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During the last couple of years, the urban planning department of Örebro Municipality has worked in several ways to make innovation a natural part of our work. Like many cities, we believe that fostering innovation is beneficial to both our internal processes, but also society as a whole. In a time where the Earth, and the cities on it, are confronted with a multitude of, so-called, complex problems, innovation is that which helps us adapt and find solutions to the challenges we are confronted with. In this article, I will give an insight into our experiences with working towards innovation, building upon our ideas of ‘organisational trust’ and ‘incremental change management’, and how it could contribute to ‘urban robustness’.
Before I continue, let me just contextualize how this translates to the city where I live and work. Örebro is the 6th largest city in Sweden, however, with about 156,000 inhabitants, a mid-sized city from an international perspective. As one of Sweden’s fastest-growing cities, numbers are rising quick – just above 15% during the last decade (Fastighetsvärlden). This growth comes along with new opportunities, but also challenges. One major challenge is that this population growth is mainly driven by children and elderly, meaning that, while we have more inhabitants to care for, we do not significantly increase our tax base. Another dimension to this is the vast hinterland within the municipal border of Örebro. Due to current popular terminology (such as ‘smart city’) more peri-urban, and rural localities, that function as satellites to the city and together form a functional region, are often left out of the equation. Even though previous research in Örebro has shown that peri-urban localities are continuously growing, even in times of shrinkage (Sundström, 2013). That becomes especially interesting now that corona is diverting us from previous growth estimates (SCB, 2020). An impact that has the potential to change the dynamics between the rural and the urban. Creating a robust urban (and rural) system and finding innovative solutions effectively is, therefore, key to the sustainable provision of services within, and liveability of, our city and municipality as a whole.
DNA: to navigate, prioritize and innovate
Last autumn, a colleague and I visited the Smart City World Expo in Barcelona, one of the largest conferences within the field. The exhibition halls were enormous and the smart solutions seemed endless. Our former head of department, Ulrika K Jansson, usually encourages us to systemize, navigate, and prioritize – words that gained a new meaning, standing in these halls with seemingly endless opportunities. But how to navigate when everything seems important and useful?
Together with delegates from the city of Antwerp, we spoke about the importance of understanding one’s city. Antwerp called it – their DNA. We were charmed by this idea and understood that a thorough understanding of the self, meaning the specific challenges, opportunities and needs of the city, is the only way to navigate and prioritize the technological (or any other kind of) innovations to adopt or develop.
We use the word ‘innovation’ a lot, but what do we mean by it? To innovate comes from the Latin word ‘innovare’, meaning to ‘renew oneself’. I might know what you are thinking now, this sounds like the start of any corny speech held in almost any Hollywood high school movie, but hear me out. Innovation itself, as a concept, is often discussed among my colleagues. Some arguing that innovation is not something that happens within municipalities, because, according to them, innovation is something that happens within academia and within the public sector we just apply. Following the original Latin meaning of the word, I would argue that innovation can occur anywhere. We, for instance, innovate our policies and routines regarding the ways we work with urban planning and management. And when we do apply, new technologies, for instance, we innovate a system which is unique to our city – DNA. In that way, we aim to innovate, renew, to create the best version of ourself, instead of just implementing hyped “solutions”.
A culture of organisational trust
At the moment we do not have a formal innovation strategy in place. That goes for both the urban planning department and the city as a whole. We do, however, have strategies for innovation, scattered over several strategic documents. This, I guess, is rather common, but internally we have been dreaming of an overarching document that could tie together our thoughts on the matter.
The two main pillars, currently guiding us in innovation, are our ‘Digitalisation strategy’ and the ‘Culture and Trust Program’ (Sv: Kultur- och tillitsprogrammet). Both of these documents have their benefits and limitations when it comes to fostering innovation.
Our Trust and Culture Program describes the kind of professional culture we aim for within the department. It has a specific section on innovation, with at its core an encouragement to both managers and employees to test, experiment and dare to fail. To facilitate this, all employees are encouraged to spend time monitoring their field and come up with ideas to develop their work. Working in this way requires trust from politicians towards the department, but also between the managers and employees.
In that way, the policy aims at changing the internal culture of our department. Towards trust-based leadership, to foster, among other things, bottom-up innovation. Trust-based leadership can be seen as a reaction against the New Public Management (NPM) leadership culture, which instead focused on specific top-down set targets, continues reporting and fetishizing quantitative measures to rate success. Working towards this new kind of culture is not unique within Sweden. Helsingborg, especially, takes a forward-thinking and fun approach to this, with initiatives such as their prize for the ‘fail of the year’. In that way employees are encouraged to try new things, make mistakes and learn from them.
The digitalisation strategy builds upon the ideas found in the Culture and Trust Program and focusses first and foremost on technology as the natural field of innovation. Also, the digitalisation strategy has a stronger vision on innovation as it extents it from internal learning to the importance of external actors. Although not specifically mentioned, our digitalisation strategy promotes innovation through quadruple helix collaboration. By promoting open standards, for instance, we aim to avoid lock-in effects, and instead foster a modular system open to innovation.
The science of muddling through
Thinking of a concept that captures the cumulative idea, that is constructed out of the snippets above, the concept of incrementalism came to mind. It was with his 1959 article, the science of muddling through, that Charles Lindblom laid the foundation of ‘incrementalism’ as one of the most influential decision-making models in our time. He developed his theory as a critique of the rational comprehensive model of decision making and the practices of social engineering at the time.
Lindblom builds upon Herbert Simon’s concept of ‘bounded rationalism’, which takes in consideration the limitations in the availability of information, the cognitive limitations of the human mind, and time limitations to form a decision. Extremely simplified, we could say that this leads him to conclude that, when it comes to large scale projects (say building a smart and sustainable city or solving wicked problems), we can’t design the entire solution upfront, but should instead take small steps forward, then reflect and reassess.
In his article, Lindblom quotes Charles Hitch, who describes where the rational comprehensive model functions and where it loses its ability to deliver useful insight: “The sort of simple explicit model which operations researchers are so proficient in using can certainly reflect most of the significant factors influencing traffic control on the George Washington Bridge, but the proportion of the relevant reality which we can represent by any such model or models in studying, say a major foreign-policy decision, appears to be almost trivial” (Hitch in Lindblom 1989, P80). Here we could reason that in some instances the rational comprehensive model works quite well. When building a new road for instance. However, when deciding on how a whole set of technologies should function and interact with society, the rational comprehensive model fails and incrementalism provides a more feasible way forward.
In the image below (Figure 1), we have tried to schematically visualize how we currently work with innovation and how we draw upon the ideas from Lindblom to describe our efforts. For the time being, we have labelled our way of working ‘Incremental change management’. In this model, the goal is set to create a sustainable smart city, a goal that our politicians have decided upon. What exactly constitutes a sustainable smart city is unknown at the time the goal is set. New technologies as being developed while current ones are being implemented and, in that way, constantly change the conditions and possibilities. There is, therefore, no blueprint and no linear road towards it. Instead, the road of the collaborating actors (A1-4) are looped and intertwined (somewhat like the DNA-Helix). Within this system trust and collaboration between a high number of actors and stakeholders becomes necessary. The smaller blue dots represent more clearly defined goals/milestones – ones to which a rational comprehensive model could be applied. At what point the goal of the . It might always be just out of reach, forcing us to keep muddling through, or until we start muddling towards another paradigm.
> Figure 1: Incremental change management (Due to technical issues we link to Twitter to display the figure)
Towards urban robustness
Lastly, some thoughts on how this incremental change management perspective on innovation might contribute to urban robustness. Even though the concept isolates, just like ‘smart city’, the urban from the rural, creating a risk of neglecting important reinforcing mechanisms that could contribute to the robustness of the entire system, I believe it adds an important perspective. Urban robustness, as I currently understand it, is easiest understood when contrasted with urban resilience. Resilience is a concept that has been prominent in thinking about sustainable urban development. The problem with this concept, seen from a systems perspective, is that a resilient system, after impact, returns to its original form. Kind of like a spring or elastic cord. In that way it resists change. Robustness, on the other hand, is then the system’s ability to evolve. So, the system’s ability to deal with impact and an uncertain future and adapt and evolve through time. There seems to be a balance there. Too little change and over time the system might not be able to deal with impact, because the kind of impact has evolved while the system kept bouncing back to its original form. Too much change at once and the system becomes vulnerable because in its new form it has not been tested and proven to be able to deal with the impact. That is where Incremental change management can be a tool to keep the right balance – as it doesn’t aim to change the entire system at once but rather works towards systemic change while taking small steps in the right direction. Constantly re-evaluating, defining new steps, and searching for useful collaborations. That is where the DNA comes in again. It requires a constant good understanding of the self, one’s city, to know what next step is needed. To make it more liveable, sustainable, smart, resilient, and/or robust. In that way we just keep muddling through, to come as close to the best version of ourselves as we possibly can. Even though that version will always be a step ahead.
Disclaimer: What I describe in the text above are my reflections upon the way we work with innovation within the planning department and are not always the official view of either the department or the municipality as a whole. /Sascha
Fastighetsvärlden.se (2018) https://www.fastighetsvarlden.se/analys-fakta/topplistor/19-framsta-snabbvaxarna/
Lindblom, C. E. (1959). The science of “muddling through”.
SCB (2020). Låg folkökning i Sverige under coronapandemin. https://www.scb.se/hitta-statistik/statistik-efter-amne/befolkning/befolkningens-sammansattning/befolkningsstatistik/pong/statistiknyhet/befolkningsstatistik-forsta-halvaret-2020/
Sundström, P (2013). Orter I staden närhet. http://www.diva-portal.org/smash/get/diva2:607594/FULLTEXT02
 In October 2018 Fastighetsvärlden.se published an article listing Örebro as the 11th fastest growing city in Sweden. When we combine the municipalities making up Metropolitan Stockholm (a continues urban area known as Storstockholm), Örebro becomes 4th in the list of fastest growing cities.
 Within the rational comprehensive model of decision making one collects all the necessary information, analyses it, and picks the most successful way forward.
 I would argue that mans bounded rationality is one of the drivers in the creation of artificial intelligence today. If Lindbloms theory was a critique towards the rational comprehensive model used in the 50s and the socially engineered society, today AI promises to overcome these limitations and offer us the tools for social engineering. However, I have a hard time believing that these promises can be materialised too such an extent that we transcend bounded rationality.
 We can’t say that we truly work according the ideas of incrementalism the way Lindblom describes it. Within incrementalism, goal setting and strategy making is more or less impossible. Partly because consensus is impossible to reach. Instead, one looks historically to see if there is a trace of a consistent policy. We believe that goals and strategy can and should be set, it limits the risk for ending up in an unfavourable system or society. It is also one of the main functions of politics and the democratic process.
 A1-4 make up the actors within the quadruple helix: academia, private sector, public sector, and civil society.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857160.