Automation Tools Reduce Human Error in GIS Data Entry
Modern automation tools can process documents and data entries much faster and more accurately than humans. Many organizations still use outdated software requiring manual entry, leading to inefficiencies and errors.
Specific Examples:
- Large-Scale Lighting Project: I worked on a project where multiple programs were required instead of one. One program used for making design prints required manually numbering items by clicking arrows, which was highly inefficient. Since you couldn’t update the part number by simply typing it into the entry box, you had to click an up or down arrow hundreds of times per item, costing tons of wasted labor. I created an auto-click program in Python that updated hundreds of items faster than any manual updates, and my coworkers thanked me.
- Power Company Inefficiency: The largest power company in the US made engineers and GIS technicians manually enter data, such as downstream phases on conductors, transformers, fuses, and insulators. The system had the information internally and would use it to reject your work if left out. The lack of automation for this task was extremely frustrating.
- Manual Load Calculations: Instead of doing the required load calculations in the program that had all the hardware and specs for the design, a standard was set to use an Excel program created long ago. All the data meticulously entered into the outdated software for prints and billing had to be manually reentered into Excel. A simple Python script could automate these calculations.
Improved Accuracy and Consistency in Data Handling
GIS technicians often handle data entry manually, which is prone to errors, with accuracy rates dropping as low as 70%. Automation minimizes these errors, especially for static 2D datasets.
Even with updated GIS data collection techniques, a lot of time is wasted uploading, organizing, and entering data post-collection. Automation at the point of data collection, using GPS or numbering profiles, can save time and reduce errors.
Cost-Effectiveness
Significant Cost Savings by Replacing Human GIS Techs with Automation Tools:
Automation can lead to substantial savings by reducing the need for human labor. In 2019, a member of the automation team and I proposed a program that would have solved many of these problems, saving millions of dollars in the first year with less than three months of design, testing, and implementation carried out by just two of us. Contract plus cost is where companies make money off their inefficiencies and are literally incentivized to work slower and produce the minimum quality to compete with other contracted workers. Companies often bill clients significantly more than what they pay their employees. For instance, level one engineers billed at $90-$130 per hour may only earn $25-$28 per hour, spending much time correcting GIS technicians' errors.
Reduced Overhead Costs (Salaries, Training, Benefits):
Employing GIS technicians involves high costs, including salaries ($40,000-$60,000 annually), training, and benefits like health insurance and retirement plans. These recurring expenses can strain budgets, especially for smaller organizations.
Automation tools, while requiring an initial investment, incur lower ongoing costs. These tools reduce the need for continuous training and eliminate employee benefits, operating 24/7 without fatigue and ensuring consistent data quality. It really is unreasonable to try and compete with the most basic automated process no matter how much expertise and training your technicians have.
Scalability
Handling Larger Datasets Without Additional Costs:
Automation systems can scale effortlessly to manage increasing data volumes and complexity without incurring additional costs, unlike human workers who would require proportional increases in labor and resources.
The Role of AI in Transforming GIS
Enhanced Data Processing and Analysis:
AI algorithms can process vast amounts of geospatial data more quickly and accurately than human technicians. Machine learning models can identify patterns and insights, leading to better decision-making and allowing GIS professionals to focus on higher-level tasks.
Improved Accuracy and Precision:
Automation tools equipped with AI significantly reduce human error in data entry and analysis. Advanced error-checking algorithms ensure high data quality, enhancing GIS outputs' credibility and utility.
Real-Time Data Integration:
AI and automation enable seamless integration of real-time data from various sources, such as satellite imagery, IoT sensors, and social media feeds, providing up-to-date information for dynamic applications like disaster response and traffic management.
Automated Map Production:
AI systems can largely automate the production of detailed maps and spatial visualizations, reducing the workload on GIS technicians and allowing them to focus on more creative and complex tasks.
Predictive and Prescriptive Analytics:
AI-driven predictive analytics can forecast future trends and scenarios based on historical geospatial data. Prescriptive analytics can suggest optimal actions based on these predictions, aiding urban planners and other decision-makers.
New Career Opportunities:
While automation reduces the need for traditional data entry roles, it creates opportunities in AI model development, geospatial data science, and GIS systems integration. GIS professionals will need to develop new skills in AI and machine learning.
Enhanced Decision Support Systems:
AI-powered GIS systems will evolve into advanced decision support tools, providing real-time recommendations and insights to decision-makers and leveraging AI to analyze complex datasets.
Customization and Personalization:
AI will enable the creation of highly customized GIS applications tailored to user needs, improving user experience through personalized map interfaces that adjust based on preferences and usage patterns.
By adopting both traditional automation and AI technologies, organizations can achieve greater efficiency, accuracy, and cost savings while also paving the way for new roles and opportunities in the GIS field.