Whether in geographic information systems, excel spreadsheets, or financial accounting systems modern and archaic, the arrival of our collective awareness of the vast abyss of data has generated a spectrum of reaction and response from local governments. This spectrum ranges from fully incorporating data into decision making to being overwhelmed by the great magnitude of data collected, and everything in between.

As data-driven decision making continues to steadily gain traction in local government, we are faced with many questions. Is this too much data? How exactly can this data inform our decision making? Should decisions be data informed or data supplemented? One thing is for certain, we cannot ignore this phenomenon.

Many local governments have already jumped into the data waters to chart their course on how they will be collecting and using data in the decision-making process. As a result, we are seeing a healthy mix of success stories as well as stories of data potentially in conflict with community interests. This leads us to an initial picture of what data in local government looks like. On the one hand, technology can be a great asset to enhancing a local government’s ability to be efficient and effective. On the other hand, too much data can lead to data surplus, failing to provide decision makers with the information they need. In both scenarios, local governments must determine the following:

1. How they will collect data.

2. The extent to which data will influence their decision making.

3. How to balance data with community input in the decision-making process.

Determining the “Right” Amount of Data for Your Community, Open Data Portals

The beauty of data is that it can be customized to meet the needs of your community and local government. For example, two cities can both collect data about bus routes in a community and use that data in completely different ways depending on: (1) what they are looking to learn from the data and (2) the extent to which it influences decision making. Determining the “right” amount of data for your community is essential to leveraging data to make more informed decisions. The best way to do this is by first getting to know your community and their level of comfort with technology and data sharing. Good, effective public engagement can help local governments better understand the needs of their communities and assess digital literacy and comfort levels.

Collecting data for the sake of data collection can lead to an overwhelming surplus, thereby robbing data of its potential to be useful. The open data movement illuminated this concept to both local governments and communities simultaneously as both groups realized that local governments have plenty of data, much of it inconsistently collected, and not organized in a way that makes it accessible to the average community member. In San Diego, for example, the local government found nearly 2,000 datasets around the city, but after making it a priority to flag duplicative data or very case-specific data, while also asking the public to vote on which datasets they would be interested in seeing released, the local government prioritized proactively posting only 44 datasets in the initial launch of the portal, which today exceeds 75 datasets.

Cities soon began course correcting by building open data portals to make data more accessible to the curious community member. Cities like New York and Chicago invested in accessible websites to house the collected and sorted data. Innovative governments then doubled down on this trend by creating their own analytics shops and hiring chief data officers. Open data portals increasingly are becoming the favored means by which local governments are making data accessible to their communities, and thereby discerning what amount of data is the “right” amount for their specific needs. This process is crucial in order to ensure that data is properly being used to impact decision making.

How Local Government Uses Data to Make Decisions

While there are varying degrees by which local governments can incorporate data in the decision-making process, the following four frameworks generally capture a majority of approaches.

Data-Supplemented Decision Making

This framework relies on data to justify an already predetermined outcome. In these cases, the decision is already made based on other factors including community input, survey of stakeholders, etc…, and the data serves to supplement and support the decision.

Data-Enabled Decision Making

In this scenario, a framework for the decision is in place based on other factors, but data and information will help refine the final decision. A decision-to-be-made is known, but the decision-makers are actively considering other inputs and are flexible to make a decision even if only partially supported by the data.

For example, the city of Charlotte, North Carolina, USA, uses data to create site scoring for proposed housing locations based on proximity to transit assets and amenities, income diversity, reasonable access to jobs, and level of neighborhood change. While developers knew they wanted to build housing, the data enabled the decision to determine the exact location.

Data-Influenced/Informed Decision Making

This framework falls outside of a normal scenario because the catalyst for the decision is data. In this scenario, data is not sought, but is instead discovered or presented to kickstart a decision-making process that might otherwise not have been on the radar.

For example, in the city of San Diego, California, USA, data on the increased use of electric scooters indicated to the local government that the city needed to take a closer look at how scooters were being incorporated into traffic patterns. San Diego began collecting data on scooters to inform decision making on scooter parking corral locations and general scooter regulations.

Data-Driven Decision Making

This approach is the most theoretically pure use of data, in which data determines the course of the decision-making process, regardless of other factors. Here the data does all the talking and drives the decision.

Conclusion

Data and its usage continue to be something local governments are grappling with in real time and making adjustments as necessary to determine what works best for their specific organization and community. This process is coupled with a younger, more digitally literate and digitally comfortable generation entering the workforce. As a result, local governments are well positioned to navigate the waters of determining the “right” amount of data for their communities and the role that data plays in their decision-making process. Ultimately, that right amount is best determined by knowing your community well and working with them to create decision-making processes that have buy-in from all stakeholders.

POOJA BACHANI DI GIOVANNA is the assistant director at the Davenport Institute and works on curriculum development and program delivery, communications, and strategic relations.

ALMIS UDRYS has served as the founding director of city of San Diego’s Performance and Analytics Department and as an adjunct professor at Pepperdine’s School of Public Policy. He currently helps lead professional services for OpenGov.