Innovation ecosystem strategy

Oxford dictionary (2021) defines ecosystems as complex networks or interconnected systems. In the business industry ecosystems are defined as a networking systems

Definition Source

Dynamic capabilities are organization's capacity to

purposefully create, modify and extend their resource base (Helfat et. al, 2007)

Dynamic capabilities are companies' processes that use resources to integrate, reconfigure, gain and release resources

(Eisenhardt & Martin, 2000)

Dynamic capabilities are learned and stable patterns of activities that organizations use to modify their operational routines in pursuing improved efficiency in the market

(Winter & Zollo, 2002)

Dynamic capabilities are companies' enablers to create, deploy and protect their assets, competences and complementary assets that reinforce their superior lon-run business performance

(Teece and Augier & Teece, 2009;2009)

containing a set of objects which are linked to each other (Gomes et al. 2018). In other words, ecosystems are interlinked company networks whose performance de-pends on one another. According to Moore (1993), businesses should not be viewed as individual companies but rather as business ecosystems. The business ecosys-tems resemble the co-operative environment where companies coevolve their capa-bilities around a new innovation. In these co-operative business ecosystems compa-nies can better satisfy their customer needs and incorporate new rounds of innova-tions. In other words, the ecosystems are related to both business objectives but also to the creation of new innovations, making the ecosystems also open innovation eco-systems. As it can be interpreted from Moore’s (1993) business ecosystem definition, the innovation ecosystem can be concerned as a part of the business ecosystem.

According to Gomes et al. (2018) business ecosystems are the value creators for individual participants when the participants cannot commercialize their products or services with their own competences. Thus, companies rely on business ecosystems when they cannot capture the value on their own. Innovation ecosystems on the other hand resemble more the value creation rather than the value capture. They are con-sidered as platforms where people, cultures and technology interact, catalyse, accel-erate, and trigger new innovations in an entrepreneurship-empowered fashion.

(Carayannis & Campbell 2009)

According to Adner (2006), when innovation ecosystems work, they are the creators of value to their organization’s customers. The cornerstone in the maximized value creation through innovation ecosystems, is understanding the ecosystems them-selves. Since the organizations belonging to the ecosystems are dependent on one another, each actors’ poor performance has a degrading affect to the total perfor-mance of the ecosystem. According to Jacobides et al. (2018), the identification of different partners in the ecosystem is particularly important for the focal innovation producers, since the only thing standing between the end customer and the company may be another ecosystem partner. Without that partner’s co-operation the com-pany’s product cannot be delivered to the end customer. Despite the importance of understanding the dependencies between different partners in the innovation eco-system, companies tend to undermine the risk analysis of their ecosystem and base their expectations of projects on shaky foundations. (Adner 2012) In other words, without a thorough understanding of the internal and external partners’ effect to the innovation, success and failure are ought to occur in very random circumstances. To increase the understanding of the organization’s ecosystem and to enable a more accurate ecosystem strategy formulation, Adner (2006) presents organizations a

framework with which the ecosystem-related risk identification is more convenient.

The framework divides the innovation ecosystem risks into three different categories:

 Initiative risks

 Interdependence risks

 Integration risks.

Initiative risks present the familiar uncertainties that indulge in the markets while run-ning projects. They are the uncertainties which are usually related to project man-agement and the challenges in it (Adner 2006; Gomes et al. 2018). Interdependence risks are related to the coordination of complimentary innovators. Since the compa-nies are interdependent on one another’s performance, a poorly performing partner base will issue a greater risk for the company. (Dattée et al. 2018; Jacobides et al.

2018) Integration related risks stress the risks in the adoption process along the eco-system’s value chain. These risks resemble the possible development gaps and adoption cycles which may have delaying effects to the focal innovation’s delivery to the end customers. (Adner 2006)

Modelling an ecosystem is not easy to any company, since the number of interlinking actors is so great. Different tools for modelling an ecosystem strategy have been presented in literature, such as the “Ecosystem Pie Model” (EVP), which divides the ecosystem into different categorized sections. The EVP gives a structured view to the ecosystem itself and highlights the interlinkage to different risk factors in the eco-system. (Talmar et al. 2020) With a broader view to the ecosystem itself, the formu-lation of an ecosystem strategy in that ecosystem environment will become easier.

Nevertheless, Adner (2006) still highlights that the formulation of an ecosystem strat-egy is strongly iterative, and it should always start from the definition of the perfor-mance expectations and the target market. Through deeper analysis of the three risk categories, the performance expectations can be iterated into a more clarified and realistic form. The Ecosystem framework, presented in figure 9, illustrates the itera-tive functionality of the framework, where the starting and ending point can be the creation of an innovation strategy.

Figure 9. Formulation of an innovation ecosystem strategy modified from (Adner 2006)

Figure 9 presents the workflow for an ecosystem strategy formulation and its iterative risk analysis. For Adner (2006), the risks analysis plays a key role in this framework.

Through constructive risk analysis, the organizations are ought to become more knowledgeable about their internal and external terminal factors which cause possi-ble risks for the organization. Moreover, the iterative ecosystem formulation and cat-egorized risk assessment enables the companies to reflect with the changes hap-pening in its market environment. Along with new opportunities, also new set of risks arise related to the innovation ecosystems. This is caused by for example the de-pendencies related to the new developing aspects of the innovation ecosystem.

These dependencies, if left unacknowledged, may brutally derail company’s best ef-forts in the market environment. (Jacobides et al. 2018)

2.4.1 Initiative risks

Initiative risks resemble the possible discrepancies and uncertainties that occur in the project management scope (Gomes et al. 2018). According to Miller and Lessard (2001) project related risks can be dissected into three categories, (1) market risks:

supply, market demand and financials; (2) completion: operational and technical risks and (3) institutional: social acceptance and regulations. Additionally, most risks can be framed more as managerial problems than technical issues. Examples of project risks are e.g., the feasibility of the product/service, the competition in the market, quality of the project team, the appropriateness of the supply chain and the legislation of different market areas (Adner 2006).

Market risks relate mostly to the market demand, competition between rivals and to price and access uncertainties of supply (Miller & Lessard 2001), market acceptance

and time-to-market windows (Campbell 2014). Since the market demand has usually quite a big variance, the risk analysis itself has also quite high-risk levels (Hillson 2017). According to Leung et al. (1998) financial risks relate mostly to funding, capital costs and possible budget cuts. Inadequate funds from e.g., project owners may cause delays and inefficiency to the project. Additionally, the fluctuations in the ex-change rates of foreign currencies or inflation may have a risky effect to the project’s capital costs. The biggest difficulty in financial risk assessments is related to situa-tions where the projects offer adequate prospective returns. In these situasitua-tions, the risk-sharing arrangements are difficult and cause additional friction between different project stakeholders. (Miller & Lessard 2001)

Completion risks can be divided into operational and technical factors (Miller & Les-sard 2001). The operational risks relate mostly to the shortage of resources, incapa-ble work force, lack of coordination and insufficient precaution. Having incapaincapa-ble work force, or not having enough resources in the project increases the risk of project delays and failure of the project related activities. According to Campbell (2014) com-pleting projects on time, in budget and in schedule requires sufficient project planning and coordination. Lack of planning complicates the project management’s work and increases the risk for unforeseeable events which may delay and harm the project.

Leung et al. (1998) divide technical risks into engineering difficulties and novelty of technologies. Engineering difficulties relate to the possible difficulties appear during the project and require additional and possibly more complex engineering capabilities that were anticipated in the first place. Operating with new technologies may cause service and training related risks, since working with marginal equipment has usually also a marginal support in case of problematic situations (Campbell 2014).

Institutional risks are divided into social acceptance, sovereignty, and regulations (Miller & Lessard 2001). The changes in regulations refer to the changes of e.g., laws, permit requirements, public consultation, and government approvals. These sort of changes may have substantial effect to projects, since they are usually inter-dependent on many regulation related factors. (Leung et al. 1998) Especially new government regulations may have quite sudden and crucial effects to the project, its environment, and the project’s stakeholders (Campbell 2014). Social acceptability risks refer to the probabilities of the project’s sponsors to meet resistance from influ-ential pressure groups or regional parties. Sovereignty related risks on the other hand refer to the possible risks that the counterparties want to step out or renegotiate the contracts, property rights or concessions. (Miller & Lessard 2001)

2.4.2 Interdependence risks

Oxford dictionary (2021) defines interdependence as a “fact of consisting of parts that depend on each other”. When a component is part of a larger solution, a suc-cessful performance can only be achieved when all the components associated with the solution perform as expected. When a company belongs into an ecosystem, the dependent relationships between the actors confine the company. In other words, the product’s/service’s success is not reliant from one entity, but it depends on the performance of all relevant ecosystem actors. (Dattée et al. 2018; Jacobides et al.

2018) Thus, all components both in the internal and external processes of the solu-tion are interdependent with each other.

The recognition of the different dependent actors is not obvious since the interde-pendent actors may cross to different industries (Jacobides et al. 2018). Expressly, the dependencies may not be directly visible for the companies since the dependen-cies do not follow any industry of market specific boundaries. Nevertheless, it is of essence for the companies to try to recognize their interdependent partners from the ecosystem, since the company’s performance is highly reliant on the performance of all interdependent partners in the ecosystem. According to Adner and Adner & Feiler (2006; 2019), the interdependency risk describes the joint probability that the differ-ent actors can satisfy their commitmdiffer-ents in a specified timeframe. Adner (2006) ex-plains the effects of different partners’ executions of the commitments through math-ematical terms. For example, if a company A is dependent on the successful devel-opment and deployment of its suppliers B, C and D, and they all give a probability of 80% for a successful execution. The expected result for the company to succeed is thus 0,8*0,8*0,8 which equals to 51%. In other words, interdependence risks can be assessed by multiplying probabilities for delays caused by the complementary part-ners either within or outside the organization. Naturally, the real market environment cannot be estimated with as fine-grained numbers as are presented here. Still, the companies may apply simpler assessments for the risks such as one-to-three scale or a low/medium/high risk scale. Additionally, it is important to understand, that the higher the number of different interdependent partners there are in the ecosystem, the less control one company can have over its own success.

Although the multiplying effect of different interdependence risks cannot be calcu-lated as precisely as explained by Adner (2006), it is still crucial for the companies to attempt to recognize as many interdependence risks as they can. Moreover, it is not enough for the companies to merely identify the interdependence risks, they need to

understand the reasons for them. Table 3 presents different researchers’ discoveries of interdependence risk categories that have been commonly detected from the eco-systems.

Table 3. Examples of interdependence risks adapted from (Iansiti & Levien 2004;

Adner 2006; Cennamo et al. 2018; Adner & Feiler 2019)

The five different categories presented in table 3 are examples of the common inter-dependence risks detected from different ecosystems. Iansiti & Levien, Adner and Adner & Feiler (2004; 2006; 2019) stress especially the leadership and incentive re-lated interdependence risks. The researchers back the incentive risk with the obser-vations where different ecosystem actors may not be as dependent on the outcomes of the ecosystem as others. These actors have usually only a small part in the eco-system and hence e.g., big financial investments are experienced more as a cost than as a benefit. Leadership related risks are more related to different managerial visions in the ecosystem. The different companies’ managers may e.g., disagree of the ecosystem’s development direction which may have devastating consequences for the innovation itself. Adner and Cennamo et al. (2006; 2018) highlight the eco-system’s different actors’ financial status as a third interdependence risk category.

Although the ecosystem interlinks different actors together it does not however guar-antee an equal profitability for all actors. Thus, it is of essence for the companies to analyse their interdependent stakeholders’ financial situations since the financial col-lapse of a terminal ecosystem actor may have negative effects to the entire ecosys-tem. Lastly, Adner (2006) pinpoints the possible effects of regulations and uneven development of different ecosystem actors. Laws define the rules in different market areas, and all entities are bound to comply with them. Sudden changes in the regu-lations may affect heavily to the ecosystem actors and thus it is important for the

companies to analyse the possible changes in the legislation. The uneven develop-ment of different actors may also have delaying or even blocking effects to the eco-system’s value chain. Recognizing the weakest links in the ecosystem will help the companies to assess their ecosystem strategies more accurately.

2.4.3 Integration risks

Integration risk indicates to the uncertainties that are related to the adoption process in the innovation ecosystem’s value chain (Gomes et al. 2018). Different actors in the innovation ecosystem differ with their capabilities to deploy new ways of working.

Those actors who stand between the company and its end customer are considered to pose a probable integration risk for the company. According to Adner (2006), inte-gration risks may occur e.g., in situations when the partners’ development is not in the same level with the company itself. Thus, a possible scenario may occur that an intermediary, of which the case company is interdependent on, stands between the company and the end customer. If this intermediary’s processes are not in a sufficient level to carry out the needed processes, no matter how developed the company’s product/service is, it will not reach its targeted customer base. This will then cause the company to fail, not due to an unfeasible product, but because its partners were not ready to pick up the new ways of working.

Due to the potential integration risks with the intermediaries, companies tend to eval-uate the possibilities of acquiring the intermediaries to themselves. This way the com-panies can have more power over the value chain’s successful performance. The decision of moving upstream in the value chain is not easy. Integrating into a busi-ness area in which the company does not have networks and capabilities may turn out to be an even riskier decision than the initial integration risk was. (Williamson &

De Meyer 2012) Balancing between the decision of an upstream integration or trust-ing to the intermediaries is not easy for the companies. Accordtrust-ing to Adner (2006), one of the core things in defining the integration risks, is to analyse both the direct and indirect costs, and benefits for every adoption step throughout the value chain.

In case the costs exceed the benefits, e.g., if the solution demands the partners to heavily change their equipment or working procedures with only little benefits, it will be very unlikely for the partners to bend their processes into the company’s favour.

Table 4 presents some of the common integration risks highlighted by Adner (2006).

Table 4. Examples of integration risks (based on Adner; 2006)

Table 4 presents the risks related to the partners’ evaluation between the benefits and the total costs caused by a change to their processes. According to Adner (2006) it is worthwhile for the companies to consider helping their partners to achieve the desired performance. The companies may for example provide financial support to help their suppliers or logistics chains to purchase the needed equipment. This way, the company shoulders the responsibility to its fellow actors but at the same time ensures a successful performance in the ecosystem’s value chain. Additionally, by leaving the capabilities to the actors, the company increases the stimulus which comes from the actors’ own corporate cultures, geographies, and market contexts.

(Williamson & De Meyer 2012) The companies may also share some of their intan-gible resources to support their partners for the change. Naturally, meddling into the value chain more extensively means the birth of a new set of risks. Comparing the risks and their costs with the possible benefits will help the companies to make their decisions related to the support of their partners. (Adner 2006)