The City of Olathe, KS, is dedicated to providing the highest quality services to all citizens. Part of that promise involves ensuring the highest quality youth sports, community centers, community parks, and neighborhood parks. When a new director of the Parks and Recreation department came into the picture, emphasis was placed on improving services through data-based decision-making.
Olathe took a step back and realized that they were missing an opportunity for improved data collection. Specifically, the department realized they have always been able to measure community parks, but the smaller, neighborhood parks were a mystery. A new plan was required, and it needed to include everything from data collection to charting results so the department could tell a story about park usage and needs.
The Parks and Recreation department had a general idea of how much use their parks receive, and they decided to take the guesswork out of the equation and use data to properly determine what the actual usage rates for amenities in any given location really were. If data collection was to begin in neighborhood parks, they were going to do it properly to create a sustainable process. They decided to create a survey to use to record when and how the parks were utilized.
Surveying isn't easy, and they encountered a few challenges. Verbiage was confusing, surveyors didn't properly follow instructions, and weather was unpredictable as employees went out into parks to observe. As time went on, they made revisions to the data collection process that led to better outcomes. For instance, Olathe was able to create Livable Neighborhood Scores and a Healthy Communities Index based off the data they collected. It wasn't the initially desired outcome, but it showed that data collection can often answer more questions than originally asked. The department thought about how data could answer questions well beyond the initial scope of the survey.
After gathering all the data, Olathe needed a tool beyond Excel that would allow them to confidently go into board meetings with data that would tell a story. Paul Krueger, Park Services Manager, said, "We couldn't go into meetings with giant Excel files. We needed something that would be able to tell the story and answer our original question." They had limited time in front of the Director and were fighting with other departments for resources. They needed to tell their story quickly and support it with their data. So, Olathe turned to ClearPoint.
Data is broken down into Parks Usage, Amenities Usage, and Weather to tell the full story of how neighborhood parks are utilized. Each category has several metrics that update and chart automatically when data is uploaded with the ClearPoint Data Loader. They've also created a dashboard that pulls in daily statistics on visitors, length of stay, usage type, and other key data points.
Olathe Parks and Recreation is still early in the process of data collection, as they need many more data points to draw significant conclusions, but they are off to a strong start. The initially cumbersome process is now a well-organized framework that will allow the Parks and Recreation Department to efficiently collect data, analyze it, and turn it into a story moving forward. With the data and the story, the department can start making decisions based on the data and improve the lives of citizens.