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The research question of this study was 'how to apply the Soft Systems Methodology (SSM) in innovation context'. An intervention at a Europe-based innovation-oriented company serves as example study. To tackle ill-structured problems encountered in this firm, we propose a new methodology obtained by combining SSM and the concept of Enterprise Science. Elements of the concept of Enterprise Science will be embedded in a modified SSM. The methodology mix will be applied for consensus finding in innovation and technology context. We illustrate the combined approach with a case study and test the contribution of our proposed methodology for an application within the innovation environment. The focus is set on how to initiate and manage change processes using the proposed enhanced SSM. Finally, lessons learned from the case are discussed. The paper provides recommendations on how to use the proposed approach.
Why SSM for Innovation Systems Interventions?
The SSM of Checkland has already been adopted to the requirements of the innovation and technology environment (Checkland and Scholes, 1999).
We have chosen SSM as our founding methodology, since some elements of SSM turn out to be most suitable for the given problem characteristics in the case study: First, SSM supports stakeholders' involvement and mutual learning in a most flexible manner (Checkland and Scholes, 1999; Checkland and Poulter, 2006). Second, problems in the case study firm were poorly structured, and project goals were not strictly defined and changed over time. For treating these characteristics, SSM is recommended (Checkland, 1981; Checkland, 1985; Checkland and Poulter, 2006). In addition, there was a practical reason to choose a modified SSM approach out of many possible Soft Systems approaches: The team members were familiar with elements of SSM, this enabled a fast learning process.
There was evidence that the team members were not confident that pure SSM would lead to successful problem solving, for example, team members raised the lacking of a common language to structure poorly specified innovation problems. Multiple perspectives and high uncertainty in anticipating effects of innovation interventions and external dynamics have been identified as the root causes for the need to enhance SSM for an application in innovation context.
Challenges in Innovation Systems
Uncertainty about future technology and customer needs is a challenge for innovation teams. Looking at decision processes in innovation planning, most problems are weak structured. As innovation systems evolve over time (Adner, 2006), the possibilities to reduce the uncertainty by planning and forecasting are restricted as entrepreneurial spirit and revolutionary innovation cannot be calculated.
Decision making in innovation context is commonly structured by project milestones and innovation strategy meetings: How many resources should be invested in which technology or product development project?
As a start, we assume that these decision processes can be improved by applying SSM. This is based on the general assumption that group processes often enable better decisions than individual reasoning (Surowiecki, 2004) and that groups need certain guidance via a systemic methodology.
Structure of the Paper
Literature on the methodological background of this research is introduced, followed by a case study in a Europe-based multinational company illustrating an application of our combined approach of SSM with Enterprise Science. Results and implications from the case study are later discussed and evaluated, and then, proposals for the use of the combined methodology in practice are given. Finally, the paper concludes with an outlook to further research.
Faced by the challenge of a weak-structured problem in innovation context in a company, methodologies are needed that are able to (1) coach the process of structuring the problem, (2) analyse the problems and (3) guide to a solution.
These solution-focused research approaches can be found in the field of Design Science (van Aken, 2004: p. 231; van Aken, 2005). Keys defined Design Science as a category of research approaches 'producing knowledge to support the design and construction of useful artefacts and systems by professionals' (Keys, 2006; Keys, 2007: p. 337). Problem structuring has been addressed in literature (Flood and Jackson, 1991; Franco et al., 2007), enhanced by ideas on decision workshops (Papamichail et al., 2007), and by approaches such as the 'journey making process' (Eden and Ackermann, 2006).
Literature used in this research can be categorized in three groups: Literature on SSM and its business applications, on the concept of Enterprise Science, and on managing technology and innovation in multinational companies.
SSM and its Business Applications
The complexity and advantage of group decision processes is described by Surowiecki (2004). SSM of Checkland (1981) has been developed to support the discourse on accommodation finding processes in groups: The methodology has been interpreted and further developed by Checkland himself (1985), Kijima (1995), Rosenhead and Mingers (2001), Coughlan and Coghlan (2002), Rose (2002), and Jackson (2003). Avison et al. (1999) provided additional insight in procedures of SSM.
Evidence of a successful use of SSM in practice has been provided by Mingers and Taylor (1992). The method 'action research', as a broader methodology field including SSM, has been adopted to innovation systems with an application case by Presley et al. (2000).
Combinations of SSM and Additional Methods Mingers and Gill (1997) describe combinations of different soft systems methodologies. The authors developed a multi-methodology framework with a focus on using parts of methods to create the best methodology for the problem situation. In accordance with Minger and Gill (1997), multi-methodology is …