Ad Automation Initiative
To streamline high-volume ad production and reduce human error, I led a multi-phase automation effort within Adobe InDesign. This initiative focused on leveraging scripting and metadata to optimize design workflows, validate content, and ensure output accuracy.
Drawing on my experience as a graphic designer, I identified key pain points in daily production and tailored automation solutions to support team members with varying levels of technical skill, ensuring improvements benefited all users.
What began as a targeted refactor to reduce script bloat and prevent frequent crashes evolved into a comprehensive overhaul when I recognized the potential to not only fix legacy bugs but also introduce new functionality to eliminate common errors often discovered late in the ad lifecycle.
The original scripts had been built over a decade ago and were designed for universal compatibility across different software versions, unit measurements, and site configurations, which introduced significant complexity. A key constraint was having only the existing script arguments passed from the database to work with; I developed creative methods to store values and perform calculations that enabled expanded functionality within these limits.
My deep knowledge of file types, resolution, color spaces, and document intents was essential in refining output accuracy for both print and digital formats.
Problem or Challenge
The legacy automation was outdated, unsupported, and riddled with bugs. It lacked error-handling safeguards, leading to frequent user mistakes and workflow disruptions. Additional constraints included mandatory integration with an obsolete version of InDesign, reliance on a non-modern scripting language (VBScript), and no access to the backend database, server environment, or OS-level scripting configurations.
Tools and Techniques
VBScript, ExtendScript, Adobe InDesign, metadata-driven automation, iterative testing, team collaboration.
Result
Developed a scalable, metadata-driven system poised to improve speed, accuracy, and team efficiency. Though not fully deployed, the solution resolved existing bugs, introduced critical safeguards, and laid the groundwork for future automation enhancements.

