# Systemic Strategy: Systemic Design Methods for Complex Systems Change
A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India.
A presentation from Peter Jones and I at RSD9, virtually in Ahmedabad, India.
A paper presented at RSD7 in Turin, Italy.
I argue that an under-emphasized but crucial variable of success in systemic design is the perspective through which systemic design processes are implemented and executed. While rooted in design (a consciously empathetic discipline, especially in recent years; cf. Kimbell, 2011), it is easy for systemic designers to conduct the research required for their projects in externalized ways. These approaches risk misrepresenting the stakeholders who contribute to projects and, in turn, they are a danger to the potential impact of these misresearched problem systems. I propose to advance a theoretical argument for this danger, the development of an assessment framework to check whether an internalized perspective has been effectively achieved, and provide a proof of concept of this framework through hermeneutic case study analysis.
As I will show, systemic design processes that are not executed with the direct and explicit engagement of stakeholders – to the extent of achieving an emic (or from within) understanding of the system – may be flawed at their foundation. By fostering recognition of the importance of an emic perspective, and by providing a framework of principles, practices, and process to accomplish systemic design with this perspective, I hope to ensure that systemic design processes are as accurate and valid as possible with respect to the stakeholders of the system.
This is not to suggest that systemic design practice is “too etic”. In fact, with roots in design, systemic design is often deliberately emic. Systemic designers make use of designerly tools that help the researcher to build empathy with system stakeholders (e.g., soft systems methodology, critical systems heuristics, appreciative inquiry; Jones, 2014). They often seek to engage stakeholders in the systemic design process and include reflective analysis of what has been learned in order to assess where deeper engagement with the system is required (Ryan, 2014). That said, with the advent of crowdsourcing (the facilitated involvement of the general public in problem solving, usually using online tools; Lukyanenko & Parsons, 2012) and data science (the use of computational tools to analyze and understand large quantities of data; cf. Scepanovic, 2018), it is likely that data-driven methods will increasingly influence systemic design practice. One recent example sought input from hundreds of people to identify opportunities for change in Canadian post-secondary systems through an iterative online survey (cf. Second Muse, Intel, & Vibrant Data, 2016). This data-driven direction is a powerful opportunity, of course, but it underscores the need to develop principles and best practices for assessing and supporting emic understanding as we gain more data from these tools.
This proposal consists of two steps. First, I will look to the principles and theorists of ethnography to develop a framework for assessing the emic/etic perspective of a given research project. Namely, Geertz’ “Thick Description: Toward an Interpretive Theory of Culture” (found in The Interpretation of Cultures, 1973, chapter 1) provides a foundation for the process of emic research, while Creswell and Miller (2000) provide a set of procedural principles for emic validity. Taken together, we generate a critical research framework with which we may assess a given research project’s emic perspective. Second, I will provide a proof-of-concept of this framework (and its theoretical underpinnings) via a casebased assessment of three systemic design projects. Case studies provide an effective venue for learning about the context-dependent manifestations of the phenomena being studied (Flyvbjerg, 2006). One of these case studies is one I have developed through my experience in participating and contributing to the development of the Canadian National Youth Leadership and Innovation Strategy framework, which convened hundreds of youth and youth-serving organizations in order to understand the youth leadership and innovation system in Canada (cf. MaRS Studio Y, 2017). The second and third case studies are those profiled by Ryan and Leung (2014).
In order to interpret and analyze the chosen case studies, I turn to the methodology of phenomenological hermeneutics (Eberle, 2014, p. 196; cf. Wernet, 2014). Phenomenological hermeneutics are appropriate as I have access to the described phenomena of the systemic design projects captured by the chosen cases, but these phenomena are not explicitly captured with reference to emic or etic perspectives – thus some construction of the inherent emic or etic data is necessary in order to make judgments about the perspectives found in the projects.
In each case, I will use identify phenomena representing the practice of emic (or etic) understanding in the research orientation of the work, as acknowledged by the above framework. In each case, I will examine the step-by-step procedure and any associated notes about the experience of the researchers and participants involved. In each step or experience, I will look for evidence of the four steps of emic understanding or the six techniques of emic validation reported above.
Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), 124–130. https://doi.org/10.1207/s15430421tip3903_2
Eberle, T. S. (2014). Phenomenology as a Research Method. In U. Flick (Ed.), The SAGE Handbook of Qualitative Data Analysis (pp. 184–202). Los Angeles, Calif. [u.a.]: Sage. Retrieved from https://www.alexandria.unisg.ch/228374/
Flyvbjerg, B. (2006). Five Misunderstandings About Case-Study Research. Qualitative Inquiry, 12(2), 219245. https://doi.org/10.1177/1077800405284363
Geertz, C. (1973). The interpretation of cultures: Selected essays (Vol. 5019). Basic books.
Jones, P. (2015). Design Research Methods for Systemic Design: Perspectives from Design Education and Practice. Proceedings of the 58th Annual Meeting of the ISSS - 2014 United States, 1(1). Retrieved from http://journals.isss.org/index.php/proceedings58th/article/view/2353
Kimbell, L. (2011). Rethinking Design Thinking: Part I. Design and Culture, 3(3), 285–306. https://doi.org/10.2752/175470811X13071166525216
Lukyanenko, R., & Parsons, J. (2012). Conceptual modeling principles for crowdsourcing (pp. 3–6). ACM. https://doi.org/10.1145/2390034.2390038
MaRS Studio Y. (2017). A strategic framework for youth leadership & innovation in Canada: Insights from the 2016 National Youth Leadership and Innovation Strategy Summit. Toronto, ON. Retrieved from http://www.studioy.marsdd.com/wp-content/uploads/2016/12/MaRS_NYLISstrategic_framework_Final.pdf
Ryan, A. (2014). A Framework for Systemic Design. FORMakademisk–research Journal for Design and Design Education, 7(4). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/787
Ryan, A., & Leung, M. (2014). Systemic Design: Two Canadian Case Studies. FormAkademisk - Research Journal of Design and Design Education, 7(3). Retrieved from https://journals.hioa.no/index.php/formakademisk/article/view/794
Scepanovic, S. (2018). Data science for sociotechnical systems - from computational sociolinguistics to the smart grid. Aalto University. Retrieved from https://aaltodoc.aalto.fi:443/handle/123456789/30187
Second Muse, Intel, & Vibrant Data. (2016, May 11). What Your Data Says: Post-Secondary Education Mapping Survey Highlights. RECODE. Retrieved from http://re-code.ca/whats_happening/watch-recodewebinar-what-your-data-says/
Wernet, A. (2014). Hermeneutics and Objective Hermeneutics. In U. Flick, The SAGE Handbook of Qualitative Data Analysis (pp. 234–246). SAGE Publications, Inc. https://doi.org/10.4135/9781446282243.n16
A systems model I helped visualize for the Global Steering Group on Impact Investment in 2018:
Notes, slides, and the Innovation Auditing guide presented at the talk are found below.
The research presented during the talk is discussed on the following pages:
Find a PDF of the slides I presented at the link below. Beware: the animations don’t translate well to print, so some of the pages have graphical issues.
Innovation Auditing is a simple procedure that individuals, organizations, and governments can use to detect the gaps in the innovation process they seek to support.
See the PDF guide by clicking the link below.
What are the futures of art and design schools in Canada?
In 2015, I supported Kinetic Café in developing OCAD University’s latest Vision and Mission statements. As part of that work, I helped scan for signals, trends, and drivers in art and design school futures. Our scan revealed five important drivers of change: reforming education, creative economies and cultures, new geographies, empowering technologies, and conscious collective.
A walkthrough of this work is visualized and embedded below. If it doesn’t display, you can visit it directly here.
What are the mechanisms of education systems change? How might we use systemic design to power a reform movement? What does systems thinking teach us about opportunities and barriers for education reform in Newfoundland and Labrador?
Education reform is not a new idea. Many organizations and initiatives have reimagined the schools, universities, and colleges that are the backbone of our economy and society—yet, to many, it seems like little has changed in recent decades.
As Jal Mehta, Robert Schwartz, and Frederick Hess began their book on the subject, “if we keep doing what we’re doing, we’re never going to get there.” Traditional education reform approaches have depended on a best practices approach in what is glibly called a “silver bullet culture”.
A single idea, found successful in a specific institution or district, becomes hailed as the be-all-end-all solution. This solution is then celebrated and championed across contexts until actors realize that expected results have not materialized, and reformers move on to the next silver bullet solution.
This approach to education reform has not worked. According to Mehta, Schwartz, and Hess: “If we are to deliver transformative improvement, it is not enough to wedge new practices into familiar schools and districts; we must reimagine the system itself”. In other words, education systems change has been found to be more than difficult. It is a wicked problem: ill-defined, constantly fluxing, with many conflicting stakeholders and no true solutions.
How can we provoke change in wicked problems?
I argue that reforming education is a sociotechnical problem, involving human psychology; social, political, and economic factors; and complex interactivity–what Don Norman and Pieter Stappers have called a “DesignX” problem. These authors suggested that DesignX problems can only be solved through a process of muddling through, developing incremental sub-solutions through deep analysis. This deep analysis means partitioning the problem into modules and recognizing the intersecting dimensions of the problem.
Peter Jones provides further advice for this kind of problem solving, defining an approach called systemic design. Systemic design integrates systems thinking and systemic methods–ways of understanding complex problems through the relationships of the phenomena and actors involved–with design thinking and design methods, applying human-centred design to these seemingly intractable, large-scale problems. With systemic design, Peter says, we use “known design [tools]—form and process reasoning, social and generative research methods, and sketching and visualization practices—to describe, map, propose, and reconfigure complex services and systems”.
With this in mind, I turned to several types of modelling in order to use systemic design on the complex problem of education reform: process modelling, actor mapping, and causal loop mapping. In this modelling, I focused on Newfoundland and Labrador—my home province—and the education of innovation, examining how our system currently provides innovation learning and how we might do better.
Finally, I applied centrality analysis – a quantitative approach to assessing leverage points and bottlenecks in networks and systems maps—in order to surface potential opportunities and challenges in the system. I examined four types of centrality analytics:
Reach efficiency takes an element’s reach (the proportion of the network within two steps of that element) and divides it by the number of neighbouring elements it has. Elements that score the most on this metric tend to be less connected but have high exposure to the rest of the system, making them low-hanging fruit for change efforts.
Betweenness assesses the number of times an element lies on the shortest path between two other elements. Elements high on the betweenness metric are bridges throughout the map, controlling the flow of phenomena throughout the system. This means that these elements may be bottlenecks or single points of failure.
Eigenvector centrality measures an element’s connectedness to other well-connected elements, computing an overall value that is an indicator of the element’s influence over the whole system.
Torque calculates each element’s reach efficiency weighted by its eigenvector centrality (e.g., how influential that element is). Elements with high torque should be relatively easy to impact (as they are not densely influenced by other phenomena in the map), but will impact the rest of the map substantially. These are key leverage points of change.
The detailed methods and findings from each of these approaches are discussed in turn in the links below.
I aimed to see the education system for what it is in order to describe strategies for the transformative reform that Mehta, Schwartz, and Hess called for. The education system is therefore composed of a number of interrelated components, organized in a hierarchy, whose emergent phenomena lead to its own dynamics. Yet, many might say that this systemic chaos implies a system of constant change, while education is hallmarked for its derelict stagnancy in the 21st century. How is it that such a system has not evolved?
Well, perhaps the system is not actually that broken. As eloquently argued by Ryan Burwell, an instructional designer at the MaRS Discovery District:
The school system is not broken. It is perfectly aligned to provide equitable access to a canon of high-quality, standardized content with greater rigour and organization than any other knowledge delivery system we currently have. However, it is not designed to foster the problem-solvers, innovators and entrepreneurs that are becoming an increasingly significant part of the global economy. Incorrectly identifying this misalignment as a broken system has created a culture of fear and failure around education, leading to top-down reforms and increased numbers of mandatory programs.
I return to Mehta, Schwartz, and Hess’ depiction of school reform’s silver bullet culture. Many stakeholders with competing interests and different priorities are invested in every debate on education systems change.
Thus, there are many potential silver bullets–and many advocates for them. The misunderstanding of the problem described by Burwell and the complexities of education reform described by Mehta, Schwartz, and Hess perfectly capture the need for a systemic design-based approach to change.
From process modelling, it is clear that while NL’s education system currently offers some opportunities to learn certain constructs of innovation, the availability of these opportunities is not densely packed throughout their study. It is easy to recognize a dearth of access to the domains of Foresight and Scanning, Vision and Purpose, and Adaptability and Resilience. Further, the degree to students learn the domains and constructs of innovation skills from the public system remains unclear.
Ultimately, now that these models exist, further analysis will be able to examine these constructs more closely as students progress through the system.
This is especially true for many of the “optional” components of the broader education system. After school programs, hobbies, sports and recreation, volunteer and extra-curricular roles, self-directed learning, and employer training could each be vital sources of innovation education, but it was impossible to study these aspects of the system in any meaningful way in the present study. A dedicated effort should examine the availability of these sources and assess their utility for innovation learning.
One research approach would be to survey learners along the learning journey, testing their abilities in the different constructs I’ve outlined. This ethnographic approach could reveal hidden truths: perhaps, for instance, certain regional cultures in the province actually provide powerful learning in design through a community culture alone.
Systemic modelling reveals the power and wealth subsystems active amongst the actors of the education system.
Centrality analysis of the power subsystem illustrates that parents and the provincial government have efficient influence on the system, and change that can mobilize those bodies of actors will quickly take shape.
Meanwhile schools, the School Board, and educators have substantial global influence over the system–change efforts that engage these actors may be slow but momentous.
Finally, power bottlenecks are educators; schools and school councils; and the Department of Education and Early Childhood Development. This suggests that these actors will ultimately need to be involved if any reform effort were to achieve success.
Reach efficiency analysis of the wealth subsystem shows that the federal government, parents and students, and the provincial Department of Advanced Education and Skills each strongly influence the distribution of wealth. The Federal and Provincial Governments have powerful incentives with which to motivate and control reform efforts.
Betweenness centrality revealed that the whole system is tightly linked, making it potentially volatile: economic issues in one component of the system may ripple out and impact the others.
Finally, these maps intimated a causal loop diagram illustrating how innovation education reform might happen in the public education system.
Several loops and one archetype demonstrate significant effect over the system. The Low Definition loop describes an acceleration of the impact of ill-defined innovation on our ability to educate on it. The We Teach What We Know loop shows how a lack of innovation education leads to a lack of people capable of teaching it and vice-versa. The New Economy loop shows how economic shocks driven by drops in commodities pricing has raised our awareness of the importance of the innovation economy. The Innovation-driven Growth loop shows how innovation capacity will accelerate jobs in the knowledge economy, which will in turn drive our ability to create more innovators through education. The Limited Resources loop balances our ability to reform education for innovation due to a lack of funding for the reform effort due to austerity budgets, driven by drops in the price of oil. Finally, the R&D, Not Innovation archetype is an instance of the Fixes that Fail systems archetype, showing how a conflation of innovation with R&D efforts fails to improve our innovation capacity while also distracting from true innovation education.
The result of centrality analysis on these causally-linked phenomena is rich with pragmatic insight.
Three phenomena with efficient reach over the whole system are innovation learning from outside of the public education system, lack of emphasis on innovation education, and low price of oil. The former points to an accessible lever of change: introduce innovation education through extra- and co-curricular programs, volunteer and leadership roles, sports and recreation, or self-directed learning, and the system may catch up by offering its own programming to match. The leverage of a lack of emphasis on innovation education offers another route: increase awareness on innovation education in order to encourage the system to improve on it. Finally, low price of oil retains leverage as a dampener on the system: if the economy continues in recession, the system is less able to offer resources for reform efforts.
Other calls for reform is one force with substantial torque over the system, indicating that reformers must be co-opetitive with other education change efforts, else all reform efforts might fail due to competition with one another. The availability of accessible and practical models for innovation education is another high-torque element, however, elevating the potential of the present research to create change in the system. A third element with high torque is the generational shift in work, evidence that a substantial source of impetus for innovation education reform could come from changes in work and careers.
Finally, betweenness centrality offers a picture of the bottlenecks and points of failure within the system. Innovation capacity and innovation education are two forces semiotically central to the system, and thus it is intuitive that they will be slow to change, no matter what else is happening within the system. On the other hand, recognition of innovation deficiency, the perceived innovation gap, and the search for solutions to the innovation gap are three phenomena that are clear points of fragility in any systemic change effort. If the system does not recognize its deficiencies, perceive the gap in innovation capacity, or opt to search for solutions, reform efforts are liable to be frustrated.
Despite these clarion recommendations for systemic design, several limitations prevent wholesale adoption.
One key limitation of the presented results of systems modelling is that the connections defined in these models are unquantified. In the refined actor map, for instance, it may be that educators have little power over their school councils, or perhaps the NL Federation of School Councils has far less lobbying capacity than the NL Federation of Teachers. Evaluating the strength of these connections and including these evaluations in our analytics would improve the acuity of those metrics substantially.
As previously mentioned, if innovation learning is not coming from the public education system, it must be coming from somewhere else. Yet, these potential sources arguably include the whole of the human experience—as we have, after all, been learning to innovate since pre-history. Future research might take on an ethnographic approach to understanding the system, investigating different student-innovators and where they learned their innovation skills, or a longitudinal approach, following students as they become innovators through their years in the education system. These exercises fell outside the limits of the present research, unfortunately.
Another limitation is that, while the scope and approach to mapping were designed to increase the variety of the system as much as possible, the mapping was still completed with the perspective of only this author. The representativeness of the systems models would therefore be strengthened considerably with Delphi-inspired methods as seen in previous research, bringing the mapping process to others in order to iteratively refine and the map from alternative stakeholders’ points-of-view.
Another potential future study is to “bring the whole system into the room”. This would mean convening a group of stakeholders who were holistically representative of the actors of the system, engaging them in a systems modelling process to develop a map with their collective perspectives.
A few immediate actions stem from this research.
First, we must adopt a model of innovation skills and competencies.
Regardless of whether the adopted model is the one developed through this project or another alternative, it is imperative that we begin to recognize the skills and competencies used by successful innovators. By identifying these skills, we will be capable of examining our weaknesses and, in turn, developing ways of resolving those weaknesses. To spur this discussion, I plan on sharing the models developed here widely.
Second and in tandem, we must include the role of the education system in nurturing innovators in our provincial and national innovation strategies. Many approaches to innovation policy discuss the post-secondary education system with respect to its role in public-private partnerships and the commercialization of research. We must expand this role to include the development of innovation skills and competencies as well. In the near future I hope to meet with policymakers involved in the development of Newfoundland and Labrador’s innovation strategies to advocate for this approach there.
Education reform movements must be united in their calls for change. A host of movements relate to the notion of innovation education, from code.org (a non-profit urging computer science and programming education in K-12) to the 21st century learning movement (a pedagogical framework for the skills and knowledge necessary for the 21st century; cf. http://www.p21.org).
The present research shows that these reform efforts may conflict, however, if they are brought forward asynchronously by their champions. It is therefore crucial that these efforts learn to “co-opete” (as in “co-opetition”) and engage educators and policymakers with aligned advocacy. I hope to work with the education systems change movements I already have relationships with in the immediate future in order to begin this dialogue.
As explored by David Stroh in Systems Thinking for Social Change, systems change is only possible when the actors of the system collectively recognize the tension between where the system is and where they want it to be.
That realization isn’t possible, however, before the actors have even talked to one another—let alone come to consensus about a shared vision for the future.
We realize that Canada’s future prosperity is predicated on our ability to leverage the boons of our resource economy and evolve it into an “innovation rich” leader in the knowledge economy. Yet, as discussed at the beginning of this paper, the danger is that education’s role in this transformation has yet to be recognized in full. We are not talking about how to create innovators, let alone what strategies we should employ in doing so, or how the system is stuck in becoming better at innovation education. Worse, there are many simultaneously conversations happening in both education reform and innovation—conversations that compete with one another, threatening the potential of the whole.
This research offers a model of the education system in Newfoundland and Labrador. Yet these models are untested, and as I have noted, the research is sorely lacking a futures perspective that observes both threats and strategic opportunities in our changing environment.
**How might we spark a collective, integrative discourse on innovation and innovation education? **Then, how might we elevate its importance such that collective action is taken—before we’ve missed the opportunities of the knowledge economy? How might we refine the systemic models, and how might we augment this work with a futures perspective, using environmental scanning to develop and integrate changing trends for strategic leverage?
These questions point toward a need for a powerful, strategic theory of change, and the willingness to muddle through. In other words, **this change will not come about through the efforts of ad hoc standalone initiatives like this one. **
We need a sustained effort. We need a lab that brings together design science and systemic design, creating and testing designs of the system itself, making sure they are valid constructs of the concepts they are intended to represent, all while obeying the principles of systemic design.
This is not a new idea. Many have articulated the notion of social labs, design or change labs, or social innovation labs. In fact, the OECD’s Centre for Educational Research and Innovation seems to operate such an approach for systemic innovation in global education.
I argue that Canada–or at least, Newfoundland and Labrador–needs to take a lab-based approach to navigating complex education reform in education. This lab must unite the perspectives, strategies, and actors currently engaged in similar pursuits; build, maintain, and refine models of the systemic change taking place; be engaged in environmental scanning and strategic foresight to monitor for both threats and opportunities; and prototype change initiatives, taking lessons back to these models and strategies.
Only a dedicated, intelligent effort will help us build the education systems that will develop the skills and knowledge we need to answer the 21st century.
Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada.
What is innovation? How do we define innovation, its outputs and processes, and what are the skills and competencies necessary to practice and excel in innovation?
Many strategies and policies, both federal and provincial, have attempted to improve Canada’s innovation capacity in the last few decades. Universities and colleges are often discussed in these strategies for their role in facilitating new partnerships and in developing (potentially) actionable research.
It is rare, however, for these strategies to recognize education plays in the creation of innovators.
This is counterintuitive: education is an obvious mechanism with which to develop the knowledge and abilities of a population. Yet we lack a holistic understanding of what it takes to practice innovation, let alone the kinds of curricula that might provide those skills and competencies. Moreover, we are inconsistent in the definitions and language we use to define innovation—often obsessing over technology and commercialization. We tend to assume innovation comes from research and development processes, and that innovators are simply highly skilled people.
Presented here is the result of an intensive review of reports, strategies, policy, and theory on innovation in the Canadian context. This literature was scanned and coded—inspired by the ethnographic methods of grounded field theory—in order to synthesize a holistic theory of innovation.
This theory includes a universal definition of the innovation process, a recasting of different focuses of innovation as innovation orientations, a comprehensive model of the innovation process, and a synthesis of innovation skills and competencies into 13 learning domains, 47 learning constructs, and 227 learning outcomes. These tools provide utility for policymakers and educators in pursuit of understanding and improving innovation capacity. In particular, the model of innovation education is the most comprehensive of its kind, providing an extensive set of concepts with which to understand education gaps and build curricula.
Perhaps the most important contribution of this research, however, is the recognition that our conversations about innovation strategies and education reform must be aligned. **How exactly do people learn to be innovative, and how are our education systems currently facilitating that process? **With this study we have begun to seek answers to these questions, but there is much more work to do.
If you use these ideas and learn something from your experience, or if you have thoughts on how to improve them, don’t hesitate to make suggestions and to share your work.
Find resources on this page that detail the definitions and models of innovation developed through this research and how these concepts may be applied in innovation education programming.
Across dozens of perspectives on innovation, a set of 13 domains of skills and competencies emerged. These domains have been interactively visualized using Kumu.io. You can play with the work yourself by clicking the button. Use the controls in the bottom corners to focus on specific components of the model, to surface the innovation process so that you can explore both simultaneously, and more. Note that the visualization is best explored on a desktop!
This document provides an executive summary of the insights and models on innovation education uncovered through this research and guides educators to put these concepts and tools to use.
Education reform presents an opportunity to improve innovation education and, in turn, advance innovation capacity. I synthesize the framing and strategy of resources from provincial, national, international, and theoretical perspectives on innovation in order to develop a holistic model of innovation and a curricula for innovation education. Then, I use systemic design to model Newfoundland and Labrador’s current education system and to suggest strategies for reform to enable improvement in Newfoundland and Labrador’s innovation education. Finally, I explore how systemic reform in Newfoundland and Labrador may serve as a systems laboratory for reform efforts in other jurisdictions.
Innovation Education is a major research project presented to OCAD University in partial fulfillment of the requirements for the degree of Master of Design in Strategic Foresight & Innovation. This work was supported by the Social Sciences and Humanities Research Council of Canada.
Thus, Canada should take steps to foster the idea economy. The world is changing, and Canada needs to understand how the tenets of the idea and knowledge economy will best flourish across the primary sectors that drive the broader Canadian economy. Building regional collectives (like the Waterloo-Kitchener corridor) to advance innovation is only one step, whereas our findings suggest the need to take a collective leap and author a White Paper that will activate a national approach on the new, ideas-based economy. In doing so, the Government of Canada will engage a collective of stakeholders, thought leaders and businesses both large and small to lead a national dialogue on how innovation ought to play out across Canada’s diverse communities, companies and campuses.
Canada should change the narrative. Innovation is happening, but it is taking place in sectors and industries different than the ones we tend to pay attention to. Increasing awareness about the need for, and impact of, innovation within advanced manufacturing, natural resources and agriculture will help cross pollinate the economy with more robust, productive approaches and solutions. This will also help to shift the culture of entrepreneurship by empowering a generation of Canadians to create sustainable value and ensure they and their communities prosper.
Canada should redirect the pipeline. The ultimate step is to increase the carrying capacity of the system to generate value for entrepreneurs from outside the technology sector. Drawing sectors and industries together with the innovation ecosystem will build deeper and more diverse connections. Diverting the flow of resources—talent and capital—and binding it with existing infrastructure and institutional support will build a depth that will support a more robust Canadian economy. Furthermore, investing in improving the structures that nurture prosperity—incubators, accelerators, entrepreneurship, and innovation programs—and bringing them together with campuses and companies already making an impact, will propel Canada forward.
“Innovation drives an economy’s ability to create more economic value from an hour of work, thereby increasing economic output per capita. The resulting productivity growth creates potential for rising wages and incomes, and thus for a higher standard of living.” (University of Lethbridge Research Services, 2015)
A robust innovation ecosystem has the ability to improve productivity, economic growth, and job creation metrics in countries adequately supporting this process. In these countries, there also tend to be more resources available to support spending in education, health, and infrastructure, to name a few (“Innovation details and analysis”, 2013). Accordingly, the importance of a healthy innovation system is tied closely to that of a healthy national economy, along with its people, communities and institutions.
In Canada, however, economic discourse around innovation and entrepreneurship has recently pointed towards a decline in productive returns from startup investment. Although an improvement from previous years, in 2015 Canada was ranked 9th out of 16 peer countries in innovation by the Conference Board of Canada, receiving a letter grade of “C” on its Innovation Report Card (“Innovation details and analysis”, 2013). This ranking points to a persistent weakness in the Canadian innovation system, commonly referred to as the “innovation gap”. This phenomenon is being reported by some of the country’s top journalists, startup CEOs, established investors, think-tanks, and members of various levels of government across the country. While these reports highlight culture, politics, economics, and education as the cause of this gap, and underlining the need for reform, policy changes, and new programs, few of these calls to action are gaining traction. There is no easy answer to this wicked problem.
With the above in mind, we initially sought to answer the question “Why are investments in innovation resulting in diminishing returns in productivity?” through our research, but we quickly realized that in order to address this issue, we would first need develop a thorough understanding of the innovation ecosystem in Canada and thus we broadened our research questions to “How might we understand the Canadian innovation system?” all the while still focusing on this oft reported, elusive innovation gap.
Innovation details and analysis. (2013). The Conference Board of Canada. Retrieved from http://www.conferenceboard.ca/hcp/details/innovation.aspx
University of Lethbridge Research Services. (2015). Putting Innovation in Context. Lethbridge, Alberta, Canada: University of Lethbridge. Retrieved from http://www.agility-ulethbridge. ca/2015/09/11/putting-innovation-in-context/
This synthesis map summarizes our research on Canada’s systemic innovation challenges this past term.
We used centrality analysis to examine our map of the system for potential leverage points. The elements that surface from this analysis offer opportunities (or, in some cases, roadblocks) for policy and program interventions.
This work was completed by a team of Master of Design students in OCAD U’s Strategic Foresight & Innovation program.