7 MINUTE READ
Best practices and key success elements
Building Data-Smart City Solutions
Consultant: STEERING
Copyright: SSMIC
The implementation of a community information utility in Sault Ste. Marie focused on building data-smart city solutions through partnerships and the common goal of using public data to create return on investment and social return on investment for the community. The following are best practices and key success elements of the Sault Ste. Marie Innovation Centre and Acorn Information Solutions.
​
PEOPLE: Vision, partnerships and culture
Community vision
The critical first step to implementing a community information utility is having the unwavering commitment of the municipality for the vision of a data-smart city. The implementation of Sault Ste. Marie’s CIU was not a low-hanging-fruit solution to create economic development, better public service delivery outcomes, public safety and improved health and human services. The CIU is a worlds-first, advanced and intricate solution that is rooted in reams of complex multi-enterprise data. This project was championed by municipal leaders who understood that this data-smart city solution is an ever-evolving long-term plan. Investment isn’t just in the technology and human resources but in a shift in how a community operates. Neglecting to accept this commitment will result in lost time and resources.
​
Partnerships
Without partnerships, there is no solution. The partnership between the City of Sault Ste. Marie and the local utility, PUC Services Inc., was the impetus to creating a data-smart city solution. One of the major keys to the success of this partnership was having a shared vision, creating common operating standards and developing an agreed-upon data governance model. Partnerships between the City of Sault Ste. Marie, PUC Services, Inc., SSMIC and sixty-plus community partners have proven that information doesn’t have to be siloed, in fact, it shouldn’t, and there is tremendous value in the sharing of data. Multiple stakeholders will immediately produce savings on implementation through cost sharing. And without aggregated, multi-enterprise data, information will remain institutionalized and limited in its potential to improve the community.
DATA: Accuracy, literacy, privacy and governance
​
People and culture
​
Technology is accessible. Data can be mined, organized and layered. But it’s the people of Acorn who connect these pieces to drive solutions that create public good.
​
Central to the success of the CIU as a data-smart city solution is the leadership and work culture of Acorn. The non-profit organization employs servant leadership as their management style and have created an environment where employees feel valued, fully contribute to Acorn’s mission and stand with the organization and each other. The outcome is higher value team members who drive efforts in the same direction.
​
Acorn’s success in solving problems for the community is rooted in the diversity of their staff and multi-disciplinary approach to solutions. There is inter-office continuity between team members removing boundaries to information and expertise. Acorn’s leadership has instilled the philosophy that the solutions staff derive from data are limitless which encourages unencumbered, broader-level thinking.
​
Acorn believes in investing in continuing education and training which includes staff working towards a certified geographic information systems professional (GISP) designation. GISP professional obligations include striving to do what’s right, not just what is legal, making data findings widely available, and calling attention to emerging public issues.
​
Clean data
​
Bad data needs to be solved before solutions can be derived. ‘Bad’ data sets are incomplete or inconsistent, making them unreliable, unable to be layered and impossible to be queried in the CIU. One of the main challenges that SSMIC faced during the implementation of the CIU was collecting, scrubbing and entering accurate data into the ’s GIS platform. Accurate data is critical. For the CIU to be successful, there needs to be succession planning on how data is collected, handled and entered into the GIS. Acorn has been able to refine the process of data management through implementing pick lists tools, creating standardized data entry forms for the collection of information, and developing a data entry methodology to ensure information is current and accurate. Acorn management has observed that if bad data is addressed, the reluctance to share it is diminished.
​
Data Literacy
​
As a best practice, Acorn uses data literacy as a key tool to streamline their data management processes. Educating key partners on the importance of accurate data collection and the process of anonymizing data mitigates time spent refining information entered into the CIU. Acorn supports the capture of data by writing data entry forms for organizations complete with pick lists and fields so the information collected is correct and the end result is searchable and accurate information in the CIU.
​
Data privacy
​
Data privacy shouldn’t be viewed as a roadblock but rather part as of the process of how the CIU can make a project work. With the right checks and balances in place, it is possible to create a data-smart city solution that improves outcomes for the public without violating the privacy of citizens. Part of the best practice regarding privacy is anonymizing data by distilling information to postal codes and aggregating it to defined geographic locations like Statistics Canada dissemination areas.
​
The use of public data while maintaining privacy is attributed to established privacy policies and operating procedures designed to protect citizens. Acorn achieves data privacy through detailed data-sharing agreements, a defined privacy policy in compliance with Canada’s Personal Information Protection and Electronics Act (PIPEDA) and the Municipal Freedom of Information and Protection of Privacy Act (MFIPPA) privacy impact assessments and statement of sensitivity to determine the confidentially, integrity and availability requirements of data.
​
The CIU concept is built on the premise of offering public solutions as opposed to public data. Acorn accesses sensitive and non-sensitive data on behalf of municipal organizations to answer questions on how to better the community. Providing solutions without providing the data allows Acorn to maintain data privacy while addressing issues of public safety, municipal operations, health and human services, and more.
​
Third-party data trust
Acorn is an outward-focused not-for-profit organization that facilitates data sharing across communities and is managed by a public board.
​
The organization houses public data as a neutral-party data trust with a mandate to provide expertise in handling and analyzing data to create solutions for the community. This data trust is based on improved accountability while creating stakeholder value.
​
As a data trust, Acorn stewards shared data and distils it into solutions as a data-in-solutionsout model. Through the CIU, open solutions are created not open data. Other beneficiaries of this trust are those who have controlled access to civic data to improve municipal service delivery outcomes, manage projects, lead public safety efforts, and more. “Centralizing functionality through the Innovation Center, in my opinion, has huge operational benefits,” says Claudio Stefano, Vice President, Operations and Engineering, PUC Services Inc. “For something such as developing GIS tools they can centralize and utilize any development as a common thread across the whole group of partners who maintain our community’s infrastructure.”
​
Creating a data trust is a viable way to safeguard data privacy and create trust to facilitate data-sharing partnerships. Acorn maintains data standards, controls access and provides quality control to support the delivery of data-smart city solutions through the CIU.
Road-map for implementation
The table below offers a summary of the initial phases required for the implementation of a Community Information Utility.
​
Critical Assessment
Assess the current GIS environment, user needs and constraints. This includes meeting with municipal management, the GIS department staff, IT department, current committed shared service partners and other potential partners to clarify and identify their information requirements to undertake a shared service GIS solution.
​
Data Analysis
Review of the current Information Technology (IT) environment, existing data sets, GIS tools and software, procedures and human resource capabilities, as well as the identification and prioritization of potential GIS applications, functions, new datasets and links to legacy systems.
​
Identify Gaps
Target key issues in data, software, hardware, procedures and human resource capabilities.
​
Conceptual Design
Gather and analyze all information from the previous phases to develop a conceptual architecture design for a community information utility (CIU) that will meet the requirements of all partners.
​
Implementation
Create an implementation plan for the CIU based on the determined data, software tools, staff training needs and resources. Identify and undertake projects that will showcase the benefits of the data-smart city solution to onboard new clients.