By Leah Sattler, Contributing Author
Data doesn’t have to be the wild west. With the right systems in place, wrangling numbers can be as smooth as a freshly paved road. In the world of local government asset management, data is more than just a set of numbers. It's the backbone that supports timely decisions, cost-efficiency and long-term planning.
Without a reliable data management system, asset managers are like drivers navigating a road with no signs or maps.
The importance of Quality Assurance (QA) and Quality Control (QC) in this context can’t be overstated. Whether it's ensuring accurate repair records, tracking maintenance schedules or calculating budget allocations, flawed data can lead to mistakes and inefficiencies.
For asset managers, trusting data is paramount in making informed decisions that affect public safety, budgets and infrastructure longevity.
In Texas, the Arlington Public Works Department utilizes OpenGov Cartegraph Asset Management. Using an array of data management functions within the system, the department manages 3,000 lane miles of road, 44,000 signs, 374 signalized intersections and many more assets. Public works staff leverage the system to research, plan and track all requests, maintenance and improvements for city-owned assets.
These QA and QC steps must be taken to build a strong data management system.
Define Roles, Set Clear Expectations
Defining roles and responsibilities is essential. From data entry and quality checks to review and approval, assigning specific roles ensures that tasks are handled efficiently and accurately.
The process can be likened to assembling a crew of pirates. Each member on deck has a specialized function to contribute to the larger goal. The captain is the manager who assigns the roles within the team and provides the vision for the ship's voyage. This position also sets clear expectations and ensures that the crew has the resources necessary to do their jobs.
The quartermaster may be referred to as a supervisor within your organization. They support the captain and provide more direct guidance and oversight of the crew. The navigator might be an analyst or subject matter expert who knows the path well and can predict potential obstacles.
Each role plays a vital part. When designed with thought and care, teams can maximize their potential and increase employee satisfaction by preventing burnout and frustration. By defining these responsibilities, you prevent bottlenecks and ensure that each part of the process runs like a well-oiled machine.
Setting access limitations is another critical step. Not everyone on your team needs to see or edit all types of data. By establishing permissions based on role, you ensure that only authorized personnel can access sensitive information. This reduces the risk of accidental errors and improves security.
It’s essential to know who can view, edit and approve data at different stages in the process. For example, project managers might need to approve changes to budget allocations, while field technicians should only have access to maintenance records.
With clear access controls, you can prevent errors from spreading across your system and maintain data integrity. If nothing else, restrict the ability to delete records from your system. General users should not be granted delete permissions to any record-set within your asset management system.
Design Layout Wisely
It’s important to design a clean, logical layout for your data management system. The structure should be tailored to your team’s needs and specific tasks. This improves accessibility and avoids confusion.
Think of your data system as a map—you need to know exactly where everything is to get to your destination.
Good practices include customizing libraries to ensure consistency, designing layouts with only necessary fields and utilizing record filters to view only relevant data. These practices can prevent unnecessary data from clogging up your system and help users stay focused.
Bring your end users into the conversation so they can provide their input on what fields they need to see and what makes the most sense to them.
Streamline Reporting
Data is only useful if it can be interpreted. Visual tools like bar charts, line graphs and pie charts are indispensable for transforming raw data into clear insights. After all, no one likes sifting through endless spreadsheets. By leveraging tools to visualize numerical data, you can quickly identify trends, outliers and patterns.
For example, a chart showing the decline in road conditions over time provides an immediate overview of asset status. These visualizations can be integrated into dashboards that bring the most relevant metrics to the forefront, saving you time and effort when evaluating the health of your infrastructure.
Dashboards can be beneficial for reported KPIs like the number of signs replaced, potholes filled or inlets inspected within the quarter. Instead of relying on cumbersome reports that may take days to gather, you can view everything that matters on a single, real-time dashboard, enabling faster decision-making and more efficient resource allocation. This also helps ensure consistency each time the KPI is reported.
The ability to filter data is a key benefit of modern asset management platforms. Imagine trying to find a pothole on a map of Texas—it’s much easier if you can zoom in. Filters allow stakeholders to quickly pull data related to specific assets or conditions, ensuring they don’t have to wade through irrelevant information. Custom filters can be created to provide just about anything if the data is in the system.
Lean on Automation
One of the most effective ways to improve data quality and consistency is by embracing automation. Repetitive tasks such as data entry or report generation are prime candidates for automation, reducing the chances of human error.
By setting up thresholds for specific fields—like the amount of material used or labor hours entered —you can ensure that data inputs adhere to predefined rules, eliminating common mistakes. For example, if someone tries to input the number of potholes filled over the threshold, an automation will flag it immediately prompting the user to correct the number because 400 sounds a bit too high for one small stretch of road.
It’s much easier to prevent the error in the first place than to try to play detective months later.
Automated workflows can generate real-time productivity reports, helping track asset usage, maintenance schedules and project progress. Scheduled reports can provide instant insights, keeping your team on schedule and within budget. Pictures and hyperlinks can be added to reports to allow the reviewers to get more context.
Automated alerts are another key feature of modern data management systems. By setting up notifications for key stakeholders when data changes (such as new asset installation or work order completions), you ensure that everyone stays informed without relying on manual updates.
For instance, if a budget exceeds its allocated amount, the system can automatically notify the project manager and finance team, minimizing the risk of costly surprises. The system can notify asset managers when stocked materials are running low so they can order more.
Track Data Changes
Tracking changes to data requests is vital for maintaining accountability. For certain datasets and fields, it’s essential to log who is making changes and when. This can be especially helpful for record-sets that are published publicly or reported on regularly. Version control and activity logs are invaluable tools for this purpose.
For example, if a team member updates a road asset record, the system should automatically log the change, including the user’s name, date and a description of the update. This process mirrors how you would log every maintenance job on a road.
Tracking changes allows for easier troubleshooting when discrepancies arise. It also provides a clear audit trail for compliance purposes, ensuring that all data updates are well-documented in case of future reviews or audits. Whether you’re responding to stakeholder questions or preparing for a regulatory audit, knowing the history of every data point ensures that you stay on track.
Keep It Simple
Simplicity in your approach doesn’t mean sacrificing quality. It means ensuring that your data management system is user-friendly, intuitive and reliable—so you can spend more time improving infrastructure and less time wrangling data. The most effective systems are often simple, with a clear structure, well-defined roles and automated processes that minimize human error.
Take a step back and evaluate your current QA/QC practices. Are there areas where you could streamline processes, tighten up roles or integrate automation? Start small—perhaps by automating reports or refining your data entry protocols—and build towards a more efficient, reliable system, always checking in with the end users and stakeholders.
In the Lone Star State, we may have big roads, but that doesn’t mean our data processes are a wild ride. By implementing these strategies, you can make sure that your infrastructure management runs as smoothly as a well-maintained highway. RB
Leah Sattler is the information systems coordinator for Arlington’s public works department.
