Paper to be presented at DRUID19 Copenhagen Business School, Copenhagen, Denmark June 19-21, 2019

Learning from the Past: Soft Methodology as a Tool for Reflective Innovation Management

Chipo Nancy Ngongoni Stellenbosch University Industrial Engineering [email protected] Sara Susanna (Saartjie) Grobbelaar Stellenbosch University Industrial Engineering [email protected] Cornelius Stephanus Lodewyk Schutte Stellenbosch University Industrial Engineering [email protected]

Abstract Innovation projects sometimes fail to achieve their proposed outcomes. This is more pronounced in public sector service-delivery interventions that are affected by a wide range of infrastructural constraints, inadequate resources and the multiplicity of stakeholders. This paper proposes (SSM) as a robust methodology to review, understand and develop responses to manage innovative . We start off by outlining the critiques of the innovation ecosystems construct and highlight related research gaps. We then move on to outline some research methodologies that have been utilised to better understand innovation ecosystems after which the authors argue for the relevance of SSM in furthering ecosystems research. SSM is a recommended tool for evaluating complex environments. Learning from the Past: Soft Systems Methodology as a Tool for Reflective Innovation Ecosystem Management

Abstract: Innovation projects sometimes fail to achieve their proposed outcomes. This is more pronounced in public sector service-delivery interventions that are affected by a wide range of infrastructural constraints, inadequate resources and the multiplicity of stakeholders. This paper proposes Soft Systems Methodology (SSM) as a robust methodology to review, understand and develop responses to manage innovative ecosystems. We start off by outlining the critiques of the innovation ecosystems construct and highlight related research gaps. We then move on to outline some research methodologies that have been utilised to better understand innovation ecosystems after which the authors argue for the relevance of SSM in furthering ecosystems research. SSM is a recommended tool for evaluating complex environments.

Key words: Soft Systems Methodology; Innovation Ecosystems; Innovation for Inclusive development (II4D), Innovation Management;

Introduction Managing multi-stakeholder innovation environments has always been a contentious issue (Chesbrough, Vanhaverbeke, & West, 2006; Esterhuizen, Schutte, & du Toit, 2012; Lundvall, 2007; Vargo, Wieland, & Akaka, 2016; Vargo et al., 2015). More so, the concept of innovation ecosystems research that has taken a lot of backlash around the usage of the ecosystem construct (Oh, Phillips, Park, & Lee, 2016). Hence currently to fundamentally confirm its validity, innovation ecosystems discourse focuses on definitions, dynamics and constructs (Ritala & Gustafsson, 2018). Even though that is important in furthering the discourse it does not adequately focus on how the construct can be utilised to facilitate understanding of problem solving through value aggregation and appropriation spurred by ecosystem actor co-creation processes (Adner & Kapoor, 2010; Adner Ron & Kapoor Rahul, 2016; Autio & Thomas, 2014; Smorodinskaya, Russell, Katukov, & Still, 2017).

Innovation ecosystems have been defined in various ways which all align with the interrelations between the actors as well as the purpose of the ecosystem. Jackson (2011) emphasised the complex relationships between innovation ecosystem actors towards a functional goal (Jackson, 2011) , with Jacobides, Cennamo, & Gawer (2018) noting that an ecosystem construct is a set of actors with varying degrees of multilateral, nongeneric complementarities that are not fully hierarchically controlled (Jacobides, Cennamo, & Gawer, 2018, p. 2264). Structurally, Autio and Thomas (2014) maintained that there is usually an organization of actors around a “focal firm or a platform, and incorporating both production and use side participants, and focusing on the development of new value through innovation “ (Autio and Thomas, 2014, p. 3). Adner went on to propose to look at ecosystems as structure where the innovation ecosystem becomes “the alignment structure of the multilateral set of partners that need to interact in order for a focal value proposition to materialize” (Adner, 2017, p. 40).

The purpose of this paper is to offer insight on how, through the utilisation of the Soft Systems Methodology (SSM), researchers and innovation advocates/strategists can learn from the past and take advantage of tangible and more importantly intangible knowledge that arises from purportedly failed innovation projects. SSM is one of the most distinctive approaches in the area of applied systems thinking, bringing clarity to multi-stakeholder situations (Bernardo et al., 2018; Checkland, 2000). SSM through conceptualisation, layered thinking and visualisation supports model building and comparison of the models while the real-world offers shared insights about what should be and, in an iterative manner, allow purposeful action to be taken. Starting from the standpoint that the authors see merit in the innovation ecosystems construct, the paper will elaborate on how the innovation ecosystems construct has been critiqued along with identified research gaps. Secondly, SSM aspects are outlined and how they relate to understanding a systems perspective. Finally, a case of how SSM is utilised in a healthcare context in South Africa will be put forward and discussed.

Theoretical background Critiquing Innovation Ecosystems The ecosystems construct in itself has come under a lot of scrutiny. This has led to the construct being categorised in innovation management literature under three perspectives. These are the business ecosystem perspective that focuses on a firm and its environment (Jacobides et al., 2018; Moore, 1993; Still, Lähteenmäki, & Seppänen, 2019); innovation ecosystem perspective focusing on new value proposition and how actors come together to support it (Adner, 2017; Autio & Thomas, 2014), and platform ecosystems perspective that consider how actors organise around a platform (Gawer & Cusumano, 2014; Herman, Grobbelaar, & Pistorius, 2018; Ngongoni, Grobbelaar, & Schutte, 2018; Parker, Alstyne, & Choudary, 2016).

Oh et al. (2016) highlighted that though the ‘eco’ literature makes positive contributions they maintain that such contributions are in no way aligned to the ecosystems construct as the usage of the construct is more metaphorical and poorly developed. As a first argument Oh et al. (2016) noted that an innovation ecosystem is not an evolved entity but it is designed. Though this may be considered a valid argument, in the face of new market forces and disruptive technologies an ecosystem actually evolves from the designed state to another state just as a natural ecological ecosystem would (Jackson, 2011). Moreover, the ‘eco’ notion emphasises the non- linear nature of the collaborations that occur for innovation (Jackson, 2011; Ritala & Almpanopoulou, 2017). Oh et al. (2016) concluded that the term ‘ecosystem’ does not offer any novel ways of thinking when it comes to innovation and that the risks outweigh the benefits of such alignment (Oh et al., 2016). The argument being that the ecosystem construct has been used metaphorically in describing the interconnectedness of innovation and entrepreneurship, whilst drawing phenomena explanations from other theoretical foundations (Ritala & Gustafsson, 2018).

This is largely due to the innovation ecosystem concept being associated with ambiguous terminologies and terms and different types of ecosystems being used interchangeably with not much theory testing (Schreieck, Wiesche, & Krcmar, 2016; Smorodinskaya et al., 2017). However, there have been recent studies that have digressed from just aligning definitions with examples to consider the ecosystem construct (Adner, 2017; Cibat, Süße, & Wilkens, 2017; Ritala & Almpanopoulou, 2017). These studies have the aim of ascertaining the evolutionary characteristics of the ecosystem as well as assess how value is created in this ecosystem (Pittaway & Autio, 2017; L. Thomas & Autio, 2012). Smorodinskaya et al. (2017) realise that “In the age of non-linear innovation and digital technologies, innovation can be better nurtured within a special, innovation-conducive environment. Such an environment may be seen as an ecosystem meant for co-creation of value through collaboration. “(Smorodinskaya et al., 2017, p. 3)

In a survey gathered from innovation ecosystems researchers, aspects around the way the ecosystem concept is perceived, how research is conducted and the theoretical foundations and tools to study ecosystems empirically were highlighted as important aspects in furthering ‘ecosystems’ research (Ritala & Gustafsson, 2018). Conceptual ambiguity, methodological challenges and a lack of a rigorous foundation are all major aspects that are critiqued over the ‘ecosystems construct’ since it has a strong alignment to other systems and network level concepts (Oh et al., 2016; Ritala & Gustafsson, 2018). This paper offers an alternative methodology that assists in ecosystem theory building.

Advancing the Innovation Ecosystems Discourse The ecosystems construct research gaps are mainly centred on understanding ecosystem emergence, coordination, collaboration, value creation/capture, governance and regulation and discerning differences from other constructs.

Understanding how ecosystems actually emerge and the theory testing aligned with its emergence is of paramount importance for cementing the construct (Gawer & Cusumano, 2014; Jacobides et al., 2018; L. D. W. Thomas & Autio, 2014). This has seen complex adaptive systems and systems thinking as theoretical foundations that can assist in explaining ecosystem dynamics (Ritala & Gustafsson, 2018). The aim is to look beyond metaphoric symbolisms but actually meet the needs of better understanding the underlying dynamics of the ecosystem. Research methods such as action research and design science have been methodologies that have been commonly aligned with the building of a new ecosystem (Herselman & Botha, 2017; Tsujimoto, Kajikawa, Tomita, & Matsumoto, 2015), however in order to ensure sustainability and longevity of the ecosystem, other research methods that allow reflection are essential, and therefore we suggest the use of SSM.

When it comes to ecosystem collaboration and coordination, a call to ensure that customer involvement is in the value creation process as well as integration of complementors in ecosystem analysis is also important (Jacobides et al., 2018; Pittaway & Autio, 2017; Schreieck et al., 2016). Alternatively, going against the grain of collective analysis is a call to analyse participants individually and how being part of the ecosystem affects actors distinctly (Schreieck et al., 2016). Furthermore, the dynamics of how value is created and appropriated in an ecosystem is also still an enigma (Aarikka-Stenroos, Peltola, Rikkiev, & Saari, 2016; Adner & Kapoor, 2010; Adner Ron & Kapoor Rahul, 2016; Gomes, Facin, Salerno, & Ikenami, 2016). Through understanding such aspects then the foundational constructs of innovation ecosystems can be applicable across various contexts. An example is in Innovation for Inclusive Development (I4ID) that takes into account the ecosystem building mechanisms and business models behind ecosystem actors that operate in such challenging dynamics and resources constrained environments (Aarikka-Stenroos et al., 2016; Merwe, Grobbelaar, & Bam, 2019; Merwe & Grobbelaar, 2018). I4ID is the development of products and services for and/or by marginalised communities with the aim of improving economic and social welfare (Foster & Heeks, 2013; Heeks, Foster, & Nugroho, 2014; Merwe & Grobbelaar, 2018).

Notably, a substantial amount of innovation ecosystem studies look at technological aspects (design or implementation of a new technology) and there is a need to look beyond these technical aspects and address competency building of ecosystems from strategy, culture, institutions and organisation (Oh et al., 2016). On the other hand how technology actually evolves in an ecosystem in line with the role it plays in ecosystem management and the roles of different actors is also a valid focus-area (Aarikka-Stenroos et al., 2016). Integrating ecosystem research into existing schools-of-thought is a progressive way to further ecosystems research with more studies relying on the theoretical base of systems thinking, complex adaptive systems, network theory and social networks in order to explain the different aspects (Ritala & Gustafsson, 2018). An example of such is exemplified by looking at data as a boundary resource that can be utilised into cementing the construct and obtaining innovation ecosystem metrics (Oh et al., 2016; Schreieck et al., 2016).

Understanding Soft Systems Methodology Softs systems methodology was developed by Peter Checkland as a method for understanding human activity systems in action research (Checkland, 1981). It was further extended by Brian Wilson in the area of management of information systems (Wilson, 2001). It was meant to offer a method that digressed from traditional ‘hard’ systems based on mechanistic thing to integrate ‘soft systems’ that were aligned with human or social systems. It entails starting with unstructured problems particularly within complex social activity systems when there is an ill-defined problem situation requiring rigorous contextual understanding (Checkland, 1981; Durant-Law, 2005; Rose, 1997; Wilson, 2001). It sets out to structure the problem and offer a solution and is mostly aligned with action research, though it is applicable in any other social science related research (Rose, 1997). The SSM centres around four main activities which are (Checkland, 2000);

1. Problem Identification: what is the problem including political and cultural issues; 2. Model building: formulation of conceptual and activity models; 3. Situation analysis: understanding and debating the situation using the models on: a. changes that would improve the situation and are regarded as both desirable and (culturally) feasible, and b. the commitments between conflicting interests, which enable action to improve to be taken; 4. Taking action: steps taken in order to foster the situation’s improvement.

The reasoning strategy of SSM centres on modelling abstract features of what the problem is and forming textual definitions aligned with the problem (root definitions) as devices that are utilised to improve the problem solver’s interpretation of the problem-cyclical process (Rose, 1997). The sequence of the activities is flexible and cyclical as outlined in figure 1, cementing its relevance in line with tracing the emergence of ecosystems or analyzing what can be salvaged from failed innovation aligned projects.

Figure 1: The inquiring/learning cycle of SSM

SSM can be utilised for both theory generation and theory testing. Though primarily, the methodology has been aligned with the human activity and interactions that exist in any underlying problematic situation, from the perspective of the ecosystem those interactions, though spurred by human beings, can be governance-centric, firm-centric or ecosystem-centric. Additionally, SSM can be a sound methodology to use during the various stages of growth of the ecosystem, from conception where particular frameworks and dynamics are defined and outlined to post-mortem analysis of the ecosystem to spur evolution. Checkland argued that success of the methodology was based on information sharing as well as iterations of the concepts that are developed with what is actually happening in the (Checkland, 1981, 2000). When it comes to ecosystems it is important to have tools that guide the formulation of the framework with which to map the ecosystem value creation process flows. SSM has a set of tools such as CATWOE that can be utilised for analysis. Checkland outlined that in order to define root definitions of the system properly it is important to ask questions aligned with stakeholders in the system as well as an overview of the field in which the system operates. This was classified under Customers, Actors, Transformation, Weltanschauung (world view), Owner and Environmental constraints (CATWOE) (Brown, 1992; Checkland, 1981; Wilson, 2001). A CATWOE analysis requires listing the inputs and the nature of change these inputs undergo to be transformed into outputs. These are outlined as:

• Customers: these are the identified end users /stakeholders for whom the systems exists. This includes both stakeholders who benefit or suffer when the system changes • Actors: are the stakeholders responsible for implementing system changes • Transformation: is the change that the system or process brings about • Weltanschauung: Weltanschauung, also known as “Worldview". It is the justification for the transformation of the system or process and entails placing the process or system under analysis in its wider context to highlight the consequences or relevance of such process to the overall system. • Owner: is the actor that has the authority to make the changes, stop the project, or decide on whether to go ahead with the change. • Environmental constraints: are the external constraints under which the system works, and which may hamper or restrict the changes to the system.

When looking at CATWOE from an innovation ecosystems perspective, aspects such as the customers, owner and actors are usually all ecosystem actors. This is because ideally an ecosystem is not supposed to have any form of control or management but in innovation ecosystems that is still a point of contention (Ngongoni et al., 2018). Interestingly, SSM is also flexible enough to integrate other methodologies if needed, such as Grounded theory that offers complementary aspects to where SSM falls short (Brown, 1992; Durant-Law, 2005) see Table 1.

Table 1: Comparison of Grounded Theory and Soft Systems Methodology Steps Soft Systems Methodology Grounded Theory 1 The problem situation unstructured An unexplained phenomena or process 2 The problem situation expressed The phenomena or process identified for study 3 Root definitions of relevant systems Data collection and coding 4 Conceptual model construction Theme extraction 5 Model and problem situation comparison Postulate generalisations 6 Feasible and desirable change construction Develop taxonomies 7 Action to improve the situation Theory development Source: (Durant-Law, 2005)

Ideally, SSM is purported to offer a participative and democratic stance as the input of all system actors is supposed to be included in the system analysis. However, with the quick merging and dismemberment of innovation projects as they have life stages defined by funding, expertise, political and economic conditions amongst other things, we find that that in resource constrained regions, completely abandoning projects and looking to implement a new technology or service takes a new learning curve that causes a cyclical growth stalling of any progress towards meeting the Sustainable Development goals or national innovation strategies. The need to always invest in new trends and fads when there are already fundamental projects that have already undertaken important groundwork facets such as feasibility studies, user education means that a lot of intangible value is lost in the implementation of every new project. Using SSM as a tool to assess purportedly ‘failed’ projects as a means to see what can be salvaged is one way of speeding up the innovation ecosystem growth process.

The Role of Soft Systems Methodology in Innovation Ecosystems Management Systematically linking aspects such as knowledge production and technology in innovative environments is something that has been outlined extensively in innovation systems research. Looking past the semantics of differentiation between national, regional, sectoral and technology innovation systems (Lundvall, 2007; Lundvall, Vang, Joseph, & Chaminade, 2009; Merwe et al., 2019) there are certain overall conditions that are aligned with addressing systems of innovation. (Hekkert, Suurs, Negro, Kuhlmann, & Smits (2007) pointed out that there are two main approaches when analysing innovation systems, “components based” and “functions based” approach. The “components based” approach looked at the actors, soft and hard institutions, interactions and the physical, financial and knowledge structure (Merwe et al., 2019). The functions based approach was developed in order to make analysis more dynamic and possible to map over time where a system is also defined by its functions (Hekkert et al., 2007). Hanlin & Andersen (2019) merged these two approaches and summarised them into what they called the 4F framework shown in figure 2.

Figure 2: The 4Fs and their interlinkages

The framework outlines the system form (system actors identification, interaction and collaboration dynamics), field (markets and institutions in which the innovative activity takes place), function (the ultimate goal of the contextual innovation), and flows (the origins, creation and the ways in which the system is conceptualised) (Andersen & Hanlin, 2019). Notably, when looking at resource constrained countries that mainly align with I4ID different facets of this 4F framework have been outlined. From a study perspective to holistically address all these aspects at once would probably amount to a data intensive study. Introducing modularity in looking at the system is one way of analysing the system. Hence, Van der Merwe, Grobbelaar, & Bam (2019) outlined seven system functions for mapping events and activities over time and applied their function identifying framework to an mHealth case study (Merwe et al., 2019). These are entrepreneurial activities, knowledge development, knowledge diffusion, guidance of search, market formation, mobilisation of resources and creation of legitimacy (Merwe et al., 2019). When now looking at an innovation ecosystem perspective, the authors contend that these facets still stand but proposed to delinearise the relationships between the linkages. Hence, if taking the definition put forward by Adner (2017) of ecosystem as structure aimed at value proposition, the function of the ecosystem would be the heart of understanding why the ecosystem is necessary in the first place and the field would affect the form and flows of intangible and tangible knowledge in the ecosystem. This would give rise to a nested concentric dynamic outlined in figure 3.

Flows

Form

Field

Function

Figure 3: 4Fs aligned with Innovation Ecosystem Evolution

So when applied to the evaluation of an ecosystem through using SSM instead of the generic mapping of the current state (AS-IS) to a desired state (TO-BE) and offering more theories and frameworks, we suggest that sometimes it is important to take a pause and look at the historical state (WHAT-WAS) in terms of what was originally planned for the system and mapping it to how it has actually panned out. Instead of the historical state only looking at barriers to innovation uptake as shown on the framework proposed by Van der Merwe & Grobbelaar (2018) additional aspects are proposed across all levels of the 4F framework for ecosystem evolution. These aspects range from the intended beneficiaries of the perturbed ecosystem to changes that were made to meet changing functions of the ecosystem. We concur that the aspect of history and time is important when it comes to ensuring the longevity and evolution of any more so with innovation ecosystems (Cilliers, 1998).

Aligning systematic dimensions from the 4F framework with the questions outlined in the SSM methodology, we add another set of questions that assist in painting a clearer picture aimed at ecosystem evolution. This is shown in Figure 4

Figure 4: SSM Ecosystem alignment with Systems thinking. Source: authors’ own elaboration.

Case example South Africa has a high rate of infant and maternal mortality rates. Currently they are infant mortalities of 25 per 1,000 live births and 152 maternal mortality per 100,000 births (Dorrington, Bradshaw, Laubscher, & Nannan, 2018). Moreover these deaths are often preventable and hampered by access to information (Peter, 2018; Peter, Benjamin, LeFevre, Barron, & Pillay, 2018). Hence the National Department of Health has carried out various mHealth projects in a bid to address these disparities, with ones utilising mobile feature phones as tools in the information dissemination process. Such projects include the Mobile Alliance for Maternal Action (MAMA) and the MomConnect project. These programs, though still functional, are actually an example of how one project mapped the way for the other to function properly, through an evolution of sorts.

Mobile Alliance for Maternal Action (MAMA) In 2011, the Maternal and child survival program launched the MAMA project in South Africa through a public- private partnership between the United States Agency for International Development (USAID), Johnson & Johnson, the United Nations Foundation, and BabyCenter. MAMA’s primary aim was to address information disparities and improve the quality of healthcare (Peter et al., 2018). MAMA consisted of a platform that disseminated information to expectant and early stage mothers on the stages of pregnancy, birth and early childhood development. Information was disseminated across 5 channels-voice, SMS, USSD, mobile websites and Mxit1 using 6 official South African languages (MCSP, 2018). The program had also been launched in Bangladesh, India and Nigeria. MAMA was handed over to the South African government in 2014 after acquiring about 500 000 users. MomConnect The National Department of Health (NDoH) of South Africa, as the main initiator and facilitator, conceptualised MomConnect in 2012 and launched in 2014. The NDoH leveraged off lessons from particularly MAMA which had been operating in the same environment. In contrast MomConnect primarily uses SMS and USSD technology to disseminate information to over 1.7 million women in the 11 official languages. The program has over 20 collaborating partners and ensures interoperability of the program with the South Africa Health by being part of the Open Health Information Mediator (OpenHIM) project (Merwe & Grobbelaar, 2018).

Analysis of the Evolution of MAMA to MomConnect using SSM Initially in terms of meeting expected metrics in line with user signups and reach, the MAMA project seems to have fallen short. However, through handing over the project to the NDoH this facilitated and sped up a learning curve that the NDoH would have had to experience. The following section looks at how MomConnect leveraged off MAMA from using SSM aligned with the functions, forms, flows and field of the ecosystem, summarised in figure 2.

Figure 5: Case of MAMA to MomConnect

1 Mxit was a free instant messaging application developed by Mxit Ltd. in South Africa that ran on over 8,000 devices, including feature phones, Android, BlackBerry, iPhone, iPad, Windows Phone and tablets. It closed shop in 2015 and handed over all intellectual property to The Research Trust.

Functions: The main goal for both platforms was aligned with health systems strengthening and addressing maternal mortality and information dissemination. MAMA primarily focused on that whilst MomConnect went on to evolve to various subsystems. There was NurseConnect - a platform aimed at nurses to assist them with their jobs especially due to resource/constraint dynamics. Moreover, the platform is now being utilised to report drug shortages from expectant mothers (Peter et al., 2018). South Africa has two primary ways of disseminating health care, the public and private healthcare industry. Future plans include to integrate MomConnect into the private sector ensuring a wider base as well as a more solid picture of the issues that expectant and early stage mothers are facing. This information is all important from a data analysis perspective where strategically the NDoH can plan proactively around the feedback being given.

Forms: Taking the ecosystem as structure aspects- both platforms comprised primarily of key players in maternal and child care. The distinct difference is MAMA was facilitated by non-South African non-profit organisations whilst MomConnect was facilitated by the NDoH. Having the government being the facilitator, especially in a public service delivery system, assisted MomConnect to have direct access to expectant mothers once they registered their pregnancies. This made the signup process easier as besides being able to do it themselves assistance was offered by community health workers hence assisting the users to be on the system. Moreover for MAMA only subscribers of one mobile networks service provider had free access meaning a substantial number of users had to bear the cost of using the service. Whereas with MomConnect, the services was fundamentally free for all users as it got buy-in from all South African service providers. Notably though, as MomConnect is considering diversifying to data-centric versions of the platform, that might be a dynamic that will change but at the current market stage, data is now relatively cheaper and options of having data bundles custom made for such a purpose is a future a possibility.

Flows: On inception, MAMA had no feedback mechanism for either complaints or compliments. This is something MomConnect ensured was in the platform to ensure that the NDoH was well versed on the constraints facing users either technologically or in content. This is an important aspect when it comes to competence building of innovation ecosystems. Whilst initiating the platform it is important to consider what is of paramount importance. When it came to technology, MAMA was already ahead offering the platform users 5 alternative ways of signing up. However, such diverse ways of signing up, in a context where the users are well versed with technology might seem ideal but in this context it just seemed to add confusion. MomConnect, with just two ways to sign up, concentrated more on offering all the languages spoken in South Africa on the platform. In so doing sign-up is easier and most ethnicities are catered for. MAMA starting off with such a high level of tech advancement might be attributed to bounded rationality that arose from the same platform being launched and being successful in India and Bangladesh without considering user behaviour in the South African context. Hence the main targeted user of MAMA was a woman who spends 55% of her time mainly online and who owns a feature phone whereas with MomConnect was geared towards all women especially in the low-income bracket.

Field: South Africa has quite a supportive policy environment when it comes to technology usage in healthcare (Seebregts et al., 2016). It has amongst others a National eHealth, mHealth strategy and Health Normative Standards Framework that deals with interoperability, enterprise architecture and standards markets and institutions in innovation (Merwe & Grobbelaar, 2018). Additionally, there is the Protection of Personal Information Act (PoPI Act) No. 4 of 2013 to protect citizen data obtained from such initiatives. Though the environment is conducive for such innovative activities, the main barriers to scaling of good projects is due to funding dynamics and unsustainable business models with donor funding being the most prevalent way of sustaining projects (Merwe et al., 2019; Merwe & Grobbelaar, 2018). This was apparent with MAMA where all the main players were private institutions which unfortunately can create an alienation of the project from NDoH health system objectives. The digital divide and poverty divide is something which was necessary to also consider and a clear profile of the target user can only be fully acquired through collaboration with the NDoH.

Conclusions This paper has outlined how SSM can be used as a reflective methodology to assist in the explaining the emergence of innovation ecosystems as well as looking at how supposedly ‘failed’ innovation projects can be utilised in order to evolve the innovation ecosystem and create the purported value. This paper serves as a foundation for explaining ecosystem emergence through a systems aligned methodology. The authors intend to build on the aspect mentioned in this paper as a lens that an innovation intermediary can utilise in order to create value for the innovation ecosystem participants, especially in resource constrained environments. By reflecting on MAMA and MomConnect and understanding how one ecosystem evolved from the learnings of another, it assists in understanding how to build sustainable innovation contexts. The overall process is shown in figure 6 relaying how various tangible and intangible assets form previous innovation projects can be used as a foundation to speed up the creation of innovation ecosystems that address various societal problems.

Figure 6: Overall SSM process on an Innovation Ecosystem

Notably, this is an outline and of course the resultant dynamics will emerge differently when applied to another context. Holistically, such a process should be able to be conducted across industries. References Aarikka-Stenroos, L., Peltola, T., Rikkiev, A., & Saari, U. (2016). Multiple facets of innovation and business ecosystem research: the foci, methods and future agenda. In ISPIM Innovation Symposium; Manchester (pp. 1–33). Manchester, : The International Society for Professional Innovation Management (ISPIM). Retrieved from https://search.proquest.com/docview/1803692429/abstract/32D8A76E6F114CF8PQ/1 Adner, R. (2017). Ecosystem as Structure: An Actionable Construct for Strategy. Journal of Management, 43(1), 39–58. https://doi.org/10.1177/0149206316678451 Adner, R., & Kapoor, R. (2010). Value creation in innovation ecosystems: how the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31(3), 306–333. https://doi.org/10.1002/smj.821 Adner Ron, & Kapoor Rahul. (2016). Innovation ecosystems and the pace of substitution: Re‐examining technology S‐ curves. Strategic Management Journal, 37(4), 625–648. https://doi.org/10.1002/smj.2363 Andersen, M. H., & Hanlin, R. (2019). Putting knowledge flows front and centre in health systems strengthening. Innovation and Development, 1–36. https://www.tandfonline.com/doi/full/10.1080/2157930X.2019.1567913 Autio, E., & Thomas, L. D. W. (2014). Innovation ecosystems : implications for innovation management? The Oxford Handbook of Innovation Management. Bernardo, H., Gaspar, A., Henggeler Antunes, C., Bernardo, H., Gaspar, A., & Henggeler Antunes, C. (2018). A Combined Value Focused Thinking-Soft Systems Methodology Approach to Structure Decision Support for Energy Performance Assessment of School Buildings. Sustainability, 10(7), 2295. https://doi.org/10.3390/su10072295 Brown, A. D. (1992). Grounding soft systems research. European Journal of Information Systems, 1(6), 387–396. https://doi.org/10.1057/ejis.1992.16 Checkland, P. (1981). Systems thinking, systems practice. J. Wiley. Checkland, P. (2000). Soft systems methodology: a thirty year retrospective. Systems Research and Behavioral Science, 17(S1), S11–S58. https://doi.org/10.1002/1099-1743(200011)17:1+<::AID-SRES374>3.0.CO;2-O Chesbrough, H., Vanhaverbeke, W., & West, J. (2006). Open Innovation: Researching a New Paradigm. OUP Oxford. Cibat, J., Süße, T., & Wilkens, U. (2017). An Ecosystem Approach as a Design Principle for a PSS-Specific Business Simulation. 9th CIRP IPSS Conference: Circular Perspectives on PSS, 64, 223–228. https://doi.org/10.1016/j.procir.2017.03.035 Cilliers, P. (1998). Complexity and Postmodernism: Understanding Complex Systems (1 edition). London: Routledge. Dorrington, R., Bradshaw, D., Laubscher, R., & Nannan, N. (2018). Rapid Mortality Surveillance Report 2016. Durant-Law, G. (2005). Soft systems methodology and grounded theory combined-a knowledge management research approach? ActKM Online Journal of Knowledge Management, 2(1). Retrieved from http://www.durantlaw.info/sites/durantlaw.info/files/Soft%20Systems%20Methodology%20and%20Grounded% 20Theory%20Combined.pdf Esterhuizen, D., Schutte, C. S. L., & du Toit, A. S. A. (2012). Knowledge creation processes as critical enablers for innovation. International Journal of Information Management, 32(4), 354–364. https://doi.org/10.1016/j.ijinfomgt.2011.11.013 Foster, C., & Heeks, R. (2013). Conceptualising Inclusive Innovation: Modifying Systems of Innovation Frameworks to Understand Diffusion of New Technology to Low-Income Consumers. The European Journal of Development Research, 25(3), 333–355. https://doi.org/10.1057/ejdr.2013.7 Gawer, A., & Cusumano, M. A. (2014). Industry Platforms and Ecosystem Innovation. Journal of Product Innovation Management, 31(3), 417–433. https://doi.org/10.1111/jpim.12105 Gomes, L. A. de V., Facin, A. L. F., Salerno, M. S., & Ikenami, R. K. (2016). Unpacking the innovation ecosystem construct: Evolution, gaps and trends. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2016.11.009 Heeks, R., Foster, C., & Nugroho, Y. (2014). New models of inclusive innovation for development. Innovation and Development, 4(2), 175–185. https://doi.org/10.1080/2157930X.2014.928982 Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413– 432. https://doi.org/10.1016/j.techfore.2006.03.002 Herman, H., Grobbelaar, S. S., & Pistorius, C. W. I. (2018). Towards a framework for technology platform design, development and implementation in South African health: Preliminary validation. In 2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC) (pp. 1–5). https://doi.org/10.1109/SAIBMEC.2018.8363194 Herselman, M. E., & Botha, A. (2017). The value of co-creation through Design Science Research in developing a Digital Health Innovation Ecosystem for South Africa. Retrieved from https://researchspace.csir.co.za/dspace/handle/10204/9670 Jackson, D. J. (2011). What is an Innovation Ecosystem? Retrieved from https://pdfs.semanticscholar.org/a4ca/09537e99faad7616bd8d88be2fc2f3a4ccfc.pdf Jacobides, M. G., Cennamo, C., & Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255–2276. https://doi.org/10.1002/smj.2904 Lundvall, B.-Å. (2007). National Innovation Systems—Analytical Concept and Development Tool. Industry and Innovation, 14(1), 95–119. https://doi.org/10.1080/13662710601130863 Lundvall, B.-Å., Vang, J., Joseph, K. J., & Chaminade, C. (2009). Innovation system research and developing countries. Handbook of Innovation Systems and Developing Countries: Building Domestic Capabilities in a Global Setting, 1–30. MCSP. (2018). MAMA Lessons Learned Report. Retrieved April 20, 2018, from https://www.mcsprogram.org/resource/mama-lessons-learned-report/ Merwe, E. van der, Grobbelaar, S., & Bam, W. (2019). Exploring the functional dynamics of innovation for inclusive development innovation systems: a case study of a large scale maternal mHealth project in South Africa. Innovation and Development, 0(0), 1–22. https://doi.org/10.1080/2157930X.2019.1567884 Merwe, E. van der, & Grobbelaar, S. S. (Saartjie). (2018). Systemic policy instruments for inclusive innovation systems: Case study of a maternal mHealth project in South Africa. African Journal of Science, Technology, Innovation and Development, 0(0), 1–18. https://doi.org/10.1080/20421338.2018.1491678 Moore, J. F. (1993). Predators and prey: a new ecology of competition. Harvard Business Review, 71(3), 75–86. Ngongoni, C. N., Grobbelaar, S. S., & Schutte, C. S. L. (2018). Platforms in healthcare innovation ecosystems: The lens of an innovation intermediary. In 2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC) (pp. 1–4). https://doi.org/10.1109/SAIBMEC.2018.8363191 Oh, D.-S., Phillips, F., Park, S., & Lee, E. (2016). Innovation ecosystems: A critical examination. Technovation, 54, 1–6. https://doi.org/10.1016/j.technovation.2016.02.004 Parker, G. G., Alstyne, M. W. V., & Choudary, S. P. (2016). Platform Revolution: How Networked Markets Are Transforming the Economy - and How to Make Them Work for You (1 edition). New York London: W. W. Norton & Company. Peter, J. (2018). Achieving scale, sustainability and impact: a donor perspective on a mobile health messaging service and help desk (MomConnect) for South African mothers. BMJ Global Health, 3(Suppl 2), e000562. https://doi.org/10.1136/bmjgh-2017-000562 Peter, J., Benjamin, P., LeFevre, A. E., Barron, P., & Pillay, Y. (2018). Taking digital health innovation to scale in South Africa: ten lessons from MomConnect. BMJ Global Health, 3(Suppl 2). https://doi.org/10.1136/bmjgh-2017- 000592 Pittaway, J. J., & Autio, E. (2017). Toward Strategies for Capturing Latent Value In Ecosystems. Retrieved from http://www.academia.edu/download/44062949/2015-02- 25_Toward_Strategies_for_Capturing_Latent_Value_in_Ecosystems_-_SMS_2015_FINAL.pdf Ritala, P., & Almpanopoulou, A. (2017). In defense of ‘eco’ in innovation ecosystem. Technovation, 60, 39–42. https://doi.org/10.1016/j.technovation.2017.01.004 Ritala, P., & Gustafsson, R. (2018). Q&A. Innovation and Entrepreneurial Ecosystem Research: Where Are We Now and How Do We Move Forward? Technology Innovation Management Review, 8(7), 52–57. https://doi.org/10.22215/timreview/1171 Rose, J. (1997). Soft systems methodology as a social science research tool. Systems Research and Behavioral Science, 14(4), 249–258. https://doi.org/10.1002/(SICI)1099-1743(199707/08)14:4<249::AID-SRES119>3.0.CO;2-S Schreieck, M., Wiesche, M., & Krcmar, H. (2016). Design and Governance of Platform Ecosystems-Key Concepts and Issues for Future Research. In ECIS (p. ResearchPaper76). Retrieved from http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1081&context=ecis2016_rp Seebregts, C., Seebregts, C., Barron, P., Tanna, G., Benjamin, P., & Fogwill, T. (2016). MomConnect : an exemplar implementation of the Health Normative Standards Framework in South Africa. South African Health Review, 2016(1), 125–135. Smorodinskaya, N., Russell, M., Katukov, D., & Still, K. (2017). Innovation Ecosystems vs. Innovation Systems in Terms of Collaboration and Co-creation of Value. https://doi.org/10.24251/HICSS.2017.636 Still, K., Lähteenmäki, I., & Seppänen, M. (2019). Innovation Relationships in the Emergence of Fintech Ecosystems. Retrieved from http://scholarspace.manoa.hawaii.edu/handle/10125/60071 Thomas, L., & Autio, E. (2012). Modeling the ecosystem: a meta-synthesis of ecosystem and related literatures. In DRUID 2012 Conference, Copenhagen (Denmark). Retrieved from http://druid8.sit.aau.dk/druid/acc_papers/3j47kk0b5qlck1ghyor6f8osorh8.pdf Thomas, L. D. W., & Autio, E. (2014). The Fifth Facet: The Ecosystem as an Organizational Field. Academy of Management Proceedings, 2014(1), 10306–10306. https://doi.org/10.5465/AMBPP.2014.10306abstract Tsujimoto, M., Kajikawa, Y., Tomita, J., & Matsumoto, Y. (2015). Designing the coherent ecosystem: Review of the ecosystem concept in strategic management. In 2015 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 53–63). https://doi.org/10.1109/PICMET.2015.7273192 Vargo, S. L., Wieland, H., & Akaka, M. A. (2016). Innovation in Service Ecosystems. Invited Paper Journal of Serviceology, 1(1). Retrieved from http://www.serviceology.org/journal/JSEO15001.pdf Vargo, S. L., Wieland, H., Akaka, M. A., Vargo, S. L., Wieland, H., & Akaka, M. A. (2015). Innovation through institutionalization: A service ecosystems perspective. Industrial Marketing Management, (44), 63–72. Wilson, B. (2001). Soft systems methodology: conceptual model building and its contribution. Retrieved from http://www.citeulike.org/group/2050/article/2286262