How can you make your planning organization data-driven?

1 Assess your data needs

The first step to make your planning organization data-driven is to assess your data needs. What are the goals and objectives of your planning projects? What are the key questions and indicators that you need to answer and measure? What are the data sources and formats that you have access to? How reliable and timely are they? How can you integrate and analyze them? By conducting a data needs assessment, you can identify the gaps and opportunities in your data landscape and prioritize your data collection and management efforts.

2 Develop a data strategy

The second step to make your planning organization data-driven is to develop a data strategy. A data strategy is a plan that outlines how you will collect, store, process, analyze, and share data to support your planning goals. It should include the following elements: a data governance framework that defines the roles, responsibilities, and rules for data quality, security, and privacy; a data infrastructure that provides the tools and platforms for data storage, integration, and analysis; a data culture that fosters data literacy, collaboration, and innovation among your staff and stakeholders; and a data communication plan that defines how you will visualize and disseminate your data insights and stories.

3 Implement data solutions

The third step to make your planning organization data-driven is to implement data solutions. Data solutions are the specific applications and methods that you use to collect, analyze, and communicate data. They can range from simple surveys and spreadsheets to advanced geospatial and statistical models. Depending on your data needs and strategy, you can choose the best data solutions for your planning projects. Some examples of data solutions for urban planning are: participatory mapping, urban sensors, mobility analytics, scenario planning, and dashboards.

4 Evaluate data impact

The fourth step to make your planning organization data-driven is to evaluate data impact. Data impact is the extent to which data influences your planning decisions, outcomes, and impacts. To evaluate data impact, you need to establish a monitoring and evaluation system that tracks and measures the performance and results of your data solutions. You also need to collect feedback and testimonials from your staff and stakeholders on how data has helped or hindered their planning work. By evaluating data impact, you can learn from your successes and failures and improve your data practices.

5 Share data stories

The fifth step to make your planning organization data-driven is to share data stories. Data stories are the narratives that you create and tell with data to inform, persuade, and inspire your audience. They can help you communicate your planning vision, challenges, and achievements to different stakeholders, such as policymakers, funders, partners, and communities. To create effective data stories, you need to follow some basic principles: know your audience and purpose, choose the right data and format, craft a clear and compelling message, and use visual aids and interactive elements.

6 Learn from data communities

The sixth and final step to make your planning organization data-driven is to learn from data communities. Data communities are the networks and platforms that connect you with other data practitioners and experts in your field or sector. They can help you exchange ideas, insights, and best practices, as well as access resources, tools, and opportunities for data learning and collaboration. Some examples of data communities for urban planning are: Open Data Institute, Urban Data Lab, Data Collaboratives, and Smart Cities Network.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?