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Ecosystem Pie Model
This document is the official online appendix to the academic paper titled ‘Mapping, analyzing
and designing innovation ecosystems: The Ecosystem Pie Model’ (2018), authored by M.
Talmar, B. Walrave, K.S. Podoynitsyna, J. Holmström and A.G.L. Romme and published at Long
Range Planning
What is this manual for?
This is a methodological guidelines manual for the use of the qualitative innovation ecosystem
modeling tool Ecosystem Pie Model (EPM). The EPM incorporates a graphical tool and a mode-
ling process which enables the mapping, designing and analyzing of innovation ecosystems
both for managerial and scholarly purposes. This guidelines document was created to assist
with the understanding and using the EPM framework. In this manual, we cover the following
1. What are innovation ecosystems and what is ecosystem strategy? (pg2)
2. The target audiences for the EPM (pg3)
3. The power of EPM and other related tools (pg7)
4. One-by-one overview of the building blocks of the EPM (pg9)
5. Examples of ecosystem models (pg23)
6. Frequently asked questions (pg37)
7. Templates for ease of modeling with the EPM (pg41)
For questions/comments on the EPM tool and ecosystem modeling methodology, you are
welcome to contact Madis Talmar at or the other co-authors of this work.
The authors would greatly appreciate if you let us know of your use of the EPM tool. This is for
the purpose of following the spread of the tool and to receive your feedback.
What are innovation ecosystems?
Innovation ecosystems are networks of organizations whose (innovative) products/services
combine together toward achieving an overarching (ecosystem’s) value proposition (Adner,
2017). Consider the following example. As a customer, you might be interested in driving more
sustainably, so you decide to buy an electric car. But the electric car alone is not enough to
accomplish your greener driving experience. There must also be a network of charging points,
which is typically provided by the local utility company. Before you can buy the car, it must first
be developed and produced, needing high quality batteries and thousands of other compo-
nents, originating from a network of suppliers to the car manufacturer. Furthermore, the car is
probably sold to you as a final customer by a local dealer, and to buy it, you might need a leas-
ing contract with a bank/leasing agency. Finally, and to return to the very beginning, govern-
mental policy (subsidies) possibly played a large role in shifting your preference to buying an
electric vehicle (as opposed to one powered by a combustion engine) in the first place. What we
see is that a sustainable driving experience is much more than a car. It is in fact accomplished
by the interplay of many related products/services. It is contexts like this where we speak of an
innovation ecosystem as a network configuration of a number of actors that together make a
complex value proposition possible.
From the example, we learn that the product or the service that a particular innovating compa-
ny A is developing is often critically dependent on the availability of certain complementarities
originating from other actors. Unless these complementarities become available, the specific
innovation of company A is also unlikely to breach successful commercialization. Therefore, if
company A is to better manage their innovation process, they might undertake an explicit
analysis of the willingness and ability of external organizations in supplying complementa-
rities that support the commercialization of their innovation. Such an analysis goes beyond
the traditional focus in innovation where company A would mostly concern itself with the
effectiveness of the innovation process within their own organization.
Such analysis also goes beyond partnerships as such. A key feature in innovation ecosystems
is the frequent lack of explicit partnerships between value-creating actors and/or any formal
control of actors by other actors. As such, important complementarities may originate from
parties that your organization has no ties with and that your organization does not transact
with. Still, the fact that these complementarities are critical to your innovation implies that they
are of interest in developing an informed innovation strategy.
As per Adner (2012), in analyzing our innovation ecosystem, we should distinguish between
two types of (potentially) critical complementarities: a) the willingness and ability of actors
that are in between our organization and the end users to adopt our innovation (i.e., the ‘adop-
tion chain’), and thus progress its successful commercialization, and b) (novel) products/ser-
vices by other actors that also need to be available for our innovation to become successful (i.e.,
the ‘co-innovators’). In the example above, from the point of view of the car manufacturer, the
local car dealers would constitute an example of necessary adopters. Meanwhile, sufficiently
frequent charging points are an example of a product/service that needs also to become avail-
able for electric vehicle manufacturers to succeed in selling their vehicles.
The possibility that one or both types of complementarities are not available when a firm
launches its own innovation may be a critical issue for the innovating firm. Toward tackling that
issue, we speak of the necessity to analyze ones’ own innovation ecosystem and ultimately to
develop an explicit ecosystem (management) strategy.
Questions specific to ecosystem analysis toward strategy making include:
- what is the overarching value proposition (e.g., sustainable driving) that our inno-
vation contributes to and who is it targeted toward?;
- which complementary contributions are necessary for that value proposition to be
accomplished, both in terms of adopters and in terms of other products/services that
need to be available for ours to become successful?;
- who (could) supply these other complementarities?;
are these parties willing and able to supply these complementarities?
(i.e., do they constitute a risk to our innovation?)
- how to influence external parties to align their activities to accomplishing the over-
arching value proposition we have in mind?;
- or perhaps the opposite: how to re-design the overarching value proposition so as
to fit an existing set of industrial relationships better?;
- are there ways to accomplish the overarching value proposition with less depend-
ence on external actors?;
- how to reduce the risk that specific critical actors are not willing or able to contrib-
ute the complementarity we expect them to contribute?;
- should we attempt to duplicate the activities of these actors who are risky from the
point of view of not contributing as we expect them?
The Ecosystem Pie Model is a tool that enables the qualitative mapping, analysis and design of
innovation ecosystems with such questions taken into consideration.
Who is the EPM tool for?
There are five major groups of users who can regularly benefit from modeling innovation
ecosystems using the EPM tool.
Innovators: If you represent an organization that aims to introduce a new technology/pro-
duct/service or a business concept to the market, you can use the EPM to consider the interde-
pendence of your new offering with other actors and their offerings. Moreover, you can use the
EPM to compare different approaches (scenarios) to taking your novelty to the market. Think of
this as an exercise of organizational network design with the goal of making sure that your
organization chooses the most beneficial network configuration to introduce its product/ser-
vice/technology. In this respect, the EPM can be used in modeling both technology push and
market pull. For instance, if you have a radically new technology, you can use the EPM to con-
sider the required ecosystem support of placing this technology to particular different applica-
tion areas and analyze the implications of each application area. Conversely, you can consider
the potential ecosystem constellations required to capture a market opportunity. The key pur-
pose for practitioners to model their innovation ecosystem is to develop an ecosystem strategy
as an inherent part of a new product/service strategy.
Strategists: If you represent an organization that in creating and capturing value already is
embedded into a network of ties with other organizations, you can use the EPM to analyze this
existing network constellation and to develop strategies to operate more successfully within it.
Such a strategy may include choices regarding what your own company should do internally,
as well as choices regarding how to influence other actors around your organization to act more
favorably to your goals. For instance, as a wholesaler of goods, you might have difficulties
making enough margins on the products. One of the possible avenues of business model
change for your organization might then be to bypass the retailers that are your immediate
customers and attempt to sell to end customers directly. You can use the EPM to analyze the
implication of changing your business model on the rest of the ecosystem network and under-
stand what kind of a business model change might bring you highest benefits.
Policy-makers and analysts: If you represent a policy-maker, an innovation intermediary or
similar, you can use the EPM to gain an understanding of the kinds of ecosystem constellations
that exist for accomplishing certain value propositions, and/or for considering what kinds of
ecosystem constellations could there be for accomplishing certain value propositions. Such
analysis might point to structural deficiencies that potentially require policy intervention. In
the above-mentioned example, if you wished to boost electric driving, using the EPM might
bring you to the conclusion that there is a dual barrier to this value proposition in having not
enough electric vehicles and not enough charging points. Either of these complementarities can
be boosted by policy.
Investors: The ecosystem of an organization constitutes an important, but often underestimat-
ed source of risk for the innovation activities of that organization. The EPM enables investors to
explicitly consider what are the ecosystem-based assumptions and potential risks underlying
a novel value proposition. An investor can do this by using the EPM on their own, by requesting
an explicit ecosystem analysis from the venture/project, or by taking part in a collective
ecosystem modeling exercise involving the organization and its (prospective) ecosystem part-
Scholars and students: As an academic or a student, you can use the EPM in order to develop
descriptive knowledge on existing and future ecosystems, which can be used in contributing to
ecosystem research and/or for achieving learning outcomes. For instance, you may compare
the different ecosystem constellations by which certain value propositions are achieved, and
use that knowledge to report on a particular industry.
In a later section, we provide examples including most of these viewpoints to modeling with the
What is the EPM tool like?
The EPM consists of a graphical ecosystem modeling tool, accompanied by a number of princi-
ples that guide the process of ecosystem modeling. On Figure 1, you can see the EPM in its
blank form – that is, prior to any data entry.
On Figure 2, following the electric driving example from earlier, we illustrate the end result of
an ecosystem modeling exercise around the prominent electric vehicle model of Tesla Model S.
We might call this the ‘Tesla Model S innovation ecosystem’, although one should bear in mind
that the version presented is a heavily simplified model of the ecosystem that Tesla maintains
around its company. This especially in recent developments, where the company is converging
residential power storage (Powerwall), home power generation (Solarcity and Tesla BIPV roof)
and self-driving functionality to enhance the overarching value proposition they contribute to.
The rest of this guidelines document is dedicated to explaining step-by-step, how you too can
perform an ecosystem analysis with the help of the EPM tool, and arrive at a result similar to
the Tesla example in Figure 2.
However, as will become clear later, at least as much as it is about the outcome of the model in
a graphical form, modeling ecosystems with the EPM is about the process and the inclusiveness
this process can create for the people involved in the modeling exercise.
Figure 1. The EPM tool as a blank canvas
EL:1. Intended value arising from
the system-level overarching
offering by the supply-side agents
in the ecosystem
EL: 2. Sub-secon of the market that
is targeted by the ecosystem’s value
EL: 3. The organizaons, instuons,
communies and individuals that
are engaged with value creaon
and capture on the supply side of
the ecosystem. Posioned clockwise
toward end users
AL: 1. Resources at the disposal of the
actor to be ulized for value creaon
within the ecosystem
AL: 2. Acvies performed in converng
resources into value addions toward
the ecosystem
AL: 3. The unique producve
contribuon of the actor to
the ecosystem
AL: 4. The type, mechanism and
quanty of value captured by
the actor from the ecosystem
AL: 6. The potenal inability
and unwillingness of the actor
to supply their producve
contribuon to the ecosystem.
Represented by coloring in
the secon: red-high, yellow-
medium, green-low
AL: 5. The extent to which the actor is
dependent on the success of the ecosystem.
Represented by retaining or coloring in the
appropriate leer: L-low, M-medium, H-high
FILLING IN: For secons other than
Risk and Dependence, the input is
(most commonly) descripve text.
To enable rapid reorganizing, it is
suggested to use (one or more)
post-it note per secon.
FILLING IN: Actors are
color-coded based on
which sub-system (i.e.,
value chain) they
contribute to
FILLING IN: Relaonships
between elements not
explained otherwise are
indicated with arrows
Figure 2. Tesla Model S ecosystem
The power of EPM
Any tool has its strengths and weaknesses and this implies that there are also more and less
appropriate situations to apply a tool. In this section, we briefly reflect upon the specific posi-
tive traits of the EPM as arising from our experience in applying and facilitating the application
of the tool. We do this in order to pinpoint to the types of situations where we think the EPM
has the most analytical power and where it generates most value to modelers. In doing so, we
also refer to several other potentially useful tools that we believe are appropriate in some use
First, the EPM has been developed foremost to facilitate awareness concerning the inevitable
embeddedness of a future product/service in a broader industrial context. As originally
emphasized by Adner (2006; 2012), each step in the value chain that your organization is
embedded in, as well as each step in necessary parallel value chains that eventually flow into
yours’ (even if just at the customer) can be a major source of risk for your innovation project.
The crux of ecosystem modeling is thus risk management with risk being the ultimate measure
in analyzing every actor in the innovation ecosystem. EPM measures risk in much the same way
as the parsimonious Value Blueprint tool by Adner (2012) that includes just two key elements:
the industrial structure (i.e., the modules in the ecosystem and the flows between them) and a
risk assessment for every flow within it. If your purpose of ecosystem modeling is to quickly
generate and convey the structure of the modules (and the actors producing them) in the
ecosystem, and to mark down the potential risks in that structure, we highly recommend the
Value Blueprint tool. What the EPM adds to the benefit received from the Value Blueprint tool
is a detailed description of each actor by the key characteristics that influence what the risk
assessment for them would be. Put otherwise, much more of the argument justifying the moti-
vations and abilities of the other actors are featured on the EPM. Corresponding to this feature,
the modeler that benefits most from using the EPM is one that is either in the process of new
product/service development, or funding someone who is. The main benefit gained is a thinking
‘path’ to systematically and in detail consider the industrial structure that the product/service
will be part of and the potential risks in that industrial structure to the success of the product
or service. These points together then set the modeler up for making well-informed ecosystem
strategy choices as part of the new product/service development process.
Second, building on the argument of innovation ecosystems as ‘structures’ (Adner, 2017), the
EPM is tuned to assist at developing ecosystem strategy in industrial contexts with several
distinguishable value chains that (ultimately) flow together, enabling a coherent overarching
value proposition of some kind. The analytical power of the EPM is lower if the modeler specifi-
cally aims to understand how to build and manage platforms. A platform in this case should be
understood as a set of technologies, typically sponsored by a particular entity, that enable
either entrepreneurial action among other actors, or transactions among distinct groups of
users (Jacobides et al., 2018). Modeling a platform-based ecosystem using the EPM is possible,
but especially in cases where the platform facilitates many diverse types of user value (e.g.,
operating system with many types of applications), the way the EPM is designed may limit the
number of complementors that can be meaningfully modeled. Furthermore, the EPM does not
feature elements to help a modeler make sense of platform-oriented design and governance
choices such as openness, lock-in mechanisms, network effects, and transaction cost reductions
mechanisms. For explicitly modeling platform ecosystems, we suggest considering the Plat-
form Design Toolkit (
Third, the EPM is neutral to the industrial position of the entity of interest. This means that
the intended innovation of the modeler may be positioned far upstream in a value chain, in
direct interaction with the user, as well as anywhere in between. The only difference in ecosys-
tem modeling across that spectrum would be in the number of actors to be considered as con-
stituting the adoption chain vs. as (necessary) co-innovators. Furthermore, modeling can also
proceed without any entity in focus at all, for example in educational or research settings.
The EPM is also neutral to the level of power that the entity of interest has within the ecosys-
tem structure. In alignment with the argument that other actors in the ecosystem are often a
source of risk to accomplishing the overarching value proposition, the EPM effectively assumes
a limitation to the power of any actor. The purpose of the EPM then is to help the modeler
become aware of and navigate around their limitations. Meanwhile, in case the context of mod-
eling includes a particular end customer oriented focal actor that seeks to integrate offerings
from other actors into a coherent boundary-spanning business model, we suggest considering
either the Business Model Connect tool (Brehmer et al., 2018), if focus is to be placed on the
specification of flows between parties; or the Service Dominant Business Model Radar (Lüfte-
negger, 2014), if focus is to be placed on the characteristics of the involved partners.
Finally, the EPM is neutral to the environmental or social sustainability effects achieved as
result of innovation activities. Any such potential effects are neither neglected nor explicitly
included and instead it is dependent on the choice of the modeler whether to include these
effects in characterizing some of the actors or not. However, if the modeler has specific interest
toward understanding or designing multi-actor value systems that give rise to either environ-
mental or social sustainability, there may be merit in considering the Business Model Connect
Tool (Brehmer et al., 2018), or the Cambridge Value Mapping Tool (Bocken et al., 2013).
The real-world performance of an ecosystem emerges in the interplay of features held by indi-
vidual actors in the ecosystem, and the structure by which these individual actors interact in
creating and capturing value. Correspondingly, mapping, designing and analyzing ecosystems
assumes that we simultaneously consider properties on both levels: on the level of the ecosys-
tem and on the level of each of the contributing actors.
Ecosystem-level building blocks
In the previous sections, you were already briefly acquainted with the three main components
of the EPM that lie on the level of the whole ecosystem. These are Actors, an overarching value
proposition, which we refer to as the Ecosystem’s value proposition (EVP), and User segments.
It is with these components that we start to develop an understanding of what an ecosystem
constellation is like and how value is created and captured in a particular ecosystem. Note, that
while we present these components in a certain sequence here, depending on the particular
ecosystem it may be a good idea to switch the order of considering the Actors, the EVP and the
User Segments. This choice depends for example on whether you are modeling an ecosystem
to perform a technology push, or a market pull. In the case of the former, it often makes sense
to start modeling first by considering the Actors (most prominently, your own organization);
while in the case of the latter, you might start with considering first who are the User segments
and what kind of value could be proposed to them.
(1) Actors. Innovation ecosystems are networks of organizations that supply certain comple-
mentary offerings that in their interaction create user-oriented value. In that sense, the organi-
zations within an ecosystem are dependent on each other, although at the same time each gen-
erally constitutes a separate legal entity. In the EPM, to represent the separation (boundaries)
of involved parties, each Actor is represented by a sector of the ‘ecosystem pie’ as shown in
Figure 3.
In the ‘pie’, the Actors are presented clockwise in a sequence that follows their distance from
the end user, starting with the most distant (the so-called upstream) Actors. So, for example,
the battery producer for the electric car would come earlier than the car producer, who in turn
is followed by the local car shop/maintenance center who actually sells the car to the user and
later takes it in for maintenance. These Actors constitute a value chain where each subsequent
actor takes the product/service of the previous one as input and produces an output that incor-
porates some value-added element from that Actor.
In most ecosystems, there are in fact several such value chains, which run in parallel and com-
plement each other. Think again of the example of electric driving where it is minimally neces-
sary for there to be a value chain around accomplishing the vehicle and another one providing
the possibility to charge the vehicle. In such a case where the ecosystem encompasses several
value chains, each of the value chains follows the same logic of moving clockwise from
upstream Actors towards downstream actors. There is no one rule for considering how the
several value chains position against each other in the EPM, although a modeler may want to
keep in mind best readability of the graphical model. Read also on parallel value chains in the
section titled ‘Relationships’.
Figure 3. Representing actors in the EPM
To keep the number of modeled Actors limited and the model less complex, some Actors can
be pooled together to a single sector on the basis of similarity. For example, the suppliers of
standard components (wheels, breaks, doors, windows etc.) to the electric car can be pooled to
a single sector because they add value to the ecosystem by a similar logic – i.e. by developing
and supplying components to the car producer. By the same principle, a contributing communi-
ty (e.g., Kickstarter) would also best be represented on the EPM as a single Actor.
Furthermore, a modeler can choose to exclude some contributing parties without jeopardizing
analytical power, provided that these parties contribute from the point of view of the ecosystem
complementarities that are entirely generic. Generic in this context means that compared to the
standard product/service of the Actor, the Actor does not have to perform any modifications for
the complementarity that they offer to be applicable in a particular ecosystem (Jacobides et al.,
2018). Examples of generic complementarities would include parcel delivery services, bank
credit, electricity and water. In the context of most ecosystems, these (and similar) comple-
mentarities can be assumed to be available at normal market conditions so much so as not to
become problematic for the success chances of the ecosystem. Conversely, modeling should
focus on actors that, in order to be part of the ecosystem, have to customize their offering at
least somewhat in comparison to what they supply as standard, meaning that the complemen-
tarity they provide is to an extent non-generic. In the most standard case, this means that in
order to supply their complementarity to a particular ecosystem, an Actor needs to engage in
some product/service (re-)development of their own.
(2) Ecosystem’s value proposition (EVP). The EVP is the integrated output of the whole
ecosystem, as targeted to end users. In distinguishing what constitutes the EVP, authors recom-
mend thinking what ‘job’ does the combination of complementary products/services in the
ecosystem accomplish for the end users; or what exactly is the problem that is solved for the
end user. The EVP is at the center of the EPM to mark that all Actors represented on the EPM
are either directly or indirectly involved in accomplishing it. Note, however, that it is important
to understand the EVP as it is perceived by the end user. This implies that the ‘job’ an EVP does
to the user may be different than what the Actors think it is. Many argue for example that a
significant proportion of Tesla Model S cars are not bought for an intrinsic desire to be green,
but rather for the status symbol they represent. Market and user research can provide some
cues as to the methods used for research what perceived ‘job’ an EVP accomplishes. Figure 4
represents the core of the EPM: the EVP.
Figure 4. The EVP as the core of the Ecosystem Pie Model
(3) User segments. Classical marketing theory posits that a value proposition is more effective
on the marketplace when targeted to sub-sections of the market referred to as User segments.
This component of the EPM therefore specifies who the target audiences of the EVP are. For
example, for Tesla Model S, the User segments originally were tech-savvy above average
wealthy individuals living mostly in California.
Note that we speak here of ‘users’, rather than customers because the latter implies an explicit
transaction (a purchase). While in most occasions the users are indeed expected to pay for a
product/service, not in all instances do User segments have to buy the value offering. For
instance, in the case of Google’s search engine, the value offering of the search is available to
users for free, but its existence enables Google to receive revenue elsewhere from a set of
actors other than the users of the search engine (i.e., selling advertising space to businesses).
User segment(s) constitute a separate sector (or if there are several distinct segments, more
than one) in the EPM. These sectors are positioned last in the clock-wise sequence of the
ecosystem pie, representing the positioning of the user as the ultimate target of the networked
value creation and delivery logic of the entire ecosystem. Figure 5 depicts the positioning of a
User segment.
Users constitute a separate Actor in the ecosystem for three reasons. First, users are important
co-creators of value. Namely, it is not rare nowadays for users to be involved early in the
product/service development process, providing frequent feedback to how the product/service
is developed. Additionally, users can enhance the ecosystem with additional functions such as
promoting the offering of the ecosystem to new potential adopters, within, or across User seg-
ments. Second, in many ecosystems, users have some degree of choice with regard to which
Actors participate in supplying value in their particular instance of use/consumption. In the
sustainable driving example, users may choose to be customers of the power grid in public
charging spots, charge at the charging spot at their office parking lot, or alternatively purchase
their own charging hardware and load their cars up at home. As power prices are typically
different in all these three use cases, the dominant choice of users between these three options
influences greatly the amount of income to the power retailer and to the electricity supply
value chain that is part of the sustainable driving ecosystem. Finally, users can generate trans-
actable value, such as usage data, that some ecosystem Actors can use in providing further
value elsewhere in (or outside) the ecosystem. In an ecosystem, value transfer can thus be
bi-directional, moving both toward and away from the User segments. In that sense, users con-
tribute often with much more than purchasing power, and value as such can be moving both
toward and away from the User segments.
Actor-level building blocks
Sequencing the Actors, considering what is the EVP they accomplish, and to whom it is targeted
delivers to the modeler a key part of understanding what the composition of the ecosystem is
(expected to be). But ending the exercise at this stage would have its clear limitations. Most
significantly, we have gained little understanding of what exactly is the individual complemen-
tarity provided by each Actor; how each Actor accomplishes their contribution to the ecosys-
tem; and how reliable we can expect that contribution to be. Or put another way, it is unclear at
this point whether our assumption that the ecosystem composes of these particular Actors is
actually sufficient and realistic, or not. In order to increase our analytical power on understand-
ing the ecosystem, as well as to develop real-world implications (such as an ecosystem strate-
gy), it is necessary to learn significantly more about each of the Actors in the ecosystem.
Furthermore, in each ecosystem, there are a number of ways that the individual Actors use to
interact with each other in activities targeted to creating and capturing value. To represent
these important elements of an ecosystem and ultimately to draw implications from the
ecosystem modeling exercise, we complement the ecosystem-level building blocks with
Actor-level building blocks1 which are: Value addition, Resources, Activities, Value capture,
Dependence and Risk. Again, the exact sequence of considering each of these constructs may
differ depending on the particular ecosystem in question. First time ecosystem modelers are
advised to consider first either the element of Value addition, or the element of Resources.
Figure 5. Representing User segments
1 The generic visual representation structure where a circle is divided into sectors based on categories/modules that
are then split to sub-sections by concentric circles that represent certain characteristics of each module has been
employed in several earlier methods for modeling network-based value structures, including by Bourne and Walker
(2005) for stakeholder value mapping, by Bocken et al., (2013) for sustainable business modeling and by Lüftenegger
(2014) for service-dominant business modeling; as well as in a number of other business tools, including The Digital
Marketing Radar (Chaffer, 2010), The Agile Marketing Radar (Agile Marketing Agency, n.a.), The primary investigative
domains circle of usability-oriented design (van Kuijk, 2012), The Agility Health Team Measurement Tool (BeAgile,
n.a.), and various trend radars.
(4) Value addition. The EVP is realized as a combination of the complementary offerings
provided by the Actors in the ecosystem. From the viewpoint of the whole ecosystem, each of
the Actors therefore has a particular contribution to the EVP, which we refer to as the Value
addition of that Actor. The Value addition element incorporates the products/services (or sup-
port of other kind, such as funding) provided by the Actor, but also the ‘job’ these accomplish
from the viewpoint of the EVP. As a quick test to know if your model is approaching consistency
with regard to the overall modulation (i.e., division into individual distinguishable complemen-
tary contributions) of the ecosystem, when considering each of the individual value additions
provided by the ecosystem Actors, one should get a full list of the complements that together
accomplish the EVP. This test should be applied both to considering if each individual value
chain within the ecosystem has all necessary elements in place, as well as to whether the
ecosystem as a whole has all necessary value chains represented.
(5) Resources. This building block describes the most important assets that form the basis for
value creation of a particular Actor. Resources should be perceived in the broad sense here
including all kinds of tangible and intangible assets, capabilities, organizational processes,
firm attributes, information and knowledge that are available to the Actor for performing value
creating activities. Particular Resources can be owned by the Actor in question, but they can
also be acquired through other Actors, for example by means of licensing intellectual property.
See more about Resource acquisition in a later section ‘Relationships’.
Here, it is also important to bear in mind that in considering the building block Resources, as
well as subsequent building blocks in this chapter, one should think which elements of the
Actor are actually relevant within the particular ecosystem. As such, we would for example
include into the Resources section of an electric vehicle battery developer (e.g., Panasonic) not
all the resources of that Actor, but only these resources that are basis for developing and man-
ufacturing batteries. That point is particularly important to keep in mind when characterizing
larger organizations that maintain many parallel business lines.
(6) Activities. The building block Activities encompasses the mechanisms by which an Actor
uses the Resources available to it and generates its productive contribution to the ecosystem.
Put another way, we map here the (sets of) activities by which the organization generates its
Value addition and insures that it has an opportunity to earn sufficient returns in the process.
Activities often cross Actor boundaries and combine with Activities of other Actors. See more
about this in the section ‘Relationships’.
(7) Value capture. In exchange for subjecting their Resources and Activities (resulting in a
Value addition) to accomplishing a particular EVP, Actors are interested in receiving a gain of
some kind. This gain can be either financial or non-financial. For example, for a (local) govern-
ment, welfare of their citizens is a gain that might justify support to a particular ecosystem. On
the other hand, for-profit organizations typically assume financial gains, or at least gains that
they can ultimately monetize in some way. An example of a direct financial gain might be the
sales price received from selling an electric vehicle to a local dealership; while an example of
a gain that is not directly financial but monetizable elsewhere might be the usage data that an
ICT company acquires within one application, but uses in another application (potentially in a
different innovation ecosystem).
The building block Value capture represents what kind of return is the Actor gaining, how does
the Actor gain that return, and how much of the return can the Actor gain from participation in
the ecosystem. The aim of this building block is essentially to show the mechanism by which
the Actor is gaining returns, which can then be assessed whether it is sufficient to insure their
participation. In evaluating the sufficiency, the Value capture opportunity for the Actor should
be compared to the costs (including opportunity cost) associated with accomplishing the Value
addition. This means that Value capture is inherently related to the other Actor-level building
blocks. As a rule of thumb, the more an Actor would have to customize their Resources, Activi-
ties and Value addition to contribute to the ecosystem, the higher their demand for Value cap-
ture is expected to be. For instance, if a software application requires thousands of hours of
re-development to be adjusted from one operating system to another, a software development
company would likely need a high level of confidence that they can earn significant revenue
from their association to the new operating system.
Especially for prospective (yet non-operational) ecosystems, the section Value capture might
include thus information in a conditional form, reflecting the minimum expectations of the
Actor. An example of considering in the Value capture section simultaneously the questions of
what kind, how and how much value an Actor can capture in a conditional manner might for
example state:
- What kind: monetary
- How: earning revenue from unit sales to local distributors
- How much: in order for the business to be lucrative, at least 10,000 units per month
should be sold
(8) Dependence (on the EVP). Ecosystems are networks which often include Actors of a variety
of profiles (e.g., small and large, private and public). For some of these Actors, accomplishing
the EVP may be of utmost importance. For instance, if a company produces parts only for
Caterpillar tractors, they are highly dependent on the success of these tractors. For others, con-
tributing to a particular EVP is just a small share of the total operation of the Actor. For exam-
ple, if you consider a car workshop that installs tires from Goodyear, Bridgestone, Cooper,
Hankook, Michelin, etc., their dependence on the new products of any of these companies is low,
which means that any single tire manufacturer would have to seriously consider how to influ-
ence the workshop to invest in new installation equipment that is specialized to just one brand.
We speak thus of the level of dependence that an actor has on whether the particular EVP is
accomplished or not. In the EPM, this is measured by three levels: L - low dependence, M -
medium, and H - high dependence. On the graphical EPM template, the respective grade is
marked on the right-side separation line of the Actor by filling in the relevant circle as depicted
on Figure 6.
(9) Risk. From the viewpoint of the whole ecosystem and its other complementors, it is critical
that all the important Value additions required to accomplish the EVP are indeed accomplished.
This condition assumes that the Actors expected to deliver these are both willing and able to
provide their productive contribution to the ecosystem. However, unless the assumed contribu-
tion is entirely generic (see section ‘Actors’ for explanation), neither of these conditions should
be assumed to exist automatically. Reasons for the assumed contribution of an Actor not to
become accomplished include the following. Inability as a dominant reason may arise for
instance because the assumed technological solution is too difficult to accomplish, because the
Actor experiences restrictions to their freedom to operate from an intellectual property point
of view; or perhaps because the Actor has cash flow, staffing or legal problems. Meanwhile,
potential sources of unwillingness span at least three categories, including a) low effort (i.e.,
disinterest) of the Actor, corresponding usually to a low Dependence of that Actor on the
ecosystem, b) the necessity of the Actor to invest in resources, activities and/or products/ser-
vice configurations that are specific to that particular ecosystem and that they could not rede-
ploy elsewhere (i.e., so-called fungibility of the resources or activities) with the associated cost
(incl., opportunity cost) outweighing the prospective return of these investments (Jacobides et
al., 2018), and c) a mismatch between the characteristics of the ecosystem and the strategic
interests of the Actor. An example of the latter might include for instance a disagreement on
which Actor establishes the technological (or relational) standards in the ecosystem, how the
ecosystem as such is likely to change the competitive landscape in the industry and/or even
whether the facets of the particular ecosystem match the vision of the entrepreneurial team of
the Actor on the positioning of their organization in the industrial landscape. As such, Risk is in
fact influenced by all the other Actor-based components.
Figure 6. Marking the dependence of actors (on the EVP)
With regard to the potential inability of the Actor to accomplish their value addition, we advise
modelers to focus on considering if the Resources and Activities of that Actor really correspond
to the assumed Value addition. Meanwhile, in assessing the willingness of the Actor to contrib-
ute, one should consider whether the Actor possesses a Value capture mechanism that enables
the Actor to reap enough gain from the ecosystem; and whether the actor is sufficiently inter-
ested in accomplishing their respective Value addition for sake of the particular ecosystem in
comparison to the other alternatives available to that Actor (consider here their Dependence on
the EVP). In doing so, one should also keep in mind that even though there may be a viable
Value capture mechanism that would allow a particular Actor to reap gain from the ecosystem,
they may be able to capture even more value from complementing to a a different ecosystem.
Across the willingness and ability evaluation, the building block Risk is a compound assess-
ment about the likelihood of the Actor to be contributing the Value addition that accomplishing
the EVP would assume from them. Risk is represented on the EPM by filling the respective
section in with a specific color (e.g., red - high risk, yellow - medium risk, green - low risk),
although it can further be specified in words, or by a percentage-based grade which stands for
the likelihood of the Actor to be both committed and able to contribute to the EVP in the
assumed way.
Adequate risk assessment is among the most critical inputs to developing an ecosystem strate-
gy. Thus, if there are Actors characterized by high or medium Risk, it may be a good idea to
mark down a separate explanation aside of the graphical EPM on how a particular color code
was assumed. This generally helps greatly at later managerial decision making on necessary
action. The works of Ron Adner (Adner, 2006 and 2012) are especially valuable in operational-
izing the Risk construct in ecosystem strategy-making. In particular, Adner established that
once we have assessed the Risks of all the critical Actors in the ecosystem, the overall likeli-
hood of the EVP to come together is calculated by multiplying the individual likelihoods of
each critical Actor to accomplish their part. For example, in an ecosystem consisting of six criti-
cal Actors whose contributions are necessary for the EVP to be accomplished, if each of the
Actors has a likelihood of 80% to contribute their Value addition, the ecosystem as a whole
only has a 26.2% likelihood (i.e., 0.86) of accomplishing the EVP. In performing analysis of this
kind, it is important to think twice if indeed an Actor is critical to the EVP, or it provides a contri-
bution that enhances the value of the EVP without really being critical. On the EPM, those
Actors supplying critical complements are marked with a red asterisk ( ). For the sake of actu-
ally calculating Risk mathematically, an ecosystem modeler would have to convert the initial
green (low Risk), yellow (medium Risk), red (high Risk) assessment to a numeric %-value. This,
however, constitutes an advanced level of ecosystem analysis which assumes a very good
understanding of the Risk profile of each involved Actor.
Finally, note that a common mistake in modeling ecosystems is to think of Risk in the meaning
of ‘risk of the ecosystem TO THE ACTOR’ (i.e., whether it is risky to be involved in the ecosys-
tem). This, however, is not the correct way to conceptualize Risk. In modeling the ecosystem by
EPM, the Risk grade stands for the ‘risk OF THE ACTOR to achieving and maintaining the EVP’.
All the Actor-level building blocks are represented in Figure 7.
As was perhaps evident already in previous sections, the building blocks of the EPM influence
each other across Actors, as well as within the boundaries of each Actor. To make these rela-
tionships more explicit, we represent here first all the intra-actor relationships on Figure 8; and
proceed then to review how certain Relationships connect ecosystem building blocks by span-
ning Actor boundaries.
Figure 7. Actor-level building blocks of the EPM
Figure 8. The relationships between actor-specific building blocks
Across Actor boundaries, the building blocks can be related in the following ways. First, the
Value additions of the actors combine to the EVP either by the end user, such as the charging
grid and the electric vehicle; or in the exchange of the Actors in the ecosystem, such as when
the battery is incorporated in the electric vehicle. Second, Resources from different Actors can
be shared or combined to enhance the ability of any particular Actor(s) to create value. Third,
the Activities of an actor are typically boundary-spanning, combining with the Activities of
other actors. For example, the activity of developing a higher capacity battery associates with
the efforts of the electric vehicle manufacturer in developing the technical specifications of the
rest of the vehicle; in which case there is a bi-directional information flow between the two
actors. Fourth, because the finite amount of value created in the ecosystem is distributed based
on the individual revenue model of each Actor and the ability of an Actor to enforce their reve-
nue model in the face of the other Actors, the Value capture of an Actor is influenced by the
Value capture of other Actors. For instance, toward a particular target price per cup of coffee,
the revenue model for a coffee machine producer and the revenue model of coffee capsules (as
coming from another producer) are interdependent. There is thus potential struggle between
the parties to capture more value to themselves. Finally, the Risk level of Actor(s) may influ-
ence the Activities of other Actors and consequently the Value addition and Value capture
properties of Actors, and the whole ecosystem.
On the EPM, both the intra- and the inter-actor relationships can be indicated by uni- or bidi-
rectional arrows that connect elements of the model, emphasizing a relationship between them.
However, representing all the applicable relationships with arrows is clearly excessive for two
reasons. First, in each value chain in the ecosystem within which components are incorporated
or transformed into new products/services, transfer of value is already indicated in the posi-
tioning of Actors in a clockwise manner. Second, in most cases, the content input in a particular
element would already explain related Relationships. For instance, you might write into the
Activities cell of a biogas factory: “using biologic waste in their refinery, biogas is produced”
referring to the Relationship that the refinery takes biologic waste as input. Arrows have a
tendency to complicate the model, so we suggest limiting the number of represented relation-
ships to the most relevant and/or these potentially least comprehensible without explicit
representation. A good test here is to consider if a particular relationship would already be
implicit in the general principles of modeling by the EPM tool. An example of how relationships
might be shown on the EPM is presented in Figure 9, based on the Tesla example from previous
A second example (Figure 10) shows how the transfer of Value additions might be represented
by arrows as well. Here we see that there are two critical complementary value chains that
together achieve a green driving experience – accomplishing the car and the charging infra-
structure; and that these value chains are combined by the end user where they together
enable the EVP. This would probably also be intuitive to a reader, but since the point is vital to
analyzing the ecosystem properly, it might be worth explicating with arrows.
It is worth paying attention also to something else featured on Figure 10. Namely, that the
Actors involved in achieving these two complementary value chains are color-coded respec-
tively to yellow and green. Depending on the complexity of the ecosystem, there may be any
number of such value chains. You can distinguish each value chain by color-coding with the
same color these Actor sequences where Value additions are being carried from upstream
Actors towards the User segments by transfers between Actors. On Figure 10, we have separat-
ed the electric mobility ecosystem into two distinguishable value chains since the vehicle value
chain does not have any transfers with the local grid companies supplying the electricity and
the charging points.
Figure 9. An example of relations between the Activities of Actors
The final EPM on Tesla with all the components present is seen on Figure 11. Because this is
already a functional ecosystem that has been operational for several years, there is little con-
cern over the Risk of individual Actors. This with one exception. Namely, we have still coded the
Risk assessment for Local Grid Companies as yellow. While electric vehicle are adopted more
and more, the existence of a sufficient charging grid appears to be one of the issues still ham-
pering vehicle adoption in many geographies. The grid companies around the world are
currently not always incentivized enough to develop a full charging grid because in the
absence of a major fleet of electric vehicles, their immediate revenues from electric vehicle
charging would not be worth it. Furthermore, EVs are known to create grid imbalance, which is
a major problem in the electricity supply chain. Therefore, grid companies are generally cau-
tious in enabling additional EV charging points. And yes, to provide a way out of this
‘chicken-egg’ problem, some governments have already heavily subsidizied charging infra-
structure set-up, but that may be a shaky revenue source for local grid companies because
subsidies are subject to policy and policy can change. Hence also the yellow assessment.
In fact, on the question of charging, Tesla provides an example of how ecosystem analysis can
influence innovation strategy. Namely, because the public charging infrastructure often is
underdeveloped, Tesla has chosen to internalize the offering of the necessary complementary
good of EV power supply by innovating in two additional directions: a) they have developed a
home charging unit for Tesla owners, and b) they have developed a proprietary fast charging
network which is operations in some select geographies.
Figure 10. An example of product/service flows
Figure 11. Full EPM for Tesla Model S (this is a repeat of Figure 2)
EPM examples
In this section, we present three additional examples of EPMs.
Example #1 – modeling ecosystems prospectively
The first example involves a novel process for storing (renewable) power in liquid form, devel-
oped at a Dutch university. The generic nature of this technology made it possible to commer-
cialize the invention in a number of different application areas. However, it was also clear that
in all of these possible applications, wide-scale adoption of the technology could only be
achieved with a substantial shift in the activities of incumbent actors. The team developing the
technology considered this to be a major barrier. Nevertheless, a spin-off from the university
was created to (try to) bring the technology to the market in such a way as to increase the
chances of its adoption. The team engaged in ecosystem modeling by using the EPM, with a
focus on considering multiple ecosystem alternatives for the commercialization pathway of the
technology. Three of these alternatives were positioned within the domain of mobility (i.e.,
using the technology in city public transport, in trucks, or in boats) and another one in power
storage for use in buildings. We focus here on modeling one of these applications and present
a sequence of graphs (Figures 12-18) which follow the thought process of the technology team
at modeling that scenario. The seven steps taken by the team in using the EPM are outlined in
Table 1.
Table 1. Steps in the EPM process
Steps in process
Description of step
Addition to EPM
Step 1 (Figure 13)
The team considers first its own
characteristics and openly asks: what could
our technology be used for?
General characteristics of
our organization as related
to the new technology.
Step 2 (Figure 14)
In this scenario they decided to test out a
potential ecosystem design of potential
uptake of the new technology in public
transportation. This implies a market
segment of local inhabitants.
Potential EVP and
corresponding User
segment. Dependence for
focal Actor considered high.
Step 3 (Figure 15)
Choosing public transportation also implies
the existence of operator companies, who
receive their mandate from a particular
municipality. For that purpose,
municipalities typically organize a tender.
The team realized here that for the focal
venture, the potential sustainability
conditions in that tender may provide an
opportunity for eventual uptake of their
Characteristics of the
customer-facing final Actor
in the adoption chain
(operator), and the actor to
provide their mandate
(municipality). Focal actor
characteristics specified to
public transport scenario.
Step 4 (Figure 16)
Assuming the operator company generates
market pull for more sustainable buses, a
bus manufacturer could in principle
consider the uptake of the technology of
the focal venture. However, if they did, the
focal venture would lack manufacturing
capability to produce the necessary energy
conversion module so a chemical
equipment manufacturer would need to be
added in between.
Adding two missing middle
Actors to the main value
Step 5 (Figure 17)
Despite the bus value chain being
complete, the ecosystem overall is not yet
complete due to the lack of fuel supply. A
parallel value chain must therefore be
added, including Actors in producing the
fuel and in enabling its tanking to buses.
The value chain for
supplying the main critical
complementary product to
vehicles (i.e., the fuel).
Step 6 (Figure 18)
The team considers each Actor from the
point of view of the EVP and determines
that the Dependence and Risk assessments
of multiple Actors are potentially
problematic for future uptake. These
problems would require special attention
from the technology team in the future,
especially concerning critical Actors.
Risk and Dependence grade
added for each Actor.
Critical Actors emphasized
with red asterisk.
Step 7 (Figure 19)
Implied in the argumentation earlier are
several enforcing relationships that (in
theory) could make the ecosystem function
successfully. These include for example the
way a political decision for much more
sustainable city transportation could
trigger several other Actors to new kind of
Select Relationships
emphasized on the EPM.
Figure 12. General characteristics of the focal venture mapped
Figure 13. Added EVP and User segment for a particular application which defines this scenario
Figure 14. Adding the direct customer-facing Actor and the origin of their mandate to operate
Figure 15. Finalizing the main stages in central value chain (i.e., vehicles + operating them)
Figure 16. Adding a parallel value chain for fuel supply
Figure 17. Considering Risk and Dependence of each Actor
Figure 18. Adding relationship arrows to emphasize certain key mechanisms in
how the ecosystem could become operational
Example #2 – modeling an ecosystem to reflect and redevelop it
The second example originates from a managerially oriented instance of ecosystem modeling
where the purpose of the exercise was to evaluate the effectiveness of a nascent ecosystem
constellation in order to develop strategies for its improvement. Here, the modeling is in that
sense both retrospective/descriptive as well as prospective/prescriptive at the same time. The
results of the backward-looking exercise in analyzing what was already a functional ecosystem
are included in Figure 19, while Figure 20 outlines a potential intervention to the functional
Figure 19. The innovation ecosystem at the end of a pilot period of a new heating service
The case originates from the pilot period of a nascent ecosystem in the field of demand side
management in residential heating. Namely, in collaboration with a manufacturer of automa-
tion and communication equipment, a software company in Finland developed a soft-
ware-hardware package (henceforth: ‘solution’) that landlords can implement in their proper-
ties for automatic heating control, based simultaneously on the conditions in the building (the
demand) and the prices on the energy market (the supply). The solution provides stable and
healthy indoor conditions, while delivering energy savings to the landlord, as well as grid
balancing capacity to energy suppliers. Because accomplishing the full potential of the
demand response functionality of the solution assumes swift removal of any faults in build-
ings, as a necessary complementary functionality, the solution also performs fault detection in
building elements and sub-systems.
The solution was adopted by a major housing corporation and implemented over a two-year
pilot period. Ecosystem modeling was used here as a reflection upon that period to summarize
any structural shortcomings in the ecosystem composition, and then to consider strategies for
alleviating any issues. One identified shortcoming concerns the use of data from the solution
to improve actual maintenance. The modeling exercise indicated three likely reasons: (1) the
maintenance organization lacks the competencies to analyze the rich data; (2) the maintenance
organization is not incentivized toward energy efficiency by their contract structure; and (3)
while the solution data would allow for proactive maintenance, the value capture logic of main-
tenance organizations leads them to reactive maintenance only. Second, members of the build-
ing management organization who govern maintenance operations found it difficult to work
with the solution, underperforming on their task to coordinate maintenance in an accurate and
timely manner. Third, responsibilities between the Actors were somewhat ill-determined. For
instance, there have been unnecessary site visits where representatives of the software compa-
ny or the maintenance organization were present for failures in each other’s domain.
While the pilot was still rather successful, these shortcomings collectively prevented it from
reaching full potential, particularly with regard to delivering the total cost savings. The mode-
ling process here entailed first mapping the ecosystem as it was structured during the pilot
(Figure 19), analyzing the shortcomings of the existing system and then proceeding with iden-
tifying alternatives for how the ecosystem should be restructured. In particular, three alterna-
tives to restructuring were identified.
Figure 20 presents one of these three alternatives where the intervention would entail the
introduction of an additional actor to the ecosystem to take over these tasks of the building
management organization and the maintenance company that concern interacting with the
solution. Referring to this actor as the ‘Technical maintenance organization’, it would include
personnel and tools specifically tuned for proactive (as opposed to reactive) building mainte-
nance and timely repairs based on full utilization of the data generated by the solution. Corre-
spondingly, the organization would be compensated based on the achieved performance of the
buildings. As such, the responsibilities concerning the solution would be shifted to the new
actor, reducing the dependence of the ecosystem on the previous underperformers.
Example #3 – modeling ecosystems descriptively to learn and compare
To illustrate a third major use context for the EPM, we present here an academic/educational
example where the EPM is used to model two existing ecosystem constellations for the purpose
of describing and comparing them. This means the exercise was purely retrospective and
performed from the point of view of an outsider to the ecosystem. In particular, we observe here
how two ecosystem integrator firms—a recent entrant and an incumbent, both in the position of
energy retailers—achieve a similar value proposition toward similar market segments, but do
so via structurally different ecosystem compositions. The firms are respectively referred to as
EneRe1 (Figure 21) and EneRe2 (Figure 22).
EneRe1 maintains a market platform where a prominent feature is the choice provided to con-
sumers on which exact sustainable energy producer to buy their energy from. As such, energy
is effectively decommoditized by creating a previously missing link between the profiles of
agents on either side of the market. This implies a mutual agreement on transparency and
assumes an added effort on the supply side in profiling themselves. The supplier side of the
market is populated here predominantly by farmer-entrepreneurs, who require substantial
quantities of energy themselves, but not necessarily at the same moments when generation
assets, such as wind turbines or solar panels, are actively producing. The participation in the
market platform of EneRe1 provides the farms with an effective means to hedge against this
intermittency of renewable (power) generation: sell upon excess and buy upon shortage.
Furthermore, the premium priced purchase contract provided by EneRe1 gives suppliers a clear
incentive to invest in capacity exceeding their own needs. Meanwhile, in actual purchases of
energy, EneRe1 relies on a B2B broker firm, which acts also as consultant to the supply side in
investing in new generation assets. However, EneRe1 places little emphasis on empowering the
household level consumers to become energy prosumers, or to invest in generation assets on
their own properties.
Figure 20. An alternative for restructuring the ecosystem
Meanwhile, in delivering a very similar value proposition, EneRe2, has sought different kinds of
strategic partnerships. First, in partnering with a crowdfunding platform, they mediate the pos-
sibility for consumers to collectively purchase large scale renewable generation assets, the
return on investment of which effectively reduces the energy bill of the consumer. For this
scheme to work, however, the consumer must have their electricity contract with EneRe2. Here,
we find thus a complementarity between the value capture mechanisms of the energy retailer
and the crowdfunding platform. Similarly, EneRe2 uses its direct relationship with consumers
to mediate the installation of micro-generation assets and efficient appliances. Both of these
activities are preceded by consultancy of EneRe2 toward the consumers with regard to assess-
ing the potential benefits of such equipment. As such, EneRe2 is particularly active on the
demand side of the market, empowering consumers to become prosumers and/or to reduce
their energy consumption.
Figure 21. Ecosystem of a recent entrant energy retailer (EneRe1)
Finally, because demand of renewable energy is not always matched by immediate supply,
both retailers have partners supplying fossil fuel based energy. This is in obvious friction with
the value propositions of providing 100% sustainable energy. There is thus a need to compen-
sate somehow for the use of fossil fuels, which is done by channeling the price premium
received from consumers on sustainable electricity to supporting sustainability projects. For
both EneRe1 and EneRe2, such projects are located in developing countries, though the parties
on the receiving end of the support link are different.
Figure 22. Ecosystem of an incumbent energy retailer (EneRe2)
How to model ecosystems as an external observer?
Modeling with EPM requires a relatively thorough understanding of the way each Actor con-
ducts their business, but also how the ecosystem as a whole operates (or, is expected to oper-
ate). Modeling an ecosystem that involves an industry and/or Actors that are not well known
to you can therefore be challenging. The best approach in this situation is probably to gather
data from more than one of the Actors (ideally all of them) and attempt to combine them
together to a holistic view of the ecosystem. Interviews with the representatives of the Actors
are particularly useful for that purpose. Meanwhile, it is quite likely that an interviewee is not
familiar with the ‘innovation ecosystem’ concept. While not exactly accurate, a strategy for the
interviewer might then be to ask first about the ‘value chain’ of the company. This is a term that
practicing managers are usually better acquainted with. It will not immediately provide a com-
plete picture of the ecosystem, but when complemented later by a question about important
‘parallel value chains’, a more complete picture of the entire ecosystem can start revealing
itself. Other useful questions in ecosystem-oriented interviews include for example: “Who
else needs to succeed so that your product/service would become successful?” or “What would
have to happen in other organizations so that you could become successful with your innova-
How to model an ecosystem that does not yet exist?
As is depicted also in Example #1, one of the major application areas of the EPM is the design
of a new ecosystem. That means composing a constellation that does not yet exist in real life,
most often in order to accommodate the success of a particular innovation that our own organi-
zation is attempting to develop and commercialize. There are at least two approaches to model
ecosystems in a forward-looking exercise. First, if you are designing an ecosystem for an EVP
that is in some other form already accomplished by an existing ecosystem constellation, the
basis for a new ecosystem might be found in first modeling that other ecosystem, and then
reconfiguring it towards a novel one. For instance, if the modeler represents a company that has
invented a new kind of bus for public transport (example #1), they might first map the current
public transportation ecosystem. Subsequently, the exercise might involve conceptually
removing the current bus supplier and replacing it with one of their own, considering carefully
the implications and strategies for doing so in real life. As such, the modeling process would
essentially follow the expected real-world process of change in an existing network.
Alternatively, an ecosystem might be established around an EVP that has no current analogy.
For instance, the EVP built by the company AirBnB constituted the creation of a market where
there previously was none - i.e., remotely organized short-term stay at the property of another
individual. In such an occasion, the consideration of which Actors in which kind of structure are
necessary to accomplish the EVP can necessitate an entire business development exercise.
Significant analysis of user needs and/or current market failures may be needed in order to
put together an ecosystem constellation and it is particularly likely that the mapping exercise
would benefit from modeling out more than one ecosystem version or scenario, which differ in
terms of the features of the ecosystem and/or the implications it would have to accomplishing
it in real life.
How to use the EPM in a physical workshop?
There are at least two effective techniques to use the EPM model as a physical (as opposed to
a digital) modeling tool. Probably the most straightforward of these is to simply print the blank
canvas out on paper size A3 or larger, and then use small post-it notes to gradually fill in the
elements of the model. The use of post-its, as opposed to writing on the canvas, allows you to
relatively quickly change content, or the positions of content without the need to rewrite the
entire model on a new sheet. We have supported this approach by placing printable canvas
versions of the EPM at the end of this guidelines document.
Meanwhile, especially in situations where ecosystem modeling involves representatives of
different Actors that are designing and analyzing a (novel) ecosystem constellation together,
another excellent approach for using the EPM is to model it by the LEGO® SERIOUS PLAY®
(LSP) methodology (see for example Blair and Rillo, 2016). This entails gradually building a
physical model of the ecosystem using Lego blocks. The key benefit we have experienced in
using the LSP in the context of ecosystem modeling is that the building of an ecosystem struc-
ture with LEGO-blocks is a highly inclusive process that explicitly creates understanding
between the involved parties. Furthermore, the LSP can take advantage of the opportunity to
add a third special dimension to the EPM where the intra-actor building blocks are represented
as components in a 3D-building which itself constitutes an island (marking an Actor).
With the Actors each represented as LEGO islands, they can be repositioned swiftly and the
relationships between them rebuilt quickly, making the LSP a favored approach to rapidly
prototyping ecosystem constellations. See an example outcome of a LEGO-based ecosystem
modeling session in Figure 23.
However, LSP also comes with at least two shortcomings. First, because the various ecosystem
components are represented not as words but as physical buildings, communicating the results
of a modeling session to third parties may require comprehensive additional explanation.
Second, in order to achieve maximum effectiveness of an LSP-based ecosystem modeling
session, generally an experienced LEGO® SERIOUS PLAY® facilitator is suggested.
Figure 23. Example of ecosystem modeling with LEGO® SERIOUS PLAY®
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Lüftenegger, E.R. (2014). Service-Dominant Business Design (PhD Thesis). Eindhoven
University of Technology.
van Kuijk, J.I. (ed.) (2012). Design for Usability: Methods & Tools - A practitioner’s guide.
Design for Usability.
In the following four pages, you can find templates for using the EPM tool in practice. The
templates include:
a - blank canvas of the EPM with no actor separation lines
b - blank canvas of the EPM divided to six sectors
c - blank canvas of the EPM divided to seven sectors
d - blank canvas of the EPM divided to eight sectors
If you wish to use any of the canvases to model ecosystems by hand, we suggest
printing the particular sheet (pages 42, 43, 44 or 45 of this document) out in size A3
or bigger.
High resolution versions of the post-it background image in six colors are available
ResearchGate has not been able to resolve any citations for this publication.
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Research Summary The recent surge of interest in “ecosystems” in strategy research and practice has mainly focused on what ecosystems are and how they operate. We complement this literature by considering when and why ecosystems emerge, and what makes them distinct from other governance forms. We argue that modularity enables ecosystem emergence, as it allows a set of distinct yet interdependent organizations to coordinate without full hierarchical fiat. We show how ecosystems address multilateral dependences based on various types of complementarities ‐ supermodular or unique, unidirectional or bidirectional, which determine the ecosystem's value‐add. We argue that at the core of ecosystems lie non‐generic complementarities, and the creation of sets of roles that face similar rules. We conclude with implications for mainstream strategy and suggestions for future research. Managerial summary We consider what makes ecosystems different from other business constellations, including markets, alliances or hierarchically managed supply chains. Ecosystems, we posit, are interacting organizations, enabled by modularity, not hierarchically managed, bound together by the non‐redeployability of their collective investment elsewhere. Ecosystems add value as they allow managers to coordinate their multilateral dependence through sets of roles that face similar rules, thus obviating the need to enter into customized contractual agreements with each partner. We explain how different types of complementarities (unique or supermodular, generic or specific, uni‐ or bi‐directional) shape ecosystems, and offer a “theory of ecosystems” that can explain what they are, when they emerge and why alignment occurs. Finally, we outline the critical factors affecting ecosystem emergence, evolution, and success ‐‐ or failure.
Full-text available
This disertiation introduces the service-dominant business design framework for designing service businesses. The framework consist on four layers: strategy, business models, service compositions and business services. These layers are implementend in four tools: the service-dominant strategy canvas, the business model radar, the business service composition blueprint and the service catalogue
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Sustainable innovation requires collaboration across organizational boundaries, hence in this research, we take a boundary-spanning perspective on the business model. This perspective focuses on how value is created and captured across organizational boundaries, by investigating the value transfers between the focal organization and the external network of business model actors. We analyze the business models of 64 innovative sustainable organizations from The Netherlands in terms of how environmental and social sustainability is manifested in the content, structure, and governance of their business models. We find that environmental sustainability is mainly represented in value creation content, whereas social sustainability is achieved by serving underprivileged user groups and mainly is reflected in value capture content. We observe that social sustainability in both for-profit and non-profit organizations is often achieved by having an imbalance in value exchanges that is compensated elsewhere in the business model. In terms of business model structure we show that sustainable organizations use the same underlying business model structures as can be found in conventional firms. All in all, we demonstrate that analyzing the environmental and social sustainability of organizations using the boundary-spanning perspective on business models provides complementary insights to the traditional component-based view of the business model.
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Over the past 20 years, the term “ecosystem” has become pervasive in discussions of strategy, both scholarly and applied. Its rise has mirrored an increasing interest and concern among both researchers and managers with interdependence across organizations and activities. This article presents a structuralist approach to conceptualizing the ecosystem construct. It presents a clear definition of the ecosystem construct, a grammar for characterizing ecosystem structure, and a characterization of the distinctive aspects of ecosystem strategy. This approach offers an explicit examination of the relationship among ecosystems and a host of alternative constructs (business models, platforms, coopetition, multisided markets, networks, technology systems, supply chains, value networks) that helps characterize where the ecosystem construct adds, and does not add, insight for the strategy literature.
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The Design for Usability research project was set up to integrate the worlds of research and product development, looking specifically at development issues in the rapidly changing field of product development of electronic goods. The researchers delved into the issues of user-centred development, working on case studies and interviewing users, designers, manufacturers - everyone involved in the development chain. An exciting, innovative project involving the three Dutch universities of technology, design companies and leading electronic product development manufacturers. The results of five years of hard work are presented here; the methods and tools that will help designers and practitioners design and develop better, more user-friendly products. This book reflects this practitioner-centred attitude. It takes a hands-on approach, provides in-depth discussion of the new methods and tools, how to apply them and what the benefits are. It is richly illustrated throughout and provides links to online resources. It is a must-read for any student, designer and product developer with a passion for user-centred design.
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Purpose – Although business models that deliver sustainability are increasingly popular in the literature, few tools that assist in sustainable business modelling have been identified. This paper investigates how businesses might create balanced social, environmental and economic value through integrating sustainability more fully into the core of their business. A value mapping tool is developed to help firms create value propositions better suited for sustainability. Design/methodology/approach – In addition to a literature review, six sustainable companies were interviewed to understand their approaches to business modelling, using a case study approach. Building on the literature and practice, a tool was developed which was pilot tested through use in a workshop. The resulting improved tool and process was subsequently refined through use in 13 workshops.
Full-text available
Purpose – The purpose of this paper is to offer insights into a tool that one of the authors has developed to help map, and thus visualise, stakeholder power and influence within the performing organisation. Design/methodology/approach – The concept described in this paper has been tested at several large international gatherings to well over 200 active professional project managers. The feedback to date has been very positive. This positive feedback led to testing of these ideas through research being conducted during 2004/2005 by one of the authors who is a candidate for the doctor of project management (DPM) at RMIT. Findings – The research is centred around this tool, the stakeholder circle, as a means to provide a useful and effective way to visualise stakeholder power and influence that may have pivotal impact on a project's success or failure. The stakeholder‐circle tool is developed for each project through a methodology that identifies and prioritises key project stakeholders and then develops an engagement strategy to build and maintain robust relationships with those key stakeholders. An example of the tool is presented. Originality/value – Future papers will provide case study examples currently under way of the use of this tool. The implication for this tool's use is that project managers can clearly visualise and map stakeholder influence patterns that have significant impact on stakeholder outcome expectations.
High-definition televisions should, by now, be a huge success. Philips, Sony, and Thompson invested billions of dollars to develop TV sets with astonishing picture quality. From a technology perspective, they've succeeded: Console manufacturers have been ready for the mass market since the early 1990s. Yet the category has been an unmitigated failure, not because of deficiencies, but because critical complements such as studio production equipment were not developed or adopted in time. Under-performing complements have left console producers in the position of offering a Ferrari in a world without gasoline or highways--an admirable engineering feat, but not one that creates value for customers. The HDTV story exemplifies the promise and peril of innovation ecosystems--the collaborative arrangements through which firms combine their individual offers into a coherent, customer-facing solution. When they work, innovation ecosystems allow companies to create value that no one firm could have created alone. The benefits of these systems are real. But for many organizations the attempt at ecosystem innovation has been a costly failure. This is because, along with new opportunities, innovation ecosystems also present a new set of risks that can brutally derail a firm's best efforts. Innovation ecosystems are characterized by three fundamental types of risk: initiative risks--the familiar uncertainties of managing a project; interdependence risks--the uncertainties of coordinating with complementary innovators; and integration risks--the uncertainties presented by the adoption process across the value chain. Firms that assess ecosystem risks holistically and systematically will be able to establish more realistic expectations, develop a more refined set of environmental contingencies, and arrive at a more robust innovation strategy. Collectively, these actions will lead to more effective implementation and more profitable innovation.
The Wide Lens: A New Strategy for Innovation
  • R Adner
Adner, R. (2012). The Wide Lens: A New Strategy for Innovation. Portfolio Penguin.
Serious Work: How to Facilitate Meetings & Workshops Using the Lego Serious Play method
  • S Blair
  • M Rillo
Blair, S., Rillo, M. (2016). Serious Work: How to Facilitate Meetings & Workshops Using the Lego Serious Play method. ProMeet.