. Finally, the
NPD SEG contains representatives from the whole
chain (R&D, moulding, purchasing, manufacturing,
services, finance, etc.). Every decision can influence
the financial cost of the other. Especially here, the
tension of the various forces can be intense.
These stakeholders are returning stakeholders
during every project and therefore people know by
experience how to act. The play of forces of the
different stakeholders’ interests, culture and politics
are managed by imbedded procedures and RASCIs.
The influence of the stakeholders at each stage differs
(see Table 2). Furthermore, an unexpected event can
lead to big power impact of a stakeholder which
would not have much influence during a certain stage
under other circumstances. Therefore, it is important
to give more insight in the relations between these
stakeholders in the next paragraph.
5.2 Recognize Relations
In the first step, we mapped the stakeholders per stage
and we do the same for this step, using the e3-value
model per stage. When done for every stage, we get
an extended view on the influence of stakeholders:
not only on the power aspect but on the value aspect
as well. Figure 1 shows the e3-value model of stage 3.
During the case study, an economic crisis
influenced the market dramatically. Governments
economised on subsidies for alternative resources
such as wind energy, which directly influenced
budgets. Other possible scenarios, such as radical
innovation because of a breakthrough in a technology
project, capacity problems in a department, or a
political change can be assessed per stage using the
e3-value model.
5.3 Specify Activities
An organisation needs to adapt the Stage-Gate system
according to its own needs (Cooper, 2009). This
Figure 1: e3-value model of SB43 Stage 3.
Figure 2: Departmental activity per stage.
Figure 3: e3-value model of SB43 Stage 4, 5, 6.
Fifth International Symposium on Business Modeling and Software Design
102
allows the method to be applicable to various kinds of
R&D organisation. At SBT, all the stages are present,
but stages are split up, and/or named differently, to fit
with the specific situation of SBT. Although stage 1
is part of the NPD process, it is not part of an NPD
project. In the best case, the activities of stage 1 are
assigned to a Technology project and, if possible, an
NPD project is set up at the start of stage 2.
The organisation has a structured innovation
process for NPD projects, which has all the elements
that the literature appoints. The projects at SBT are
managed on costs, which means in this case on hours
spent. At the end of each stage, there is a Go/No Go
decision and a new budget is assigned/approved. To
review the activities within the stages, the assigned
hours and the hours spent need to be compared.
Unfortunately, the setup of the budgets is not yet
aligned with the hour registration, which makes
comparison impossible.
An alternative comparison is possible because
SBT clusters departmental activities and embeds
them in their stage gate model as well. Clustering is
universal over all their NPD projects and shows
which departments are involved at what stage. Their
involvement is based on the needed output at the end
of each stage. Figure 2 gives an overview of the
departmental activity.
In Figure 4, the hours per department are put
against the SBT process model.
This figure shows that all the departments are
already involved at stage 2 and 3, which does not
match the distribution of the departmental activities
in Figure 2. However, the activities of department SD
should occur at stage 5, but most of them occur at
stage 6A and 6B. Furthermore, the activities of
department A&L are most spent at stages 2 and 3, but
should occur at stage 4 and 5.
Figure 4 shows a difference between the
clustering of activities at SBT and the actual
clustering. This can be related to step 1 and 2. For
example, the portfolio board allocates resources at
Table 3: Stage-Gate at SBT compared to Cooper (2008).
Stage SBTStageGateSystem StageGateSystem (Cooper,2008)
1 Marketneedsandbusinessperspectives 1 Scoping
2 FeasibilityStudy
2 Businesscase
3 ProjectPlanningandCommitment
4 SystemSpecification/Requirements
3 Development
5 PreliminaryDesign
6A StableDesign
6B StableDesign(incl.Prototyping)
7 SystemValidation 4 Testing&Verification
8 InitialLaunch
5 Launch
9 SeriesLaunch
10 ProjectClosure
Figure 4: Hours of departments involved at each stage.
Tailoring the Business Modelling Method for R&D
103
stage 3, but taking figure x into account, the allocation
already happened.
5.4 Quantify Model
A straightforward cost allocation method is used.
Typical for an R&D organisation, most costs occur
from labour hours. All indirect and direct costs can be
summed up and allocated to a single cost pool. In
Figure 5, the total cost of one of the projects is
calculated by adding all the direct and indirect costs.
The figure shows that the total costs are largely
build up out of indirect costs. For one of the projects
this percentage is as high as 96%. It can be expected
from a R&D organisation that most activities involve
labour hours. The amount of hours spent, which we
used in step 3 as a review of the clustering of
activities, is in line with the allocation in figure X.
Also, it indicates that the labour rate has a great
influence on the cost of a project. Using step 1, 2 and
3, potential threats for the labour rate can be assessed.
By demonstrating the BMM4R&D, we did a
quick scan of the current situation at SBT.
Furthermore, at every step we showed the possibility
to evaluate possible scenarios.
6 CONCLUSIONS: A BUSINESS
MODELLING METHOD FOR
RESEARCH AND
DEVELOPMENT
In this paper, we built a business model for a research
and development organisation. To achieve this, we
further specified the business modelling method
(BMM) (Meertens et al., 2011), to align it with
characteristics of research and development (R&D).
This led to the BMM4R&D: a Business Modelling
Method for Research and Development
organisations. The case studies for the field of R&D
illustrate that it is possible to tailor the BMM to
specific needs, as was originally proposed.
6.1 Academic and Business
Contributions
Our main contribution is the demonstration of how
the BMM can be tailored. Using the design science
approach, we deliver a level 2 artefact (Gregor &
Hevner, 2013), namely the BMM4R&D. It is a
tailored specialisation of the BMM The approach that
we used to tailor the BMM, improves the usability of
it for specific fields. The approach consists of
attaching applicable, field-specific methods to the
available hooks (steps) in the BMM. This opens the
way to tailoring the BMM to other fields as well, so
it can be used in practice.
The business contribution of this paper is
threefold. First, we define a set of characteristics for
R&D. Second, we provide a method to create
business models for R&D organisations: the
BMM4R&D. Third and final, we provide two cases
where a business model shows the value of R&D.
These all add to the relevance of this paper.
6.2 Limitations and Further Research
As part of this design science research, we built a
business model for an R&D organisation, using two
projects as cases. This demonstrates the use of the
BMM4R&D. To evaluate this new artefact further, it
should be applied to more cases. Additional case
studies could come from within the same
organisation, but also from other R&D organisations,
especially in other industries.
We tailored the BMM for R&D; however, we
advocate that the BMM can also be tailored to other
fields (Meertens et al., 2011). The originally proposed
BMM has several hooks where different methods
may be attached. Thus, tailoring to new fields is easy
to do. Yet, finding out which methods are most
suitable for a field is a harder challenge.
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