Automated repetitive reporting and data preparation tasks so recurring outputs could be produced faster and more consistently.
Not every OrbitalIQ project starts with a map, and not every project ends with one either. Sometimes the work starts with a spreadsheet, a recurring report, a folder of exports, or a process that technically works but takes too much time to repeat every week or month.
This project focused on improving a recurring reporting and data-preparation workflow. OrbitalIQ helped turn a manual process into something cleaner, more consistent, and easier to repeat, so the team could spend less time preparing information and more time using it.
Project Summary
OrbitalIQ completed an automation and reporting project to help the client reduce the time spent preparing recurring outputs. The existing process relied on manual steps, repeated data handling, and checks that were easy to miss when deadlines were tight.
The work involved reviewing the current process, identifying repeatable steps, cleaning the input structure, building automation where appropriate, and documenting how the workflow should be used and maintained.
Project Phases
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The first step was to understand how the work was currently being done and where time was being lost.
Reviewed input files, manual steps, outputs, naming rules, and reporting requirements.
Identified bottlenecks, repeated tasks, and places where errors could occur.
Confirmed which parts needed human review and which could be automated.
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Automation works best when the inputs are predictable. The next step was making the source information easier to process.
Standardized fields, naming conventions, formats, and folder structures.
Reduced unnecessary manual preparation steps.
Prepared the data for repeatable processing.
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The repeatable steps were turned into a technical workflow that could produce consistent outputs.
Built scripts, models, formulas, templates, or processing workflows.
Added checks to catch missing values, formatting issues, or obvious errors.
Tested the workflow against real project inputs and revised where needed.
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The final step was making sure the workflow could be used confidently after delivery.
Prepared simple instructions and maintenance notes.
Explained what the workflow does and what still needs human review.
Supported revisions based on user feedback.
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Automated or semi-automated workflow.
Cleaned input templates or folder structure.
Python, FME, Excel, SQL, ArcGIS, or related processing steps where appropriate.
QA/QC checks and error flags
Repeatable report or export outputs.
User instructions and maintenance notes.
Recommendations for future improvements.
Spending too much time on repetitive data preparation, reports, exports, or manual checks?
OrbitalIQ Solutions can help turn those repeatable tasks into cleaner workflows that save time and reduce avoidable errors.