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Abstract Innovation Projects Sometimes Fail to Achieve Their Proposed Outcomes

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Abstract Innovation Projects Sometimes Fail to Achieve Their Proposed Outcomes Paper to be presented at DRUID19 Copenhagen Business School, Copenhagen, Denmark June 19-21, 2019 Learning from the Past: Soft Systems Methodology as a Tool for Reflective Innovation Ecosystem 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 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. 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
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