28th Bled eConference
June 7 - 10, 2015; Bled, Slovenia
Business Modelling Agility:
Turning ideas into business
Jukka Heikkilä
University of Turku, Finland
jups@utu.fi
Marikka Heikkilä
University of Turku, Finland
marikka.heikkila@utu.fi
Harry Bouwman
TuDelft, The Netherlands
Åbo Akademi, Finland
W.A.G.A.Bouwman@tudelft.nl
Abstract
Business Model Innovation is attracting more and more attention from business as well
as from academics. Business Model Innovation deals with both technological and
knowledge related changes that either may disrupt or sustain existing product/market
strategies. Timing of Business Model Innovation both with regard to the right moment
as well as speed of implementing competitive concepts becomes crucial. In this
conceptual paper we discuss and evaluate possibilities for shortening the lead‐time and
increasing impact of Business Model Innovation aiming at low‐end and new market
disruptions. We are building our discussion on recent findings and identifying
anomalies for further research by reflecting on exemplary business design cases.
Keywords: Business Model, Business Model Innovation, Business modelling, Business
Scrum, Agility, Disruptive Business Models, Radical Innovation
1 Introduction
Business Model Innovation (BMI) is a topic that becomes more and more central in
strategic analyses of companies (Bouwman et al., 2012). Whereas strategy is
concerned with the long‐term positioning of a company, business model (BM) is more
related to describing the business logic or operational model of a company. BMs are
lately acknowledged as instruments for strategy execution (Casadesus‐Masanell and
Ricart, 2010; Teece, 2010; Cortemiglia et al., 2015). BMs are used in designing and
analysing how new innovative concepts can enhance competiveness of companies or
business networks. These new concepts can, for instance be based on new
technological inventions, extending usage of existing technologies, or making a shift
Business Modelling Agility: Turning ideas into business
from a product to a service oriented logic. In all above situations timing and shortening
the time to implementation of BMI is crucial to capture value, and re‐organize it
activities with respect to competition.
In this paper we focus on Knowledge intensive services (KIS). The motivation for this
focus is that KIS is one of the growth sectors in most economies. In Europe KIS include
high‐tech services (e.g. R&D, and ICT), market services (e.g., transport, property
management, equipment rentals), financial services (e.g., intermediation, insurance),
education, health and recreation, both cultural and physical. Besides their growth
potential KIS serve other economic activity by leveraging the innovative capacity and
efficiency of industries. KIS are also expected to benefit from ICT, i.e. its disruptive
power replaces old practices and creates, entry points to, new markets. Examples of
such KIS are born global companies, whose modus operandi have proofed to be
extremely efficient at unforeseeable scale. Think for example companies in the gaming
industry, or in social media, where rapid product development combined with agile
business modelling has brought supernormal profits with millions of customers and
high valuations to SMEs (e.g., Supercell acquisition by Softbank and GungHo, Skype
acquisition by Microsoft, WhatsApp acquisition by Facebook). These companies differ
from others due to their right timing and short time‐to‐market, and meticulous real‐
time analysis of the success of the products on the market.
The objective of this paper is to conceptually analyse the ways to reduce time to
market for KIS by focusing on agile Business Modelling and proposing a research
direction. Bouwman et al. (2014) argue that BM design needs to start in early phases
of ideation of new products and services. In this paper we take this argumentation a
step further by arguing that BMI should follow the principles of agile software
development, focusing on fast iterations. We build our argumentation on recent
understanding of the innovation activity in the market, and apply them to KIS with an
agile business modelling point of view. In our perception the industry of KIS is in need
of faster methods for developing new services. We follow the idea of product
innovation business literature such as Christensen & Raynor (2003), and apply the
similar thinking in the design of business. Essentially, Christensen & Raynor (2003)
propose three tactics: start early, start fast, and bring in the benefits early.
Unfortunately, existing methods like Quality Function Deployment, Service
Blueprinting and New Service Development become easily cumbersome and heavy
weight endeavours of mapping existing practices instead of implementing innovations.
As implied by e.g. Teece (2010), more lightweight methods are needed to ramp‐up and
grow the operations quickly. In this article we propose an agile BMI method that
interacts closely with the demand. In order to achieve our objective, we first build on
the basic concepts of Christensen’s Theory of Disruption (2006, 1997; Christensen &
Raynor, 2003) and related recent research (e.g. Markides, 2006; Dan & Chieh, 2008;
Wohlfeil & Terzidis, 2014). Then we pay attention to the objectives of BMI in the light
of disruption and use the lessons learnt on speeding up business model design for
Knowledge Intensive Services, an emerging approach of Agile Business Modelling.
2 Research Background
As the business environment has grown interconnected and co‐opetitive
(Brandenburger & Nalebuff, 1997) ‐ i.e. forming networks of companies on contractual
agreements, organizational arrangements like joint ventures (Hung & Chang, 2012), or
loosely coupled trust based eco‐systems ‐ there is a need to show how results are
related to business relationships in innovation activities (Christensen & Raynor, 2003;
Dan & Chieh, 2008; Ritala & Hurmelinna‐Laukkanen, 2009; Dedehayir et al., 2014) and
harness new technology use in a systematic manner (Gnyawali and Park, 2011; Kunz &
Warren, 2011; Heikkilä et al., 2015). It has been found, that obvious characteristics of
companies such as size, complexity, technology intensity cannot be used as predictors
for successful disruption, because the effort in and success of innovation at company
level is very contingent to the market, competitor (e.g., Hung & Chang, 2012) and
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Jukka Heikkilä, Marikka Heikkilä, Harry Bouwman
regulatory situation, as well as resource mobilization (Sinha & Noble, 2005; Chiaroni et
al., 2011). The need for further research is summarized by Ritala and Sainio (2014):
“Thus, the conceptual and empirical evidence is still inconsistent in terms of how
coopetition affects the emergence of radical innovations.”
2.1 Disruptive Innovation Strategies
Many leading companies are spending big to maintain their competitive position to
create better products for their customers (like for instance Nokia did in recent
history) (Christensen, 2006). The dilemma of this sustaining strategy is, that an
incumbent aiming at bringing better, or converging products onto established markets
primarily will easily develop too complicated products whose extra performance is not
valued by the average customers (Norman, 1998, depicted in figure 1. below).
Incumbents end up in this fallacy, because the improvements serve their present
customer base, demanding ever more improved, rich and expensive set of features.
Hence, the company becomes vulnerable to product/market disruptions.
Figure 1. The Transition point in Technology Development
Another complication with sustaining strategy is in growth of complexity, especially in
infrastructural products, which refers to product innovations serving a wide range of
industries with backward compatible products, like for example banks, energy and
mobility providers, or telecom industries. They are constantly developing new services,
while complying with regulations and specialized code‐of‐conduct as advocated by
authorities; or consumers sticking to an old technology (manual bank accounts, un‐
adjustable energy contracts, out‐dated cell‐phones, etc.). This increases the
incumbents’ production and transaction costs and creates complexity hard to tackle
both in maintaining and innovating products, or operations in the context of KISs. On
the other hand, these complications serve also as an obstacle for entrants to the
market, especially if supported with significant need for investments in organizing
structure, processes and capabilities (e.g. mixed and conglomerate organizations for
talent development and transfer, Galbraith, 2014).
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Business Modelling Agility: Turning ideas into business
So, newcomers need BMs which outperform incumbents on the market with a novel,
sometimes initially not even superior, solution providing in the long run substantial
performance (price, quality) improvements over the products, sweeping eventually
through all market segments (Figure 2). Typically this calls for more efficient business
models to serve larger customer segment better, or at lower cost, disrupting the
incumbents business.
Figure 2. Disruptive Technology takes over market segments over time (c.f. Wikipedia, adapted
and generalized from Christensen & Raynor 2003).
Such disruptions can be divided typically in two categories (Figure 3.): “Low‐End
Disruption" means that some customers are served better by providing simple choice
for unbundled service at more affordable price (e.g., RyanAir vs. British Airways). The
entrant's dilemma is that it is a constant up‐hill battle taking time and ample resources
to win new markets (illustrated in Fig 2.). The other type of disruption, "New‐Market
Disruption", takes place when it becomes possible to serve customers, who were not
previously served by existing incumbents (Fig 3.). Break‐through on an uncovered
market is a dream come true for every innovator, getting onto the ‘blue ocean’ instead
of severe competition on the ‘red ocean’ (Kim and Mauborgne, 2005). But this blue
ocean approach calls for special skills, the appropriation of which incumbents
according to Doz & Kosonen are incapable: “Beyond scale‐up, and the fit of the
business model and activity system to the strategy they currently pursue, [incumbent]
executives seldom take the time, or perhaps do not have the skills, to reflect on new
ecosystems and industry structures, or new business models and activity systems’
architectures. … Being the designer or architect of a new system calls for very different
skills from being the successful operator – or even builder – of an already designed
business system.” (Doz & Kosonen, 2008, p. 27). This kind of disruption is claimed to be
boosted often by open networked innovative activities (Christensen et al., 2009),
where the incumbents seem to be at their weakest. In essence, the New‐Market
Disruption is about design, thinking out of the box, relating it to the external
environment, and managing the implementation fast.
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Jukka Heikkilä, Marikka Heikkilä, Harry Bouwman
Figure 3. Strategies under different circumstances (Christensen & Raynor, 2003)
Figure 4: Tentative Benefits of Business Modelling in Service Innovation (the authors’
adaptation of Christensen & Raynor, 2003).
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Business Modelling Agility: Turning ideas into business
For the purposes of our inquiry, the most interesting areas for studying business
modelling and its effects on agile innovations are denoted with dotted arrows in Figure
4. With the help of business modelling, we should reach the higher market segments
(the top most arrow) faster. An example of this evolution is Apple’s success with their
high‐end market design and user experience. The other option is to find the minimal
viable solutions for the market faster, or for a specific market segment (arrow starting
from Low‐end Disruption). Here we can use Android as an example overtaking ruling
Symbian market in the first decade of 2nd Millennium. And finally, Apple can be seen
to simultaneously redefining the mobile device market segment with their limited
family of devices with high emphasis on connectivity and ease of use (New‐Market
Disruption).
2.2 Service Innovation and Business Modelling: the current state of
the art
This paper focuses on how time‐to‐market can be shortened for KIS by agile business
modelling. Our view is that of the entrant attempting to generate profit on the market,
with the help of business modelling. The other side of the coin, generic strategies of
incumbents against disruption are out of our focus, but is discussed in Wessel &
Christensen (2012).
Service design literature is characterized by formal methods like stage gate models
(Cooper, 2000), Quality Function Deployment QFD (Cohen, 1995; Chan &Wu, 2002),
service blueprinting (Shostack, 1984), service concept analysis (Goldstein et al., 2002)
and New Service Design (Menor et al., 2002). Bullinger, Fähnrich & Meiren (2003) as
well as Karni & Kaner (2007) are proposing an engineering approach to service
innovation. In a service engineering service components, specifically those based in
software, can be re‐used. All these methods can be used to help product‐oriented
companies to switch to a more service oriented approach. All the service innovation
models and approaches have their own merits. They are characterized by a kind of
phasing model, a number of steps to take, and, or formal analyses to be executed.
Although valuable in themselves, most approaches are cumbersome and time
consuming to implement in practice, and in practice they often lack the strategic
connection to the market entry strategies of Low‐End or New‐Market Disruption.
Also the Business Model literature, either from a strategic management or marketing
perspective (Zott & Amit, 2010; Osterwalder & Pigneur, 2010) or from an Information
Systems perspective (Heikkila et al., 2010; Bouwman et al, 2008; El Sawy & Perreira,
2012), are following rather laborious and cumbersome steps or are specific towards
value creation, or implementing business logic with IT. The activity system perspective
(Zott & Amin, 2010) is rather holistic, high‐level, and does not provide practical
implementation guidelines. CANVAS as developed by Osterwalder & Pigneur (2010) is
in our view a brainstorming tool, mainly focused on marketing of new products and
services. The unit of analysis is a specific business and the business marketing and
customer value creation process. These services can fit a sustainable, a low‐end or a
market disruptive strategy, but seldom is such a strategic orientation included in
CANVAS‐based BMs. CSOFT (Heikkilä et al., 2010) and STOF (Bouwman et al, 2008)
share some communalities but also some differences. CSOFT is more focussed on
product‐customer segments, and derives quantifiable objectives explicitly from the
strategies of a business – the innovativeness is essentially subject to strategic goals.
STOF is more focussed on technological architectures and platforms, in combination
with value networks and eco‐systems that bring about a specific service or product. In
STOF the service or product is the unit of analysis, which provides a basis for objectives
setting, road mapping and stress‐testing of the practical implementation of tentative
services on the market (De Reuver et al., 2013). Both methods support the three
sustainable, low‐end or market disruptive strategies. However, in practice the focus is
often on disruptive technologies as far as the work with STOF is concerned. VISOR (El
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Jukka Heikkilä, Marikka Heikkilä, Harry Bouwman
Sawy & Pereira, 2012), in turn, is a relatively new BM method, and its applications are
still scant and mainly from incumbents. VISOR focuses on changes in Digital Businesses
and therefore also on platforms and interfaces. The main applications, to our
knowledge, are in the mobile application domain.
2.3 Agile development and BM
Agile approaches ‐ such as XP (Beck and Andres 2005), Scrum (Schwaber and Beedle
2002), DSDM (Stapleton 1997) and FDD (Coad et al. 1999) ‐ have been introduced in
the context of software development as an alternative to the traditional, plan driven
and heavy documentation focused methods (Lee & Xia, 2010). Agile development
views the software development process to be dynamic, evolving, and organic, instead
of predefined, mechanistic and static (Lee & Xia, 2010). It welcomes changing
requirements and aims at satisfying customer needs by iterative development cycles
(e.g. sprints) and co‐design with customers and users.
Agile methods align development effort with business values by making business
people and developers working together. The business view is expected to come from
the product owner representing the customer. This has been found rather demanding
role for individual persons and for instance Ktata and Lévesque (2009) suggest that to
improve the approach there should be a steering committee which would help to
identify the right product and requirements and govern the project toward business
value maximization. In order to succeed the steering committee "should share and
maintain a common artifact that provides enough visibility on business expectations
and sources of value during the evolution of a project".
In line with Ktata and Lévesque (2009) we see the benefit from combining the
business view with agile development methods. The common artifact could be BM ‐
visualised with ontologies and tools ‐ that are found to be useful boundary object
between the stakeholders, customers and developers (Bouwman et al, 2012; Heikkilä,
2010). This extension to the development process ‐ which we call as business scrum ‐
would provide methods and tools for the team to work on business modelling issues
either in a pre‐BM phase or in cycles during the technical development of the product.
2.4 Summary of the background
Although the BM frameworks have a focus on exploiting technological opportunities,
follow a service engineering or logic approach, or relate business logic to systematic
change with enterprise architectures, it seems that practical, fast, and flexible methods
are in short supply. In this paper we aim to study and create an agile way of developing
BMs that would help in understanding product/service development position, and in
achieving satisfactory business performance faster. In all the three situations, e.g.
Sustaining Strategy, Low‐End Disruption and New‐Market Disruption, the main
question is, whether we can show that business modelling helps us to reach our initial
(?t=0, as‐is) and targeted positions (?t=n, to‐be). Especially, if we can innovate with
agile BM methods to reach them faster without sacrificing profits, by showing
improved economic performance. Finally, both the achievement of objectives and
economic performance requires a flexible set of metrics (right hand dashed
performance indicators in Fig 4).
Building on the above reasoning we suggest the following development of tooling and
targeted research for KIS to
• speed up the business innovation significantly to enter market quickly and
implement novel business conducts (Christensen & Raynor, 2003; Markides,
2006).
• select suitable business modelling techniques that can describe the necessary
changes from present way of operating business to BMI. For instance,
incumbents tend to start from their existing resource base (e.g, Cortemiglia et
al., 2015) and entrants, in turn, are facing the problem with market vs.
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Business Modelling Agility: Turning ideas into business
technology orientation in innovating their services (Govindarajan & Kopalle,
2006).
• set objectives for the change and economic performance to improve the BM
capabilities (Heikkilä et al., 2014).
• identify feed‐forward and feedback metrics to monitor implementation of
sustaining or disrupting strategies (Heikkilä et al., 2014).
The above elements set up our model that can be used to analyse and design the
existing business model and to identify the strategic position of specific empirical
cases. This can be depicted coarsely as follows:
Ideation ‐> Method for formalizing the business idea ‐> Identifying the extent of
change, or gap ‐> Feeding forward BMI objectives ‐> changing and feeding back
the strategic position with operational and economic performance.
3 Beta-testing the analysis of BMI agility
We chose four European SMEs providing KIS to ‘beta‐test’ our idea and discuss the
reasoning. The selection of cases (Table 1) was motivated by both theoretical and
pragmatic considerations so that they represent differing industries and have differing
approaches to BMI, and the researchers had access to the case data. We applied
design case approach (Sein et al., 2011; Van Aken and Romme, 2009) focusing on
developing new business models.
Case 1:
Case 2:
Case 3:
Case 4:
Big data analytics
platform service
PA prescription &
measurement service
Mobile operator
service
Wind turbine
diagnosis service
Industry
Information
Technology
Health & Wellbeing
Telecom
Energy
Company size
SME
SME
SME
SME
Growth
Start‐up
Mature
Mature
Netherlands
National
B‐to‐B
Finland
National
B‐to‐B, B‐to‐C
Finland
Local
B‐to‐B, B‐to‐C
Denmark
International
B‐to‐B
Maturity
Location
Market
Table 1: Case organisations
Case 1 is developing service platform that would make big data analytics more
accessible for Small and Medium sized Enterprises (SMEs). It is a knowledge intensive
service aiming at new market disruption, opening a new business branch for the
company. The case focused on utilising technological advancements in cloud
computing, mainly virtualization and reduced cost of storage. After initial development
rounds, SMEs were found to experience different kind of needs: varying access and
collaboration mechanisms that required major design revisions and change of goals for
the development. Only after piloting could the developers renew the technical
architecture to achieve specified goals and requirements, which called for using STOF
BM‐ontology (Bouwman et al, 2008). Two iterations were made starting from value
proposition for the SMEs, while the other customer segment was analysed in less
detail. A marketing strategy was defined in order to achieve critical mass for the
platform, but in practice lead customers were targeted to generate cash flow for
further development. Because the case was technology driven the major development
was focused on fast download speed, open source infrastructure technologies,
development of APIs for data providers, as well as device agnostic applications, etc.
with extra attention to security and management of users' profiles. Furthermore, the
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Jukka Heikkilä, Marikka Heikkilä, Harry Bouwman
business ecosystem was described in detail including value‐, and information flows and
actual operational processes in the latter stages of development, where after costs
were estimated, risks assessed, a pricing strategy defined, and the revenue model, a
mixed model combining a commission, a one time dataset download fee and a licence
fee for longitudinal data, was developed. The BM was then evaluated by project team
and external experts and customers using criteria such as completeness, consistency,
viability, scalability and sustainability. The conclusion was that the business model was
not yet complete and viable, and the project was discontinued. We can depict the
development in Figure 5 as example 1, where technology dominates the design and
BMI starts late.
Case 2 of Physical Activity Prescription and measurement service, is a reincarnation of a
well‐known, proved idea with new technology and business model, and has
characteristics of both Low‐End Disruption and New‐Market Disruption. Ideation was
started years earlier by an entrepreneur willing to expand from pharmacy consulting
towards novel platform based data fusion and analysis services for b‐to‐b customers in
occupational health. The idea was developed into initial business model CANVAS in a
project with a network of business partners, some of whom were incumbents having
good contacts to potential customers. With the help of an IT solution provider the
entrepreneur defined the information systems requirements for information exchange
between the parties. The project group piloted the service with real customers. Based
on a set of business model metrics (Heikkilä et al., 2014) the pilot indicated that one
business model would not fit all customer segments, and introducing varying customer
segments complicated the technical requirements. Furthermore, one of the
incumbents questioned the benefits from committing to risky and complex network of
partners. After three years of the business modelling design kick‐off, the service
innovation development was suspended for the time being by the incumbent. In Fig 5.
the case can be illustrated with the market opportunity in the beginning that after
tentative BM is aiming at joint technological solutions, but the complications of the
technology and unsolved BM problems halt the BMI.
Case 3, a company of 300 employees providing mobile and Internet access and
services was willing to redefine the incumbent dominated, oligopolistic market by
introducing mass‐customized services for their existing and potential clients. It is a low‐
end disruption strategy providing better, more agile and affordable service with the
leap of new technology. The work started with a consultant’s recommendation of
building a specific information technology solution as add‐on to existing operating
model. The management realised that there were inherent discrepancies of the
suggested technical solution with various client segments’ needs and desired
objectives of winning new markets. Business modelling discussion started to clarify the
design into a level of service technology design and building on automated common
infrastructure and service components to all customer segments, distinct from
customer segment specific processes. CSOFT was used for innovating the BM. The case
changed quickly in the beginning from technology dominant design to parallel
technology and business model development, and finally into iterative, alternating
design of technology and business model. It also appeared that the metrics of guiding
the process and design outcome were different for the business model and technology
development in order to maintain the integrity of strategic objectives. The business
model has been implemented for three years now, and the company has been
expanding according to its strategic objectives in a profitable manner, taking
advantage of the separate realms, and performance measures of technology
development and business model implementation with mergers and acquisitions (Fig
5, example 3).
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Business Modelling Agility: Turning ideas into business
Figure 5
Proposed BMI processes
Case 4 concerns a SME company in the wind energy industry. The case is an example of
servitization. The company intended to exploit patented prototype add‐on technology
to increase wind turbine efficiency by reducing turbine misalignment with dominant
wind flow based on Low‐End Market ‐disruption. One‐off sales BM was to replaced, or
at least tried with an alternative mass‐customized service‐oriented BM, starting with
competing technologies and stakeholders analysis. The requirements analysis followed
in two‐layers: requirements for the BM design as well for the service offering.
Interviews with lead‐users from different customer groups within the value chain were
executed to get insights in the service offering, as well as interviews & design
workshop within the company were conducted to get an understanding of the
requirements for the BM design, and the availability of companies’ resources and
capabilities. The results were continuously confronted for attestation on usability and
on the BM. As a consequence present one‐off sales got replaced with a two‐step
approach: First offering a cheap software based wind turbine diagnosis service, based
on which the company will be able to estimate potential efficiency loss. At second
stage an add‐on hardware device can correct the misalignment and its cost to the
customer is charged based on performance improvement. This two stage BMI
appeared universally attractive to all newer customer segments, where the diagnostic
can be done with software. The technological know‐how and production capabilities
reside in‐house to provide both hardware as well as complementary software in a
bundle, but the iterative critical reviews and analyses of the product in parallel with
BM development did really lead to an alternative BMI without keen competition. Case
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Jukka Heikkilä, Marikka Heikkilä, Harry Bouwman
4 followed the last process, example 4, depicted in Fig 5, that is the business
modelling, technology development and customer validation were carried out in
cyclical manner.
4 Lessons Learnt and Further Research
Our study is a tentative probe into BM and BMI, illustrated with four select design
cases. We intend to use the results for developing more lightweight, BM method for
Knowledge Intensive Services entrants’ fast implementation of BMI for different
strategic situations and grounding the development of the method on sound research.
The better understanding of the strategic intent is crucial to concentrate resources in
improving existing products for existing customer base with Sustaining Strategy, or to
introduce disruptive technological solutions with BMI on Low‐End Disruption and New‐
Market Disruption. Against this backdrop, we claim that innovation calls for the
utilization of new technology and novel business models simultaneously.
Simultaneously means in this context that they are considered in together, preferably
in the market context, because the business model can then act as a boundary object
between the stakeholders, customers and developers (Heikkilä, 2010; Heikkilä &
Heikkilä, 2013). It also can act as an intermediator of the external market forces
(reception and competition) similarly as agile product development probes the
alternative solutions and user experiences. Balanced view on both is necessary in quick
BMI realization ‐ emphasising too much of the other seem to have negative, and
different, problematic consequences on the speed of the implementation of the BMI.
The cases are divers, but nevertheless they indicate the need for rapid iteration.
Iteration can be implemented by dividing innovation in parallel product development
and Business Modelling streams and by maintaining integrity between the two by
rapid review cycles, or by balancing the performance measures between product
development and BM according to the strategic intent. This helps to maintain
customer focus and meet the market requirements early enough. The postulated need
for iteration is well in line with some recent findings in KIS: “a SaaS client’s agility to
leverage external resources, reconfigure its internal resources for strategic move and
service provision, and mitigate the effect of environmental turbulence plays a critical
role in competitive performance.” (Chou et al., 2014). In other words, in response to
the turbulent market and technological environment an organization must be
constantly and quickly scanning and responding to the changes by reconfiguration of
internal and external resources and activities.
In this paper we illustrated our ideas with four illustrative design cases. Further
research on agility in BMI is clearly needed. Our intention is to confirm the findings
with a larger data set collected from various entrants in the forthcoming years.
Acknowledgement
The authors wish to thank Lyubomir Nedyalkov and Stefan Marges for data collection
and analyses in two of the cases. The work leading to these results has received
funding from Data to Intelligence (D2I) Programme and the European Community’s
Horizon 2020 Programme (2014–2020) under grant agreement 645791. The content
herein reflects only the authors’ view. The European Commission is not responsible for
any use that may be made of the information it contains.
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