5. Building innovation and data use capacity in city government

The COVID-19 crisis shifted the relationship between local governments and their residents. It is evident how deeply city residents rely on local government for efficient service delivery, communication and agile policy making. At the same time, cities showed that, when put under pressure, they can make significant changes in a short time—including greater incorporation of innovation and data use into government work.

What began as a health crisis became an economic and social crisis, inducing a full-scale societal transformation over a short period. Cities are no strangers to crisis management and have longstanding experience dealing with severe climate hazards, cyber-attacks, disinvestment by national governments and population influxes, which challenge their capacity to ensure residents’ well-being. However, COVID-19 magnified such challenges and prompted city leaders to act on all fronts simultaneously due to the concomitant nature of many challenges. Work, school and democratic processes were rapidly digitalised. The structure of traditional working hours was called into question. Use of cars, bicycles and public transport were totally reimagined. Cities took a direct role in food and medical distribution. Almost overnight, public space was reallocated for bike lanes, outdoor dining and pop-up clinics.

The urgency of the pandemic required data use, innovation and decision making in general to happen in real time, with instant impacts on policies, procedures and people. Public sector innovation and data use can support cities in their efforts to improve residents’ well-being. The evidence in Chapter 2 of this report demonstrates a strong correlation between public sector innovation capacity and several areas of well-being, including safety, accessibility, environmental quality, and city and life satisfaction. Meanwhile, Chapter 3 documents strong links between data use and education, health, affordability of housing, and city and life satisfaction. Often, innovation and data use can be deployed in concert – e.g. using data analytics to monitor and measure the outcomes of innovation policies and programmes. This approach allows local governments that cultivate public sector innovation and data use capacity together to benefit most from these tools.

These findings are not just significant for cities in normal times; they may be especially significant for times of crisis and long-term recovery. A majority of surveyed cities report that public sector innovation helps them improve service delivery and internal operations, while roughly half claim innovation helps them anticipate future challenges. Cities also report having sufficient data in at least 16 distinct policy sectors – a goldmine of potential insights that, with the capacity for collection, analysis and maintenance, can be used to improve current policy and plan for future crises.

Innovation and data use can do more than help cities cut costs or publish data dashboards. Robust capacity and deployment of innovation and data use can help cities deliver higher quality public services, target those most in need, incorporate resident feedback and make residents active partners in service delivery. Data use can help cities identify areas of low-performance, measure outcomes compared to goals and adjust programmes accordingly, and plan for future crisis scenarios so that plans are in place before a crisis hits. The potential of innovation and data use mean they should not be viewed as peripheral projects but deployed to help cities achieve their core missions. Nor should innovation and data only be utilised in moments of crisis, but developed consistently as part of cities’ efforts to govern effectively and improve residents’ well-being.

It is imperative that cities transition from a general understanding of correlations between innovation, data use and residents’ well-being to identifying where they are in the process of deploying these tools for that purpose and making evidence-based decisions on how to bolster their efforts to do so.

The recommendations contribute to this transition based on a combination of desk research, a granular analysis of 147 cities’ responses to the 2018 and 2020 OECD/Bloomberg surveys on innovation capacity, and a quantitative analysis of correlations between the data use practices of 145 cities engaged in the What Works Cities Programme and their outcomes for residents.

While touching on different domains, the recommendations for both innovation and data use capacity below are grounded in three common elements: Vision, Capacity and Engagement (see Figure 5.1). “Vision” is considered an indispensable building block in boosting cities’ capacity throughout this report. Mayors, city leaders, and innovation and data stewards (i.e. CIOs, CDOs and similar functions) feed and lead such vision. Their leadership establishes and disseminates an enabling culture for experimentation, calculated risk-taking and evidence-based decision making, and implements strategy to allow such vision to come to fruition. At the same time, cities should focus on improving their technical “Capacity” by dedicating funding to strategic programmes related to innovation and data use, investing in staff skills and institutionalising evaluation and monitoring. Lastly, cities cannot effectively boost their innovation and data use capacity without “Engagement” of residents, external partners, other levels of governments and most importantly their own municipal staff. With these elements in place, cities can enhance their capacity to leverage innovation and data use to improve well-being outcomes for residents.

The 2018 and 2020 OECD/Bloomberg Surveys identified five components of public sector innovation capacity in cities analysed in this report: (1) innovation strategy, (2) innovation staff and a conducive organisational structure, (3) funding for innovation, (4) data use for innovation and (5) innovation outcomes evaluation. While Chapter 2 of this report addresses each component of innovation individually, the five are interdependent – and a strong culture of innovation across an administration (or across an entire city, including among residents) can ensure that the components develop in tandem. Cross-cutting factors to innovation, such as leadership and culture, do not fit neatly into any single component but can positively impact all five, and are included in the recommendations as well.

  1. 1. Make innovation a top priority

As discussed in Chapter 2, surveyed cities associate innovation most with the terms “experimentation” and “human-centred design”, while 100% of surveyed cities consider mayoral leadership central to local innovation. Combined, these observations convey the mandate for a dual approach to innovation that originates both from city leadership and from residents and city staff. Research consistently identifies administrative leadership, risk-taking and experimentation among staff, and robust resident involvement as primary factors in executing public sector innovation (Lewis, Ricard and Klijn, 2018[1]) (Demircioglu and Audretsch, 2017[2]) (Arundel and Es-Sadki, 2019[3]).

Concerning innovation driven by leadership, the message is clear: for cities to dedicate sufficient attention and resources to innovation and reap its benefits, innovation must be a priority for the mayor and agency-level management. Cities led by mayors curious about innovation but hesitant to prioritise it through allocation of staff, funding and other resources might struggle to foster a transformational innovation culture that impacts residents’ lives. Cities in this situation can struggle to spread an innovative mindset throughout the administration and find imaginative, experimental thinking and activity quarantined to an isolated innovation staff with little influence over or interaction with staff of other agencies or residents at large. Even cities with innovative mayors might see efforts stall if agency-level managers do not embrace innovation or encourage calculated risk-taking.

Cities can foster strong, culture-shifting top-down innovation leadership by:

  • Elevating innovation from a stand-alone practice to achieve core mayoral goals.

  • Moving beyond rhetoric to prioritise funding and resources (e.g. staff) for innovation activity:

    • Funding must be consistent, but not exorbitant – the more reliable the funding, the more likely an innovation can be built durably for maximum impact on residents’ well-being.

    • In-house vs. cleaning house – hiring specialised experts is not the only solution to innovation staffing; existing staff have institutional knowledge and can be trained in innovation skills.

  • Ensuring, through hiring process and training, that agency heads and managers are comfortable with innovative thinking, experimentation, and risk taking.

  • Injecting an innovation component into staff and agency review processes.

  • Establishing and elevating an administrative position to champion public sector innovation and ensuring this position is integrated into the broader work of the city.

While there seems to be consensus among cities and in the research that leadership is vital to innovation activity, sourcing innovation from staff and residents is essential too. Such an approach to public sector innovation can mean direct, robust co-creation with residents or empowering existing city staff with institutional knowledge and place-based experience to experiment. Research demonstrates that increased resident engagement in the innovation process leads to better outcomes, while roughly 75% of surveyed cities’ staff are interested in co-creative methods such as innovation labs and human-centred design. Therefore, cities cannot allow innovation originating from residents and staff to be cast aside in favour of innovation spearheaded solely by city leadership. While the latter can provide a cogent vision with a clear set of goals, the former is necessary to channel imaginative solutions grounded in the experience of residents and staff through the tool of innovation.

Cities can promote inclusive, experimental bottom-up innovation by:

  • Investing in and prioritising co-creation approaches with citizens, including human-centred design, innovation labs, participatory budgeting and soliciting resident input through community surveys.

  • Embedding innovation training and/or competency both in hiring practices for all new staff (not just innovation staff) and in the performance review process for current staff.

  • Reimagining and reforming how rank-and-file staff are incentivised (or disincentivised) to take risks, experiment and collaborate, especially across agencies

  • Ensuring that the administration’s high-level approach to innovation is infused into the everyday work of every agency and activity of city government, rather than narrowly focused on any single sector, outcome or methodology

Approaches to innovation originating with staff and/or residents can provide a safeguard against wasteful spending driven by motives other than improving well-being (Vera and Salge, 2012[4]).

  1. 2. Nurture a culture of innovation throughout the city, so it becomes second nature

Developing and investing in a culture of innovation is crucial to advancing all the innovation components together in an organic way. Investing in innovation skills beyond the core innovation team, and promoting experimentation and calculated risk-taking can ensure that all public employees work innovatively. Such efforts to build a culture of innovation can break down departmental silos, promote inter-agency collaboration and reduce friction around programme implementation.

Conversely, in a weak innovation culture, the same administrative separations that undermine innovation can isolate innovation components from each other. For instance, a strong innovation team is vital to broader innovation activity, but innovation culture is limited to that team, their overall impact on the city will be curtailed (Goldsmith and Kleiman, 2017[5]).

Innovation culture is not limited to the administration. Resident engagement throughout the conceptualisation, development, pilot and implementation process of innovation activity can lead to higher-quality, longer-lasting and more effective innovations (Arundel and Es-Sadki, 2019[3]). This is especially true when the goal of innovation is to improve outcomes for residents: cities that treat residents as partners in the creation process (rather than simply end-users and recipients) can establish feedback loops between residents and local government that generate a virtuous cycle.

Cities can build a culture of innovation by:

  • Hiring staff with a background in human-centred design.

  • Deploying tools such as data analytics, hack-a-thons, innovation labs, participatory budgeting, resident surveys and co-creation to foster a culture of innovation among residents and city staff.

  • Applying human-centred design to engage stakeholders in co-creating new programs, services and policies through in-person and digital interactions (e.g. during COVID-19).

  • Identifying weaknesses in innovation capacity and establishing partnerships that can double as training and allow city staff to gain skills and knowledge.

  • Integrating innovation training for all staff, with a focus on empowering them to innovate in their current roles; embed innovation into hiring practices relevant to demonstrated needs.

  • Investing in management and leadership with prior experience in innovation and human-centred design across the administration, not just for Chief Innovation Officer positions.

  • Encouraging and incentivising calculated risk-taking, spearheaded by innovation leadership.

  • “Silo-busting” and inter-agency collaboration (e.g. data or document sharing); incorporating cross-agency performance reviews centred on cross-cutting themes (e.g. pollution) rather than sectors.

  • Enshrining these concepts and priorities in the city’s formal innovation strategy wherever possible.

  • Engaging stakeholders for co-creation with an eye toward in-person interactions between stakeholders post-COVID-19 (and interactive digital options in the interim).

  • Gleaning feedback on innovation activity from residents through tools such as surveys and apps, and requiring that insights be incorporated into budget and policy decisions.

  1. 3. Create a formal, publicly shared innovation strategy with measurable goals

Cities must define what innovation means in their local context, adopt a formalised strategy and set concrete, outcome-oriented goals that can be evaluated throughout the innovation process. Residents of cities with a formal innovation strategy report higher satisfaction with their city than residents of cities without one (see Chapter 2), suggesting a formal innovation strategy may be the linchpin for building capacity in each of the five components. For example, to identify staffing needs, select datasets for analysis, earmark funds and settle on performance benchmarks for measurement, a city must first formalise its goals and priorities through adoption of a formal strategy. While cities’ applying innovation to specific policy sectors can help cities target specific challenges, a holistic approach to public sector innovation is among the principal drivers of correlation between innovation capacity and city satisfaction. In addition, while public administrations (and/or residents) might be resistant to wholesale implementation of innovation strategies, city agency staff and residents could be more receptive to sweeping changes if they are included in the design process.

Cities can adopt/update their innovation strategy to produce better resident outcomes by:

  • Ensuring that the strategy includes goals that are measurable, concrete and translate to better outcomes for residents (e.g. “improved resident health”, not “improved efficiency”).

  • Prioritising a holistic approach to innovation that cuts across all sectors, rather than a strictly sector-based approach (while allowing sector-specific work to flourish within a holistic framework).

  • Clarifying the role of existing staff in strategy implementation (e.g. trainings, required number of hours dedicated to innovation work, etc.), preferred skills and backgrounds for new hires, and/or how innovative approaches will be assessed in performance reviews.

  • Including realistic, concrete expectations and needs concerning funding and data use.

  • Identifying resistance to strategy implementation (e.g. administrative inertia, lack of staff familiarity, sceptical residents), and including steps to address these challenges.

  1. 4. Invest in dedicated innovation staff that reports to senior leadership

City satisfaction is significantly higher among residents in cities with a robust innovation staff, and a strong correlation exists between the time cities’ innovation teams have been in place and the percentage of cities evaluating innovation outcomes and/or strategy. Cities can use hiring practices and professional development to equip administrative employees with the innovation skills and experience to improve residents’ well-being through innovation. However, innovation teams “depend on strong relationships with city agencies”, and can only deliver new approaches to governance if they “first get information and buy-in from the people who will be implementing the plans” (Goldsmith and Kleiman, 2017[5]). If innovation staff remain “outsiders” detached from or dismissive of core local government, they may “almost never have an impact” on budgets, internal operations or residents (Goldsmith and Kleiman, 2017[5]).

Cities can ensure innovation staff have an impact on residents’ well-being by:

  • Clarifying priority skills (e.g. basic data analysis, experimental thinking) and backgrounds for future hires relative to stated goals, not just for innovation teams, but all staff members, where possible.

  • Incorporating innovation skills and thinking into ongoing training and/or performance evaluation of employees, relative to stated goals.

  • Ensuring that innovation staff is embedded into the administrative context through joint agency meetings and reviews, short-term staff swaps, collaborative projects, etc.

  • Creating feedback loops for lower-level staff (e.g. using surveys and trainings, so that they are empowered to innovate in their positions while applying their institutional knowledge).

  • Providing innovation staff funding and resources to stabilise and sustain workflows, understanding that results (e.g. evaluation-based evidence) might take time to emerge.

  1. 5. Build stable, long-term innovation funding into the city’s budget

Innovation funding plays a significant role in the development of all other components – but that does not mean cities need exorbitant standalone innovation budgets, or that cities with strained budgets must forfeit their innovation aspirations. Instead, it means that cities must be realistic about what they can accomplish with their budget, creative in tapping partnerships and other resources (e.g. staff on loan, capstone projects with local universities) and consistent in their innovation funding despite mayoral or staff turnover. As Chapter 2 shows, cities appear to be re-allocating their innovation budgets from a focus on strategy and staffing to data work and impact evaluation. This shift is likely reflective of cities’ innovation activity maturing over time, from establishing fundamental needs to capturing evidence and measuring outcomes concerning the value of investments.

Cities can ensure that innovation receives stable funding regardless of budget size by:

  • Setting a dedicated budget for innovation ex ante, enshrined in the city’s formal innovation strategy and incorporated into budget discussions, rather than waiting to see “what’s left over”.

  • Spending smarter: prioritise low-cost or self-sustaining innovations over “shiny new toys” (beware of expensive/complex technologies billed as innovative, or for innovation “bridges to nowhere”).

  • Extending innovation funding requirements beyond leadership turnover, so projects sustain funding throughout development, implementation, results and evaluation of innovation activity.

  • Engaging Chief Innovation Officers (where they exist) or other champions in budget hearings.

  • Investing in, producing and leveraging evidence on innovation impact through outcomes evaluation, data analytics, qualitative surveys and tracking savings generated by innovation to substantiate decisions about resource allocation and advocate for future funding.

  • Leveraging strategic partnerships to fill funding gaps and grow long-term capacity: in lieu of direct funding, cities can partner with local organisations to provide skills or resources (e.g. data analytics) the city cannot afford, with “knowledge sharing” between those organisations and city staff.

  • Generating buy-in and champions on city councils and in the community.

  1. 6. Leverage data to make decisions and evaluate outcomes

Innovation and data use can be nebulous concepts that cities struggle to define and deploy in a way that improves residents’ well-being. While “some data-driven ideas are substantive…others are bright, shiny objects” (Goldsmith and Kleiman, 2017[5]). Yet data use does have a role in monitoring and evaluating innovation activity and decision making by allowing cities to re-allocate resources, staff and funding based on evidence rather than hunches or politics. Despite these advantages, just 39% of surveyed cities report that data plays a significant role in their innovation efforts and decision making (see Chapter 2). This low level is not due to a lack of data (at least half of surveyed cities report having “sufficient data” in nine policy sectors) or a lack of staff capability (two-thirds of cities have a data scientist on staff). Instead, the problem may stem from insufficient emphasis on all aspects of data use, and a weak data-driven culture (see Chapters 2 and 3).

Cities can bolster their data use for innovation activity and decision making by:

  • Prioritising basic data use training among all existing and future city staff.

  • Co-ordinating city data collection and generation efforts: render various formats of data compatible upfront for better access, sharing and analysis.

  • Enshrining data competency standards (beyond just open data) in the city’s formal innovation strategy – open data is a first step to a widespread data use culture, but other capacities are needed.

  • Engaging and expanding the community of city (open) data users through events (e.g. hack-a-thons) and trainings on how to access and use city data.

  • Incorporating data methods (e.g. randomised control trials, results-driven vendor contracts, resident surveys, etc.), enabling the city to evaluate innovation activity and guide decision making.

The term “data use” refers to much more than open data. It also refers to cities’ capacity for collecting data, opening and sharing data in a comprehensible way for external shareholders, combining data (e.g. ensuring compatibility), and analysing data to guide decision making (Janssen et al., 2017[6]). Only by building capacity in these and other areas of data use (explored below) can cities leverage the potential of data to improve innovation implementation and decision making in general.

Assessing the outcomes of public sector innovation eludes governments and researchers alike because it is difficult to identify a good outcome. As summarised by Mintzberg (1996[7]), “many activities are in the public sector precisely because of measurement problems: If everything was crystal clear and every benefit so easily attributable, those activities would have been in the private sector long ago.” Most cities struggle to evaluate innovation outcomes systematically and comprehensively, which can undermine their ability to acquire resources such as funding. Without evidence of impact, successful projects can fail to secure funding necessary to scale up. Robust evaluation capacity can also help cities monitor and assess innovation initiatives throughout the development and implementation process, allowing them to make changes and identify new opportunities to innovate continuously.

Cities can improve both their innovation evaluation practices and residents’ well-being by:

  • Setting goals up-front: cities must enshrine clear, measurable goals in their innovation strategies so that innovation teams are clear on what to measure and how to do so.

  • Keeping it simple: instead of investing in a long-term, complex and expensive data metrics programme, start with qualitative resident surveys or targeted, randomised control trials to generate actionable data:

    • Cities should take a full inventory of what data they already possess, both publicly and among agencies, to measure outcomes.

    • Cities must not delay evaluation efforts because they lack “sufficient” data in a certain area – use qualitative metrics, interviews, etc., but insist on a system of evaluation.

  • Monitoring and evaluating an innovation project from its inception and throughout its lifespan to determine what’s working, what’s not, and whether to terminate before further investment.

  • Having a back-end plan: beyond ensuring that outcomes are measured, cities must also specify how analytics and insights resulting from evaluation will be used, e.g.:

    • Establish channels of how insights will be conveyed between those conducting the evaluation and those responsible for implementation/maintenance of innovation activity.

    • Ensure clear communication of innovation results (good and bad) with the public and other funding sources in the name of accountability and good government.

As discussed in Chapter 2, there are hints that evaluating innovation outcomes ramps up as cities’ innovation teams and other components mature. However, to make all other innovation investments worth staff time and residents’ tax money, cities must not wait. They should prioritise the evaluation of outcomes relative to innovation activity by any means. As mentioned, evaluating innovation outcomes to demonstrate evidence of impacts can help teams secure stable funding and scale-up projects.

  1. 7. Build and institutionalize good data governance practices

Leadership and vision are crucial elements of a good data governance strategy. At the local level, city governments should integrate fragmented strategies by institutionalising data leadership and stewardship, and developing a longer-term and coherent data strategy. While data use can be adopted in the absence of any formal strategy, a flexible yet well-conceived data strategy can ensure accountability and transparency, define leadership roles, set measurable objectives and outline expectations. A coherent data strategy can also serve as a foundation for municipalities to embrace and sustain a wide range of best practices at the tactical and delivery level.

Cities can secure a strategy for data practices by:

  • Recognising data as a strategic asset to be enhanced, leveraged and shared within and across city government as well as with external stakeholders.

  • Setting a clear vision, aspiration and incentives for city government to pursue ambitious.

  • Communicating and demonstrating to municipal staff and external partners that data-driven governance and evidence-based decision making are an institutional priority.

  • Institutionalising citywide data stewardship in the forms of a dedicated data team(s) and/or leader(s) to embed, enhance and accelerate the strategic use of data.

  • Expanding the structure of data stewardship to include technical, organisational and legal dimensions to ensure that city government approaches each stage of the government data value cycle in a strategic, efficient, user-friendly and compliant manner.

  1. 8. Develop and implement coherent data strategies

Cities should focus their capacity on developing and implementing coherent data strategies, policies and initiatives. This capacity can be cultivated through elements such as data skills and staff capabilities, data openness and stakeholder engagement.

Cities can improve the data skills and capabilities of municipal staff by:

  • Focusing on skills for collecting, processing, storing, analysing, sharing and (re)using data.

  • Identifying municipal employees whose duties involve data management and analysis, and creating a central resource to upskill these staff.

  • Identifying data skills gaps in specific programmes, activities or initiatives (e.g. randomised control trials, results-driven contracting, impact measurement, performance analysis, predictive analytics) strategic to achieving the municipality’s policy objectives.

  • Equipping non-specialist municipal employees with basic data literacy so that they can understand how key decisions are made based on quality data, and communicate these standards to external partners and residents, if needed.

  • Recognising data as the tool rather than the solution: flawed approach to data management and analytics distort insights and lead to ineffective interventions.

Cities can enhance data openness by:

  • Publishing city data in user-friendly and machine-readable formats to a central, public, online location (in the absence of conflicting interests and privacy concerns).

  • Rendering real- and/or near-time city data accessible for the purposes of openness, transparency and accountability of local government activities, and boosting public trust.

  • Rendering real- and/or near-time city data accessible for the purposes of maximising the social and economic impact of these data (e.g. developing new services and business opportunities).

  • Formulating a publicly available codified open data policy that commits to transparency and proactive public disclosure.

  • Establishing mechanisms to facilitate data sharing across agencies and levels of government (where there are explicit efforts to support intra-government data sharing).

Cities can engage stakeholders by:

  • Fostering a vibrant community of data users:

    • Gathering information on public data users and their uses of these data.

    • Communicating, consulting and incorporating their needs, and collaborating and involving them in the design of the city’s data practices and the construction of its open data portal.

    • Providing guidance to access and utilise public data in a user-friendly and effective manner.

    • Providing for collaboration that incentivises the use of public data to solve community problems.

  • Building an extensive network of trusted public and private partners:

    • Identifying needs in the city’s programmes, activities or initiatives to set the level of stakeholder engagement that matches intentions and fulfils policy objectives.

    • Forming partnerships for the purpose of mutually enriching data sets, co-producing databases and pooling resources and capabilities to perform advanced analysis.

    • Leveraging competences, skills, technologies, expertise and resources of data partners to deepen the impact of data.

  1. 9. Establish well-defined, transparent regulatory frameworks for using and sharing data

Tactical approaches must also consider the legal and regulatory aspects of data, from technical and organisational standards of compliance to data-related rules and guidelines, put in place by municipalities to ensure openness, protection, transparency and accountability.

Cities can create well-defined legal and regulatory frameworks for data practices by:

  • Establishing regulatory standards that define, drive and ensure compliance with data-related rules and policies, including data management, sharing and protection.

  • Embedding legal mechanisms that strengthen data sharing and co-ordination, horizontally across different municipal departments, vertically with other levels of government and externally with stakeholders and partners.

  • Formulating regulations that balance efforts at data sharing and integration with the security, privacy and ethical dimensions of data.

  • Balancing the opportunity of linking up data for more comprehensive datasets for in-depth analysis against potential security breaches, especially for personally identifiable data or data that can easily be de-anonymised.

  1. 10. Make data strategies standard in all operational procedures

While not explicitly discussed in the OECD data governance framework for the local public sector, delivery is as important as strategic and tactical aspects because its implementation of data strategies considers the technical and policy implications of actions undertaken at various stages of the data value cycle. Local governments need to enforce and maintain high operational standards for delivery. When it comes to the day-to-day management of data, local governments should be aware of the practical implications, risks and barriers to optimal data use at each stage of the government data value cycle. By mapping the flow of city data – from unprocessed data and information to insights for decision making – city administrations will be able to navigate and unlock the full potential of their strategic assets. Improper handling of data at any stage of the cycle can start a cascade onto subsequent stages. Delivery also touches on data infrastructure (i.e. adopting or adapting technological solutions such as application programming interfaces, cloud-based services, data lakes) and data architecture (e.g. standards, interoperability, semantics, etc.) to help public sector organisations achieve objectives defined in their strategies.

Cities can enforce high operational standards in daily data management and practices by:

  • Moving away from generating (administrative) data for “single-use only” purpose: residents, agencies and private firms should only provide data once for access to public services.

  • Being rigorous in the collection and generation of reliable, representative and up-to-date data sets to maximise their insights.

  • Co-ordinating data collection efforts among city agencies to avoid data duplication and incompatibility.

  • Appraising the quality of data: cleanse, sort, inventory and determine whether certain personally identifiable data can be linked up and/or anonymised before being stored for future use.

Cities can use data architecture and infrastructure to optimise their daily operations by:

  • Acquiring and upgrading the technical infrastructure needed to facilitate data sharing, integration and management across institutions.

  • Right-sizing data and technological solutions to ensure that the procurement of infrastructure fits the current needs and internal competences of the municipality.

  • Securing municipal networks and digital infrastructure.


[3] Arundel, A. and N. Es-Sadki (2019), D2.7 Preliminary survey results report: Understanding value co-creation in public services for transforming European public administrations, https://www.co-val.eu/blog/2020/01/31/preliminary-survey-results-on-innovation-and-the-use-of-co-creation-methods/ (accessed on 11 February 2021).

[2] Demircioglu, M. and D. Audretsch (2017), “Conditions for innovation in public sector organizations”, Research Policy, Vol. 46/9, pp. 1681-1691, https://doi.org/10.1016/j.respol.2017.08.004.

[5] Goldsmith, S. and N. Kleiman (2017), A New City O/S: The Power of Open, Collaborative, and Distributed Governance, Brookings Institution Press, http://www.jstor.org/stable/10.7864/j.ctt1vjqnwd.

[6] Janssen, M. et al. (2017), “Driving public sector innovation using big and open linked data (BOLD)”, Information Systems Frontiers, Vol. 19/2, pp. 189-195, https://doi.org/10.1007/s10796-017-9746-2.

[1] Lewis, J., L. Ricard and E. Klijn (2018), “How innovation drivers, networking and leadership shape public sector innovation capacity”, International Review of Administrative Sciences, Vol. 84/2, pp. 288-307, https://doi.org/10.1177/0020852317694085.

[7] Mintzberg, H. (1996), Managing Government, Governing Management, Harvard Business Review, https://hbr.org/1996/05/managing-government-governing-management (accessed on 24 February 2021).

[4] Vera, A. and O. Salge (2012), “Benefiting from Public Sector Innovation: The Moderating Role of Customer and Learning Orientation”, Public Administration Review, Vol. 72, Issue 4, https://doi.org/10.2307/41506805.

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